D02.25 - Performance Assessment and Validation of Process Stream Analyzer Systems

SIGNIFICANCE AND USE
5.1 The primary purpose of this practice is to permit the user to validate numerical values produced by a multivariate, infrared or near-infrared laboratory or process (online or at-line) analyzer calibrated to measure a specific chemical concentration, chemical property, or physical property. If the analyzer results agree with the primary test method to within limits based on the multivariate model for the user-prespecified statistical confidence level, these results can be considered ’validated’ to the user pre-specified confidence limit for a specific application, and hence can be considered useful for that specific application.  
5.2 Procedures are described for verifying that the instrument, the model, and the analyzer system are stable and properly operating.  
5.3 A multivariate analyzer system inherently utilizes a multivariate calibration model. In practice, the model both implicitly and explicitly spans some subset of the population of all possible samples that could be in the complete multivariate sample space. The model is applicable only to samples that fall within the subset population used in the model construction. A sample measurement cannot be validated unless applicability is established. Applicability cannot be assumed.  
5.3.1 Outlier detection methods are used to demonstrate applicability of the calibration model for the analysis of the process sample spectrum. The outlier detection limits are based on historical as well as theoretical criteria. The outlier detection methods are used to establish whether the results obtained by an analyzer are potentially valid. The validation procedures are based on mathematical test criteria that indicate whether the process sample spectrum is within the range spanned by the analyzer system calibration model. If the sample spectrum is an outlier, the analyzer result is invalid. If the sample spectrum is not an outlier, then the analyzer result is valid providing that all other requirements for validity are...
SCOPE
1.1 This practice covers requirements for the validation of measurements made by laboratory, field, or process (online or at-line) infrared (near- or mid-infrared analyzers, or both), and Raman analyzers, used in the calculation of physical, chemical, or quality parameters (that is, properties) of liquid petroleum products and fuels. The properties are calculated from spectroscopic data using multivariate modeling methods. The requirements include verification of adequate instrument performance, verification of the applicability of the calibration model to the spectrum of the sample under test, and verification that the uncertainties associated with the degree of agreement between the results calculated from the infrared or Raman measurements and the results produced by the PTM used for the development of the calibration model meets user-specified requirements. Initially, a limited number of validation samples representative of current production are used to do a local validation. When there is an adequate number of validation samples with sufficient variation in both property level and sample composition to span the model calibration space, the statistical methodology of Practice D6708 can be used to provide general validation of this equivalence over the complete operating range of the analyzer. For cases where adequate property and composition variation is not achieved, local validation shall continue to be used.  
1.1.1 For some applications, the analyzer and PTM are applied to the same material. The application of the multivariate model to the analyzer output (spectrum) directly produces a PPTMR for the same material for which the spectrum was measured. The PPTMRs are compared to the PTMRs measured on the same materials to determine the degree of agreement.  
1.1.2 For other applications, the material measured by the analyzer system is subjected to a consistent additive treatment prior to being analyzed by the PTM...

SIGNIFICANCE AND USE
5.1 This practice can be used to quantify the performance of a process stream analyzer system or its subsystem in terms of precision and bias relative to those of a primary test method for the property of interest.  
5.2 This practice provides developers or manufacturers of process stream analyzer systems with useful procedures for evaluating the capability of newly designed systems for industrial applications that require reliable prediction of measurements of a specific property by a primary test method of a flowing component or product.  
5.3 This practice provides purchasers of process stream analyzer systems with some reliable options for specifying acceptance test requirements for process stream analyzer systems at the time of commissioning to ensure the system is capable of making the desired property measurement with the appropriate precision or bias specifications, or both.  
5.4 PPTMR from Analyzer Systems validated in accordance with this practice can be used to predict, with a specified confidence, what the PTMR would be, to within a specified tolerance, if the actual primary test method was conducted on the materials that are within the validated property range and type.  
5.5 This practice provides the user of a process stream analyzer system with useful information from on-going quality control charts to monitor the variation in δ over time, and trigger update of correlation relationship between the analyzer system and primary test method in a timely manner.  
5.6 Validation information obtained in the application of this practice is applicable only to the material type and property range of the materials used to perform the validation. Selection of the property levels and the compositional characteristics of the samples must be suitable for the application of the analyzer system. This practice allows the user to write a comprehensive validation statement for the analyzer system including specific limits for the validated range of application. Th...
SCOPE
1.1 This practice describes procedures and methodologies based on the statistical principles of Practice D6708 to validate whether the degree of agreement between the results produced by a total analyzer system (or its subsystem), versus the results produced by an independent test method that purports to measure the same property, meets user-specified requirements. This is a performance-based validation, to be conducted using a set of materials that are not used a priori in the development of any correlation between the two measurement systems under investigation. A result from the independent test method is herein referred to as a Primary Test Method Result (PTMR).  
1.1.1 The degree of agreement described in 1.1 can be either for PPTMRs and PTMRs measured on the same materials, or for PPTMRs measured on basestocks and PTMRs measured on these same basestocks after constant level additivation.  
1.1.2 In some cases, a two-step procedure is employed. In the first step, the analyzer and PTM are applied to the measurement of the same blendstock material. If the analyzer employed in Step 1 is a multivariate spectrophotometric analyzer, then Practice D6122 is used to access the agreement between the PPTMRs and the PTMRs for this first step. Otherwise, this practice is used to compare the PPTMRs to the PTMRs measured for this blendstock to determine the degree of agreement. In a second step, the PPTMRs produced in Step 1 are used as inputs to a second model that predicts the results obtained when the PTM is applied to the analysis of the finished blended product. Since this second step does not use analyzer readings, the validation of the second step is done independently. Step 2 is only performed on valid Step 1 results. Note that the second model might accommodate variable levels or multiple material additions to the blendstock.  
1.2 This practice assumes any correlation necessary to mitigate systemic biases between the ...

SIGNIFICANCE AND USE
5.1 This practice is intended for use by parties interested in releasing product by use of vibrational spectroscopic analyzer systems. It is expected to meet the industry need for a written practical reference describing a scientifically systematic approach to show the degree of confidence and degree of uncertainty in analyzer predicted values in relation to the PTM.  
5.2 This is a performance-based practice that relies on the demonstrated quality of the test result and on strict adherence to the referenced standards and the additional requirements in this practice.  
5.3 As part of demonstrating performance, this practice incorporates by reference other ASTM standardized practices as key steps in the process.  
5.4 There are prescriptive requirements included for this practice.  
5.4.1 The practice requires sample temperature to be carefully controlled in analyzer system hardware or that effects of temperature change be compensated in modeling or software.  
5.4.2 Outlier detection capability is required for demonstrating the multivariate calibration model is applicable for the analysis of the sample spectrum, that is, that the analysis interpolates the model, that the sample does not contain a statistically significant amount of unmodeled components above a certain limit based on spectral residual statistic and that the sample spectrum does not fall within gap in the multivariate calibration space.  
5.5 In order to follow this practice, all criteria must be met.  
5.5.1 The user shall investigate the cause of not meeting the practice requirements.  
5.5.2 For any nonconformities noticed, the user shall make corrections to the analyzer system or procedures to conform to the requirements of this practice.
SCOPE
1.1 This practice covers requirements for establishing performance-based qualification of vibrational spectroscopic analyzer systems intended to be used to predict the test result of a material that would be produced by a Primary Test Method (PTM) if the same material is tested by the PTM.  
1.1.1 This practice provides methodology to establish the lower/upper prediction limits associated with the Predicted Primary Test Method Result (PPTMR) in 1.1 with a specified degree of confidence that would contain the PTM result (if tested by the PTM).  
1.1.2 The prediction limits in 1.1.1 can be used to estimate the confidence that product released using the analyzer system based on a PPTMR that meets PTM-based specification limits will meet PTM-based specification limits when tested by a PTM.  
1.2 The practice covers the qualification of on-line, at-line, or laboratory infrared or Raman analyzers used to predict physical, chemical, or performance properties of liquid petroleum products and fuels. Infrared analyzers can operate in the near-infrared (NIR) region, mid-infrared (MIR) region, or both.  
1.2.1 This practice applies to all analyzer systems that can meet the performance requirements defined within.  
1.2.2 This practice is not limited to analyzers designed by any specific instrument manufacturer.  
1.2.3 This practice allows for multiple calibration techniques to create a multivariate model which relates the spectra produced by the analyzer to the corresponding property determined by a PTM. Spectra can be used to predict multiple properties, but the analyzer system performance of each predicted property is qualified individually.  
1.3 The practice describes procedures for establishing performance requirements for analyzer system applications. The user of this practice must establish written protocols to confirm the procedures are being followed.  
1.4 This practice makes use of standard practices, guides, and methods already established in ASTM. Additional requirements are listed within this practice.  
1.5 Any multivariate model that meets performance requirements and detects when the spectrum of a sample is an outlier (analysis that represents an extrapolation...

SIGNIFICANCE AND USE
4.1 If ASTM Committee E13 has not specified an appropriate test procedure for a specific type of instrument, or if the sample specified by a Committee E13 procedure is incompatible with the intended instrument operation, then this practice can be used to develop practical performance tests.  
4.1.1 For instruments which are equipped with permanent or semi-permanent sampling accessories, the test sample specified in a Committee E13 practice may not be compatible with the instrument configuration. For example, for FT-MIR instruments equipped with transmittance or IRS flow cells, tests based on putting polystyrene films into the sample position are impractical. In such cases, this practice suggests means by which the recommended test procedures can be modified by changing the test material or the location of the recommended test material.  
4.1.2 For instruments used in process measurements, the choice of test materials may be limited due to process contamination and safety considerations. The practice suggests means of developing performance tests based on materials which are compatible with the intended use of the analyzer.  
4.2 Tests developed using the practice are intended to allow the user to compare the performance of an instrument on any given day with prior performance, and specifically to compare performance during calibration of the analyzer to performance during validation of the analyzer and during routine use of the analyzer. The tests are intended to uncover malfunctions or other changes in instrument operation, but they are not designed to diagnose or quantitatively assess the malfunction or change. The tests are not intended for the comparison of analyzers of different manufacture.  
4.3 Tests developed using this practice are also intended to allow the user to compare the performance of a primary analyzer used in development of a multivariate model to the performance of secondary analyzers used to apply that model for the analysis of process or p...
SCOPE
1.1 This practice covers basic procedures that can be used to develop instrument performance tests for spectroscopic based online, at-line, laboratory and field analyzers. The practice is intended to be applicable to Raman spectrometers and to infrared spectrophotometers operating in the near-infrared and mid-infrared regions.  
1.2 This practice is not intended as a replacement for specific practices, such as Practices E275, E925, E932, E958, E1421, or E1683 that exist for measuring performance of specific types of laboratory spectroscopic instruments. Instead, this practice is intended to provide guidelines as to how similar practices should be developed when specific practices do not exist for a particular instrument type, or when specific practices are not applicable due to sampling or safety concerns. This practice can be used to develop instrument performance tests for on-line process spectroscopic-based analyzers.  
1.2.1 The performance tests described in this practice typically only evaluate the performance of the infrared spectrophotometer or Raman spectrometer part of the analyzer system, referred to herein as the instrument.  
1.2.2 Instrument performance tests do not typically evaluate performance of analyzer sampling systems.  
1.3 This practice describes univariate level zero and level one tests, and multivariate level A and level B tests which can be implemented to measure instrument performance. These tests are designed to be used as rapid, routine checks of instrument performance. They are designed to uncover malfunctions or other changes in instrument operation, but do not specifically diagnose or quantitatively assess the malfunction or change. The tests are not intended for the comparison of instruments or analyzers of different manufacture.  
1.4 The instrument performance tests described in this practice are used during the development of multivariate calibrations via Practice D8321 to establ...

SIGNIFICANCE AND USE
5.1 This practice can be used to establish the validity of the results obtained by an infrared (IR) spectrophotometer or Raman spectrometer at the time the calibration is developed. The ongoing validation of PPTMRs produced by analysis of unknown samples using the multivariate model is covered separately (see for example, Practice D6122).  
5.2 The multivariate calibration procedures define the range over which measurements are valid and demonstrate whether the accuracy and precision of the analysis outputs meet user requirements.  
5.3 This practice describes sampling procedures that must be followed to ensure that the sample which is analyzed by the spectrophotometer or spectrometer is the same as the sample analyzed by the PTM. The sampling procedures apply to analyses done on lab analyzers, at-line analyzers, and online analyzers.
SCOPE
1.1 This practice covers a guide for the multivariate calibration of infrared (IR) spectrophotometers and Raman spectrometers used in determining the physical, chemical, and performance properties of petroleum products, liquid fuels including biofuels, and lubricants. This practice is applicable to analyses conducted in the near infrared (NIR) spectral region (roughly 780 nm to 2500 nm) through the mid infrared (MIR) spectral region (roughly 4000 cm-1 to 40 cm-1). For Raman analyses, this practice is generally applied to Stokes shifted bands that occur roughly 400 cm-1 to 4000 cm-1 below the frequency of the excitation.
Note 1: While the practice described herein deals specifically with mid-infrared, near-infrared, and Raman analysis, much of the mathematical and procedural detail contained herein is also applicable for multivariate quantitative analysis done using other forms of spectroscopy. The user is cautioned that typical and best practices for multivariate quantitative analysis using other forms of spectroscopy may differ from the practice described herein for mid-infrared, near-infrared, and Raman spectroscopies.  
1.2 Procedures for collecting and treating data for developing IR and Raman calibrations are outlined. Definitions, terms, and calibration techniques are described. The calibration establishes a multivariate correlation between the spectral features and the properties to be predicted. This correlation is herein referred to as the multivariate model. Criteria for validating the performance of the multivariate model are described. The properties against which a multivariate model is calibrated and validated are measured by Primary Test Methods (PTMs) and the results of the PTM measurement are herein referred to as Primary Test Method Results (PTMR). The analysis of the spectra using the multivariate model produces a Predicted Primary Test Method Result (PPTMR).  
1.3 The implementation of this practice requires that the IR spectrophotometer or Raman spectrometer has been installed in compliance with the manufacturer's specifications. In addition, it assumes that, at the time of calibration, validation, and analysis, the analyzer is operating at the conditions specified by the manufacturer. The practice includes instrument performance tests which define the instrument performance at the time of calibration, and which qualify the instrument by demonstrating comparable performance during validation and analysis.  
1.4 This practice covers techniques that are routinely applied for online, at-line, and laboratory quantitative analysis. The practice outlined covers the general cases for liquids and solids that are single phase homogeneous samples when presented to the analyzers. Online application is limited by sample viscosity and the ability to introduce sample to the analyzer. All techniques covered require the use of a computer for data collection and analysis.  
1.5 This practice is most typically applied when the spectra and the PTMR against which the analysis is calibrated are measured on the same sample. However, for some applic...

SIGNIFICANCE AND USE
5.1 Analyzer systems require representative samples of petroleum products delivered in a timely manner to (1) facilitate the control of process or blending units or (2) calculate a flow proportioned property value.  
5.2 Representative samples of petroleum products are required for the determination of chemical and physical properties. These properties are used to establish the relationship between the analyzer system and the primary test method during initial and ongoing validation of the system.  
5.3 Representative samples of petroleum products are tested to determine the chemical and physical properties of a batch offered for tender.
SCOPE
1.1 This practice covers the performance requirements for sample systems employed to deliver process stream samples (1) to analyzer system for analyses or (2) for analyzer validation or (3) for composite sample systems. It also outlines the selection and operation of line or batch sampling equipment intended for analyzer flow proportioned average property value system validation. Sample handling, mixing, and conditioning procedures are required to ensure that a representative sample of the liquid petroleum product is collected from the sampling source.  
1.2 Applicable Fluids—This practice is applicable to single liquid phase petroleum products whose vapor pressure at sampling and sample storage conditions is less than or equal to 110 kPa (16.0 psi), and, with a D86 final boiling point less than or equal to 400 °C (752 °F).  
1.2.1 Specialized sample handling may be necessary to maintain sample integrity of more volatile materials at high temperatures or extended residence time in the receiver. Such handling requirements are not within the scope of this practice. Users should consult the analytical methods to be performed on the sample for special sample storage or conditioning requirements.  
1.3 Some or all of the processes outlined in this practice may be applicable to other liquids. Applying this practice to other liquids will require the consideration of additional methods and practices. It is the responsibility of the user of this standard to identify any and all applicable safety and sampling considerations and establish appropriate procedures to handle these additional considerations.  
1.4 The values stated in SI units are to be regarded as the standard. The values given in parentheses are for information only.  
1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.  
1.6 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

SIGNIFICANCE AND USE
4.1 The analyzer site precision is an estimate of the variability that can be expected in a UAR or a PPTMR produced by an analyzer when applied to the analysis of the same material over an extended time period.  
4.2 For applications where the process analyzer system results are required to agree with results produced from an independent PTM, a mathematical function is derived that relates the UARs to the PPTMRs. The application of this mathematical function to an analyzer result produces a predicted PPTMR. For analyzers where the mathematical function, that is, a correlation, is developed by D7235, the analyzer site precision of the UARs is a required input to the computation.  
4.3 After the correlation relationship between the analyzer results and primary test method results has been established, a probationary validation (see D3764 and D6122) is performed using an independent but limited set of materials that were not part of the correlation activity. This probationary validation is intended to demonstrate that the PPTMRs agree with the PTMRs to within user-specified requirements for the analyzer system application. The analyzer site precision is a required input to the probationary validation procedures.  
4.3.1 If the process stream analyzer system and the primary test method are based on the same measurement principle(s), or, if the process stream analyzer system uses a direct and well-understood measurement principle that is similar to the measurement principle of the PTM then validation is done via D3764. Practice D3764 also applies if the process stream analyzer system uses a different measurement technology from the PTM, provided that the calibration protocol for the direct output of the analyzer does not require use of the PTM.  
4.3.2 If the process stream analyzer system utilizes an indirect or mathematically modeled measurement principle such as chemometric or multivariate analysis techniques where PTMRs are required for the development of the che...
SCOPE
1.1 This practice describes a procedure to quantify the site precision of a process analyzer via repetitive measurement of a single process sample over an extended time period. The procedure may be applied to multiple process samples to obtain site precision estimates at different property levels  
1.1.1 The site precision is required for use of the statistical methodology of D6708 in establishing the correlation between analyzer results and primary test method results using Practice D7235.  
1.1.2 The site precision is also required when employing the statistical methodology of D6708 to validate a process analyzer via Practices D3764 or D6122.  
1.2 This practice is not applicable to in-line analyzers where the same quality control sample cannot be repetitively introduced.  
1.3 This practice is meant to be applied to analyzers that measure physical properties or compositions.  
1.4 This practice can be applied to any process analyzer system where the feed stream can be captured and stored in sufficient quantity with no stratification or stability concerns.  
1.4.1 The captured stream sample introduction must be able to meet the process analyzer sample conditioning requirements, feed temperature and inlet pressure.  
1.4.2 This practice is designed for use with samples that are single liquid phase, petroleum products whose vapor pressure, at sampling and sample storage conditions, is less than or equal to 110 kPa (16.0 psi) absolute and whose D86 final boiling point is less than or equal to 400 °C (752 °F).
Note 1: The general procedures described in this practice may be applicable to materials outside this range, including multiphase materials, but such application may involve special sampling and safety considerations which are outside the scope of this practice.  
1.5 The values for operating conditions are stated in SI units and are to be regarded as the standard. The values given in parentheses are the hi...

SIGNIFICANCE AND USE
4.1 This guide is intended to be used in conjunction with Practice D3764 (Case 1) and Practice D6122 (Case 2). Methodology in this guide can be used to determine if a linear correlation can improve the performance of the total analyzer system in terms of its ability to predict the results that the PTM would have been if applied to the same material. This methodology, which is based on the same statistical data treatment as Practice D6708, is used to derive the parameters of the linear relationship and to assess the degree of improvement.  
4.2 This guide provides developers or manufacturers of process stream analyzer systems with useful procedures for developing the capability of newly designed systems for industrial applications that require reliable prediction of measurements of a specific property by a primary test method of a flowing component or product.  
4.3 This guide provides purchasers of process stream analyzer systems with some reliable options for specifying performance requirements for process stream analyzer systems that are used in applications requiring reliable prediction of measurements of a specific property by a primary test method of a flowing component or product.  
4.4 This guide provides the user of a process stream analyzer system with useful information on the work process for establishing the PTM prediction relationship and prediction performance.  
4.5 Prediction (correlation) relationship obtained in the application of this guide is applicable only to the material type and property range of the materials used to perform the study. Selection of the property levels and the compositional characteristics of the samples must be suitable for the application of the analyzer system. Users are cautioned against extrapolation of the prediction relationship beyond the material type and property range used to obtain the relationship.  
4.6 The degree-of-agreement assessment promoted in this guide is based on the statistical principles articula...
SCOPE
1.1 This guide covers a general methodology to develop and assess the linear relationship between results produced by a total analyzer system versus the results produced by the corresponding primary test method (PTM) that the analyzer system is intended to emulate, using the principles and approaches outlined in relevant ASTM standard practices and guides.  
1.2 This guide describes how the statistical methodology of Practice D6708 can be employed to assess agreement between the PTM and analyzer results, and, if necessary, develop linear correlation to further improve the agreement over the complete operating range of the analyzer. For instances where there is insufficient variation in property level to apply the Practice D6708 multi-level methodology, users are referred to Practice D3764 to perform a level specific bias evaluation. The correlation relationship information obtained in the application of this guide is applicable only to the material type and property range of the materials representative of those used to perform the assessment. Users are cautioned against extrapolation of the relationship beyond the material type and property range being studied.  
1.3 This guide applies if the process stream analyzer system and the primary test method are based on the same measurement principle(s), or, if the process stream analyzer system uses a direct and well-understood measurement principle that is similar to the measurement principle of the primary test method. If the process stream analyzer system uses a different measurement technology from the primary test method, provided that the calibration protocol for the direct output of the analyzer does not require use of the PTM, this practice also applies.  
1.4 This guide does not apply if the process stream analyzer system utilizes an indirect or mathematically modeled measurement principle such as chemometric or multivariate analysis techniques where results from ...

SIGNIFICANCE AND USE
5.1 The analyzer sample system lag time estimated by this guide can be used in conjunction with the analyzer output to aid in optimizing control of blender facilities or process units. A known and constant lag time is key for the use in optimizing control.  
5.2 The lag time can be used in the tuning of control programs to set the proper optimization frequency.  
5.3 The application of this guide is not for the design of a sample system but to help understand the design and to estimate the performance of existing sample systems. Additional detailed information can be found in the references provided in the section entitled Additional Reading Material.
SCOPE
1.1 This guide covers the application of routine calculations to estimate sample system lag time, in seconds, for gas, liquid, and mixed phase systems.  
1.2 This guide considers the sources of lag time from the process sample tap, tap conditioning, sample transport, pre-analysis conditioning and analysis.  
1.3 Lag times are estimated based on a prediction of flow characteristics, turbulent, non turbulent, or laminar, and the corresponding purge requirements.  
1.4 Mixed phase systems prevent reliable representative sampling so system lag times should not be used to predict sample representation of a mixed phase stream.  
1.5 The values stated in inch-pound units are to be regarded as standard. Other units of measurement are included in this standard and Appendix X1 examples where normally seen in industry.  
1.6 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.  
1.7 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

SIGNIFICANCE AND USE
4.1 Contractual or local regulation, or both, permitting, the FPAPV calculated according to this practice can be used to represent the average property of the quantity of material collected.  
4.2 Due to the averaging and appropriate weighting of analysis results, the FPAPV estimate of the property for the collected material is expected to be more representative and more precise than an estimate based on a small number of analyses on a few samples.
Note 1: For applications where the on-line analyzer system result is being used in direct feedback control in a contiguous manner, the true property distribution for a large population of batches with essentially identical FPAPV's is expected to be Gaussian, centered at the FPAPV value, with a standard deviation that is no less than the long term site precision standard deviation of the analyzer system.  
4.3 If the measured property value is used to predict another property value through the use of an appropriate correlation equation, the FPAPV can also be used as a suitable prediction of that property.  
4.4 The most recently updated FPAPV can be used to represent the property of the material currently accumulated in the tank or vessel for process control or material disposition decisions, or both.
SCOPE
1.1 This practice covers a technique for calculating a flow-proportioned average property value (FPAPV) for a batch of in-line blended product or process stream material that is collected over time and isolated in a storage tank or vessel, using a combination of on-line or at-line measurements taken at regular intervals of the property and flow rates.  
1.2 The FPAPV methodology uses regularly collected on- line or at-line process analyzer measurements, flow, and assessment of other appropriate process measurements or values, to calculate a flow-proportioned average property value in accordance with flow quantity units of material produced.  
1.3 When the collecting vessel contains a heel (retained material prior to receipt of the production batch), both the property value and quantity of the heel material can be predetermined and factored into the calculation of the FPAPV for the new batch.  
1.4 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.  
1.5 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

SIGNIFICANCE AND USE
4.1 The standards employed in the Process Stream Analyzer PSPV Generation Flow Diagram each have a specific deliverable that when combined into a single system produces a PSPV enabling the representation of product by process stream analyzer.  
4.2 The description of each standard in the process provides the user with an overview of the application of the standard in the process for developing a PSPV.
SCOPE
1.1 This practice covers generating a Process Stream Property Value (PSPV) from the application of a process stream analyzer, which requires the use of several ASTM standards. These standards describe procedures to collect a representative sample, establish and validate the relationship to the primary test method, and calculate a property value with an expected uncertainty. Each standard builds or prepares data, or both, to be used in another standard. The workflow process culminates to produce a process stream analyzer result that represents a user defined batch of product. The sequence in which the standards are to be utilized is defined in this practice.  
1.2 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.  
1.3 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

SIGNIFICANCE AND USE
5.1 This practice can be used to quantify the performance of a process stream analyzer system or its subsystem in terms of precision and bias relative to those of a primary test method for the property of interest.  
5.2 This practice provides developers or manufacturers of process stream analyzer systems with useful procedures for evaluating the capability of newly designed systems for industrial applications that require reliable prediction of measurements of a specific property by a primary test method of a flowing component or product.  
5.3 This practice provides purchasers of process stream analyzer systems with some reliable options for specifying acceptance test requirements for process stream analyzer systems at the time of commissioning to ensure the system is capable of making the desired property measurement with the appropriate precision or bias specifications, or both.  
5.4 PPTMR from Analyzer Systems validated in accordance with this practice can be used to predict, with a specified confidence, what the PTMR would be, to within a specified tolerance, if the actual primary test method was conducted on the materials that are within the validated property range and type.  
5.5 This practice provides the user of a process stream analyzer system with useful information from on-going quality control charts to monitor the variation in δ over time, and trigger update of correlation relationship between the analyzer system and primary test method in a timely manner.  
5.6 Validation information obtained in the application of this practice is applicable only to the material type and property range of the materials used to perform the validation. Selection of the property levels and the compositional characteristics of the samples must be suitable for the application of the analyzer system. This practice allows the user to write a comprehensive validation statement for the analyzer system including specific limits for the validated range of application. Th...
SCOPE
1.1 This practice describes procedures and methodologies based on the statistical principles of Practice D6708 to validate whether the degree of agreement between the results produced by a total analyzer system (or its subsystem), versus the results produced by an independent test method that purports to measure the same property, meets user-specified requirements. This is a performance-based validation, to be conducted using a set of materials that are not used a priori in the development of any correlation between the two measurement systems under investigation. A result from the independent test method is herein referred to as a Primary Test Method Result (PTMR).  
1.1.1 The degree of agreement described in 1.1 can be either for PPTMRs and PTMRs measured on the same materials, or for PPTMRs measured on basestocks and PTMRs measured on these same basestocks after constant level additivation.  
1.1.2 In some cases, a two-step procedure is employed. In the first step, the analyzer and PTM are applied to the measurement of the same blendstock material. If the analyzer employed in Step 1 is a multivariate spectrophotometric analyzer, then Practice D6122 is used to access the agreement between the PPTMRs and the PTMRs for this first step. Otherwise, this practice is used to compare the PPTMRs to the PTMRs measured for this blendstock to determine the degree of agreement. In a second step, the PPTMRs produced in Step 1 are used as inputs to a second model that predicts the results obtained when the PTM is applied to the analysis of the finished blended product. Since this second step does not use analyzer readings, the validation of the second step is done independently. Step 2 is only performed on valid Step 1 results. Note that the second model might accommodate variable levels or multiple material additions to the blendstock.  
1.2 This practice assumes any correlation necessary to mitigate systemic biases between the ...

SIGNIFICANCE AND USE
5.1 The primary purpose of this practice is to permit the user to validate numerical values produced by a multivariate, infrared or near-infrared laboratory or process (online or at-line) analyzer calibrated to measure a specific chemical concentration, chemical property, or physical property. If the analyzer results agree with the primary test method to within limits based on the multivariate model for the user-prespecified statistical confidence level, these results can be considered ’validated’ to the user pre-specified confidence limit for a specific application, and hence can be considered useful for that specific application.  
5.2 Procedures are described for verifying that the instrument, the model, and the analyzer system are stable and properly operating.  
5.3 A multivariate analyzer system inherently utilizes a multivariate calibration model. In practice, the model both implicitly and explicitly spans some subset of the population of all possible samples that could be in the complete multivariate sample space. The model is applicable only to samples that fall within the subset population used in the model construction. A sample measurement cannot be validated unless applicability is established. Applicability cannot be assumed.  
5.3.1 Outlier detection methods are used to demonstrate applicability of the calibration model for the analysis of the process sample spectrum. The outlier detection limits are based on historical as well as theoretical criteria. The outlier detection methods are used to establish whether the results obtained by an analyzer are potentially valid. The validation procedures are based on mathematical test criteria that indicate whether the process sample spectrum is within the range spanned by the analyzer system calibration model. If the sample spectrum is an outlier, the analyzer result is invalid. If the sample spectrum is not an outlier, then the analyzer result is valid providing that all other requirements for validity are...
SCOPE
1.1 This practice covers requirements for the validation of measurements made by laboratory, field, or process (online or at-line) infrared (near- or mid-infrared analyzers, or both), and Raman analyzers, used in the calculation of physical, chemical, or quality parameters (that is, properties) of liquid petroleum products and fuels. The properties are calculated from spectroscopic data using multivariate modeling methods. The requirements include verification of adequate instrument performance, verification of the applicability of the calibration model to the spectrum of the sample under test, and verification that the uncertainties associated with the degree of agreement between the results calculated from the infrared or Raman measurements and the results produced by the PTM used for the development of the calibration model meets user-specified requirements. Initially, a limited number of validation samples representative of current production are used to do a local validation. When there is an adequate number of validation samples with sufficient variation in both property level and sample composition to span the model calibration space, the statistical methodology of Practice D6708 can be used to provide general validation of this equivalence over the complete operating range of the analyzer. For cases where adequate property and composition variation is not achieved, local validation shall continue to be used.  
1.1.1 For some applications, the analyzer and PTM are applied to the same material. The application of the multivariate model to the analyzer output (spectrum) directly produces a PPTMR for the same material for which the spectrum was measured. The PPTMRs are compared to the PTMRs measured on the same materials to determine the degree of agreement.  
1.1.2 For other applications, the material measured by the analyzer system is subjected to a consistent additive treatment prior to being analyzed by the PTM...

SIGNIFICANCE AND USE
5.1 This practice is intended for use by parties interested in releasing product by use of vibrational spectroscopic analyzer systems. It is expected to meet the industry need for a written practical reference describing a scientifically systematic approach to show the degree of confidence and degree of uncertainty in analyzer predicted values in relation to the PTM.  
5.2 This is a performance-based practice that relies on the demonstrated quality of the test result and on strict adherence to the referenced standards and the additional requirements in this practice.  
5.3 As part of demonstrating performance, this practice incorporates by reference other ASTM standardized practices as key steps in the process.  
5.4 There are prescriptive requirements included for this practice.  
5.4.1 The practice requires sample temperature to be carefully controlled in analyzer system hardware or that effects of temperature change be compensated in modeling or software.  
5.4.2 Outlier detection capability is required for demonstrating the multivariate calibration model is applicable for the analysis of the sample spectrum, that is, that the analysis interpolates the model, that the sample does not contain a statistically significant amount of unmodeled components above a certain limit based on spectral residual statistic and that the sample spectrum does not fall within gap in the multivariate calibration space.  
5.5 In order to follow this practice, all criteria must be met.  
5.5.1 The user shall investigate the cause of not meeting the practice requirements.  
5.5.2 For any nonconformities noticed, the user shall make corrections to the analyzer system or procedures to conform to the requirements of this practice.
SCOPE
1.1 This practice covers requirements for establishing performance-based qualification of vibrational spectroscopic analyzer systems intended to be used to predict the test result of a material that would be produced by a Primary Test Method (PTM) if the same material is tested by the PTM.  
1.1.1 This practice provides methodology to establish the lower/upper prediction limits associated with the Predicted Primary Test Method Result (PPTMR) in 1.1 with a specified degree of confidence that would contain the PTM result (if tested by the PTM).  
1.1.2 The prediction limits in 1.1.1 can be used to estimate the confidence that product released using the analyzer system based on a PPTMR that meets PTM-based specification limits will meet PTM-based specification limits when tested by a PTM.  
1.2 The practice covers the qualification of on-line, at-line, or laboratory infrared or Raman analyzers used to predict physical, chemical, or performance properties of liquid petroleum products and fuels. Infrared analyzers can operate in the near-infrared (NIR) region, mid-infrared (MIR) region, or both.  
1.2.1 This practice applies to all analyzer systems that can meet the performance requirements defined within.  
1.2.2 This practice is not limited to analyzers designed by any specific instrument manufacturer.  
1.2.3 This practice allows for multiple calibration techniques to create a multivariate model which relates the spectra produced by the analyzer to the corresponding property determined by a PTM. Spectra can be used to predict multiple properties, but the analyzer system performance of each predicted property is qualified individually.  
1.3 The practice describes procedures for establishing performance requirements for analyzer system applications. The user of this practice must establish written protocols to confirm the procedures are being followed.  
1.4 This practice makes use of standard practices, guides, and methods already established in ASTM. Additional requirements are listed within this practice.  
1.5 Any multivariate model that meets performance requirements and detects when the spectrum of a sample is an outlier (analysis that represents an extrapolation...

SIGNIFICANCE AND USE
4.1 This guide is intended to be used in conjunction with Practice D3764 (Case 1) and Practice D6122 (Case 2). Methodology in this guide can be used to determine if a linear correlation can improve the performance of the total analyzer system in terms of its ability to predict the results that the PTM would have been if applied to the same material. This methodology, which is based on the same statistical data treatment as Practice D6708, is used to derive the parameters of the linear relationship and to assess the degree of improvement.  
4.2 This guide provides developers or manufacturers of process stream analyzer systems with useful procedures for developing the capability of newly designed systems for industrial applications that require reliable prediction of measurements of a specific property by a primary test method of a flowing component or product.  
4.3 This guide provides purchasers of process stream analyzer systems with some reliable options for specifying performance requirements for process stream analyzer systems that are used in applications requiring reliable prediction of measurements of a specific property by a primary test method of a flowing component or product.  
4.4 This guide provides the user of a process stream analyzer system with useful information on the work process for establishing the PTM prediction relationship and prediction performance.  
4.5 Prediction (correlation) relationship obtained in the application of this guide is applicable only to the material type and property range of the materials used to perform the study. Selection of the property levels and the compositional characteristics of the samples must be suitable for the application of the analyzer system. Users are cautioned against extrapolation of the prediction relationship beyond the material type and property range used to obtain the relationship.  
4.6 The degree-of-agreement assessment promoted in this guide is based on the statistical principles articula...
SCOPE
1.1 This guide covers a general methodology to develop and assess the linear relationship between results produced by a total analyzer system versus the results produced by the corresponding primary test method (PTM) that the analyzer system is intended to emulate, using the principles and approaches outlined in relevant ASTM standard practices and guides.  
1.2 This guide describes how the statistical methodology of Practice D6708 can be employed to assess agreement between the PTM and analyzer results, and, if necessary, develop linear correlation to further improve the agreement over the complete operating range of the analyzer. For instances where there is insufficient variation in property level to apply the Practice D6708 multi-level methodology, users are referred to Practice D3764 to perform a level specific bias evaluation. The correlation relationship information obtained in the application of this guide is applicable only to the material type and property range of the materials representative of those used to perform the assessment. Users are cautioned against extrapolation of the relationship beyond the material type and property range being studied.  
1.3 This guide applies if the process stream analyzer system and the primary test method are based on the same measurement principle(s), or, if the process stream analyzer system uses a direct and well-understood measurement principle that is similar to the measurement principle of the primary test method. If the process stream analyzer system uses a different measurement technology from the primary test method, provided that the calibration protocol for the direct output of the analyzer does not require use of the PTM, this practice also applies.  
1.4 This guide does not apply if the process stream analyzer system utilizes an indirect or mathematically modeled measurement principle such as chemometric or multivariate analysis techniques where results from ...

SIGNIFICANCE AND USE
5.1 The primary purpose of this practice is to permit the user to validate numerical values produced by a multivariate, infrared or near-infrared laboratory or process (online or at-line) analyzer calibrated to measure a specific chemical concentration, chemical property, or physical property. If the analyzer results agree with the primary test method to within limits based on the multivariate model for the user-prespecified statistical confidence level, these results can be considered ’validated’ to the user pre-specified confidence limit for a specific application, and hence can be considered useful for that specific application.  
5.2 Procedures are described for verifying that the instrument, the model, and the analyzer system are stable and properly operating.  
5.3 A multivariate analyzer system inherently utilizes a multivariate calibration model. In practice, the model both implicitly and explicitly spans some subset of the population of all possible samples that could be in the complete multivariate sample space. The model is applicable only to samples that fall within the subset population used in the model construction. A sample measurement cannot be validated unless applicability is established. Applicability cannot be assumed.  
5.3.1 Outlier detection methods are used to demonstrate applicability of the calibration model for the analysis of the process sample spectrum. The outlier detection limits are based on historical as well as theoretical criteria. The outlier detection methods are used to establish whether the results obtained by an analyzer are potentially valid. The validation procedures are based on mathematical test criteria that indicate whether the process sample spectrum is within the range spanned by the analyzer system calibration model. If the sample spectrum is an outlier, the analyzer result is invalid. If the sample spectrum is not an outlier, then the analyzer result is valid providing that all other requirements for validity are...
SCOPE
1.1 This practice covers requirements for the validation of measurements made by laboratory, field, or process (online or at-line) infrared (near- or mid-infrared analyzers, or both), and Raman analyzers, used in the calculation of physical, chemical, or quality parameters (that is, properties) of liquid petroleum products and fuels. The properties are calculated from spectroscopic data using multivariate modeling methods. The requirements include verification of adequate instrument performance, verification of the applicability of the calibration model to the spectrum of the sample under test, and verification that the uncertainties associated with the degree of agreement between the results calculated from the infrared or Raman measurements and the results produced by the PTM used for the development of the calibration model meets user-specified requirements. Initially, a limited number of validation samples representative of current production are used to do a local validation. When there is an adequate number of validation samples with sufficient variation in both property level and sample composition to span the model calibration space, the statistical methodology of Practice D6708 can be used to provide general validation of this equivalence over the complete operating range of the analyzer. For cases where adequate property and composition variation is not achieved, local validation shall continue to be used.  
1.1.1 For some applications, the analyzer and PTM are applied to the same material. The application of the multivariate model to the analyzer output (spectrum) directly produces a PPTMR for the same material for which the spectrum was measured. The PPTMRs are compared to the PTMRs measured on the same materials to determine the degree of agreement.  
1.1.2 For other applications, the material measured by the analyzer system is subjected to a consistent additive treatment prior to being analyzed by the PTM...

SIGNIFICANCE AND USE
5.1 This practice can be used to establish the validity of the results obtained by an infrared (IR) spectrophotometer or Raman spectrometer at the time the calibration is developed. The ongoing validation of PPTMRs produced by analysis of unknown samples using the multivariate model is covered separately (see for example, Practice D6122).  
5.2 The multivariate calibration procedures define the range over which measurements are valid and demonstrate whether the accuracy and precision of the analysis outputs meet user requirements.  
5.3 This practice describes sampling procedures that must be followed to ensure that the sample which is analyzed by the spectrophotometer or spectrometer is the same as the sample analyzed by the PTM. The sampling procedures apply to analyses done on lab analyzers, at-line analyzers, and online analyzers.
SCOPE
1.1 This practice covers a guide for the multivariate calibration of infrared (IR) spectrophotometers and Raman spectrometers used in determining the physical, chemical, and performance properties of petroleum products, liquid fuels including biofuels, and lubricants. This practice is applicable to analyses conducted in the near infrared (NIR) spectral region (roughly 780 nm to 2500 nm) through the mid infrared (MIR) spectral region (roughly 4000 cm-1 to 40 cm-1). For Raman analyses, this practice is generally applied to Stokes shifted bands that occur roughly 400 cm-1 to 4000 cm-1 below the frequency of the excitation.
Note 1: While the practice described herein deals specifically with mid-infrared, near-infrared, and Raman analysis, much of the mathematical and procedural detail contained herein is also applicable for multivariate quantitative analysis done using other forms of spectroscopy. The user is cautioned that typical and best practices for multivariate quantitative analysis using other forms of spectroscopy may differ from the practice described herein for mid-infrared, near-infrared, and Raman spectroscopies.  
1.2 Procedures for collecting and treating data for developing IR and Raman calibrations are outlined. Definitions, terms, and calibration techniques are described. The calibration establishes a multivariate correlation between the spectral features and the properties to be predicted. This correlation is herein referred to as the multivariate model. Criteria for validating the performance of the multivariate model are described. The properties against which a multivariate model is calibrated and validated are measured by Primary Test Methods (PTMs) and the results of the PTM measurement are herein referred to as Primary Test Method Results (PTMR). The analysis of the spectra using the multivariate model produces a Predicted Primary Test Method Result (PPTMR).  
1.3 The implementation of this practice requires that the IR spectrophotometer or Raman spectrometer has been installed in compliance with the manufacturer's specifications. In addition, it assumes that, at the time of calibration, validation, and analysis, the analyzer is operating at the conditions specified by the manufacturer. The practice includes instrument performance tests which define the instrument performance at the time of calibration, and which qualify the instrument by demonstrating comparable performance during validation and analysis.  
1.4 This practice covers techniques that are routinely applied for online, at-line, and laboratory quantitative analysis. The practice outlined covers the general cases for liquids and solids that are single phase homogeneous samples when presented to the analyzers. Online application is limited by sample viscosity and the ability to introduce sample to the analyzer. All techniques covered require the use of a computer for data collection and analysis.  
1.5 This practice is most typically applied when the spectra and the PTMR against which the analysis is calibrated are measured on the same sample. However, for some applic...

SIGNIFICANCE AND USE
5.1 This practice is intended for use by parties interested in releasing product by use of vibrational spectroscopic analyzer systems. It is expected to meet the industry need for a written practical reference describing a scientifically systematic approach to show the degree of confidence and degree of uncertainty in analyzer predicted values in relation to the PTM.  
5.2 This is a performance-based practice that relies on the demonstrated quality of the test result and on strict adherence to the referenced standards and the additional requirements in this practice.  
5.3 As part of demonstrating performance, this practice incorporates by reference other ASTM standardized practices as key steps in the process.  
5.4 There are prescriptive requirements included for this practice.  
5.4.1 The practice requires sample temperature to be carefully controlled in analyzer system hardware or that effects of temperature change be compensated in modeling or software.  
5.4.2 Outlier detection capability is required for demonstrating the multivariate calibration model is applicable for the analysis of the sample spectrum, that is, that the analysis interpolates the model, that the sample does not contain a statistically significant amount of unmodeled components above a certain limit based on spectral residual statistic and that the sample spectrum does not fall within gap in the multivariate calibration space.  
5.5 In order to follow this practice, all criteria must be met.  
5.5.1 The user shall investigate the cause of not meeting the practice requirements.  
5.5.2 For any nonconformities noticed, the user shall make corrections to the analyzer system or procedures to conform to the requirements of this practice.
SCOPE
1.1 This practice covers requirements for establishing performance-based qualification of vibrational spectroscopic analyzer systems intended to be used to predict the test result of a material that would be produced by a Primary Test Method (PTM) if the same material is tested by the PTM.  
1.1.1 This practice provides methodology to establish the lower/upper prediction limits associated with the Predicted Primary Test Method Result (PPTMR) in 1.1 with a specified degree of confidence that would contain the PTM result (if tested by the PTM).  
1.1.2 The prediction limits in 1.1.1 can be used to estimate the confidence that product released using the analyzer system based on a PPTMR that meets PTM-based specification limits will meet PTM-based specification limits when tested by a PTM.  
1.2 The practice covers the qualification of on-line, at-line, or laboratory infrared or Raman analyzers used to predict physical, chemical, or performance properties of liquid petroleum products and fuels. Infrared analyzers can operate in the near-infrared (NIR) region, mid-infrared (MIR) region, or both.  
1.2.1 This practice applies to all analyzer systems that can meet the performance requirements defined within.  
1.2.2 This practice is not limited to analyzers designed by any specific instrument manufacturer.  
1.2.3 This practice allows for multiple calibration techniques to create a multivariate model which relates the spectra produced by the analyzer to the corresponding property determined by a PTM. Spectra can be used to predict multiple properties, but the analyzer system performance of each predicted property is qualified individually.  
1.3 The practice describes procedures for establishing performance requirements for analyzer system applications. The user of this practice must establish written protocols to confirm the procedures are being followed.  
1.4 This practice makes use of standard practices, guides, and methods already established in ASTM. Additional requirements are listed within this practice.  
1.5 Any multivariate model that meets performance requirements and detects when the spectrum of a sample is an outlier (analysis that represents an extrapolation...

SIGNIFICANCE AND USE
5.1 The primary purpose of this practice is to permit the user to validate numerical values produced by a multivariate, infrared or near-infrared laboratory or process (online or at-line) analyzer calibrated to measure a specific chemical concentration, chemical property, or physical property. If the analyzer results agree with the primary test method to within limits based on the multivariate model for the user-prespecified statistical confidence level, these results can be considered ’validated’ to the user pre-specified confidence limit for a specific application, and hence can be considered useful for that specific application.  
5.2 Procedures are described for verifying that the instrument, the model, and the analyzer system are stable and properly operating.  
5.3 A multivariate analyzer system inherently utilizes a multivariate calibration model. In practice, the model both implicitly and explicitly spans some subset of the population of all possible samples that could be in the complete multivariate sample space. The model is applicable only to samples that fall within the subset population used in the model construction. A sample measurement cannot be validated unless applicability is established. Applicability cannot be assumed.  
5.3.1 Outlier detection methods are used to demonstrate applicability of the calibration model for the analysis of the process sample spectrum. The outlier detection limits are based on historical as well as theoretical criteria. The outlier detection methods are used to establish whether the results obtained by an analyzer are potentially valid. The validation procedures are based on mathematical test criteria that indicate whether the process sample spectrum is within the range spanned by the analyzer system calibration model. If the sample spectrum is an outlier, the analyzer result is invalid. If the sample spectrum is not an outlier, then the analyzer result is valid providing that all other requirements for validity are...
SCOPE
1.1 This practice covers requirements for the validation of measurements made by laboratory, field, or process (online or at-line) infrared (near- or mid-infrared analyzers, or both), and Raman analyzers, used in the calculation of physical, chemical, or quality parameters (that is, properties) of liquid petroleum products and fuels. The properties are calculated from spectroscopic data using multivariate modeling methods. The requirements include verification of adequate instrument performance, verification of the applicability of the calibration model to the spectrum of the sample under test, and verification that the uncertainties associated with the degree of agreement between the results calculated from the infrared or Raman measurements and the results produced by the PTM used for the development of the calibration model meets user-specified requirements. Initially, a limited number of validation samples representative of current production are used to do a local validation. When there is an adequate number of validation samples with sufficient variation in both property level and sample composition to span the model calibration space, the statistical methodology of Practice D6708 can be used to provide general validation of this equivalence over the complete operating range of the analyzer. For cases where adequate property and composition variation is not achieved, local validation shall continue to be used.  
1.1.1 For some applications, the analyzer and PTM are applied to the same material. The application of the multivariate model to the analyzer output (spectrum) directly produces a PPTMR for the same material for which the spectrum was measured. The PPTMRs are compared to the PTMRs measured on the same materials to determine the degree of agreement.  
1.1.2 For other applications, the material measured by the analyzer system is subjected to a consistent additive treatment prior to being analyzed by the PTM...

SIGNIFICANCE AND USE
5.1 This practice is intended for use by parties interested in releasing product by use of vibrational spectroscopic analyzer systems. It is expected to meet the industry need for a written practical reference describing a scientifically systematic approach to show the degree of confidence and degree of uncertainty in analyzer predicted values in relation to the PTM.  
5.2 This is a performance-based practice that relies on the demonstrated quality of the test result and on strict adherence to the referenced standards and the additional requirements in this practice.  
5.3 As part of demonstrating performance, this practice incorporates by reference other ASTM standardized practices as key steps in the process.  
5.4 There are prescriptive requirements included for this practice.  
5.4.1 The practice requires sample temperature to be carefully controlled in analyzer system hardware or that effects of temperature change be compensated in modeling or software.  
5.4.2 Outlier detection capability is required for demonstrating the multivariate calibration model is applicable for the analysis of the sample spectrum, that is, that the analysis interpolates the model, that the sample does not contain a statistically significant amount of unmodeled components above a certain limit based on spectral residual statistic and that the sample spectrum does not fall within gap in the multivariate calibration space.  
5.5 In order to follow this practice, all criteria must be met.  
5.5.1 The user shall investigate the cause of not meeting the practice requirements.  
5.5.2 For any nonconformities noticed, the user shall make corrections to the analyzer system or procedures to conform to the requirements of this practice.
SCOPE
1.1 This practice covers requirements for establishing performance-based qualification of vibrational spectroscopic analyzer systems intended to be used to predict the test result of a material that would be produced by a Primary Test Method (PTM) if the same material is tested by the PTM.  
1.1.1 This practice provides methodology to establish the lower/upper prediction limits associated with the Predicted Primary Test Method Result (PPTMR) in 1.1 with a specified degree of confidence that would contain the PTM result (if tested by the PTM).  
1.1.2 The prediction limits in 1.1.1 can be used to estimate the confidence that product released using the analyzer system based on a PPTMR that meets PTM-based specification limits will meet PTM-based specification limits when tested by a PTM.  
1.2 The practice covers the qualification of on-line, at-line, or laboratory infrared or Raman analyzers used to predict physical, chemical, or performance properties of liquid petroleum products and fuels. Infrared analyzers can operate in the near-infrared (NIR) region, mid-infrared (MIR) region, or both.  
1.2.1 This practice applies to all analyzer systems that can meet the performance requirements defined within.  
1.2.2 This practice is not limited to analyzers designed by any specific instrument manufacturer.  
1.2.3 This practice allows for multiple calibration techniques to create a multivariate model which relates the spectra produced by the analyzer to the corresponding property determined by a PTM. Spectra can be used to predict multiple properties, but the analyzer system performance of each predicted property is qualified individually.  
1.3 The practice describes procedures for establishing performance requirements for analyzer system applications. The user of this practice must establish written protocols to confirm the procedures are being followed.  
1.4 This practice makes use of standard practices, guides, and methods already established in ASTM. Additional requirements are listed within this practice.  
1.5 Any multivariate model that meets performance requirements and detects when the spectrum of a sample is an outlier (analysis that represents an extrapolation...

SIGNIFICANCE AND USE
5.1 This practice can be used to establish the validity of the results obtained by an infrared (IR) spectrophotometer or Raman spectrometer at the time the calibration is developed. The ongoing validation of PPTMRs produced by analysis of unknown samples using the multivariate model is covered separately (see for example, Practice D6122).  
5.2 The multivariate calibration procedures define the range over which measurements are valid and demonstrate whether the accuracy and precision of the analysis outputs meet user requirements.  
5.3 This practice describes sampling procedures that must be followed to ensure that the sample which is analyzed by the spectrophotometer or spectrometer is the same as the sample analyzed by the PTM. The sampling procedures apply to analyses done on lab analyzers, at-line analyzers, and online analyzers.
SCOPE
1.1 This practice covers a guide for the multivariate calibration of infrared (IR) spectrophotometers and Raman spectrometers used in determining the physical, chemical, and performance properties of petroleum products, liquid fuels including biofuels, and lubricants. This practice is applicable to analyses conducted in the near infrared (NIR) spectral region (roughly 780 nm to 2500 nm) through the mid infrared (MIR) spectral region (roughly 4000 cm-1 to 40 cm-1). For Raman analyses, this practice is generally applied to Stokes shifted bands that occur roughly 400 cm-1 to 4000 cm-1 below the frequency of the excitation.
Note 1: While the practice described herein deals specifically with mid-infrared, near-infrared, and Raman analysis, much of the mathematical and procedural detail contained herein is also applicable for multivariate quantitative analysis done using other forms of spectroscopy. The user is cautioned that typical and best practices for multivariate quantitative analysis using other forms of spectroscopy may differ from the practice described herein for mid-infrared, near-infrared, and Raman spectroscopies.  
1.2 Procedures for collecting and treating data for developing IR and Raman calibrations are outlined. Definitions, terms, and calibration techniques are described. The calibration establishes a multivariate correlation between the spectral features and the properties to be predicted. This correlation is herein referred to as the multivariate model. Criteria for validating the performance of the multivariate model are described. The properties against which a multivariate model is calibrated and validated are measured by Primary Test Methods (PTMs) and the results of the PTM measurement are herein referred to as Primary Test Method Results (PTMR). The analysis of the spectra using the multivariate model produces a Predicted Primary Test Method Result (PPTMR).  
1.3 The implementation of this practice requires that the IR spectrophotometer or Raman spectrometer has been installed in compliance with the manufacturer's specifications. In addition, it assumes that, at the time of calibration, validation, and analysis, the analyzer is operating at the conditions specified by the manufacturer. The practice includes instrument performance tests which define the instrument performance at the time of calibration, and which qualify the instrument by demonstrating comparable performance during validation and analysis.  
1.4 This practice covers techniques that are routinely applied for online, at-line, and laboratory quantitative analysis. The practice outlined covers the general cases for liquids and solids that are single phase homogeneous samples when presented to the analyzers. Online application is limited by sample viscosity and the ability to introduce sample to the analyzer. All techniques covered require the use of a computer for data collection and analysis.  
1.5 This practice is most typically applied when the spectra and the PTMR against which the analysis is calibrated are measured on the same sample. However, for some applic...

SIGNIFICANCE AND USE
5.1 The primary purpose of this practice is to permit the user to validate numerical values produced by a multivariate, infrared or near-infrared laboratory or process (online or at-line) analyzer calibrated to measure a specific chemical concentration, chemical property, or physical property. If the analyzer results agree with the primary test method to within limits based on the multivariate model for the user-prespecified statistical confidence level, these results can be considered ’validated’ to the user pre-specified confidence limit for a specific application, and hence can be considered useful for that specific application.  
5.2 Procedures are described for verifying that the instrument, the model, and the analyzer system are stable and properly operating.  
5.3 A multivariate analyzer system inherently utilizes a multivariate calibration model. In practice, the model both implicitly and explicitly spans some subset of the population of all possible samples that could be in the complete multivariate sample space. The model is applicable only to samples that fall within the subset population used in the model construction. A sample measurement cannot be validated unless applicability is established. Applicability cannot be assumed.  
5.3.1 Outlier detection methods are used to demonstrate applicability of the calibration model for the analysis of the process sample spectrum. The outlier detection limits are based on historical as well as theoretical criteria. The outlier detection methods are used to establish whether the results obtained by an analyzer are potentially valid. The validation procedures are based on mathematical test criteria that indicate whether the process sample spectrum is within the range spanned by the analyzer system calibration model. If the sample spectrum is an outlier, the analyzer result is invalid. If the sample spectrum is not an outlier, then the analyzer result is valid providing that all other requirements for validity are...
SCOPE
1.1 This practice covers requirements for the validation of measurements made by laboratory, field, or process (online or at-line) infrared (near- or mid-infrared analyzers, or both), and Raman analyzers, used in the calculation of physical, chemical, or quality parameters (that is, properties) of liquid petroleum products and fuels. The properties are calculated from spectroscopic data using multivariate modeling methods. The requirements include verification of adequate instrument performance, verification of the applicability of the calibration model to the spectrum of the sample under test, and verification that the uncertainties associated with the degree of agreement between the results calculated from the infrared or Raman measurements and the results produced by the PTM used for the development of the calibration model meets user-specified requirements. Initially, a limited number of validation samples representative of current production are used to do a local validation. When there is an adequate number of validation samples with sufficient variation in both property level and sample composition to span the model calibration space, the statistical methodology of Practice D6708 can be used to provide general validation of this equivalence over the complete operating range of the analyzer. For cases where adequate property and composition variation is not achieved, local validation shall continue to be used.  
1.1.1 For some applications, the analyzer and PTM are applied to the same material. The application of the multivariate model to the analyzer output (spectrum) directly produces a PPTMR for the same material for which the spectrum was measured. The PPTMRs are compared to the PTMRs measured on the same materials to determine the degree of agreement.  
1.1.2 For other applications, the material measured by the analyzer system is subjected to a consistent additive treatment prior to being analyzed by the PTM...

SIGNIFICANCE AND USE
5.1 The primary purpose of this practice is to permit the user to validate numerical values produced by a multivariate, infrared or near-infrared laboratory or process (online or at-line) analyzer calibrated to measure a specific chemical concentration, chemical property, or physical property. If the analyzer results agree with the primary test method to within limits based on the multivariate model for the user-prespecified statistical confidence level, these results can be considered ’validated’ to the user pre-specified confidence limit for a specific application, and hence can be considered useful for that specific application.  
5.2 Procedures are described for verifying that the instrument, the model, and the analyzer system are stable and properly operating.  
5.3 A multivariate analyzer system inherently utilizes a multivariate calibration model. In practice, the model both implicitly and explicitly spans some subset of the population of all possible samples that could be in the complete multivariate sample space. The model is applicable only to samples that fall within the subset population used in the model construction. A sample measurement cannot be validated unless applicability is established. Applicability cannot be assumed.  
5.3.1 Outlier detection methods are used to demonstrate applicability of the calibration model for the analysis of the process sample spectrum. The outlier detection limits are based on historical as well as theoretical criteria. The outlier detection methods are used to establish whether the results obtained by an analyzer are potentially valid. The validation procedures are based on mathematical test criteria that indicate whether the process sample spectrum is within the range spanned by the analyzer system calibration model. If the sample spectrum is an outlier, the analyzer result is invalid. If the sample spectrum is not an outlier, then the analyzer result is valid providing that all other requirements for validity are...
SCOPE
1.1 This practice covers requirements for the validation of measurements made by laboratory or process (online or at-line) near- or mid-infrared analyzers, or both, used in the calculation of physical, chemical, or quality parameters (that is, properties) of liquid petroleum products and fuels. The properties are calculated from spectroscopic data using multivariate modeling methods. The requirements include verification of adequate instrument performance, verification of the applicability of the calibration model to the spectrum of the sample under test, and verification that the uncertainties associated with the degree of agreement between the results calculated from the infrared measurements and the results produced by the PTM used for the development of the calibration model meets user-specified requirements. Initially, a limited number of validation samples representative of current production are used to do a local validation. When there is an adequate number of validation samples with sufficient variation in both property level and sample composition to span the model calibration space, the statistical methodology of Practice D6708 can be used to provide general validation of this equivalence over the complete operating range of the analyzer. For cases where adequate property and composition variation is not achieved, local validation shall continue to be used.  
1.1.1 For some applications, the analyzer and PTM are applied to the same material. The application of the multivariate model to the analyzer output (spectrum) directly produces a PPTMR for the same material for which the spectrum was measured. The PPTMRs are compared to the PTMRs measured on the same materials to determine the degree of agreement.  
1.1.2 For other applications, the material measured by the analyzer system is subjected to a consistent additive treatment prior to being analyzed by the PTM. The application of the multivariate model to th...

SIGNIFICANCE AND USE
5.1 This practice can be used to quantify the performance of a process stream analyzer system or its subsystem in terms of precision and bias relative to those of a primary test method for the property of interest.  
5.2 This practice provides developers or manufacturers of process stream analyzer systems with useful procedures for evaluating the capability of newly designed systems for industrial applications that require reliable prediction of measurements of a specific property by a primary test method of a flowing component or product.  
5.3 This practice provides purchasers of process stream analyzer systems with some reliable options for specifying acceptance test requirements for process stream analyzer systems at the time of commissioning to ensure the system is capable of making the desired property measurement with the appropriate precision or bias specifications, or both.  
5.4 PPTMR from Analyzer Systems validated in accordance with this practice can be used to predict, with a specified confidence, what the PTMR would be, to within a specified tolerance, if the actual primary test method was conducted on the materials that are within the validated property range and type.  
5.5 This practice provides the user of a process stream analyzer system with useful information from on-going quality control charts to monitor the variation in Δ over time, and trigger update of correlation relationship between the analyzer system and primary test method in a timely manner.  
5.6 Validation information obtained in the application of this practice is applicable only to the material type and property range of the materials used to perform the validation. Selection of the property levels and the compositional characteristics of the samples must be suitable for the application of the analyzer system. This practice allows the user to write a comprehensive validation statement for the analyzer system including specific limits for the validated range of application. Th...
SCOPE
1.1 This practice describes procedures and methodologies based on the statistical principles of Practice D6708 to validate whether the degree of agreement between the results produced by a total analyzer system (or its subsystem), versus the results produced by an independent test method that purports to measure the same property, meets user-specified requirements. This is a performance-based validation, to be conducted using a set of materials that are not used a priori in the development of any correlation between the two measurement systems under investigation. A result from the independent test method is herein referred to as a Primary Test Method Result (PTMR).  
1.1.1 The degree of agreement described in 1.1 can be either for PPTMRs and PTMRs measured on the same materials, or for PPTMRs measured on basestocks and PTMRs measured on these same basestocks after constant level additivation.  
1.1.2 In some cases, a two-step procedure is employed. In the first step, the analyzer and PTM are applied to the measurement of the same blendstock material. If the analyzer employed in Step 1 is a multivariate spectrophotometric analyzer, then Practice D6122 is used to access the agreement between the PPTMRs and the PTMRs for this first step. Otherwise, this practice is used to compare the PPTMRs to the PTMRs measured for this blendstock to determine the degree of agreement. In a second step, the PPTMRs produced in Step 1 are used as inputs to a second model that predicts the results obtained when the PTM is applied to the analysis of the finished blended product. Since this second step does not use analyzer readings, the validation of the second step is done independently. Step 2 is only performed on valid Step 1 results. Note that the second model might accommodate variable levels or multiple material additions to the blendstock.  
1.2 This practice assumes any correlation necessary to mitigate systemic biases between the ...

SIGNIFICANCE AND USE
5.1 The primary purpose of this practice is to permit the user to validate numerical values produced by a multivariate, infrared or near-infrared laboratory or process (online or at-line) analyzer calibrated to measure a specific chemical concentration, chemical property, or physical property. If the analyzer results agree with the primary test method to within limits based on the multivariate model for the user-prespecified statistical confidence level, these results can be considered ’validated’ to the user pre-specified confidence limit for a specific application, and hence can be considered useful for that specific application.  
5.2 Procedures are described for verifying that the instrument, the model, and the analyzer system are stable and properly operating.  
5.3 A multivariate analyzer system inherently utilizes a multivariate calibration model. In practice, the model both implicitly and explicitly spans some subset of the population of all possible samples that could be in the complete multivariate sample space. The model is applicable only to samples that fall within the subset population used in the model construction. A sample measurement cannot be validated unless applicability is established. Applicability cannot be assumed.  
5.3.1 Outlier detection methods are used to demonstrate applicability of the calibration model for the analysis of the process sample spectrum. The outlier detection limits are based on historical as well as theoretical criteria. The outlier detection methods are used to establish whether the results obtained by an analyzer are potentially valid. The validation procedures are based on mathematical test criteria that indicate whether the process sample spectrum is within the range spanned by the analyzer system calibration model. If the sample spectrum is an outlier, the analyzer result is invalid. If the sample spectrum is not an outlier, then the analyzer result is valid providing that all other requirements for validity are...
SCOPE
1.1 This practice covers requirements for the validation of measurements made by laboratory or process (online or at-line) near- or mid-infrared analyzers, or both, used in the calculation of physical, chemical, or quality parameters (that is, properties) of liquid petroleum products and fuels. The properties are calculated from spectroscopic data using multivariate modeling methods. The requirements include verification of adequate instrument performance, verification of the applicability of the calibration model to the spectrum of the sample under test, and verification that the uncertainties associated with the degree of agreement between the results calculated from the infrared measurements and the results produced by the PTM used for the development of the calibration model meets user-specified requirements. Initially, a limited number of validation samples representative of current production are used to do a local validation. When there is an adequate number of validation samples with sufficient variation in both property level and sample composition to span the model calibration space, the statistical methodology of Practice D6708 can be used to provide general validation of this equivalence over the complete operating range of the analyzer. For cases where adequate property and composition variation is not achieved, local validation shall continue to be used.  
1.1.1 For some applications, the analyzer and PTM are applied to the same material. The application of the multivariate model to the analyzer output (spectrum) directly produces a PPTMR for the same material for which the spectrum was measured. The PPTMRs are compared to the PTMRs measured on the same materials to determine the degree of agreement.  
1.1.2 For other applications, the material measured by the analyzer system is subjected to a consistent treatment prior to being analyzed by the PTM. The application of the multivariate model to the analyze...

SIGNIFICANCE AND USE
4.1 Contractual or local regulation, or both, permitting, the FPAPV calculated according to this practice can be used to represent the average property of the quantity of material collected.  
4.2 Due to the averaging and appropriate weighting of analysis results, the FPAPV estimate of the property for the collected material is expected to be more representative and more precise than an estimate based on a small number of analyses on a few samples.
Note 1: For applications where the on-line analyzer system result is being used in direct feedback control in a contiguous manner, the true property distribution for a large population of batches with essentially identical FPAPV's is expected to be Gaussian, centered at the FPAPV value, with a standard deviation that is no less than the long term site precision standard deviation of the analyzer system.  
4.3 If the measured property value is used to predict another property value through the use of an appropriate correlation equation, the FPAPV can also be used as a suitable prediction of that property.  
4.4 The most recently updated FPAPV can be used to represent the property of the material currently accumulated in the tank or vessel for process control or material disposition decisions, or both.
SCOPE
1.1 This practice covers a technique for calculating a flow-proportioned average property value (FPAPV) for a batch of in-line blended product or process stream material that is collected over time and isolated in a storage tank or vessel, using a combination of on-line or at-line measurements taken at regular intervals of the property and flow rates.  
1.2 The FPAPV methodology uses regularly collected on- line or at-line process analyzer measurements, flow, and assessment of other appropriate process measurements or values, to calculate a flow-proportioned average property value in accordance with flow quantity units of material produced.  
1.3 When the collecting vessel contains a heel (retained material prior to receipt of the production batch), both the property value and quantity of the heel material can be predetermined and factored into the calculation of the FPAPV for the new batch.  
1.4 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.  
1.5 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

SIGNIFICANCE AND USE
5.1 The primary purpose of this practice is to permit the user to validate numerical values produced by a multivariate, infrared or near-infrared laboratory or process (online or at-line) analyzer calibrated to measure a specific chemical concentration, chemical property, or physical property. If the analyzer results agree with the primary test method to within limits based on the multivariate model for the user-prespecified statistical confidence level, these results can be considered ’validated’ to the user pre-specified confidence limit for a specific application, and hence can be considered useful for that specific application.  
5.2 Procedures are described for verifying that the instrument, the model, and the analyzer system are stable and properly operating.  
5.3 A multivariate analyzer system inherently utilizes a multivariate calibration model. In practice, the model both implicitly and explicitly spans some subset of the population of all possible samples that could be in the complete multivariate sample space. The model is applicable only to samples that fall within the subset population used in the model construction. A sample measurement cannot be validated unless applicability is established. Applicability cannot be assumed.  
5.3.1 Outlier detection methods are used to demonstrate applicability of the calibration model for the analysis of the process sample spectrum. The outlier detection limits are based on historical as well as theoretical criteria. The outlier detection methods are used to establish whether the results obtained by an analyzer are potentially valid. The validation procedures are based on mathematical test criteria that indicate whether the process sample spectrum is within the range spanned by the analyzer system calibration model. If the sample spectrum is an outlier, the analyzer result is invalid. If the sample spectrum is not an outlier, then the analyzer result is valid providing that all other requirements for validity are...
SCOPE
1.1 This practice covers requirements for the validation of measurements made by laboratory or process (online or at-line) near- or mid-infrared analyzers, or both, used in the calculation of physical, chemical, or quality parameters (that is, properties) of liquid petroleum products and fuels. The properties are calculated from spectroscopic data using multivariate modeling methods. The requirements include verification of adequate instrument performance, verification of the applicability of the calibration model to the spectrum of the sample under test, and verification that the degree of agreement between the results calculated from the infrared measurements and the results produced by the PTM used for the development of the calibration model meets user-specified requirements. Initially, a limited number of validation samples representative of current production are used to do a local validation. When there is an adequate number of validation samples with sufficient variation in both property level and sample composition to span the model calibration space, the statistical methodology of Practice D6708 can be used to provide general validation of this equivalence over the complete operating range of the analyzer. For cases where adequate property and composition variation is not achieved, local validation continues to be used.  
1.1.1 For some applications, the analyzer and PTM are applied to the same material. The application of the multivariate model to the analyzer output (spectrum) directly produces a PPTMR for the same material for which the spectrum was measured. The PPTMRs are compared to the PTMRs measured on the same materials to determine the degree of agreement.  
1.1.2 For other applications, the material measured by the analyzer system is subjected to a consistent treatment prior to being analyzed by the PTM. The application of the multivariate model to the analyzer output (spectrum) produces a PPTMR fo...

SIGNIFICANCE AND USE
5.1 Analyzer systems require representative samples of petroleum products delivered in a timely manner to (1) facilitate the control of process or blending units or (2) calculate a flow proportioned property value.  
5.2 Representative samples of petroleum products are required for the determination of chemical and physical properties. These properties are used to establish the relationship between the analyzer system and the primary test method during initial and ongoing validation of the system.  
5.3 Representative samples of petroleum products are tested to determine the chemical and physical properties of a batch offered for tender.
SCOPE
1.1 This practice covers the performance requirements for sample systems employed to deliver process stream samples (1) to analyzer system for analyses or (2) for analyzer validation or (3) for composite sample systems. It also outlines the selection and operation of line or batch sampling equipment intended for analyzer flow proportioned average property value system validation. Sample handling, mixing, and conditioning procedures are required to ensure that a representative sample of the liquid petroleum product is collected from the sampling source.  
1.2 Applicable Fluids—This practice is applicable to single liquid phase petroleum products whose vapor pressure at sampling and sample storage conditions is less than or equal to 110 kPa (16.0 psi), and, with a D86 final boiling point less than or equal to 400 °C (752 °F).  
1.2.1 Specialized sample handling may be necessary to maintain sample integrity of more volatile materials at high temperatures or extended residence time in the receiver. Such handling requirements are not within the scope of this practice. Users should consult the analytical methods to be performed on the sample for special sample storage or conditioning requirements.  
1.3 Some or all of the processes outlined in this practice may be applicable to other liquids. Applying this practice to other liquids will require the consideration of additional methods and practices. It is the responsibility of the user of this standard to identify any and all applicable safety and sampling considerations and establish appropriate procedures to handle these additional considerations.  
1.4 The values stated in SI units are to be regarded as the standard. The values given in parentheses are for information only.  
1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.  
1.6 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

SIGNIFICANCE AND USE
4.1 The analyzer site precision is an estimate of the variability that can be expected in a UAR or a PPTMR produced by an analyzer when applied to the analysis of the same material over an extended time period.  
4.2 For applications where the process analyzer system results are required to agree with results produced from an independent PTM, a mathematical function is derived that relates the UARs to the PPTMRs. The application of this mathematical function to an analyzer result produces a predicted PPTMR. For analyzers where the mathematical function, that is, a correlation, is developed by D7235, the analyzer site precision of the UARs is a required input to the computation.  
4.3 After the correlation relationship between the analyzer results and primary test method results has been established, a probationary validation (see D3764 and D6122) is performed using an independent but limited set of materials that were not part of the correlation activity. This probationary validation is intended to demonstrate that the PPTMRs agree with the PTMRs to within user-specified requirements for the analyzer system application. The analyzer site precision is a required input to the probationary validation procedures.  
4.3.1 If the process stream analyzer system and the primary test method are based on the same measurement principle(s), or, if the process stream analyzer system uses a direct and well-understood measurement principle that is similar to the measurement principle of the PTM then validation is done via D3764. Practice D3764 also applies if the process stream analyzer system uses a different measurement technology from the PTM, provided that the calibration protocol for the direct output of the analyzer does not require use of the PTM.  
4.3.2 If the process stream analyzer system utilizes an indirect or mathematically modeled measurement principle such as chemometric or multivariate analysis techniques where PTMRs are required for the development of the che...
SCOPE
1.1 This practice describes a procedure to quantify the site precision of a process analyzer via repetitive measurement of a single process sample over an extended time period. The procedure may be applied to multiple process samples to obtain site precision estimates at different property levels  
1.1.1 The site precision is required for use of the statistical methodology of D6708 in establishing the correlation between analyzer results and primary test method results using Practice D7235.  
1.1.2 The site precision is also required when employing the statistical methodology of D6708 to validate a process analyzer via Practices D3764 or D6122.  
1.2 This practice is not applicable to in-line analyzers where the same quality control sample cannot be repetitively introduced.  
1.3 This practice is meant to be applied to analyzers that measure physical properties or compositions.  
1.4 This practice can be applied to any process analyzer system where the feed stream can be captured and stored in sufficient quantity with no stratification or stability concerns.  
1.4.1 The captured stream sample introduction must be able to meet the process analyzer sample conditioning requirements, feed temperature and inlet pressure.  
1.4.2 This practice is designed for use with samples that are single liquid phase, petroleum products whose vapor pressure, at sampling and sample storage conditions, is less than or equal to 110 kPa (16.0 psi) absolute and whose D86 final boiling point is less than or equal to 400 °C (752 °F).
Note 1: The general procedures described in this practice may be applicable to materials outside this range, including multiphase materials, but such application may involve special sampling and safety considerations which are outside the scope of this practice.  
1.5 The values for operating conditions are stated in SI units and are to be regarded as the standard. The values given in parentheses are the hi...

SCOPE
1.1 This practice covers requirements for the validation of measurements made by laboratory or process (online or at-line) near- or mid-infrared analyzers, or both, used in the calculation of physical, chemical, or quality parameters (that is, properties) of liquid petroleum products and fuels. The properties are calculated from spectroscopic data using multivariate modeling methods. The requirements include verification of adequate instrument performance, verification of the applicability of the calibration model to the spectrum of the sample under test, and verification that the degree of agreement between the results calculated from the infrared measurements and the results produced by the PTM used for the development of the calibration model meets user-specified requirements. Initially, a limited number of validation samples representative of current production are used to do a local validation. When there is an adequate number of validation samples with sufficient variation in both property level and sample composition to span the model calibration space, the statistical methodology of Practice D6708 can be used to provide general validation of this equivalence over the complete operating range of the analyzer. For cases where adequate property and composition variation is not achieved, local validation continues to be used.  
1.1.1 For some applications, the analyzer and PTM are applied to the same material. The application of the multivariate model to the analyzer output (spectrum) directly produces a PPTMR for the same material for which the spectrum was measured. The PPTMRs are compared to the PTMRs measured on the same materials to determine the degree of agreement.  
1.1.2 For other applications, the material measured by the analyzer system is subjected to a consistent treatment prior to being analyzed by the PTM. The application of the multivariate model to the analyzer output (spectrum) produces a PPTMR for the treated material. The PPTMRs based on the analyzer outputs are compared to the PTMRs measured on the treated materials to determine the degree of agreement.  
1.2 Multiple physical, chemical, or quality properties of the sample under test are typically predicted from a single spectral measurement. In applying this practice, each property prediction is validated separately. The separate validation procedures for each property may share common features, and be affected by common effects, but the performance of each property prediction is evaluated independently. The user will typically have multiple validation procedures running simultaneously in parallel.  
1.3 Results used in analyzer validation are for samples that were not used in the development of the multivariate model, and for spectra which are not outliers or nearest neighbor inliers relative to the multivariate model.  
1.4 When the number, composition range or property range of available validation samples do not span the model calibration range, a local validation is done using available samples representative of current production. When the number, composition range and property range of available validation samples becomes comparable to those of the model calibration set, a general validation can be done.  
1.4.1 Local Validation:  
1.4.1.1 The calibration samples used in developing the multivariate model must show adequate compositional and property variation to enable the development of a meaningful correlation, and must span the compositional range of samples to be analyzed using the model to ensure that such analyses are done via interpolation rather than extrapolation. The Standard Error of Calibration (SEC) is a measure of how well the PTMRs and PPTMRs agree for this set of calibration samples. SEC includes contributions from spectrum measurement error, PTM measurement error, and model error. Sample (type) specific biases are a part of the model error. Typically, spectroscopic analyzers are very precise, so that spe...

SIGNIFICANCE AND USE
5.1 Analyzer systems require representative samples of petroleum products delivered in a timely manner to (1) facilitate the control of process or blending units or (2) calculate a flow proportioned property value.  
5.2 Representative samples of petroleum products are required for the determination of chemical and physical properties. These properties are used to establish the relationship between the analyzer system and the primary test method during initial and ongoing validation of the system.  
5.3 Representative samples of petroleum products are tested to determine the chemical and physical properties of a batch offered for tender.
SCOPE
1.1 This practice covers the performance requirements for sample systems employed to deliver process stream samples (1) to analyzer system for analyses or (2) for analyzer validation or (3) for composite sample systems. It also outlines the selection and operation of line or batch sampling equipment intended for analyzer flow proportioned average property value system validation. Sample handling, mixing, and conditioning procedures are required to ensure that a representative sample of the liquid petroleum product is collected from the sampling source.  
1.2 Applicable Fluids—This practice is applicable to single liquid phase petroleum products whose vapor pressure at sampling and sample storage conditions is less than or equal to 110 kPa (16.0 psi), and, with a D86 final boiling point less than or equal to 400 °C (752 °F).  
1.2.1 Specialized sample handling may be necessary to maintain sample integrity of more volatile materials at high temperatures or extended residence time in the receiver. Such handling requirements are not within the scope of this practice. Users should consult the analytical methods to be performed on the sample for special sample storage or conditioning requirements.  
1.3 Some or all of the processes outlined in this practice may be applicable to other liquids. Applying this practice to other liquids will require the consideration of additional methods and practices. It is the responsibility of the user of this standard to identify any and all applicable safety and sampling considerations and establish appropriate procedures to handle these additional considerations.  
1.4 The values stated in SI units are to be regarded as the standard. The values given in parentheses are for information only.  
1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use.  
1.6 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee.

SIGNIFICANCE AND USE
4.1 This guide is intended to be used in conjunction with Practice D3764 (Case 1) and Practice D6122 (Case 2). Methodology in this guide can be used to determine if a linear correlation can improve the performance of the total analyzer system in terms of its ability to predict the results that the PTM would have been if applied to the same material. This methodology, which is based on the same statistical data treatment as Practice D6708, is use to derive the parameters of the linear relationship and to assess the degree of improvement.  
4.2 This guide provides developers or manufacturers of process stream analyzer systems with useful procedures for developing the capability of newly designed systems for industrial applications that require reliable prediction of measurements of a specific property by a primary test method of a flowing component or product.  
4.3 This guide provides purchasers of process stream analyzer systems with some reliable options for specifying performance requirements for process stream analyzer systems that are used in applications requiring reliable prediction of measurements of a specific property by a primary test method of a flowing component or product.  
4.4 This guide provides the user of a process stream analyzer system with useful information on the work process for establishing the PTM prediction relationship and prediction performance.  
4.5 Prediction (correlation) relationship obtained in the application of this guide is applicable only to the material type and property range of the materials used to perform the study. Selection of the property levels and the compositional characteristics of the samples must be suitable for the application of the analyzer system. Users are cautioned against extrapolation of the prediction relationship beyond the material type and property range used to obtain the relationship.  
4.6 The degree-of-agreement assessment promoted in this guide is based on the statistical principles articulat...
SCOPE
1.1 This guide covers a general methodology to develop and assess the linear relationship between results produced by a total analyzer system versus the results produced by the corresponding primary test method (PTM) that the analyzer system is intended to emulate, using the principles and approaches outlined in relevant ASTM standard practices and guides.  
1.2 This guide describes how the statistical methodology of Practice D6708 can be employed to assess agreement between the PTM and analyzer results, and, if necessary, develop linear correlation to further improve the agreement over the complete operating range of the analyzer. For instances where there is insufficient variation in property level to apply the Practice D6708 multi-level methodology, users are referred to Practice D3764 to perform a level specific bias evaluation. The correlation relationship information obtained in the application of this guide is applicable only to the material type and property range of the materials representative of those used to perform the assessment. Users are cautioned against extrapolation of the relationship beyond the material type and property range being studied.  
1.3 This guide applies if the process stream analyzer system and the primary test method are based on the same measurement principle(s), or, if the process stream analyzer system uses a direct and well-understood measurement principle that is similar to the measurement principle of the primary test method. If the process stream analyzer system uses a different measurement technology from the primary test method, provided that the calibration protocol for the direct output of the analyzer does not require use of the PTM, this practice also applies.  
1.4 This guide does not apply if the process stream analyzer system utilizes an indirect or mathematically modeled measurement principle such as chemometric or multivariate analysis techniques where results from ...

SIGNIFICANCE AND USE
5.1 The analyzer sample system lag time estimated by this guide can be used in conjunction with the analyzer output to aid in optimizing control of blender facilities or process units.  
5.2 The lag time can be used in the tuning of control programs to set the proper optimization frequency.  
5.3 The application of this guide is not for the design of a sample system but to help understand the design and to estimate the performance of existing sample systems. Additional detailed information can be found in the references provided in the section entitled Additional Reading Material.
SCOPE
1.1 This guide covers the application of routine calculations to estimate sample system lag time, in seconds, for gas, liquid, and mixed phase systems.  
1.2 This guide considers the sources of lag time from the process sample tap, tap conditioning, sample transport, pre-analysis conditioning and analysis.  
1.3 Lag times are estimated based on a prediction of flow characteristics, turbulent, non turbulent, or laminar, and the corresponding purge requirements.  
1.4 Mixed phase systems prevent reliable representative sampling so system lag times should not be used to predict sample representation of the stream.  
1.5 The values stated in inch-pound units are to be regarded as standard. No other units of measurement are included in this standard.  
1.6 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SIGNIFICANCE AND USE
5.1 The primary purpose of this practice is to permit the user to validate numerical values produced by a multivariate, infrared or near-infrared laboratory or process (online or at-line) analyzer calibrated to measure a specific chemical concentration, chemical property, or physical property. The validated analyzer results are expected to be statistically indistinguishable, over diverse samples whose spectra are neither outliers or nearest neighbor inliers, to those produced by the primary test method to within control limits established by control charts for the prespecified statistical confidence level.  
5.2 Procedures are described for verifying that the instrument, the model, and the analyzer system are stable and properly operating.  
5.3 A multivariate analyzer system inherently utilizes a multivariate calibration model. In practice the model both implicitly and explicitly spans some subset of the population of all possible samples that could be in the complete multivariate sample space. The model is applicable only to samples that fall within the subset population used in the model construction. A sample measurement cannot be validated unless applicability is established. Applicability cannot be assumed.  
5.3.1 Outlier detection methods are used to demonstrate applicability of the calibration model for the analysis of the process sample spectrum. The outlier detection limits are based on historical as well as theoretical criteria. The outlier detection methods are used to establish whether the results obtained by an analyzer are potentially valid. The validation procedures are based on mathematical test criteria that indicate whether the process sample spectrum is within the range spanned by the analyzer system calibration model. If the sample spectrum is an outlier, the analyzer result is invalid. If the sample spectrum is not an outlier, then the analyzer result is valid providing that all other requirements for validity are met. Additional, optional ...
SCOPE
1.1 This practice covers requirements for the validation of measurements made by laboratory or process (online or at-line) near- or mid-infrared analyzers, or both, used in the calculation of physical, chemical, or quality parameters (that is, properties) of liquid petroleum products and fuels. The properties are calculated from spectroscopic data using multivariate modeling methods. The requirements include verification of adequate instrument performance, verification of the applicability of the calibration model to the spectrum of the sample under test, and verification that the degree of agreement between the results calculated from the infrared measurements and the results produced by the PTM used for the development of the calibration model meets user-specified requirements. When there is adequate variation in property level, the statistical methodology of Practice D6708 is used to provide general validation of this equivalence over the complete operating range of the analyzer. For cases where there is inadequate property variation, methodology for level specific validation is used.  
1.1.1 For some applications, the analyzer and PTM are applied to the same material. The application of the multivariate model to the analyzer output (spectrum) directly produces a PPTMR for the same material for which the spectrum was measured. The PPTMRs are compared to the PTMRs measured on the same materials to determine the degree of agreement.  
1.1.2 For other applications, the material measured by the analyzer system is subjected to a consistent treatment prior to being analyzed by the PTM. The application of the multivariate model to the analyzer output (spectrum) produces a PPTMR for the treated material. The PPTMRs based on the analyzer outputs are compared to the PTMRs measured on the treated materials to determine the degree of agreement.  
1.2 Performance Validation is conducted by calculating the precision and bias of ...

SIGNIFICANCE AND USE
5.1 This practice can be used to quantify the performance of a process stream analyzer system or its subsystem in terms of precision and bias relative to those of a primary test method for the property of interest.  
5.2 This practice provides developers or manufacturers of process stream analyzer systems with useful procedures for evaluating the capability of newly designed systems for industrial applications that require reliable prediction of measurements of a specific property by a primary test method of a flowing component or product.  
5.3 This practice provides purchasers of process stream analyzer systems with some reliable options for specifying acceptance test requirements for process stream analyzer systems at the time of commissioning to ensure the system is capable of making the desired property measurement with the appropriate precision or bias specifications, or both.  
5.4 PPTMR from Analyzer Systems validated in accordance with this practice can be used to predict, with a specified confidence, what the PTMR would be, to within a specified tolerance, if the actual primary test method was conducted on the materials that are within the validated property range and type.  
5.5 This practice provides the user of a process stream analyzer system with useful information from on-going quality control charts to monitor the variation in Δ over time, and trigger update of correlation relationship between the analyzer system and primary test method in a timely manner.  
5.6 Validation information obtained in the application of this practice is applicable only to the material type and property range of the materials used to perform the validation. Selection of the property levels and the compositional characteristics of the samples must be suitable for the application of the analyzer system. This practice allows the user to write a comprehensive validation statement for the analyzer system including specific limits for the validated range of application. Th...
SCOPE
1.1 This practice describes procedures and methodologies based on the statistical principles of Practice D6708 to validate whether the degree of agreement between the results produced by a total analyzer system (or its subsystem), versus the results produced by an independent test method that purports to measure the same property, meets user-specified requirements. This is a performance-based validation, to be conducted using a set of materials that are not used a priori in the development of any correlation between the two measurement systems under investigation. A result from the independent test method is herein referred to as a Primary Test Method Result (PTMR).  
1.1.1 The degree of agreement described in 1.1 can be either for the same materials, or, for materials including effect from additional treatment to the base stock material.
Note 1: Subsection 1.1.1 refers to the application where PPTMR for the same material can be used as an input to a mathematical model to predict the effect of an additive added to the base stock material as by a PTM.  
1.2 This practice assumes any correlation necessary to mitigate systemic biases between the analyzer system and PTM have been applied to the analyzer results. See Guide D7235 for procedures for establishing such correlations.  
1.3 This practice assumes any modeling techniques employed have the necessary tuning to mitigate systemic biases between the analyzer PPTMR and PTMR have been applied to the model results. Model form and tuning is not covered by this practice, only the validation of the model output.  
1.4 This practice requires that both the primary method against which the analyzer is compared to, and the analyzer system under investigation, are in statistical control. Practices described in Practice D6299 should be used to ensure this condition is met.  
1.5 This practice applies if the process stream analyzer system and the primary test method are based o...

SIGNIFICANCE AND USE
5.1 This practice can be used to quantify the performance of a process stream analyzer system or its subsystem in terms of precision and bias relative to those of a primary test method for the property of interest.  
5.2 This practice provides developers or manufacturers of process stream analyzer systems with useful procedures for evaluating the capability of newly designed systems for industrial applications that require reliable prediction of measurements of a specific property by a primary test method of a flowing component or product.  
5.3 This practice provides purchasers of process stream analyzer systems with some reliable options for specifying acceptance test requirements for process stream analyzer systems at the time of commissioning to ensure the system is capable of making the desired property measurement with the appropriate precision or bias specifications, or both.  
5.4 PPTMR from Analyzer Systems validated in accordance with this practice can be used to predict, with a specified confidence, what the PTMR would be, to within a specified tolerance, if the actual primary test method was conducted on the materials that are within the validated property range and type.  
5.5 This practice provides the user of a process stream analyzer system with useful information from on-going quality control charts to monitor the variation in Δ over time, and trigger update of correlation relationship between the analyzer system and primary test method in a timely manner.  
5.6 Validation information obtained in the application of this practice is applicable only to the material type and property range of the materials used to perform the validation. Selection of the property levels and the compositional characteristics of the samples must be suitable for the application of the analyzer system. This practice allows the user to write a comprehensive validation statement for the analyzer system including specific limits for the validated range of application. Th...
SCOPE
1.1 This practice describes procedures and methodologies based on the statistical principles of Practice D6708 to validate whether the degree of agreement between the results produced by a total analyzer system (or its subsystem), versus the results produced by an independent test method that purports to measure the same property, meets user-specified requirements. This is a performance-based validation, to be conducted using a set of materials that are not used a priori in the development of any correlation between the two measurement systems under investigation. A result from the independent test method is herein referred to as a Primary Test Method Result (PTMR).  
1.1.1 The degree of agreement described in 1.1 can be either for the same materials, or, for materials including effect from additional treatment to the basestock material.
Note 1: Subsection 1.1.1 refers to the application where PPTMR for the same material can be used as an input to a mathematical model to predict the effect of an additive added to the basestock material as by a PTM.  
1.2 This practice assumes any correlation necessary to mitigate systemic biases between the analyzer system and PTM have been applied to the analyzer results. See Guide D7235 for procedures for establishing such correlations.  
1.3 This practice assumes any modeling techniques employed have the necessary tuning to mitigate systemic biases between the analyzer PPTMR and PTMR have been applied to the model results. Model form and tuning is not covered by this practice, only the validation of the model output.  
1.4 This practice requires that both the primary method against which the analyzer is compared to, and the analyzer system under investigation, are in statistical control. Practices described in Practice D6299 should be used to ensure this condition is met.  
1.5 This practice applies if the process stream analyzer system and the primary test method are based on ...

SIGNIFICANCE AND USE
5.1 Analyzer systems require representative samples of petroleum products delivered in a timely manner to (1) facilitate the control of process or blending units or (2) calculate a flow proportioned property value.  
5.2 Representative samples of petroleum products are required for the determination of chemical and physical properties. These properties are used to establish the relationship between the analyzer system and the primary test method during initial and ongoing validation of the system.  
5.3 Representative samples of petroleum products are tested to determine the chemical and physical properties of a batch offered for tender.
SCOPE
1.1 This practice covers the performance requirements for sample systems employed to deliver process stream samples (1) to analyzer system for analyses or (2) for analyzer validation or  (3) for composite sample systems. It also outlines the selection and operation of line or batch sampling equipment intended for analyzer flow proportioned average property value system validation. Sample handling, mixing, and conditioning procedures are required to ensure that a representative sample of the liquid petroleum product is collected from the sampling source.  
1.2 Applicable Fluids—This practice is applicable to single liquid phase petroleum products whose vapor pressure at sampling and sample storage conditions is less than or equal to 110 kPa (16.0 psi), and, with a D86 final boiling point less than or equal to 400 °C (752 °F).  
1.2.1 Specialized sample handling may be necessary to maintain sample integrity of more volatile materials at high temperatures or extended residence time in the receiver. Such handling requirements are not within the scope of this practice. Users should consult the analytical methods to be performed on the sample for special sample storage or conditioning requirements.  
1.3 Some or all of the processes outlined in this practice may be applicable to other liquids. Applying this practice to other liquids will require the consideration of additional methods and practices. It is the responsibility of the user of this standard to identify any and all applicable safety and sampling considerations and establish appropriate procedures to handle these additional considerations.  
1.4 The values stated in SI units are to be regarded as the standard. The values given in parentheses are for information only.  
1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SIGNIFICANCE AND USE
4.1 This guide is intended to be used in conjunction with Practice D3764 (Case 1) and Practice D6122 (Case 2). Methodology in this guide can be used to determine if a linear correlation can improve the performance of the total analyzer system in terms of its ability to predict the results that the PTM would have been if applied to the same material. This methodology, which is based on the same statistical data treatment as Practice D6708, is use to derive the parameters of the linear relationship and to assess the degree of improvement.  
4.2 This guide provides developers or manufacturers of process stream analyzer systems with useful procedures for developing the capability of newly designed systems for industrial applications that require reliable prediction of measurements of a specific property by a primary test method of a flowing component or product.  
4.3 This guide provides purchasers of process stream analyzer systems with some reliable options for specifying performance requirements for process stream analyzer systems that are used in applications requiring reliable prediction of measurements of a specific property by a primary test method of a flowing component or product.  
4.4 This guide provides the user of a process stream analyzer system with useful information on the work process for establishing the PTM prediction relationship and prediction performance.  
4.5 Prediction (correlation) relationship obtained in the application of this guide is applicable only to the material type and property range of the materials used to perform the study. Selection of the property levels and the compositional characteristics of the samples must be suitable for the application of the analyzer system. Users are cautioned against extrapolation of the prediction relationship beyond the material type and property range used to obtain the relationship.  
4.6 The degree-of-agreement assessment promoted in this guide is based on the statistical principles articulat...
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1.1 This guide covers a general methodology to develop and assess the linear relationship between results produced by a total analyzer system versus the results produced by the corresponding primary test method (PTM) that the analyzer system is intended to emulate, using the principles and approaches outlined in relevant ASTM standard practices and guides.  
1.2 This guide describes how the statistical methodology of Practice D6708 can be employed to assess agreement between the PTM and analyzer results, and, if necessary, develop linear correlation to further improve the agreement over the complete operating range of the analyzer. For instances where there is insufficient variation in property level to apply the Practice D6708 multi-level methodology, users are referred to Practice D3764 to perform a level specific bias evaluation. The correlation relationship information obtained in the application of this guide is applicable only to the material type and property range of the materials representative of those used to perform the assessment. Users are cautioned against extrapolation of the relationship beyond the material type and property range being studied.  
1.3 This guide applies if the process stream analyzer system and the primary test method are based on the same measurement principle(s), or, if the process stream analyzer system uses a direct and well-understood measurement principle that is similar to the measurement principle of the primary test method. If the process stream analyzer system uses a different measurement technology from the primary test method, provided that the calibration protocol for the direct output of the analyzer does not require use of the PTM, this practice also applies.  
1.4 This guide does not apply if the process stream analyzer system utilizes an indirect or mathematically modeled measurement principle such as chemometric or multivariate analysis techniques where results from ...

SIGNIFICANCE AND USE
4.1 Contractual or local regulation, or both, permitting, the FPAPV calculated according to this practice can be used to represent the average property of the quantity of material collected.  
4.2 Due to the averaging and appropriate weighting of analysis results, the FPAPV estimate of the property for the collected material is expected to be more representative and more precise than an estimate based on a small number of analyses on a few samples.
Note 1: Theoretically speaking, the true property distribution for an infinite number of batches with essentially identical FPAPV's is expected to be Gaussian, centered at the FPAPV value, with a standard deviation that is no less than the long term site precision standard deviation of the analyzer system.  
4.3 If the measured property value can be used to predict another property value through the use of an appropriate correlation equation, the FPAPV can also be used as a suitable prediction of that property.  
4.4 The most recently updated FPAPV can be used to represent the property of the material currently accumulated in the tank or vessel for process control or material disposition decisions, or both.
SCOPE
1.1 This practice covers a technique for calculating a flow-proportioned average property value (FPAPV) for a batch of in-line blended product or process stream material that is collected over time and isolated in a storage tank or vessel, using a combination of on-line or at-line measurements taken at regular intervals of the property and flow rates.  
1.2 The FPAPV methodology uses regularly collected on- line or at-line process analyzer measurements, flow, and assessment of other appropriate process measurements or values, to calculate a flow-proportioned average property value in accordance with flow quantity units of material produced.  
1.3 When the collecting vessel contains a heel (retained material prior to receipt of the production batch), both the property value and quantity of the heel material can be predetermined and factored into the calculation of the FPAPV for the new batch.  
1.4 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SIGNIFICANCE AND USE
5.1 This practice can be used to quantify the performance of a process stream analyzer system or its subsystem in terms of precision and bias relative to those of a primary test method for the property of interest.  
5.2 This practice provides developers or manufacturers of process stream analyzer systems with useful procedures for evaluating the capability of newly designed systems for industrial applications that require reliable prediction of measurements of a specific property by a primary test method of a flowing component or product.  
5.3 This practice provides purchasers of process stream analyzer systems with some reliable options for specifying acceptance test requirements for process stream analyzer systems at the time of commissioning to ensure the system is capable of making the desired property measurement with the appropriate precision or bias specifications, or both.  
5.4 PPTMR from Analyzer Systems validated in accordance with this practice can be used to predict, with a specified confidence, what the PTMR would be, to within a specified tolerance, if the actual primary test method was conducted on the materials that are within the validated property range and type.  
5.5 This practice provides the user of a process stream analyzer system with useful information from on-going quality control charts to monitor the variation in Δ over time, and trigger update of correlation relationship between the analyzer system and primary test method in a timely manner.  
5.6 Validation information obtained in the application of this practice is applicable only to the material type and property range of the materials used to perform the validation. Selection of the property levels and the compositional characteristics of the samples must be suitable for the application of the analyzer system. This practice allows the user to write a comprehensive validation statement for the analyzer system including specific limits for the validated range of application. ...
SCOPE
1.1 This practice describes procedures and methodologies based on the statistical principles of Practice D6708 to validate whether the degree of agreement between the results produced by a total analyzer system (or its subsystem), versus the results produced by an independent test method that purports to measure the same property, meets user-specified requirements. This is a performance-based validation, to be conducted using a set of materials that are not used a priori in the development of any correlation between the two measurement systems under investigation. A result from the independent test method is herein referred to as a Primary Test Method Result (PTMR).  
1.2 This practice assumes any correlation necessary to mitigate systemic biases between the analyzer system and PTM have been applied to the analyzer results. See Guide D7235 for procedures for establishing such correlations.  
1.3 This practice requires that both the primary method against which the analyzer is compared to, and the analyzer system under investigation, are in statistical control. Practices described in Practice D6299 should be used to ensure this condition is met.  
1.4 This practice applies if the process stream analyzer system and the primary test method are based on the same measurement principle(s), or, if the process stream analyzer system uses a direct and well-understood measurement principle that is similar to the measurement principle of the primary test method. This practice also applies if the process stream analyzer system uses a different measurement technology from the primary test method, provided that the calibration protocol for the direct output of the analyzer does not require use of the PTMRs (see Case 1 in Note 1).  
1.5 This practice does not apply if the process stream analyzer system utilizes an indirect or mathematically modeled measurement principle such as chemometric or multivariate analysis techniques where...

SIGNIFICANCE AND USE
5.1 The primary purpose of this practice is to permit the user to validate numerical values produced by a multivariate, infrared or near-infrared laboratory or process (online or at-line) analyzer calibrated to measure a specific chemical concentration, chemical property, or physical property. The validated analyzer results are expected to be equivalent, over diverse samples whose spectra are neither outliers or nearest neighbor inliers, to those produced by the primary test method to within control limits established by control charts for the prespecified statistical confidence level.  
5.2 Procedures are described for verifying that the instrument, the model, and the analyzer system are stable and properly operating.  
5.3 A multivariate analyzer system inherently utilizes a multivariate calibration model. In practice the model both implicitly and explicitly spans some subset of the population of all possible samples that could be in the complete multivariate sample space. The model is applicable only to samples that fall within the subset population used in the model construction. A sample measurement cannot be validated unless applicability is established. Applicability cannot be assumed.  
5.3.1 Outlier detection methods are used to demonstrate applicability of the calibration model for the analysis of the process sample spectrum. The outlier detection limits are based on historical as well as theoretical criteria. The outlier detection methods are used to establish whether the results obtained by an analyzer are potentially valid. The validation procedures are based on mathematical test criteria that indicate whether the process sample spectrum is within the range spanned by the analyzer system calibration model. If the sample spectrum is an outlier, the analyzer result is invalid. If the sample spectrum is not an outlier, then the analyzer result is valid providing that all other requirements for validity are met. Additional, optional tests may be performe...
SCOPE
1.1 This practice covers requirements for the validation of measurements made by laboratory or process (online or at-line) near- or mid-infrared analyzers, or both, used in the calculation of physical, chemical, or quality parameters (that is, properties) of liquid petroleum products. The properties are calculated from spectroscopic data using multivariate modeling methods. The requirements include verification of adequate instrument performance, verification of the applicability of the calibration model to the spectrum of the sample under test, and verification of equivalence between the result calculated from the infrared measurements and the result produced by the primary test method used for the development of the calibration model. When there is adequate variation in property level, the statistical methodology of Practice D6708 is used to provide general validation of this equivalence over the complete operating range of the analyzer. For cases where there is inadequate property variation, methodology for level specific validation is used.  
1.2 Performance Validation is conducted by calculating the precision and bias of the differences between results from the analyzer system (or subsystem) produced by application of the multivariate model, (such results are herein referred to as Predicted Primary Test Method Results (PPTMRs)), versus the Primary Test Method Results (PTMRs) for the same sample set. Results used in the calculation are for samples that are not used in the development of the multivariate model. The calculated precision and bias are statistically compared to user-specified requirements for the analyzer system application.  
1.2.1 For analyzers used in product release or product quality certification applications, the precision and bias requirement for the degree of agreement are typically based on the site or published precision of the Primary Test Method.Note 1—In most applications of this type, the...

SIGNIFICANCE AND USE
4.1 The standards employed in the Process Stream Analyzer PSPV Generation Flow Diagram each have a specific deliverable that when combined into a single system produces a PSPV enabling the representation of product by process stream analyzer.  
4.2 The description of each standard in the process provides the user with an overview of the application of the standard in the process for developing a PSPV.
SCOPE
1.1 This guide covers and provides a workflow overview of the necessary steps related to generating a Process Stream Property Value obtained from the application of a process stream analyzer.  
1.2 Generating a Process Stream Property Value from the application of a process stream analyzer requires the use of several ASTM standards. These standards describe procedures to collect a representative sample, establish and validate the relationship to the primary test method, and calculate a property value with an expected uncertainty. Each standard builds or prepares data, or both, to be used in another standard. The workflow process culminates to produce a process stream analyzer result that represents a user defined batch of product. The sequence in which the standards are to be utilized is defined in this guide.  
1.3 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SIGNIFICANCE AND USE
4.1 The analyzer site precision is an estimate of the variability that can be expected in a UAR or a PPTMR produced by an analyzer when applied to the analysis of the same material over an extended time period.  
4.2 For applications where the process analyzer system results are required to agree with results produced from an independent PTM, a mathematical function is derived that relates the UARs to the PPTMRs. The application of this mathematical function to an analyzer result produces a predicted PPTMR. For analyzers where the mathematical function, that is, a correlation, is developed by D7235, the analyzer site precision of the UARs is a required input to the computation.  
4.3 After the correlation relationship between the analyzer results and primary test method results has been established, a probationary validation (see D3764 and D6122) is performed using an independent but limited set of materials that were not part of the correlation activity. This probationary validation is intended to demonstrate that the PPTMRs agree with the PTMRs to within user-specified requirements for the analyzer system application. The analyzer site precision is a required input to the probationary validation procedures.  
4.3.1 If the process stream analyzer system and the primary test method are based on the same measurement principle(s), or, if the process stream analyzer system uses a direct and well-understood measurement principle that is similar to the measurement principle of the PTM then validation is done via D3764. Practice D3764 also applies if the process stream analyzer system uses a different measurement technology from the PTM, provided that the calibration protocol for the direct output of the analyzer does not require use of the PTM.  
4.3.2 If the process stream analyzer system utilizes an indirect or mathematically modeled measurement principle such as chemometric or multivariate analysis techniques where PTMRs are required for the development of the che...
SCOPE
1.1 This practice describes a procedure to quantify the site precision of a process analyzer via repetitive measurement of a single process sample over an extended time period. The procedure may be applied to multiple process samples to obtain site precision estimates at different property levels  
1.1.1 The site precision is required for use of the statistical methodology of D6708 in establishing the correlation between analyzer results and primary test method results using Practice D7235.  
1.1.2 The site precision is also required when employing the statistical methodology of D6708 to validate a process analyzer via Practices D3764 or D6122.  
1.2 This practice is not applicable to in-line analyzers where the same quality control sample cannot be repetitively introduced.  
1.3 This practice is meant to be applied to analyzers that measure physical properties or compositions.  
1.4 This practice can be applied to any process analyzer system where the feed stream can be captured and stored in sufficient quantity with no stratification or stability concerns.  
1.4.1 The captured stream sample introduction must be able to meet the process analyzer sample conditioning requirements, feed temperature and inlet pressure.  
1.4.2 This practice is designed for use with samples that are single liquid phase, petroleum products whose vapor pressure, at sampling and sample storage conditions, is less than or equal to 110 kPa (16.0 psi) absolute and whose D86 final boiling point is less than or equal to 400°C (752°F).Note 1—The general procedures described in this practice may be applicable to materials outside this range, including multiphase materials, but such application may involve special sampling and safety considerations which are outside the scope of this practice.  
1.5 The values for operating conditions are stated in SI units and are to be regarded as the standard. The values given in parentheses are the historic...

SIGNIFICANCE AND USE
Contractual or local regulation, or both, permitting, the FPAPV calculated according to this practice can be used to represent the average property of the quantity of material collected.
Due to the averaging and appropriate weighting of analysis results, the FPAPV estimate of the property for the collected material is expected to be more representative and more precise than an estimate based on a small number of analyses on a few samples.
Note 1—Theoretically speaking, the true property distribution for an infinite number of batches with essentially identical FPAPV's is expected to be Gaussian, centered at the FPAPV value, with a standard deviation that is no less than the long term site precision standard deviation of the analyzer system.
If the measured property value can be used to predict another property value through the use of an appropriate correlation equation, the FPAPV can also be used as a suitable prediction of that property.
The most recently updated FPAPV can be used to represent the property of the material currently accumulated in the tank or vessel for process control or material disposition decisions, or both.
SCOPE
1.1 This practice covers a technique for calculating a flow-proportioned average property value (FPAPV) for a batch of in-line blended product or process stream material that is collected over time and isolated in a storage tank or vessel, using a combination of on-line or at-line measurements taken at regular intervals of the property and flow rates.
1.2 The FPAPV methodology uses regularly collected on- line or at-line process analyzer measurements, flow, and assessment of other appropriate process measurements or values, to calculate a flow-proportioned average property value in accordance with flow quantity units of material produced.
1.3 When the collecting vessel contains a heel (retained material prior to receipt of the production batch), both the property value and quantity of the heel material can be predetermined and factored into the calculation of the FPAPV for the new batch.
1.4 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SIGNIFICANCE AND USE
The analyzer sample system lag time estimated by this guide can be used in conjunction with the analyzer output to aid in optimizing control of blender facilities or process units.
The lag time can be used in the tuning of control programs to set the proper optimization frequency.
The application of this guide is not for the design of a sample system but to estimate the performance of existing sample systems. The principles listed in this guide are there to help understand design concepts and allow the application of this guide for its intended scope. Additional detailed information can be found in the references provided in the section entitled Additional Reading Material.
SCOPE
1.1 This guide covers the application of routine calculations to estimate sample system lag time, in seconds, for gas, liquid, and mixed phase systems.
1.2 This guide considers the sources of lag time from the process sample tap, tap conditioning, sample transport, pre-analysis conditioning and analysis.
1.3 Lag times are estimated based on a prediction of flow characteristics, turbulent, nonturbulent, or laminar, and the corresponding purge requirements.
1.4 Mixed phase systems prevent reliable representative sampling so system lag times should not be used to predict sample representation of the stream.
This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.

SIGNIFICANCE AND USE
This guide is intended to be used in conjunction with Practice D3764 (Case 1) and Practice D6122 (Case 2). Methodology in this guide can be used to determine if a linear correlation can improve the performance of the total analyzer system in terms of its ability to predict the results that the PTM would have been if applied to the same material. This methodology, which is based on the same statistical data treatment as Practice D6708, is use to derive the parameters of the linear relationship and to assess the degree of improvement.
This guide provides developers or manufacturers of process stream analyzer systems with useful procedures for developing the capability of newly designed systems for industrial applications that require reliable prediction of measurements of a specific property by a primary test method of a flowing component or product.
This guide provides purchasers of process stream analyzer systems with some reliable options for specifying performance requirements for process stream analyzer systems that are used in applications requiring reliable prediction of measurements of a specific property by a primary test method of a flowing component or product.
This guide provides the user of a process stream analyzer system with useful information on the work process for establishing the PTM prediction relationship and prediction performance.
Prediction (correlation) relationship obtained in the application of this guide is applicable only to the material type and property range of the materials used to perform the study. Selection of the property levels and the compositional characteristics of the samples must be suitable for the application of the analyzer system. Users are cautioned against extrapolation of the prediction relationship beyond the material type and property range used to obtain the relationship.
The degree-of-agreement assessment promoted in this guide is based on the statistical principles articulated in Practice D6708, which i...
SCOPE
1.1 This guide covers a general methodology to develop and assess the linear relationship between results produced by a total analyzer system versus the results produced by the corresponding primary test method (PTM) that the analyzer system is intended to emulate, using the principles and approaches outlined in relevant ASTM standard practices and guides.
1.2 This guide describes how the statistical methodology of Practice D6708 can be employed to assess agreement between the PTM and analyzer results, and, if necessary, develop linear correlation to further improve the agreement over the complete operating range of the analyzer. For instances where there is insufficient variation in property level to apply the Practice D6708 multi-level methodology, users are referred to Practice D3764 to perform a level specific bias evaluation. The correlation relationship information obtained in the application of this guide is applicable only to the material type and property range of the materials representative of those used to perform the assessment. Users are cautioned against extrapolation of the relationship beyond the material type and property range being studied.
1.3 This guide applies if the process stream analyzer system and the primary test method are based on the same measurement principle(s), or, if the process stream analyzer system uses a direct and well-understood measurement principle that is similar to the measurement principle of the primary test method. If the process stream analyzer system uses a different measurement technology from the primary test method, provided that the calibration protocol for the direct output of the analyzer does not require use of the PTM, this practice also applies.
1.4 This guide does not apply if the process stream analyzer system utilizes an indirect or mathematically modeled measurement principle such as chemometric or multivariate analysis techniques where results from PTM...

SIGNIFICANCE AND USE
The primary purpose of this practice is to permit the user to validate numerical values produced by a multivariate, infrared or near-infrared laboratory or process (online or at-line) analyzer calibrated to measure a specific chemical concentration, chemical property, or physical property. The validated analyzer results are expected to be equivalent, over diverse samples whose spectra are neither outliers or nearest neighbor inliers, to those produced by the primary test method to within control limits established by control charts for the prespecified statistical confidence level.
Procedures are described for verifying that the instrument, the model, and the analyzer system are stable and properly operating.
A multivariate analyzer system inherently utilizes a multivariate calibration model. In practice the model both implicitly and explicitly spans some subset of the population of all possible samples that could be in the complete multivariate sample space. The model is applicable only to samples that fall within the subset population used in the model construction. A sample measurement cannot be validated unless applicability is established. Applicability cannot be assumed.
Outlier detection methods are used to demonstrate applicability of the calibration model for the analysis of the process sample spectrum. The outlier detection limits are based on historical as well as theoretical criteria. The outlier detection methods are used to establish whether the results obtained by an analyzer are potentially valid. The validation procedures are based on mathematical test criteria that indicate whether the process sample spectrum is within the range spanned by the analyzer system calibration model. If the sample spectrum is an outlier, the analyzer result is invalid. If the sample spectrum is not an outlier, then the analyzer result is valid providing that all other requirements for validity are met. Additional, optional tests may be performed to determine if the...
SCOPE
1.1 This practice covers requirements for the validation of measurements made by laboratory or process (online or at-line) near- or mid-infrared analyzers, or both, used in the calculation of physical, chemical, or quality parameters (that is, properties) of liquid petroleum products. The properties are calculated from spectroscopic data using multivariate modeling methods. The requirements include verification of adequate instrument performance, verification of the applicability of the calibration model to the spectrum of the sample under test, and verification of equivalence between the result calculated from the infrared measurements and the result produced by the primary test method used for the development of the calibration model. When there is adequate variation in property level, the statistical methodology of Practice D6708 is used to provide general validation of this equivalence over the complete operating range of the analyzer. For cases where there is inadequate property variation, methodology for level specific validation is used.
1.2 Performance Validation is conducted by calculating the precision and bias of the differences between results from the analyzer system (or subsystem) produced by application of the multivariate model, (such results are herein referred to as Predicted Primary Test Method Results (PPTMRs)), versus the Primary Test Method Results (PTMRs) for the same sample set. Results used in the calculation are for samples that are not used in the development of the multivariate model. The calculated precision and bias are statistically compared to user-specified requirements for the analyzer system application.
1.2.1 For analyzers used in product release or product quality certification applications, the precision and bias requirement for the degree of agreement are typically based on the site or published precision of the Primary Test Method.
Note 1—In most applications of this type, t...

SIGNIFICANCE AND USE
The primary purpose of this practice is to permit the user to validate numerical values produced by a multivariate, infrared or near-infrared, online, process analyzer calibrated to measure a specific chemical concentration, chemical property, or physical property. The validated analyzer results are expected to be equivalent, over diverse samples whose spectra are neither outliers or nearest neighbor inliers, to those produced by the primary test method to within control limits established by control charts for the prespecified statistical confidence level.
Procedures are described for verifying that the instrument, the model, and the analyzer system are stable and properly operating.
A multivariate analyzer system inherently utilizes a multivariate calibration model. In practice the model both implicitly and explicitly spans some subset of the population of all possible samples that could be in the complete multivariate sample space. The model is applicable only to samples that fall within the subset population used in the model construction. A sample measurement cannot be validated unless applicability is established. Applicability cannot be assumed.
Outlier detection methods are used to demonstrate applicability of the calibration model for the analysis of the process sample spectrum. The outlier detection limits are based on historical as well as theoretical criteria. The outlier detection methods are used to establish whether the results obtained by an analyzer are potentially valid. The validation procedures are based on mathematical test criteria that indicate whether the process sample spectrum is within the range spanned by the analyzer system calibration model. If the sample spectrum is an outlier, the analyzer result is invalid. If the sample spectrum is not an outlier, then the analyzer result is valid providing that all other requirements for validity are met. Additional, optional tests may be performed to determine if the process sample spectrum ...
SCOPE
1.1 This practice covers requirements for the validation of measurements made by online, process near- or mid-infrared analyzers, or both, used in the calculation of physical, chemical, or quality parameters (that is, properties) of liquid petroleum products. The properties are calculated from spectroscopic data using multivariate modeling methods. The requirements include verification of adequate instrument performance, verification of the applicability of the calibration model to the spectrum of the sample under test, and verification of equivalence between the result calculated from the infrared measurements and the result produced by the primary test method used for the development of the calibration model. When there is adequate variation in property level, the statistical methodology of Practice D 6708 is used to provide general validation of this equivalence over the complete operating range of the analyzer. For cases where there is inadequate property variation, methodology for level specific validation is used.
1.2 Performance Validation is conducted by calculating the precision and bias of the differences between results from the analyzer system (or subsystem) produced by application of the multivariate model, (such results are herein referred to as Predicted Primary Test Method Results (PPTMRs)), versus the Primary Test Method Results (PTMRs) for the same sample set. Results used in the calculation are for samples that are not used in the development of the multivariate model. The calculated precision and bias are statistically compared to user-specified requirements for the analyzer system application.
1.2.1 For analyzers used in product release or product quality certification applications, the precision and bias requirement for the degree of agreement are typically based on the site or published precision of the Primary Test Method.
Note 1—In most applications of this type, the PTM is the specificati...

SIGNIFICANCE AND USE
This practice can be used to quantify the performance of a process stream analyzer system or its subsystem in terms of precision and bias relative to those of a primary test method for the property of interest.
This practice provides developers or manufacturers of process stream analyzer systems with useful procedures for evaluating the capability of newly designed systems for industrial applications that require reliable prediction of measurements of a specific property by a primary test method of a flowing component or product.
This practice provides purchasers of process stream analyzer systems with some reliable options for specifying acceptance test requirements for process stream analyzer systems at the time of commissioning to ensure the system is capable of making the desired property measurement with the appropriate precision or bias specifications, or both.
PPTMR from Analyzer Systems validated in accordance with this practice can be used to predict, with a specified confidence, what the PTMR would be, to within a specified tolerance, if the actual primary test method was conducted on the materials that are within the validated property range and type.
This practice provides the user of a process stream analyzer system with useful information from on-going quality control charts to monitor the variation in Δ over time, and trigger update of correlation relationship between the analyzer system and primary test method in a timely manner.  
Validation information obtained in the application of this practice is applicable only to the material type and property range of the materials used to perform the validation. Selection of the property levels and the compositional characteristics of the samples must be suitable for the application of the analyzer system. This practice allows the user to write a comprehensive validation statement for the analyzer system including specific limits for the validated range of application. This practice does not recomme...
SCOPE
1.1 This practice describes procedures and methodologies based on the statistical principles of Practice D 6708 to validate whether the degree of agreement between the results produced by a total analyzer system (or its subsystem), versus the results produced by an independent test method that purports to measure the same property, meets user-specified requirements. This is a performance-based validation, to be conducted using a set of materials that are not used a priori in the development of any correlation between the two measurement systems under investigation. A result from the independent test method is herein referred to as a Primary Test Method Result (PTMR).
1.2 This practice assumes any correlation necessary to mitigate systemic biases between the analyzer system and PTM have been applied to the analyzer results.
1.3 This practice requires that both the primary method against which the analyzer is compared to, and the analyzer system under investigation, are in statistical control. Practices described in Practice D 6299 should be used to ensure this condition is met.
1.4 This practice applies if the process stream analyzer system and the primary test method are based on the same measurement principle(s), or, if the process stream analyzer system uses a direct and well-understood measurement principle that is similar to the measurement principle of the primary test method. This practice also applies if the process stream analyzer system uses a different measurement technology from the primary test method, provided that the calibration protocol for the direct output of the analyzer does not require use of the PTMRs (see Case 1 in Note 1).  
1.5 This practice does not apply if the process stream analyzer system utilizes an indirect or mathematically modeled measurement principle such as chemometric or multivariate analysis techniques where PTMRs are required for the chemometric or multivariate model develop...

SIGNIFICANCE AND USE
Analyzer systems require representative samples of petroleum products delivered in a timely manner to (1) facilitate the control of process or blending units or (2) calculate a flow proportioned property value.
Representative samples of petroleum products are required for the determination of chemical and physical properties. These properties are used to establish the relationship between the analyzer system and the primary test method during initial and ongoing validation of the system.
Representative samples of petroleum products are tested to determine the chemical and physical properties of a batch offered for tender.
SCOPE
1.1 This practice covers the performance requirements for sample systems employed to deliver process stream samples (1) to analyzer system for analyses or (2) for analyzer validation or (3) for composite sample systems. It also outlines the selection and operation of line or batch sampling equipment intended for analyzer flow proportioned average property value system validation. Sample handling, mixing, and conditioning procedures are required to ensure that a representative sample of the liquid petroleum product is collected from the sampling source.
1.2 Applicable Fluids—This practice is applicable to single liquid phase petroleum products whose vapor pressure at sampling and sample storage conditions is less than or equal to 110 kPa (16.0 psi), and, with a D 86 final boiling point less than or equal to 400°C (752°F).
1.2.1 Specialized sample handling may be necessary to maintain sample integrity of more volatile materials at high temperatures or extended residence time in the receiver. Such handling requirements are not within the scope of this practice. Users should consult the analytical methods to be performed on the sample for special sample storage or conditioning requirements.
1.3 Some or all of the processes outlined in this practice may be applicable to other liquids. Applying this practice to other liquids will require the consideration of additional methods and practices. It is the responsibility of the user of this standard to identify any and all applicable safety and sampling considerations and establish appropriate procedures to handle these additional considerations.
1.4 The values stated in SI units are to be regarded as the standard. The values given in parentheses are for information only.
1.5 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety and health practices and determine the applicability of regulatory limitations prior to use.