GPA TP-31-2014 GPA 2261 and GPA 2177 Methods Precision Statements Calculation.pdf
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1、Technical PublicationTP-31GPA 2261 and GPA 2177 Methods Precision Statements CalculationRicardo AguiarMovilab, S.A. de C.V.Naucalpan, Edo. MexicoApril 2014GasProcessorsAssociation 6526 East 60th Street Tulsa, Oklahoma 74145 Phone: 918/493-3872 GPAglobal.org1 GPA Disclaimer GPA publications necessari
2、ly address problems of a general nature and may be used by anyone desiring to do so. Every effort has been made by GPA to assure accuracy and reliability of the information contained in its publications. With respect to particular circumstances, local, state, and federal laws and regulations should
3、be reviewed. It is not the intent of GPA to assume the duties of employers, manufacturers, or suppliers to warn and properly train employees, or others exposed, concerning health and safety risks or precautions. GPA makes no representation, warranty, or guarantee in connection with this publication
4、and hereby expressly disclaims any liability or responsibility for loss or damage resulting from its use or for the violation of any federal, state, or municipal regulation with which this publication may conflict, or for any infringement of letters of patent regarding apparatus, equipment, or metho
5、d so covered. Forward The “Precision Criteria” derived from the work behind RR-188 and the data regression described in TP-31 may be significantly tighter in many cases than what was listed in previous revisions of GPA 2261 and GPA 2177. Therefore, the determination of what constitutes a “Pass/Fail”
6、 may need to be based on more than a single component failing to meet the precision criteria (depending on the degree of failure). It is feasible that an instrument could fail to meet the new “Precision Criteria”, yet produce analytical results that are acceptable otherwise. Agreements between parti
7、es should consider this and determine “Pass/Fail” based on actual impact of the instrument performance. Some parameters other than concentration for consideration are Heating Value, Relative Density and Theoretical Hydrocarbon Liquid Content. “Copyright2014 by Gas Processors Association. All rights
8、reserved. No part of this Report may be reproduced without the written consent of the Gas Processors Association.“ 2 TECHNICAL PAPER TP-31 GPA 2261 AND GPA 2177 METHODS PRECISION STATEMENTS CALCULATION 1. INTRODUCTION. This technical paper summarizes calculations for GPA 2261 and GPA 2177 methods pr
9、ecision statements, repeatability and reproducibility from data obtained during Round Robin RR 188. The interlaboratory study design for GPA 2261 consisted of 10 samples with 10 components covering the application range. Such samples were analyzed in duplicate by six laboratories, resulting in a 60
10、pair data set. The GPA 2277 design consisted of six samples including 10 components analyzed in duplicate by six laboratories, resulting in a 36 pair data set. Two international standards were selected for data analysis: ISO 5725-2:94 “Accuracy (trueness and precision) of measurement methods and res
11、ults Part 2: Basic method for the determination of repeatability and reproducibility of a standard measurement method”, and ASTM D6300-08 “Standard Practice for Determination of Precision and Bias Data for Use in Test Methods for Petroleum Products and Lubricants”. This Practice differs slightly fro
12、m related portions of the ISO 4259:06 standard, “Petroleum products Determination and application of precision data in relation to methods of test”. Both procedures include sample outlier identification, as well as rejection and calculation of precision estimates. The ASTM procedure requests at leas
13、t 30 degrees of freedom. That means 30 pairs of repeatability results covered in the RR 188. Some differences between selected procedures are: - In the ASTM D6300 (ASTM) procedure, identification and rejection of sample outliers come after a function transformation; therefore, in some cases, both pr
14、ocedures present different data to be rejected. - For precision estimate calculation, both methods use different weighting for regression. ASTM forces obtaining of the same exponent for repeatability and reproducibility; nevertheless, in the case of natural gas, only four out of 10 components have a
15、 dispersion profile that fits this condition. In the other cases, the repeatability function is forced to the exponent obtained in the estimated function of ISO 5725-2 (ISO). - ISO produces three estimates: a) linear zero origin, b) linear and c) exponential. ASTM is not limited to a specific functi
16、on, but produces a unique function with the same exponent and different coefficients for repeatability and reproducibility. When the repeatability function is 3 not adequate, a new regression for repeatability is performed forced with the founded ISO repeatability exponent. These differences in proc
17、edures yielded different estimates. Many of them have very tight overlapping; however, only in some cases significant differences requiring intervention were found. In those cases the rule applied was selection of the less strict function. Precision calculations were performed with a commercial spre
18、adsheet. For purposes of validation of calculation sheets, example 3 of method ISO 5725-2:1994 and data from Table A.2.1 of the ASTM D 6300-08 method were calculated with satisfactory results. For outlier identification purposes, both procedures used Grubbs, Cochrans and/or Mandels approaches. In fe
19、w cases, rejection of more than one or two values was necessary. At some level of rejection or inclusion of outliers no appreciable effect was observed because these data fell outside precision function obtained. For data rejection purposes, one of many considerations taken is the fact that when a r
20、eproducibility outlier is found in one component, such data should be rejected for all the components due to the normalization process causing a data set for a sample to be dependent upon components. This is true when concentration of that component is large enough to affect the total composition. D
21、ata were not rejected in cases where influence of a component outlier did not produce significant difference against a robust mean. This consideration was based upon the robustness of the normalization process applied to the analytical results that compensated the bias for a specific component in th
22、e whole composition. A deviation from the GPA 2261 standard was found because the sum of raw concentration (external standard calculations) reported by some laboratories did not comply with Note 14 of the method. Only 66% (2 out of 3) fell from 99% to 101% of the not normalized total, and 75% (3 out
23、 of 4) fell from 98% to 102%. This deviation may be attributed to the concentration scope of the Round Robin which exceeded the limits of concentration for both methods. For data analysis reported for participant laboratories, outliers and stragglers were identified through Mandels h and k statistic
24、s. Graphical representation thereof is shown in graphs 1 to 4. Graphs 1 and 3 show number k statistics, related to repeatability, before outlier rejection for each single component. Graphs 2 and 4 show reproducibility related Mandels h statistics, in which suspected outliers are easily identified in
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