ASME PTC 19.1:2018 pdf free download – Test Uncertainty”
The object of this Standard is to define, describe, and illustrate the terms and methods used to provide mean- ingful estimates ofthe uncertainty in test measurements, parameters, and methods, and the effects ofthose uncer- tainties on derived test results.
1-1.1 Objectives
An uncertainty analysis of test measurements, para- meters, and methods is useful because it
(a) provides an objective estimate ofthe quality oftest data and results
(b) facilitates communication regarding measurement and test results
(c) fosters an understanding ofpotential error sources in a measurement system, and the effects ofthose poten- tial error sources on test results
(d) guides the decision-making process for selecting appropriate and cost-effective measurement systems and methods
(e) reduces the risk of making erroneous decisions based on test results (f) documents uncertainty for assessing compliance with test requirements
(g) substantiates the test uncertainty budget When an uncertaintyanalysis is completed, a numerical characterization of the quality of test results is available with an appropriate level of confidence, typically 95%.
1-2.1 Uncertainty Propagation Methods
This Standard incorporates two internationally accepted methods of propagating uncertainties in measured parameters to a derived test result.
1-2.1.1 Taylor Series Method (TSM).
This method of propagation is consistent with ISO/IEC Guide 98-3 (GUM) [2]. The TSM requires the determination ofsensi- tivitycoefficients foreachinputvariable(howthe resultis affected byvariations in the inputvariables) and standard uncertainties for each error source.
1-2.1.2 The Monte Carlo Method (MCM).
This method ofpropagation is consistent with JCGM 101 [3]. The MCM requires estimation ofprobability distributions and stan- dard uncertainties (standard deviations) for each error source. The distribution determined as the output of an MCM analysis allows direct determination of the lower and upperlimits of acoverage in terval that containsa specified percentage of the distribution. Thus there are no addi- tional assumptions required to arrive at an “expansion factor,” as is necessary in the TSM approach, to obtain a confidence interval estimate.
1-2.2.3 ISO GUM Classification. The ISO GUM uses a differentclassification: TypeAuncertaintiesareevaluated withstatisticalmethodsandTypeBuncertaintiesareeval- uatedusingothermeans, suchas models orjudgment. The terms identify the pedigree of the error sources. The uncertainty of a test result is independent of whether the elemental uncertainties are classified as systematic or random, or as Type A or Type B. Regardless of the uncertainty classification used, the calculated uncertaintyofthe resultwill be the same. While this Stan- dard utilizes systematic and random terms, there may be situations where it is useful to classify elemental uncer- tainties by effect, source, or both.
1-3 APPLICATIONS
This Standard is intended to serve as a reference to other supplements in the ASME PTC 19 Series and to ASME performance test codes and standards in general. Inaddition, itisapplicableforallknownmeasure- ment and test uncertainty analyses. NOTE: The nominal values for the parameters and the uncer- tainty levels used throughout this Standard are for illustrative purposes only and are not intended to be typical of standard tests. Values and uncertainty levels shall be evaluated for the specific test and measurement system used.