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CONSIDERATION OF CO-VARIANCE IN POWER PLANT TEST UNCERTAINTY CALCULATIONS

机译:考虑电厂测试不确定性计算中的共差

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One of the most important aspects of American Society of Mechanical Engineers (ASME) Performance Test Code (PTC) thermal performance testing is the proper determination of test uncertainty since the Uncertainty Analysis (UA) validates the quality of a test as well as demonstrates that the test meets code requirements. It can also carry a commercial relevance when test tolerances are linked to uncertainty figures.This paper introduces an approach to the calculation of the random component of uncertainty when co-variance exists between certain primary measurements in thermal performance testing. It demonstrates how to identify parameters that are co-variant, provides a methodology for properly calculating the aggregated random uncertainty of co-variant measurements, and discusses the effect of co-variance on UA results.
机译:美国机械工程师协会(ASME)性能测试代码(PTC)热性能测试中最重要的一个方面之一是由于不确定性分析(UA)验证了测试的质量,因此正确确定了测试不确定性的正确确定,并表明了测试符合代码要求。当测试公差与不确定数字相关时,它还可以进行商业相关性。本文介绍了一种在热性能测试中的某些初级测量之间存在共传出时的不确定度的随机分量的方法。它展示了如何识别作为共变量的参数,提供了一种正确计算共变量测量的聚合随机不确定性的方法,并讨论了对UA结果的共方的影响。

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