A General Methodology for Uncertainty Quantification in Engineering Analyses Using a Credible Probability Box

IF 0.5 Q4 ENGINEERING, MECHANICAL
M. E. Ewing, B. Liechty, D. L. Black
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引用次数: 9

Abstract

Uncertainty quantification (UQ) is gaining in maturity and importance in engineering analysis. While historical engineering analysis and design methods have relied heavily on safety factors (SF) with built-in conservatism, modern approaches require detailed assessment of reliability to provide optimized and balanced designs. This paper presents methodologies that support the transition toward this type of approach. Fundamental concepts are described for UQ in general engineering analysis. These include consideration of the sources of uncertainty and their categorization. Of particular importance are the categorization of aleatory and epistemic uncertainties and their separate propagation through an UQ analysis. This familiar concept is referred to here as a “two-dimensional” approach, and it provides for the assessment of both the probability of a predicted occurrence and the credibility in that prediction. Unique to the approach presented here is the adaptation of the concept of a bounding probability box to that of a credible probability box. This requires estimates for probability distributions related to all uncertainties both aleatory and epistemic. The propagation of these distributions through the uncertainty analysis provides for the assessment of probability related to the system response, along with a quantification of credibility in that prediction. Details of a generalized methodology for UQ in this framework are presented, and approaches for interpreting results are described. Illustrative examples are presented.
工程分析不确定性量化的通用方法
不确定性量化在工程分析中日益成熟和重要。虽然历史工程分析和设计方法在很大程度上依赖于具有内在保守性的安全系数(SF),但现代方法需要对可靠性进行详细评估,以提供优化和平衡的设计。本文介绍了支持向这种方法过渡的方法。介绍了通用工程分析中UQ的基本概念。其中包括考虑不确定性的来源及其分类。特别重要的是对述情性和认识性不确定性的分类,以及它们通过UQ分析的单独传播。这个熟悉的概念在这里被称为“二维”方法,它提供了对预测发生的概率和预测可信度的评估。这里提出的方法的独特之处在于,将边界概率框的概念改编为可信概率框。这需要对与所有不确定性相关的概率分布进行估计,包括推理和认识。这些分布通过不确定性分析的传播提供了与系统响应相关的概率评估,以及该预测可信度的量化。介绍了该框架中UQ的通用方法的细节,并描述了解释结果的方法。举例说明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.60
自引率
16.70%
发文量
12
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