不确定度分析
计算机科学
不确定度量化
不确定性传播
风险分析(工程)
测量不确定度
机器学习
算法
数学
模拟
医学
统计
作者
Andrew W. Cary,John A. Schaefer,Earl P. N. Duque,Manas Khurana,Erin C. DeCarlo
摘要
Uncertainty quantifcation is an important part of engineering analysis but it is often bypassed in fuids engineering often due to the complexity adequately estimating the effect. While physical testing has standards that are widely accepted for performing error analysis, uncertainty quantifcation methods for computational fuid dynamics and other fuids analyses are less well established. This paper identifes a number of the challenges often encountered when attempting to perform uncertainty analysis on this class of problems and provides examples of approaches that mitigate the issues. It highlights that adequate uncertainty analysis can take many forms and be of varying complexity depending on the requirement on the level of confdence in the uncertainty estimate. To further examine diferent approaches, a sample problem is proposed that can be used independently by multiple researchers and stakeholders to demonstrate and compare different methods.
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