Uncertainty, validation of computer models and the myth of numerical predictability.

Hemez, F. M.

Technical Information Center Oak Ridge Tennessee

关键词: Computer models;    Modeling;    Uncertainty quantification;    Model validation;    Numerical predictability;   

RP-ID  :  DE2001780698

学科分类：工程和技术（综合）

美国|英语

来源: National Technical Reports Library

【 摘 要 】

This publication addresses the issues of modeling, uncertainly quantification, model validation and numerical predictability. With the increasing role of numerical simulation in science, technology as well as every day decision-making, assessing the predictive accuracy of computer models becomes essential. Conventional approaches such as finite element model updating or Bayesian inference are undeniably useful tools but they do not fully answer the question: How accurately does the model represent reality. First, the evolution of scientific computing and consequences in terms of modeling and analysis practices are discussed. The intimate relationship between modeling and uncertainly is explored by defining uncertainly as an integrate part of the model, not just parametric variability or the lack of knowledge about the physical system being investigated. Examples from nuclear physics, climate prediction and structural dynamics are provided to illustrate issues related to uncertainly, validation and predictability. Feature extraction or the characterization of the dynamics of interest from time series is also discussed. Finally, a general framework based on response surface methodology is proposed for the fusion of model predictions, validation data sets and uncertainly analysis.