## Abstract

Today's computers allow us to simulate large, complex physical problems. Many times the mathematical models describing such problems are based on a relatively small amount of available information such as experimental measurements. The question arises whether the computed data could be used as the basis for decision in critical engineering, economic, and medicine applications. The representative list of engineering accidents occurred in the past years and their reasons illustrate the question. The paper describes a general framework for verification and validation (V&V) which deals with this question. The framework is then applied to an illustrative engineering problem, in which the basis for decision is a specific quantity of interest, namely the probability that the quantity does not exceed a given value. The V&V framework is applied and explained in detail. The result of the analysis is the computation of the failure probability as well as a quantification of the confidence in the computation, depending on the amount of available experimental data.

Original language | English (US) |
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Pages (from-to) | 753-784 |

Number of pages | 32 |

Journal | Numerical Methods for Partial Differential Equations |

Volume | 23 |

Issue number | 4 |

DOIs | |

State | Published - Jul 2007 |

Externally published | Yes |

## Keywords

- Bayesian update
- Failure probability
- Model validation
- Uncertainty quantification

## ASJC Scopus subject areas

- Analysis
- Numerical Analysis
- Computational Mathematics
- Applied Mathematics