### Abstract

The origin of the term validation traces to the Latin valere, meaning worth. In the context of scientific computing, validation aims to determine the worthiness of a model in regard to its support of critical decision making. This determination of worthiness must occur in the face of unavoidable idealizations in the mathematical representation of the phenomena the model is intended to represent. These models are often parameterized further complicating the validation problem due to the need to determine appropriate parameter values for the imperfect mathematical representations. The determination of worthiness then becomes assessing whether an unavoidably imperfect mathematical model, subjected to poorly known input parameters, can predict sufficiently well to serve its intended purpose. To achieve this, we herein evaluate the agreement between a model’s predictions and associated experiments as well as the robustness of this agreement given imperfections in both the model’s mathematical representation of reality as well as its input parameter values.

Original language | English (US) |
---|---|

Article number | A27 |

Pages (from-to) | 189-198 |

Number of pages | 10 |

Journal | Conference Proceedings of the Society for Experimental Mechanics Series |

Volume | 3 |

DOIs | |

State | Published - Jan 1 2015 |

Event | 2014 Annual Conference on Experimental and Applied Mechanics, SEM 2014 - Greenville, SC, United States Duration: Jun 2 2014 → Jun 5 2014 |

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### All Science Journal Classification (ASJC) codes

- Engineering(all)
- Computational Mechanics
- Mechanical Engineering

### Cite this

*Conference Proceedings of the Society for Experimental Mechanics Series*,

*3*, 189-198. [A27]. https://doi.org/10.1007/978-3-319-15224-0_20

}

*Conference Proceedings of the Society for Experimental Mechanics Series*, vol. 3, A27, pp. 189-198. https://doi.org/10.1007/978-3-319-15224-0_20

**Model validation in scientific computing : Considering robustness to non-probabilistic uncertainty in the input parameters.** / Roche, Greg; Prabhu, Saurabh; Shields, Parker; Atamturktur, Sez.

Research output: Contribution to journal › Conference article

TY - JOUR

T1 - Model validation in scientific computing

T2 - Considering robustness to non-probabilistic uncertainty in the input parameters

AU - Roche, Greg

AU - Prabhu, Saurabh

AU - Shields, Parker

AU - Atamturktur, Sez

PY - 2015/1/1

Y1 - 2015/1/1

N2 - The origin of the term validation traces to the Latin valere, meaning worth. In the context of scientific computing, validation aims to determine the worthiness of a model in regard to its support of critical decision making. This determination of worthiness must occur in the face of unavoidable idealizations in the mathematical representation of the phenomena the model is intended to represent. These models are often parameterized further complicating the validation problem due to the need to determine appropriate parameter values for the imperfect mathematical representations. The determination of worthiness then becomes assessing whether an unavoidably imperfect mathematical model, subjected to poorly known input parameters, can predict sufficiently well to serve its intended purpose. To achieve this, we herein evaluate the agreement between a model’s predictions and associated experiments as well as the robustness of this agreement given imperfections in both the model’s mathematical representation of reality as well as its input parameter values.

AB - The origin of the term validation traces to the Latin valere, meaning worth. In the context of scientific computing, validation aims to determine the worthiness of a model in regard to its support of critical decision making. This determination of worthiness must occur in the face of unavoidable idealizations in the mathematical representation of the phenomena the model is intended to represent. These models are often parameterized further complicating the validation problem due to the need to determine appropriate parameter values for the imperfect mathematical representations. The determination of worthiness then becomes assessing whether an unavoidably imperfect mathematical model, subjected to poorly known input parameters, can predict sufficiently well to serve its intended purpose. To achieve this, we herein evaluate the agreement between a model’s predictions and associated experiments as well as the robustness of this agreement given imperfections in both the model’s mathematical representation of reality as well as its input parameter values.

UR - http://www.scopus.com/inward/record.url?scp=84945589751&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84945589751&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-15224-0_20

DO - 10.1007/978-3-319-15224-0_20

M3 - Conference article

AN - SCOPUS:84945589751

VL - 3

SP - 189

EP - 198

JO - Conference Proceedings of the Society for Experimental Mechanics Series

JF - Conference Proceedings of the Society for Experimental Mechanics Series

SN - 2191-5644

M1 - A27

ER -