Defining coverage of a domain using a modified nearest-neighbor metric

Matthew C. Egeberg, Sez Atamturktur, François M. Hemez

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


Validation experiments are conducted at discrete settings within the domain of interest to assess the predictive maturity of a model over the entire domain. Satisfactory model performance merely at these discrete tested settings is insufficient to ensure that the model will perform well throughout the domain, particularly at settings far from validation experiments. The goal of coverage metrics is to reveal how well a set of validation experiments represents the entire operational domain. The authors identify the criteria of an exemplary coverage metric, evaluate the ability of existing coverage metrics to fulfill each criterion, and propose a new, improved coverage metric. The proposed metric favors interpolation over extrapolation through a penalty function, causing the metric to prefer a design of validation experiments near the boundaries of the domain, while simultaneously exploring inside the domain. Furthermore, the proposed metric allows the coverage to account for uncertainty associated with validation experiments. Application of the proposed coverage metric on a practical, non-trivial problem is demonstrated on the Viscoplastic Self-Consistent material plasticity code for 5182 aluminum alloy.

Original languageEnglish (US)
Title of host publicationTopics in Model Validation and Uncertainty Quantification - Proceedings of the 31st IMAC, A Conference on Structural Dynamics, 2013
Number of pages10
StatePublished - 2013
Event31st IMAC, A Conference on Structural Dynamics, 2013 - Garden Grove, CA, United States
Duration: Feb 11 2013Feb 14 2013

Publication series

NameConference Proceedings of the Society for Experimental Mechanics Series
ISSN (Print)2191-5644
ISSN (Electronic)2191-5652


Other31st IMAC, A Conference on Structural Dynamics, 2013
Country/TerritoryUnited States
CityGarden Grove, CA

All Science Journal Classification (ASJC) codes

  • General Engineering
  • Computational Mechanics
  • Mechanical Engineering


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