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Model Construction, Uncertainty Quantification, and Data Driven Modeling in Computational Mechanics

Tiernan CaseySandia National Laboratories

This mini-symposium will highlight recent advances in methodologies for performing and enabling model calibration, uncertainty quantification, and uncertainty propagation for non-linear models employed in computational mechanics, as well as their application to problems of interest.  The sessions will exhibit data-driven approaches for constructing robust models from available information, the use of statistical inference machinery to enable, e.g., model selection and experimental design, and discuss problems arising from bias in available experimental data used to constrain physical models.