The Institute for Mathematics and its Applications (IMA) at the University of Minnesota hosted the workshop, 'Uncertainty Quantification in Materials Modeling' on December 16-17, 2013. Uncertainty quantification is an umbrella term that refers to the diverse analysis methods and tools suitable for critical assessment of models and simulations. Topics in uncertainty quantification were equally broad, presenting applications of Gaussian-process methods to prediction of polymer properties, as well as introducing new techniques for managing trade-offs between computational resources and uncertainty across simulation models of different fidelities. Some of the technical challenges discussed included development of validation metrics to quantify correspondence between simulation output and data, the limited existence and/or availability of critical experimental data, and the need to expand the educational system to include uncertainty quantification into the computational material science curriculum.
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