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• W2953486030 abstract "Computer models for applications such as climate or materials have become increasingly complex. In particular, the input and output dimensions for these types of models has grown steadily larger, which has increased the computational burden of comparing these models with experimental data. This has spurred the development of statistical techniques for estimating outputs and reducing the dimension. This paper will show an example of these approaches applied to modeling and experiments for Tantalum, a material of interest for the Departments of Defense and Energy. We obtain results from a number of small-scale tests of Tantalum single crystals and use these results in a Bayesian statistical procedure to constrain the range and dimensionality of a Tantalum model." @default.
• W2953486030 created "2019-07-12" @default.
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• W2953486030 date "2019-05-31" @default.
• W2953486030 modified "2023-09-26" @default.
• W2953486030 title "Input Estimation and Dimension Reduction for Material Models" @default.
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• W2953486030 doi "https://doi.org/10.1007/978-3-030-12075-7_16" @default.
• W2953486030 hasPublicationYear "2019" @default.
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