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CGMM Parameters for Uncertainty Quantification from Physics-assisted data-driven stochastic reduced-order models for attribution of heterogeneous stress distributions in low-grain polycrystals

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DataCite Commons2025-02-19 更新2025-05-07 收录
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https://rs.figshare.com/articles/dataset/CGMM_Parameters_for_Uncertainty_Quantification_from_Physics-assisted_data-driven_stochastic_reduced-order_models_for_attribution_of_heterogeneous_stress_distributions_in_low-grain_polycrystals/28442144
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资源简介:
This file contains the parameters of the conditional Gaussian mixture model (CGMM) used for uncertainty quantification in different cases, including: mixture weights, mean vectors, and covariance matrices for bi-crystal, quad-crystal and octu-crystal configurations.
提供机构:
The Royal Society
创建时间:
2025-02-19
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