Spatially-dependent material uncertainties in anisotropic nonlinear elasticity: Stochastic modeling, identification, and propagation
نویسندگان
چکیده
This paper develops a stochastic model for the spatially-dependent material parameters parameterizing anisotropic strain energy density functions. The construction is cast within framework of information theory, which invoked to derive least-informative while ensuring consistency with theoretical requirements in finite elasticity. Specifically, almost sure polyconvexity and uniform growth conditions are enforced through proper repulsion constraints regularization, hence making forward problem uncertainty propagation well posed. In addition, transformations arising from linearization procedure introduced induce statistical dependencies primary variables. latter include moduli, weight balancing between isotropic contributions, angle defining structural tensors. identification subsequently performed, using an existing database on human arterial walls. Maximum likelihood estimators obtained provided adventitia, media, intima layers, enables use proposed as generative surrogate for, e.g., training classification data-driven approaches integrating inter-patient variability. Finally, realistic, patient-specific geometry conducted demonstrate efficiency modeling framework.
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ژورنال
عنوان ژورنال: Computer Methods in Applied Mechanics and Engineering
سال: 2022
ISSN: ['0045-7825', '1879-2138']
DOI: https://doi.org/10.1016/j.cma.2022.114897