Zobrazeno 1 - 10 of 61 pro vyhledávání: '"Philip Avery"'
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Acceleration of a Physics-Based Machine Learning Approach for Modeling and Quantifying Model-Form Uncertainties and Performing Model Updating
Autor: Marie-Jo Azzi, Chady Ghnatios, Philip Avery, Charbel Farhat
Publikováno v: Journal of Computing and Information Science in Engineering. 23
The nonparametric probabilistic method (NPM) for modeling and quantifying model-form uncertainties is a physics-based, computationally tractable, machine learning method for performing uncertainty quantification and model updating. It extracts from d
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9d07607f2b0251ff66722fc95117f058
https://doi.org/10.1115/1.4055546
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3
A computationally tractable framework for nonlinear dynamic multiscale modeling of membrane woven fabrics
Autor: Philip Avery, Wanli He, Johanna Ehlers, Charbel Farhat, Armen Derkevorkian, Daniel Z. Huang
Publikováno v: International Journal for Numerical Methods in Engineering. 122:2598-2625
A general-purpose computational homogenization framework is proposed for the nonlinear dynamic analysis of membranes exhibiting complex microscale and/or mesoscale heterogeneity characterized by in-plane periodicity that cannot be effectively treated
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::79ceb915f839bce4136947d772b03e08
https://doi.org/10.1002/nme.6634
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5
An embedded boundary approach for resolving the contribution of cable subsystems to fully coupled fluid‐structure interaction
Autor: Philip Avery, Charbel Farhat, Daniel Z. Huang
Publikováno v: International Journal for Numerical Methods in Engineering. 122:5409-5429
Cable subsystems characterized by long, slender, and flexible structural elements are featured in numerous engineering systems. In each of them, interaction between an individual cable and the surrounding fluid is inevitable. Such a Fluid-Structure I
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::62a51a1f0094f2c14b04271a9ad29fbb
https://doi.org/10.1002/nme.6322
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