Zobrazeno 1 - 10 of 29 pro vyhledávání: '"Christian Perron"'
1
Manifold Alignment-Based Nonintrusive and Nonlinear Multifidelity Reduced-Order Modeling
Autor: Kenneth Decker, Nikhil Iyengar, Dushhyanth Rajaram, Christian Perron, Dimitri Mavris
Publikováno v: AIAA Journal. 61:454-474
This study presents the development of a methodology for the construction of data-driven, parametric, multifidelity reduced-order models to emulate aerodynamic flowfields with nonlinear and discontinuous features. Realistic computational budgets ofte
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::126b6399475e5e09125448a7bf5c1d8a
https://doi.org/10.2514/1.j061720
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3
Manifold alignment-based multi-fidelity reduced-order modeling applied to structural analysis
Autor: Christian Perron, Darshan Sarojini, Dushhyanth Rajaram, Jason Corman, Dimitri Mavris
Publikováno v: Structural and Multidisciplinary Optimization. 65
This work presents the application of a recently developed parametric, non-intrusive, and multi-fidelity reduced-order modeling method on high-dimensional displacement and stress fields arising from the structural analysis of geometries that differ i
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b21d19f5d4c590281a696f35dcac48a1
https://doi.org/10.1007/s00158-022-03274-1
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6
Randomized Algorithms for Non-Intrusive Parametric Reduced Order Modeling
Autor: Christian Perron, Dimitri N. Mavris, Dushhyanth Rajaram, Tejas G. Puranik
Publikováno v: AIAA Journal. 58:5389-5407
This paper demonstrates the development of purely data-driven, nonintrusive parametric reduced-order models for the emulation of high-dimensional field outputs using randomized linear algebra techn...
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::31fe99a44cef0565aa9f84e1e9ae44e2
https://doi.org/10.2514/1.j059616
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8
Multi-fidelity non-intrusive reduced-order modelling based on manifold alignment
Autor: Dimitri N. Mavris, Christian Perron, Dushhyanth Rajaram
Publikováno v: Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences. 477
This work presents the development of a multi-fidelity, parametric and non-intrusive reduced-order modelling method to tackle the problem of achieving an acceptable predictive accuracy under a limited computational budget, i.e. with expensive simulat
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::502e044e629679ac3cb05c5411debae8
https://doi.org/10.1098/rspa.2021.0495
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