Non-stationary Gaussian process surrogates
We provide a survey of non-stationary surrogate models which utilize Gaussian processes
(GPs) or variations thereof, including non-stationary kernel adaptations, partition and local …
(GPs) or variations thereof, including non-stationary kernel adaptations, partition and local …
[PDF][PDF] MPhys: A Modular Multiphysics Library for Coupled Simulation and Adjoint Derivative Computation
A Yildirim, KE Jacobson, JL Anibal… - Structural and …, 2024 - researchgate.net
The design of many engineering systems requires multiphysics simulations and can benefit
from design optimization. Two key challenges in multidisciplinary design optimization (MDO) …
from design optimization. Two key challenges in multidisciplinary design optimization (MDO) …
Contour Location for Reliability in Airfoil Simulation Experiments using Deep Gaussian Processes
Bayesian deep Gaussian processes (DGPs) outperform ordinary GPs as surrogate models
of complex computer experiments when response surface dynamics are non-stationary …
of complex computer experiments when response surface dynamics are non-stationary …
Generalized flutter reliability analysis with adjoint and direct approaches for aeroelastic eigen-pair derivatives computation
S Kumar - Meccanica, 2024 - Springer
The article presents physics based time invariant generalized flutter reliability approach for a
wing in detail. For carrying flutter reliability analysis, a generalized first order reliability …
wing in detail. For carrying flutter reliability analysis, a generalized first order reliability …
Non-intrusive polynomial chaos approach for nonlinear aeroelastic uncertainty quantification
View Video Presentation: https://doi. org/10.2514/6.2022-3869. vid Presented is a point
collocation non-intrusive polynomial chaos approach for nonlinear aeroelastic uncertainty …
collocation non-intrusive polynomial chaos approach for nonlinear aeroelastic uncertainty …