An efficient PODI method for real-time simulation of indenter contact problems using RBF interpolation and contact domain decomposition
This paper proposes an efficient proper orthogonal decomposition with interpolation (PODI)
method for real-time simulation of indenter contact problems. In the offline stage, POD …
method for real-time simulation of indenter contact problems. In the offline stage, POD …
Deep Gaussian process enabled surrogate models for aerodynamic flows
Deep Gaussian process (DGP) models are multi-layered hierarchical generalizations of the
well-known Gaussian process (GP) models widely used to construct surrogate models of …
well-known Gaussian process (GP) models widely used to construct surrogate models of …
Projection-based model reduction of dynamical systems using space–time subspace and machine learning
This paper considers the creation of parametric surrogate models for applications in science
and engineering where the goal is to predict high-dimensional spatiotemporal output …
and engineering where the goal is to predict high-dimensional spatiotemporal output …
Nonlinear reduced order modeling using domain decomposition
View Video Presentation: https://doi. org/10.2514/6.2022-1250. vid As designers become
increasingly reliant upon expensive, high-fidelity numerical modeling and simulation …
increasingly reliant upon expensive, high-fidelity numerical modeling and simulation …
Shock wave prediction in transonic flow fields using domain-informed probabilistic deep learning
Transonic flow fields are marked by shock waves of varying strength and location and are
crucial for the aerodynamic design and optimization of high-speed transport aircraft. While …
crucial for the aerodynamic design and optimization of high-speed transport aircraft. While …
Non-intrusive parametric reduced order models with high-dimensional inputs via gradient-free active subspace
This work presents the development of a method for the construction of parametric,
interpolation-based non-intrusive Reduced Order Models (ROMs) for predicting field outputs …
interpolation-based non-intrusive Reduced Order Models (ROMs) for predicting field outputs …
Manifold alignment-based nonintrusive and nonlinear multifidelity reduced-order modeling
This study presents the development of a methodology for the construction of data-driven,
parametric, multifidelity reduced-order models to emulate aerodynamic flowfields with …
parametric, multifidelity reduced-order models to emulate aerodynamic flowfields with …
Multi-fidelity non-intrusive reduced-order modelling based on manifold alignment
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 …
order modelling method to tackle the problem of achieving an acceptable predictive …
Development of a multi-fidelity reduced-order model based on manifold alignment
This work presents the development of a novel multi-fidelity, parametric, and non-intrusive
Reduced Order Modeling (ROM) method to tackle the problem of achieving an acceptable …
Reduced Order Modeling (ROM) method to tackle the problem of achieving an acceptable …
Nonlinear Multi-Fidelity Reduced Order Modeling Method using Manifold Alignment
View Video Presentation: https://doi. org/10.2514/6.2021-3050. vid This study presents the
development of a methodology for the construction of data-driven, parametric, multi-fidelity …
development of a methodology for the construction of data-driven, parametric, multi-fidelity …