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Found 6 papers, 2 papers with code
Linear Reduced Order Model Predictive Control
Model predictive controllers use dynamics models to solve constrained optimal control problems.
Mesh sampling and weighting for the hyperreduction of nonlinear Petrov-Galerkin reduced-order models with local reduced-order bases
The energy-conserving sampling and weighting (ECSW) method is a hyperreduction method originally developed for accelerating the performance of Galerkin projection-based reduced-order models (PROMs) associated with large-scale finite element models, when the underlying projected operators need to be frequently recomputed as in parametric and/or nonlinear problems.
A Computationally Tractable Framework for Nonlinear Dynamic Multiscale Modeling of Membrane Fabric
The numerical solution of displacement driven problems involving this model can be adapted to the context of membranes by a variant of the Klinkel-Govindjee method[1] originally proposed for using finite strain, three-dimensional material models in beam and shell elements.
On the stability of projection-based model order reduction for convection-dominated laminar and turbulent flows
In the literature on projection-based nonlinear model order reduction for fluid dynamics problems, it is often claimed that due to modal truncation, a projection-based reduced-order model (PROM) does not resolve the dissipative regime of the turbulent energy cascade and therefore is numerically unstable.
Predictive Modeling with Learned Constitutive Relations from Indirect Observations
Its counterparts, like piecewise linear functions and radial basis functions, are compared, and the strength of neural networks is explored.
Numerical Analysis Numerical Analysis Computational Physics
Fast Neural Network Predictions from Constrained Aerodynamics Datasets
Incorporating computational fluid dynamics in the design process of jets, spacecraft, or gas turbine engines is often challenged by the required computational resources and simulation time, which depend on the chosen physics-based computational models and grid resolutions.
