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08/10/2023
GPLaSDI: Gaussian Process-based Interpretable Latent Space Dynamics Identification through Deep Autoencoder
Numerically solving partial differential equations (PDEs) can be challen...
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05/31/2023
Data-scarce surrogate modeling of shock-induced pore collapse process
Understanding the mechanisms of shock-induced pore collapse is of great ...
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05/24/2023
A fast and accurate domain-decomposition nonlinear manifold reduced order model
This paper integrates nonlinear-manifold reduced order models (NM-ROMs) ...
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11/24/2022
Certified data-driven physics-informed greedy auto-encoder simulator
A parametric adaptive greedy Latent Space Dynamics Identification (gLaSD...
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05/19/2022
Stress-constrained topology optimization of lattice-like structures using component-wise reduced order models
Lattice-like structures can provide a combination of high stiffness with...
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04/26/2022
Parametric Dynamic Mode Decomposition for Reduced Order Modeling
Dynamic Mode Decomposition (DMD) is a model-order reduction approach, wh...
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04/26/2022
gLaSDI: Parametric Physics-informed Greedy Latent Space Dynamics Identification
A parametric adaptive physics-informed greedy Latent Space Dynamics Iden...
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03/29/2022
S-OPT: A Points Selection Algorithm for Hyper-Reduction in Reduced Order Models
While projection-based reduced order models can reduce the dimension of ...
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03/04/2022
LaSDI: Parametric Latent Space Dynamics Identification
Enabling fast and accurate physical simulations with data has become an ...
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02/11/2022
Reduced order modeling for flow and transport problems with Barlow Twins self-supervised learning
We propose a unified data-driven reduced order model (ROM) that bridges ...
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01/18/2022
Local Lagrangian reduced-order modeling for Rayleigh-Taylor instability by solution manifold decomposition
Rayleigh-Taylor instability is a classical hydrodynamic instability of g...
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05/27/2021
A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks
This work is the first to employ and adapt the image-to-image translatio...
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04/23/2021
Reduced order models for Lagrangian hydrodynamics
As a mathematical model of high-speed flow and shock wave propagation in...
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11/20/2020
Efficient space-time reduced order model for linear dynamical systems in Python using less than 120 lines of code
A classical reduced order model (ROM) for dynamical problems typically i...
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11/13/2020
Efficient nonlinear manifold reduced order model
Traditional linear subspace reduced order models (LS-ROMs) are able to a...
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10/21/2020
Component-wise reduced order model lattice-type structure design
Lattice-type structures can provide a combination of stiffness with ligh...
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09/25/2020
A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder
Traditional linear subspace reduced order models (LS-ROMs) are able to a...
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07/23/2020
Domain-decomposition least-squares Petrov-Galerkin (DD-LSPG) nonlinear model reduction
While reduced-order models (ROMs) have demonstrated success in many appl...
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10/03/2019
Space-time reduced order model for large-scale linear dynamical systems with application to Boltzmann transport problems
A classical reduced order model for dynamical problems involves spatial ...
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09/25/2019
Accelerating design optimization using reduced order models
Although design optimization has shown its great power of automatizing t...
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09/11/2018
SNS: A Solution-based Nonlinear Subspace method for time-dependent model order reduction
Several reduced order models have been successfully developed for nonlin...
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09/11/2018
SNS: A Solution-based Nonlinear Subspace method for time-dependent nonlinear model order reduction
Several reduced order models have been successfully developed for nonlin...
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11/30/2017
Conservative model reduction for finite-volume models
This work proposes a method for model reduction of finite-volume models ...
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03/14/2017
