Frequency domain reduced order model (ROM) for second-order systems with frequency dependent matrices
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Updated
Mar 13, 2018 - Python
Frequency domain reduced order model (ROM) for second-order systems with frequency dependent matrices
Frequency domain reduced order model (ROM) for second-order systems with frequency dependent matrices
Implementation of the Generalized Multiscale Finite Element Method (GMsFEM) for solution problems in heterogeneous media with finite volume approximation on the fine grid
Hierarchical Model Reduction
Non-intrusive reduced order models using proper orthogonal decomposition (POD) and radial basis function (RBF) interpolation for shallow water equations
Neural Ordinary Differential Equations for model order reduction of time-dependent PDEs
HAPOD - Hierarchical Approximate Proper Orthogonal Decomposition
Implementation of balanced truncation method for semi-discretized heat equation, boundary control, Neumann observation. In 2018.
Python tools for non-intrusive reduced order modeling
Python libraries (NumPy-based) to perform model order reduction, clustering and data analysis for combustion and aerothermochemistry data
Supporting code for "reduced order modeling using advection-aware autoencoders"
Minimal rational interpolation (MRI) suite for time-harmonic problems in electromagnetism governed by Maxwell's equations.
The unsupervised learning problem trains a diffeomorphic spatio-temporal grid, that registers the output sequence of the PDEs onto a non-uniform parameter/time-varying grid, such that the Kolmogorov n-width of the mapped data on the learned grid is minimized.
individual convolutional autoencoders (iCAEs) for low-dimensional parametrization
Implementation of the Reduced Basis Method
Example of control simulations
morgen - Model Order Reduction for Gas and Energy Networks
Supplemental Material for "BUQEYE Guide to Projection-Based Emulators in Nuclear Physics"
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