Practical error bounds for a non-intrusive bi-fidelity approach to parametric/stochastic model reduction

DOI10.1016/j.jcp.2018.04.015zbMath1392.62352OpenAlexW2797702392WikidataQ130015170 ScholiaQ130015170MaRDI QIDQ725460

Alireza Doostan, Hillary R. Fairbanks, Jerrad Hampton, Akil C. Narayan

Publication date: 1 August 2018

Published in: Journal of Computational Physics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jcp.2018.04.015

zbMATH Keywords

low-rank approximationuncertainty quantificationparametric model reductionbifidelity approximationmatrix interpolative decompositionmultifidelity approximation

Mathematics Subject Classification ID

Related Items (22)

Nonintrusive Reduced Order Modelling of Convective Boussinesq Flows ⋮ Pass-efficient methods for compression of high-dimensional turbulent flow data ⋮ Multifidelity modeling for physics-informed neural networks (PINNs) ⋮ Neural network training using \(\ell_1\)-regularization and bi-fidelity data ⋮ A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems ⋮ A bi-fidelity surrogate modeling approach for uncertainty propagation in three-dimensional hemodynamic simulations ⋮ Coarse-proxy reduced basis methods for integral equations ⋮ Context-aware learning of hierarchies of low-fidelity models for multi-fidelity uncertainty quantification ⋮ Bi-fidelity variational auto-encoder for uncertainty quantification ⋮ An artificial neural network framework for reduced order modeling of transient flows ⋮ Adaptive multi-fidelity polynomial chaos approach to Bayesian inference in inverse problems ⋮ Bi-fidelity stochastic gradient descent for structural optimization under uncertainty ⋮ Uncertainty quantification of discontinuous outputs via a non-intrusive bifidelity strategy ⋮ A bi-fidelity method for the multiscale Boltzmann equation with random parameters ⋮ Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence ⋮ A bi-fidelity ensemble Kalman method for PDE-constrained inverse problems in computational mechanics ⋮ Bifidelity data-assisted neural networks in nonintrusive reduced-order modeling ⋮ A hybrid model reduction method for stochastic parabolic optimal control problems ⋮ Fast predictive multi-fidelity prediction with models of quantized fidelity levels ⋮ Allocation Strategies for High Fidelity Models in the Multifidelity Regime ⋮ GenMod: a generative modeling approach for spectral representation of PDEs with random inputs ⋮ Bi-fidelity reduced polynomial chaos expansion for uncertainty quantification

Uses Software

• FEniCS

Cites Work

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