Operator inference driven data assimilation for high fidelity neutron transport (Q6595882)

scientific article; zbMATH DE number 7904373

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English	Operator inference driven data assimilation for high fidelity neutron transport	scientific article; zbMATH DE number 7904373

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instance of

scholarly article

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title

Operator inference driven data assimilation for high fidelity neutron transport (English)

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Computer Methods in Applied Mechanics and Engineering

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publication date

30 August 2024

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zbMATH Keywords

non-intrusive reduced order model

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scientific machine learning

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Kalman filter

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parameter inference

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time-dependent neutron transport equation

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Publication

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cites work

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Space-time reduced order model for large-scale linear dynamical systems with application to Boltzmann transport problems

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Non-intrusive model order reduction for parametric radiation transport simulations

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A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder

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Q2957673

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Higher-order dynamic mode decomposition on-the-fly: a low-order algorithm for complex fluid flows

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Parametric dynamic mode decomposition for reduced order modeling

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Data-driven operator inference for nonintrusive projection-based model reduction

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Preserving Lagrangian structure in data-driven reduced-order modeling of large-scale dynamical systems

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Bayesian operator inference for data-driven reduced-order modeling

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Operator inference for non-intrusive model reduction of systems with non-polynomial nonlinear terms

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Nonintrusive Reduced-Order Models for Parametric Partial Differential Equations via Data-Driven Operator Inference

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Predicting solar wind streams from the inner-heliosphere to Earth via shifted operator inference

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Active Operator Inference for Learning Low-Dimensional Dynamical-System Models from Noisy Data

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Lagrangian operator inference enhanced with structure-preserving machine learning for nonintrusive model reduction of mechanical systems

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Application of stiffness confinement method within variational nodal method for solving time-dependent neutron transport equation

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Stochastic models, estimation, and control. Vol. 2,3

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Sampling Low-Dimensional Markovian Dynamics for Preasymptotically Recovering Reduced Models from Data with Operator Inference

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Operator inference with roll outs for learning reduced models from scarce and low-quality data

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Learning physics-based reduced-order models from data using nonlinear manifolds

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Operator inference for non-intrusive model reduction with quadratic manifolds

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Identifiers

Mathematics Subject Classification ID

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10.1016/J.CMA.2024.117214

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Sitelinks

Mathematics(1 entry)

mardi Publication:6595882