A marginalized unscented Kalman filter for efficient parameter estimation with applications to finite element models

DOI10.1016/j.cma.2018.05.014zbMath1440.93255OpenAlexW2804078743MaRDI QIDQ1986271

Audrey Olivier, Andrew W. Smyth

Publication date: 8 April 2020

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cma.2018.05.014

zbMATH Keywords

inverse problemsfinite element modelsdynamic analysisBayesian inferencemarginalizationextended and unscented Kalman filtering

Mathematics Subject Classification ID

Point estimation (62F10) Bayesian inference (62F15) Filtering in stochastic control theory (93E11) Finite element methods applied to problems in solid mechanics (74S05) Signal detection and filtering (aspects of stochastic processes) (60G35) Numerical methods for inverse problems for boundary value problems involving PDEs (65N21)

Related Items (5)

Simultaneous estimation and modeling of nonlinear, non-Gaussian state-space systems ⋮ Novel sparseness-inducing dual Kalman filter and its application to tracking time-varying spatially-sparse structural stiffness changes and inputs ⋮ A patching algorithm for conditional random fields in modeling material properties ⋮ Global sensitivity analysis for the design of nonlinear identification experiments ⋮ A cooperative game for automated learning of elasto-plasticity knowledge graphs and models with AI-guided experimentation

Uses Software

• FEAP
• DAISY
• DistMesh

Cites Work

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• Extended and unscented Kalman filtering based feedforward neural networks for time series prediction
• Joint state and parameter estimation for distributed mechanical systems
• Some practical procedures for the solution of nonlinear finite element equations
• Stochastic reduced order models for inverse problems under uncertainty
• On dimension reduction in Gaussian filters
• Reduced-order Unscented Kalman Filtering with application to parameter identification in large-dimensional systems
• Real-time solution of the finite element inverse problem of viscoelasticity
• Detection and quantification of flaws in structures by the extended finite element method and genetic algorithms
• Introduction to Nonlinear Finite Element Analysis
• A Simple Mesh Generator in MATLAB
• ASYMPTOTICALLY INDEPENDENT MARKOV SAMPLING: A NEW MARKOV CHAIN MONTE CARLO SCHEME FOR BAYESIAN INFERENCE
• A Novel a Priori State Computation Strategy for the Unscented Kalman Filter to Improve Computational Efficiency
• Marginalized particle filters for mixed linear/nonlinear state-space models
• Complexity analysis of the marginalized particle filter
• Kalman Filtering

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