Damage identification under uncertain mass density distributions
From MaRDI portal
Publication:2022028
DOI10.1016/j.cma.2021.113672zbMath1506.74340OpenAlexW3123968445MaRDI QIDQ2022028
Daniel A. Castello, Jari P. Kaipio, Gabriel L. S. Silva
Publication date: 27 April 2021
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.2021.113672
damage identificationmodeling errorsBayesian approximation error approachuncertain mass density field
Cites Work
- Unnamed Item
- Unnamed Item
- Approximation error approach in spatiotemporally chaotic models with application to Kuramoto-Sivashinsky equation
- Statistical inverse problems: discretization, model reduction and inverse crimes
- Approximation errors and truncation of computational domains with application to geophysical tomography
- An Introduction to Computational Stochastic PDEs
- Bayesian Updating and Model Class Selection for Hysteretic Structural Models Using Stochastic Simulation
- MARGINALIZATION OF UNINTERESTING DISTRIBUTED PARAMETERS IN INVERSE PROBLEMS APPLICATION TO DIFFUSE OPTICAL TOMOGRAPHY
- RECONSTRUCTION OF DOMAIN BOUNDARY AND CONDUCTIVITY IN ELECTRICAL IMPEDANCE TOMOGRAPHY USING THE APPROXIMATION ERROR APPROACH
- Approximation errors and model reduction with an application in optical diffusion tomography
- An approximation error approach for compensating for modelling errors between the radiative transfer equation and the diffusion approximation in diffuse optical tomography
- Correction of Model Reduction Errors in Simulations
- Estimation of aquifer dimensions from passive seismic signals with approximate wave propagation models
- Approximation error analysis in nonlinear state estimation with an application to state-space identification
This page was built for publication: Damage identification under uncertain mass density distributions