Bayesian inference calibration of the modulus of elasticity
Numerical Analysis
2025-11-03 v1 Numerical Analysis
Abstract
This work uses the Bayesian inference technique to infer the Young modulus from the stochastic linear elasticity equation. The Young modulus is modeled by a finite Karhunen Lo\'{e}ve expansion, while the solution to the linear elasticity equation is approximated by the finite element method. The high-dimensional integral involving the posterior density and the quantity of interest is approximated by a higher-order quasi-Monte Carlo method.
Keywords
Cite
@article{arxiv.2510.27060,
title = {Bayesian inference calibration of the modulus of elasticity},
author = {J. Dick and Q. T. Le Gia and K. Mustapha},
journal= {arXiv preprint arXiv:2510.27060},
year = {2025}
}
Comments
10 pages, 1 figure