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.
翻译:本研究采用贝叶斯推断技术,从随机线性弹性方程中推断杨氏模量。杨氏模量通过有限项的Karhunen-Loève展开进行建模,而线性弹性方程的解则采用有限元方法进行近似。涉及后验密度与关注量的高维积分通过高阶拟蒙特卡洛方法进行近似计算。