Direct method and Bayesian inference for uncertainty quantification on stochastic NDT problem Universiteit Gent
In this paper, we present a framework to deal with uncertainty quantification in case where the ranges of variability of the random parameters are ill-known. Namely the physical properties of the corrosion product (magnetite) which frequently clogs the tube support plate of steam generator, which is inaccessible in nuclear power plants. The methodology is based on Polynomial Chaos (PC) direct approaches and on Bayesian inference for inverse ...