9 papers
Likelihood-informed Model Reduction for Bayesian Inference of Static Structural Loads
Jakob Scheffels, Elizabeth Qian, Iason Papaioannou +1
Bayesian inverse problems use data to update a prior probability distribution on uncertain parameter values to a posterior distribution. Such problems arise in many structural engi…
A Hierarchical Bayesian Framework for Model-based Prognostics
Xinyu Jia, Iason Papaioannou, Daniel Straub
In prognostics and health management (PHM) of engineered systems, maintenance decisions are ideally informed by predictions of a system's remaining useful life (RUL) based on opera…
Sensitivity measures for engineering and environmental decision support
Daniel Straub, Wolfgang Betz, Mara Ruf +4
Information value, a measure for decision sensitivity, can provide essential information in engineering and environmental assessments. It quantifies the potential for improved deci…
A novel stratified sampler with unbalanced refinement for network reliability assessment
Jianpeng Chan, Iason Papaioannou, Daniel Straub
We investigate stratified sampling in the context of network reliability assessment. We propose an unbalanced stratum refinement procedure, which operates on a partition of network…
Efficient Bayesian inversion for simultaneous estimation of geometry and spatial field using the Karhunen-Loève expansion
Tatsuya Shibata, Michael Conrad Koch, Iason Papaioannou +1
Detection of abrupt spatial changes in physical properties representing unique geometric features such as buried objects, cavities, and fractures is an important problem in geophys…
Enhanced sequential directional importance sampling for structural reliability analysis
Kai Chenga, Iason Papaioannou, Daniel Straub
Sequential directional importance sampling (SDIS) is an efficient adaptive simulation method for estimating failure probabilities. It expresses the failure probability as the produ…