182 citations · 902 across the 17 of their papers we have counts for
20 papers
Stein Variational Rare Event Simulation
Max Ehre, Iason Papaioannou, Daniel Straub
Rare event simulation and rare event probability estimation are important tasks within the analysis of systems subject to uncertainty and randomness. Simultaneously, accurately est…
POMDP inference and robust solution via deep reinforcement learning: An application to railway optimal maintenance
Giacomo Arcieri, Cyprien Hoelzl, Oliver Schwery +3
Partially Observable Markov Decision Processes (POMDPs) can model complex sequential decision-making problems under stochastic and uncertain environments. A main reason hindering t…
Variance-based reliability sensitivity with dependent inputs using failure samples
Max Ehre, Iason Papaioannou, Daniel Straub
Reliability sensitivity analysis is concerned with measuring the influence of a system's uncertain input parameters on its probability of failure. Statistically dependent inputs pr…
A metric for assessing and optimizing data-driven prognostic algorithms for predictive maintenance
Antonios Kamariotis, Konstantinos Tatsis, Eleni Chatzi +2
Prognostic Health Management aims to predict the Remaining Useful Life (RUL) of degrading components/systems utilizing monitoring data. These RUL predictions form the basis for opt…
Bridging POMDPs and Bayesian decision making for robust maintenance planning under model uncertainty: An application to railway systems
Giacomo Arcieri, Cyprien Hoelzl, Oliver Schwery +3
Structural Health Monitoring (SHM) describes a process for inferring quantifiable metrics of structural condition, which can serve as input to support decisions on the operation an…
Bayesian improved cross entropy method for network reliability assessment
Jianpeng Chan, Iason Papaioannou, Daniel Straub
We propose a modification of the improved cross entropy (iCE) method to enhance its performance for network reliability assessment. The iCE method performs a transition from the no…
Certified Dimension Reduction for Bayesian Updating with the Cross-Entropy Method
Max Ehre, Rafael Flock, Martin Fußeder +2
In inverse problems, the parameters of a model are estimated based on observations of the model response. The Bayesian approach is powerful for solving such problems; one formulate…
On off-line and on-line Bayesian filtering for uncertainty quantification of structural deterioration
Antonios Kamariotis, Luca Sardi, Iason Papaioannou +2
Data-informed predictive maintenance planning largely relies on stochastic deterioration models. Monitoring information can be utilized to update sequentially the knowledge on time…
A framework for quantifying the value of vibration-based structural health monitoring
Antonios Kamariotis, Eleni Chatzi, Daniel Straub
The difficulty in quantifying the benefit of Structural Health Monitoring (SHM) for decision support is one of the bottlenecks to an extensive adoption of SHM on real-world structu…
Rare event estimation using stochastic spectral embedding
P. -R. Wagner, S. Marelli, I. Papaioannou +2
Estimating the probability of rare failure events is an essential step in the reliability assessment of engineering systems. Computing this failure probability for complex non-line…
Sequential active learning of low-dimensional model representations for reliability analysis
Max Ehre, Iason Papaioannou, Bruno Sudret +1
To date, the analysis of high-dimensional, computationally expensive engineering models remains a difficult challenge in risk and reliability engineering. We use a combination of d…
Decision-theoretic reliability sensitivity
Daniel Straub, Max Ehre, Iason Papaioannou
We propose and discuss sensitivity metrics for reliability analysis, which are based on the value of information. These metrics are easier to interpret than other existing sensitiv…
Value of information from vibration-based structural health monitoring extracted via Bayesian model updating
Antonios Kamariotis, Eleni Chatzi, Daniel Straub
Quantifying the value of the information extracted from a structural health monitoring (SHM) system is an important step towards convincing decision makers to implement these syste…
A unifying review of NDE models towards optimal decision support
Elizabeth Bismut, Daniel Straub
Non-destructive evaluation (NDE) inspections are an integral part of asset integrity management. The relationship between the condition of interest and the quantity measured by NDE…
Optimal adaptive inspection and maintenance planning for deteriorating structural systems
Elizabeth Bismut, Daniel Straub
Optimizing inspection and maintenance (I&M) plans for a large deteriorating structure is a computationally challenging task, in particular if one considers interdependences among i…
Cross-entropy-based importance sampling with failure-informed dimension reduction for rare event simulation
Felipe Uribe, Iason Papaioannou, Youssef M. Marzouk +1
The estimation of rare event or failure probabilities in high dimensions is of interest in many areas of science and technology. We consider problems where the rare event is expres…
Sparse Polynomial Chaos expansions using Variational Relevance Vector Machines
Panagiotis Tsilifis, Iason Papaioannou, Daniel Straub +1
The challenges for non-intrusive methods for Polynomial Chaos modeling lie in the computational efficiency and accuracy under a limited number of model simulations. These challenge…
Bayesian Network Enhanced with Structural Reliability Methods: Methodology
Daniel Straub, Armen Der Kiureghian
We combine Bayesian networks (BNs) and structural reliability methods (SRMs) to create a new computational framework, termed enhanced Bayesian network (eBN), for reliability and ri…
Bayesian Network Enhanced with Structural Reliability Methods: Application
Daniel Straub, Armen Der Kiureghian
The enhanced Bayesian network (eBN) methodology described in the companion paper facilitates the assessment of reliability and risk of engineering systems when information about th…
Reliability updating with equality information
Daniel Straub
In many instances, information on engineering systems can be obtained through measurements, monitoring or direct observations of system performances and can be used to update the s…