Browsing School of Engineering by Author "Shields, Michael"
Now showing items 1-3 of 3
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Constrained non-intrusive polynomial chaos expansion for physics-informed machine learning regression
Sharma, Himanshu; Novak, Lukas; Shields, Michael; ICASP14 (2023)This work presents a constrained polynomial chaos expansion (PCE) as a physics-informed machine learning (ML) technique to supplement data with physical constraints in the regression framework. PCE is a popular metamodeling ... -
Efficient Subset Simulations using Hamiltonian Neural Network enhanced Markov Chain Monte Carlo methods
Thaler, Denny; Shields, Michael; Markert, Bernd; Bamer, Franz; Dhulipala, Somayajulu; ICASP14 (2023)The Monte Carlo method delivers an unbiased estimate of the probability of failure. However, the variance of the estimate depends on the number of evaluated samples. This number must be very large for estimations of a low ... -
Reliability Analysis using Multiple Low-fidelity Models Coupled with Active Learning: A Robust, General, and Explainable Framework
Dhulipala, Somayajulu; Shields, Michael; Chakroborty, Promit; ICASP14 (2023)To assess the reliability of critical technologies like nuclear plants and infrastructure systems and improve the robustness of design, engineers have to quantify the uncertainties surrounding the system behavior accurately. ...