Bounds optimization of model response moments: a twin-engine Bayesian active learning method

DOI10.1007/S00466-021-01977-8zbMath1469.74092OpenAlexW3155901005WikidataQ113326758 ScholiaQ113326758MaRDI QIDQ2039068

Fangqi Hong, Pengfei Wei, Kok Kwang Phoon, Michael A. Beer

Publication date: 8 July 2021

Published in: Computational Mechanics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00466-021-01977-8

zbMATH Keywords

Bayesian inferenceimprecise probabilityuncertainty quantificationGaussian process regressionadaptive optimizationmaximal thermal stressturbine blade model

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Thermal effects in solid mechanics (74F05) Optimization of other properties in solid mechanics (74P10) Numerical and other methods in solid mechanics (74S99) Stochastic and other probabilistic methods applied to problems in solid mechanics (74S60)

Related Items (3)

A new Bayesian probabilistic integration framework for hybrid uncertainty propagation ⋮ Collaborative and adaptive Bayesian optimization for bounding variances and probabilities under hybrid uncertainties ⋮ A copula-based uncertainty propagation method for structures with correlated parametric p-boxes

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