首页|Physics-embedding multi-response regressor for time-variant system reliability assessment
Physics-embedding multi-response regressor for time-variant system reliability assessment
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NETL
NSTL
Elsevier
Efficient time-variant reliability assessment for complex systems is of great interest but challenging as the highly complex multiple output responses under time-variant uncertainties are hard to quantify. The task becomes even more challenging if the interconnected dependencies between multiple failure modes are involved. In this study, an eXtreme physics-embedding multi-response regressor (X-PMR) is presented for time-variant system reliability assessment. Firstly, by transforming time-variant multiple responses to time-invariant extreme values, an eXtreme multi-domain transformation concept is presented, to establish the time-invariant multi-input multioutput (TiMIMO) dataset; moreover, by embedding physics/mathematics knowledge into multi-objective ensemble modeling, a physics-embedding multi-response regressor is proposed, to synchronously construct the surrogate model for highly complex multiple output responses. The validation effectiveness and benefit illustration of the X-PMR method are revealed by introducing three numerical systems (i.e., series system, parallel system and series/parallel hybrid system) and a real application system (i.e., dynamic aeroengine turbine blisk), in comparison with a number of state-of-the-art methods investigated in the literature. The current efforts can provide a novel sight to address the time-variant system reliability assessment problems.
Song, Lu-Kai、Tao, Fei、Li, Xue-Qin、Yang, Le-Chang、Wei, Yu-Peng、Beer, Michael
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Beihang University International Research Institute for Multidisciplinary Science
Beihang University International Research Institute for Multidisciplinary Science||Beihang University School of Automation Science and Electrical Engineering
City University of Hong Kong Department of Civil and Architectural Engineering
University of Science and Technology Beijing School of Mechanical Engineering
NETL
NSTL
Elsevier
