Importance Measure for Fuzzy Structural Systems from the Probabilistic Perspective and Its Solving Algorithms
Source abstract
Abstract
To effectively determine the influences of fuzzy uncertainties on structural systems in engineering, according to the fuzzy failure probability (FFP) model, which is based on the probabilistic perspective, the importance measure (IM) technique is extended to fuzzy uncertain structural systems. A novel IM framework, i.e., the fuzzy-failure-probability-based IM (FFP-IM), is established. By transforming the fuzzy failure probability into the expected value of the function for the failure domain, the proposed FFP-IM index can be represented as the variance-based IM of that index function. Then, an efficient solution algorithm for the proposed FFP-IM index is established based on the state-dependent parameter method. Ultimately, the Ishigami function, alongside three practical engineering examples, validates the proposed FFP-IM’s rationality and applicability. Furthermore, these examples illustrate the solution algorithm’s superior computational efficiency and accuracy.
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Research context
OpenAlex topics: Remote Sensing and Land Use · Structural Engineering and Vibration Analysis · Simulation and Modeling Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechanics and Aerospace Engineering, Dalian University of Technology, Dalian 116024, China
Key Laboratory of Advanced Technology for Aerospace Vehicles of Liaoning Province, Dalian University of Technology, Dalian 116024, China
Aircraft Strength Research Institute, Xi’an 710065, China
National Key Laboratory of Strength and Structural Integrity, Xi’an 710065, China
Funding
National Key Laboratory of Strength and Structural Integrity Opening Fund · National Natural Science Foundation of China
References (35)
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