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Uncertainty Propagation for the Structures with Fuzzy Variables and Uncertain-but-Bounded Variables
Yanjun Xia1, Linfei Ding2, Pan Liu3
1School of Mechatronics Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
Materials (Basel, Switzerland)
|May 13, 2023
Summary
This study addresses uncertainty propagation in systems with fuzzy and bounded variables. It introduces a novel method combining fuzzy membership levels and non-probabilistic reliability indices for accurate analysis.
Area of Science:
- Engineering
- Uncertainty Quantification
- Reliability Analysis
Background:
- Practical systems face various uncertainties, often modeled using random, bounded, or fuzzy variables.
- Existing methods struggle with systems involving both epistemic uncertainty (fuzzy variables) and limited sample data (bounded variables).
Purpose of the Study:
- To investigate uncertainty propagation in systems with fuzzy variables and uncertain-but-bounded variables.
- To develop a robust method for analyzing systems with combined epistemic and data-limited uncertainties.
Main Methods:
- Utilized fuzzy variables described by membership functions and uncertain-but-bounded variables defined by multi-ellipsoid convex sets.
- Employed a combination of the membership levels method for fuzzy variables and the non-probabilistic reliability index for bounded variables.
- Solved uncertainty propagation via a nested optimization problem at each membership level.
Main Results:
- Successfully calculated the membership function of the non-probabilistic reliability index for complex systems.
- Demonstrated the model's applicability and the proposed method's efficiency through various examples.
- Provided a framework for analyzing systems with mixed uncertainty types.
Conclusions:
- The proposed combined method effectively handles uncertainty propagation in systems with fuzzy and bounded variables.
- This approach offers a valuable tool for reliability assessment in engineering and other fields facing complex uncertainties.
- The study highlights the importance of integrated methods for accurate system analysis.
Keywords:
fuzzy variablesmulti-ellipsoid convex setnon-probabilistic reliability indexuncertain-but-bounded variablesuncertainty propagationMore Related Videos
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