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Fuzzy structural analysis using α-level optimization
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AI
DOI：10.1007/s004660000204.png)
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摘要
En 中文
In this paper new concepts and developments are presented for structural analysis involving uncertain parameters. Based on a classification of the uncertainties in structural analysis the uncertainty fuzziness is identified and its quantification is demonstrated. On the basis of fuzzy set theory a general method for fuzzy structural analysis is developed and formulated in terms of the alpha -level optimization with the application of a modified evolution strategy. Every known analysis algorithm for the realistic simulation of load-bearing behavior may be applied in the fuzzy structural analysis in the sense of a deterministic fundamental solution. By way of example, geometrically and physically nonlinear algorithms are adopted in the presented study as a deterministic fundamental solution for the analysis of steel and reinforced concrete structures. The paper also describes coupling between alpha -level optimization and the deterministic fundamental solution.
Keyword:
RANDOM-VARIABLES
RELIABILITY
PREDICTION
DESIGN
