Details
| Original language | English |
|---|---|
| Pages (from-to) | 547-565 |
| Number of pages | 19 |
| Journal | Computational mechanics |
| Volume | 26 |
| Issue number | 6 |
| Publication status | Published - Dec 2000 |
| Externally published | Yes |
Abstract
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 α-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 α-level optimization and the deterministic fundamental solution.
ASJC Scopus subject areas
- Engineering(all)
- Computational Mechanics
- Engineering(all)
- Ocean Engineering
- Engineering(all)
- Mechanical Engineering
- Computer Science(all)
- Computational Theory and Mathematics
- Mathematics(all)
- Computational Mathematics
- Mathematics(all)
- Applied Mathematics
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In: Computational mechanics, Vol. 26, No. 6, 12.2000, p. 547-565.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Fuzzy structural analysis using α-level optimization
AU - Möller, B.
AU - Graf, W.
AU - Beer, M.
PY - 2000/12
Y1 - 2000/12
N2 - 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 α-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 α-level optimization and the deterministic fundamental solution.
AB - 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 α-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 α-level optimization and the deterministic fundamental solution.
UR - http://www.scopus.com/inward/record.url?scp=17344387190&partnerID=8YFLogxK
U2 - 10.1007/s004660000204
DO - 10.1007/s004660000204
M3 - Article
AN - SCOPUS:17344387190
VL - 26
SP - 547
EP - 565
JO - Computational mechanics
JF - Computational mechanics
SN - 0178-7675
IS - 6
ER -