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Keywords: optimization, robustness, reliability, particle swarm optimization, reduced model.

Summary

In this paper several help tools for the decisions during the robust design of mechanical structures in an uncertain environment are established. The problem considered in this paper is the methods to obtain an optimized structure using reliability optimization, which means the optimization with regard to reliability constraints.

This paper proposes a coupling of the reliability methods based on the particular swarm method [1,2] and dynamic metamodels or reduced models [3]. The first order reliability method FORM [4] is used to calculate the failure probability without using Monte Carlo simulation. The two simulation examples proposed in this paper illustrate the interest and the performance of the proposed method in the reliability based design optimization approach. The results show that the proposed method enables the calculation of the optimal uncertainty design parameters which produces the optimum mass of the structure with respect to an a priori fixed reliability index.

The main conclusions of this work are: 1) a robust design is obtained by introducing a performance indicator which leads to quantifying the robustness according to the uncertainty level of the parameters, 2) the coupling of a robust reduced model and heuristic optimization method that permits the efficient reliable design of complex mechanical structures with several degrees of freedom and uncertain design parameters.

References

1: J. Kennedy, R.C. Eberhart, "Particle swarm optimization", Proc. IEEE Int. Conf. on Neural Networks, 4, 1942-1948, 1995. doi:10.1109/ICNN.1995.488968
2: M. Clerc, J. Kennedy, "The Particle Swarm: Explosion, Stability, and Convergence in a Multi-Dimensional Complex Space", 2004.
3: M. Guedri, N. Bouhaddi, R. Majed, "Reduction of the stochastic finite element models using a robust dynamic condensation method", Journal of Sound and Vibration, 297, 123-145, 2006. doi:10.1016/j.jsv.2006.03.046
4: K. Breitung, F. Casciati, L. Faravelli, "Reliability based stability analysis for actively controlled structures", Engineering Structure, 20(3), 211-215, 1998. doi:10.1016/S0141-0296(97)00071-0

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 99 PROCEEDINGS OF THE ELEVENTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STRUCTURES TECHNOLOGY Edited by: B.H.V. Topping Paper 206 The Coupling of Robust Metamodel and Heuristic Methods in Reliability Based Design Optimization N. Rabhi¹, M. Guedri¹ and N. Bouhaddi² ¹Nabeul Preparatory Engineering Institute (IPEIN), M'rezgua, Nabeul, Tunisia ²FEMTO-ST Institute UMR 6174, Applied Mechanics Laboratory R. Chaléat, University of Franche-Comté, Besançon, France doi:10.4203/ccp.99.206 purchase the full-text of this paper Full Bibliographic Reference for this paper N. Rabhi, M. Guedri, N. Bouhaddi, "The Coupling of Robust Metamodel and Heuristic Methods in Reliability Based Design Optimization", in B.H.V. Topping, (Editor), "Proceedings of the Eleventh International Conference on Computational Structures Technology", Civil-Comp Press, Stirlingshire, UK, Paper 206, 2012. doi:10.4203/ccp.99.206 Keywords: optimization, robustness, reliability, particle swarm optimization, reduced model. Summary In this paper several help tools for the decisions during the robust design of mechanical structures in an uncertain environment are established. The problem considered in this paper is the methods to obtain an optimized structure using reliability optimization, which means the optimization with regard to reliability constraints. This paper proposes a coupling of the reliability methods based on the particular swarm method [1,2] and dynamic metamodels or reduced models [3]. The first order reliability method FORM [4] is used to calculate the failure probability without using Monte Carlo simulation. The two simulation examples proposed in this paper illustrate the interest and the performance of the proposed method in the reliability based design optimization approach. The results show that the proposed method enables the calculation of the optimal uncertainty design parameters which produces the optimum mass of the structure with respect to an a priori fixed reliability index. The main conclusions of this work are: 1) a robust design is obtained by introducing a performance indicator which leads to quantifying the robustness according to the uncertainty level of the parameters, 2) the coupling of a robust reduced model and heuristic optimization method that permits the efficient reliable design of complex mechanical structures with several degrees of freedom and uncertain design parameters. References 1 J. Kennedy, R.C. Eberhart, "Particle swarm optimization", Proc. IEEE Int. Conf. on Neural Networks, 4, 1942-1948, 1995. doi:10.1109/ICNN.1995.488968 2 M. Clerc, J. Kennedy, "The Particle Swarm: Explosion, Stability, and Convergence in a Multi-Dimensional Complex Space", 2004. 3 M. Guedri, N. Bouhaddi, R. Majed, "Reduction of the stochastic finite element models using a robust dynamic condensation method", Journal of Sound and Vibration, 297, 123-145, 2006. doi:10.1016/j.jsv.2006.03.046 4 K. Breitung, F. Casciati, L. Faravelli, "Reliability based stability analysis for actively controlled structures", Engineering Structure, 20(3), 211-215, 1998. doi:10.1016/S0141-0296(97)00071-0 purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £65 +P&P)
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