Compromise design of stochastic dynamical systems: A reliability-based approach |
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| Affiliation: | 1. Division of Nuclear Power Safety, Royal Institute of Technology (KTH), Roslagstullsbacken 21, SE-10691 Stockholm, Sweden;2. Nuclear Engineering, LUT School of Energy Systems, Lappeenranta University of Technology (LUT), FIN-53851 Lappeenranta, Finland;1. Institute of Mechanics, Department of Mechanical Engineering, TU Dortmund, Germany;2. Centro Universitario de la Defensa, Academia General Militar, Zaragoza, Spain;3. Applied Mechanics and Bioengineering, Aragón Institute of Engineering Research (I3A), University of Zaragoza, CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Spain;4. Laboratori de Calcul Numeric (LaCaN), Universitat Politecnica de Catalunya, Barcelona, Spain;5. Department of Anatomy, Embryology and Genetics, Veterinary Faculty, University of Zaragoza, Spain;6. Division of Solid Mechanics, Lund University, Sweden;7. 3M Deutschland GmbH, Carl-Schurz-Str. 1, D-41453 Neuss, Germany;1. Paul Scherrer Institute (PSI), OHSA/C02, Paul Scherrer Institute, 5232 Villigen PSI, Switzerland;2. Gesellschaft für Anlagen- und Reaktorsicherheit mbH (GRS) Forschungsinstitute, 85748 Garching, Germany;3. EDF R&D, SINETICS, I28/1 Avenue du Général de Gaulle, 92140 Clamart, France;4. Ruhr-Universität Bochum (RUB) Chair of Energy Systems and Energy Economics, Building IC 2-175, Universitätsstraße 150, D - 44801 Bochum, Germany;5. Institut de Radioprotection et de Sûreté Nucléaire (IRSN), IRSN/PSN-RES/SAG/LESAM, Cadarache Nuclear Center, BP 3 13 115 St Paul Lez Durance cedex, France;6. Hungarian Academy of Sciences, Centre for Energy Research (MTA EK), P.O. Box 49, H-1121 Budapest, Hungary;7. Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany;8. Nuclear Safety Institute (IBRAE), B. Tulskaya 52, 115191 Moscow, Russia;9. Institute for Nuclear Research and Nuclear Energy (INRNE), 72 Tzarigradsko chausee Blvd., 1784 Sofia, Bulgaria |
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| Abstract: | This paper presents a procedure for obtaining compromise designs of structural systems under stochastic excitation. In particular, an effective strategy for determining specific Pareto optimal solutions is implemented. The design goals are defined in terms of deterministic performance functions and/or performance functions involving reliability measures. The associated reliability problems are characterized by means of a large number of uncertain parameters (hundreds or thousands). The designs are obtained by formulating a compromise programming problem which is solved by a first-order interior point algorithm. The sensitivity information required by the proposed solution strategy is estimated by an approach that combines an advanced simulation technique with local approximations of some of the quantities associated with structural performance. An efficient Pareto sensitivity analysis with respect to the design variables becomes possible with the proposed formulation. Such information is used for decision making and tradeoff analysis. Numerical validations show that only a moderate number of stochastic analyses (reliability estimations) has to be performed in order to find compromise designs. Two example problems are presented to illustrate the effectiveness of the proposed approach. |
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