caa a22 4500 463244214 CHVBK 20180405153321.0 cr unu---uuuuu 170326e20070301xx s 000 0 eng 10.1007/s00158-006-0057-3 doi (NATIONALLICENCE)springer-10.1007/s00158-006-0057-3 An inverse-measure-based unilevel architecture for reliability-based design optimization [Elektronische Daten] [Harish Agarwal, Chandan Mozumder, John Renaud, Layne Watson] Reliability-based design optimization (RBDO) is a methodology for finding optimized designs that are characterized with a low probability of failure. Primarily, RBDO consists of optimizing a merit function while satisfying reliability constraints. The reliability constraints are constraints on the probability of failure corresponding to each of the failure modes of the system or a single constraint on the system probability of failure. The probability of failure is usually estimated by performing a reliability analysis. During the last few years, a variety of different formulations have been developed for RBDO. Traditionally, these have been formulated as a double-loop (nested) optimization problem. The upper level optimization loop generally involves optimizing a merit function subject to reliability constraints, and the lower level optimization loop(s) compute(s) the probabilities of failure corresponding to the failure mode(s) that govern(s) the system failure. This formulation is, by nature, computationally intensive. Researchers have provided sequential strategies to address this issue, where the deterministic optimization and reliability analysis are decoupled, and the process is performed iteratively until convergence is achieved. These methods, though attractive in terms of obtaining a workable reliable design at considerably reduced computational costs, often lead to premature convergence and therefore yield spurious optimal designs. In this paper, a novel unilevel formulation for RBDO is developed. In the proposed formulation, the lower level optimization (evaluation of reliability constraints in the double-loop formulation) is replaced by its corresponding first-order Karush-Kuhn-Tucker (KKT) necessary optimality conditions at the upper level optimization. Such a replacement is computationally equivalent to solving the original nested optimization if the lower level optimization problem is solved by numerically satisfying the KKT conditions (which is typically the case). It is shown through the use of test problems that the proposed formulation is numerically robust (stable) and computationally efficient compared to the existing approaches for RBDO. Springer-Verlag Berlin Heidelberg, 2006 Reliability-based design optimization nationallicence Unilevel methods nationallicence Deterministic optimization nationallicence Variables nationallicence Parameters nationallicence Agarwal Harish Department of Aerospace and Mechanical Engineering, University of Notre Dame, 46556, Notre Dame, IN, USA aut Mozumder Chandan Department of Aerospace and Mechanical Engineering, University of Notre Dame, 46556, Notre Dame, IN, USA aut Renaud John Department of Aerospace and Mechanical Engineering, University of Notre Dame, 46556, Notre Dame, IN, USA aut Watson Layne Department of Computer Science, Virginia Polytechnic Institute and State University, 24061-0106, Blacksburg, VA, USA aut Structural and Multidisciplinary Optimization Springer-Verlag 33/3(2007-03-01), 217-227 1615-147X 33:3<217 2007 33 158 https://doi.org/10.1007/s00158-006-0057-3 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00158-006-0057-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Agarwal Harish Department of Aerospace and Mechanical Engineering, University of Notre Dame, 46556, Notre Dame, IN, USA aut NATIONALLICENCE 700 1- Mozumder Chandan Department of Aerospace and Mechanical Engineering, University of Notre Dame, 46556, Notre Dame, IN, USA aut NATIONALLICENCE 700 1- Renaud John Department of Aerospace and Mechanical Engineering, University of Notre Dame, 46556, Notre Dame, IN, USA aut NATIONALLICENCE 700 1- Watson Layne Department of Computer Science, Virginia Polytechnic Institute and State University, 24061-0106, Blacksburg, VA, USA aut NATIONALLICENCE 773 0- Structural and Multidisciplinary Optimization Springer-Verlag 33/3(2007-03-01), 217-227 1615-147X 33:3<217 2007 33 158 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer