Reliability-Based Design Optimization of Large-Scale Complex Systems

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The research objective of this award is to create new theoretical foundations and numerical algorithms for large-scale, reliability-based design optimization (RBDO) of complex engineering systems. The proposed effort will involve: (1) an extended polynomial dimensional decomposition (X-PDD) method for system reliability analysis of a general, high-dimensional, stochastic system; (2) integrated X-PDD and score functions for concurrently calculating sensitivities of system reliability with respect to design variables; and (3) system-level reliability-based and robust design optimization algorithms employing X-PDD for probabilistic response and sensitivities from a single stochastic simulation. The innovative formulation of system reliability analysis and design sensitivities will dramatically accelerate RBDO process. Therefore, the research constitutes a new and possibly paradigm-shifting advance towards solving large-scale, complex optimization problems in the presence of uncertainty. Deliverables include development of new theory and algorithms, generation of modeling and simulation tools, documentation of research results, engineering student education, and hands-on design experience for K-12 students.If successful, the results of this research will be applicable to a broad multidisciplinary design optimization methodology. Potential engineering applications comprise ground vehicle design for improved durability and crashworthiness, fatigue- and fracture-resistant design for civil and aerospace applications, and reliable design of microelectronic packaging under harsh environments. Beyond engineering, potential application areas include energy, finance, management, scheduling, and transportation and logistics, where stochastic optimization plays a vital role. The transfer of knowledge created by this award will take place through organization of engineering design-related symposia, peer-reviewed journal publications, presentations at major conferences and meetings, software development, and student education. Educational goals include graduate student recruitment from an underrepresented minority group, implementation of software tools to upgrade existing graduate and undergraduate courses at The University of Iowa, and active participation in Iowa's Project Lead the Way program for middle- and high-school students.