Sponsor: U.S. National Science Foundation
Project No.: CMMI-0969044
Duration: April 1, 2010 – March 31, 2013 (Extended to March 31, 2014)
Principal Investigator: Professor Sharif Rahman
Graduate Student: Xuchun Ren
The objective of this research project is to create new theoretical foundations and numerical algorithms for large-scale, reliability-based design optimization (RBDO) of complex engineering systems. The proposed effort is based on: (1) a new extended polynomial dimensional decomposition (X-PDD) method for statistical moment and reliability analyses of a general, high-dimensional, stochastic system (Task 1); (2) integrated X-PDD and score functions for concurrently calculating the design sensitivities of statistical moments and reliability (Task 2); and (3) reliability-based and robust design optimization (RBDO/RDO) algorithms employing X-PDD and score functions (Task 3). The innovative formulation of statistical moment analysis, reliability analysis, and design sensitivities will dramatically accelerate RBDO and RDO processes. Therefore, the research constitutes a new and possibly paradigm-shifting advance towards solving large-scale, complex optimization problems in the presence of uncertainty. If successful, the results of this research are envisioned to 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 project 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, implementation of software tools to upgrade existing graduate and undergraduate courses at The University of Iowa, and active participation in Iowa’s outreach programs for middle- and high-school students.