Multidisciplinary Design Optimization Under Uncertainties Based On Sequential Optimization And Reliability Assessment

For engineering product design under uncertainty, it is important to guarantee thereliability and safety, especially for complex and coupled systems design problems usingMultidisciplinary Design Optimization (MDO). Due to the different cognitive levels tovarious uncertain parameters, it is necessary to include the mixed uncertain parameters suchas the random parameters and fuzzy parameters into consideration simultaneously. The designproblem under hybrid uncertainty of randomness and fuzziness presents a challenge. However,little attention has been paid to solve hybrid uncertainty problems until now. UMDOprocedure is the organization of all the elements involved in the uncertainty based designoptimization, such as system optimization, system analysis, disciplinary analysis, uncertaintyanalysis. How to efficiently arrange these elements into an execution sequence is the key torealize UMDO of large systems, as the complex coupling disciplinary relationship andcomputational intensive system analysis models make UMDO very time consuming andcomputationally prohibitive.This study constructs the formulation of Fuzzy Random Uncertainty based MDO(FRMDO). A FRMDO problem can be transformed into a normal RBMDO problem at theoptimal cut set level λ based on the fuzzy random variables and λ level cut set method.And a method to solve the FRMDO problems within the framework of SequentialOptimization and Reliability Assessment (SORA), called the FRMDO-SORA approach, isproposed. The FRMDO-SORA approach can be applied both in single-level and multi-levelMDO methods, and can effectively solve MDO problems where fuzzy, random andfuzzy-random uncertainties coexist. Case studies are given to demonstrate the efficiency andfeasibility of the proposed FRMDO-SORA approach.