Developing a Multi-objective Multi-Disciplinary Robust Design Optimization Framework

Abstract

The purpose of this study is to provide an efficient Multi-Objective Multidisciplinary Robust Design Optimization (MOMRDO) framework. To this end, Bi-Level Integrated System Synthesis (BLISS) framework is implemented as a fast Multi-disciplinary Design Optimization (MDO) framework. Progressive Latin Hypercube Sampling (PLHS) is developed as a Design of Experiment (DOE) of the Uncertainty Analysis (UA). This systematic approach leads to a fast, adaptive and efficient framework for Robust Design Optimization (RDO) of complex systems. The accuracy and performance of the proposed algorithm have been evaluated with various tests. Finally, the RDO of a hydrazine monopropellant thruster is defined as a case study. The results show that the proposed method is a fast and efficient method for the multi-objective optimization design of complex systems, and this approach can be used for other engineering applications as well.