Multidisciplinary Design Optimization Method And Its Application In Aircraft Design

Aircraft design involves many different disciplines, such as aerodynamics, structure, propulsion and flight control. Aircraft designers must look these disciplines as a whole one system instead of separate ones. These disciplines influence each other and each discipline has its own research field. So aircraft design may be a very huge optimization problem facing how to make effective communication among these disciplines and how to deal with the computationally expensive problem.In this background, Multidisciplinary Design Optimization (MDO) emerged. MDO is a new method to solve the complex engineering optimization problem. This paper focuses on MDO algorithm and its application on aircraft design. The main parts of this paper is as follows:1 .The aircraft MDO mathematical model is constructed. Compared with common optimization problems, the aircraft MDO has many special concepts. Based on the relationship between different disciplines, three basic kinds of aircraft MDO problems are proposed. Almost all the aircraft MDO problems can be looked as the combination of these three kinds. The difficulty of aircraft MDO is pointed out, which gives the direction of this study.2. Several approximation methods are summarized, these methods are parts of a complete MDO algorithm.3. Collaborative Optimization (CO) is an effective MDO algorithm which divides the original problem into two parts: one system-level optimization and several disciplinary level optimizations. The mathematical property of CO is analyzed, which pointed out that the main difficulty in CO is how to construct the system-level constraints. The parameterized optimization model is introduced to analyze the existed optimal sensitivity algorithm. A new angle of CO study is proposed based on which two new algorithms are put forward.4. Much effort is made to study the Concurrent Subspace Optimization (CSSO)which is also a practical MDO algorithm. Based on the analysis of its mathematical property, the conclusion is made which figures out that the actual purpose of disciplinary level optimization is to provide a good experimental point instead of the optimization itself. From this point of view, an improved CSSO algorithm is proposed which adapts the Uniform Design method as a substitute for disciplinary optimization. Compared with original CSSO, the improved one is more effective while maintains the same precision.5. Two aircraft design problems are solved by the MDO algorithms proposed in this paper, one is aircraft conceptual design and the other is aircraft wing design. The highlights of this section is that the disciplinary analysis in wing design is not experiential but numerical.