 | 2007 |
Abstract:
The early stages of the development process are critical for the final performance and cost of a structure. Multidisciplinary Optimization provides a formal methodology to identify a good (optimal) initial design. Some disciplines, such as structural and fluid mechanics may be described via numerical models. Influences from disciplines, which are part of the development process itself, often cannot be described in the same detail (e.g. new manufacturing techniques). To integrate such aspects – at least in a roughly estimated way – Hajela [1] suggest the use of fuzzy models to utilize expert knowledge. So called Fuzzy Rule Based Systems (FRBS) provide a powerful tool to model qualitative human knowledge. Natural language is utilized for parameterization of FRBS and ‘if…then’ rules link the input and output parameters which generates models capable of handling also nonlinear behavior. Based on this idea, a method for building qualitative, knowledge based models has been developed at the institute [2] and enhanced. As an example, structural components constructed from fiber reinforced metal matrix materials have been optimized. Such problems typically are characterized by a combination of continuous design parameters and discrete ones. For this purpose the evolutionary algorithm GAME is utilized [3], which uses Pareto-Ranking [4] for multiple objectives. The according manufacturing constraints are based on expert judgment and the optimized results provide the engineer with more information for choosing the appropriate design.