8th. World Congress on Computational Mechanics (WCCM8) 5th. European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2008) June 30 – July 5, 2008 Venice, Italy Multi-Objective Design Exploration (MODE) - Visualization of Design Space and Knowledge Mining *Shigeru Obayashi¹, Shinkyu Jeong ² and Takayasu Kumano³ Institute of Fluid Science, Tohoku University Katahira 2-1-1, Aoba-ku, Sendai, Japan 980-8577 ¹obayashi@ifs.tohoku.ac.jp, ² jeong@edge.ifs.tohoku.ac.jp, ³kumano@edge.ifs.tohoku.ac.jp http://www.ifs.tohoku.ac.jp/edge/indexe.html Key Words: Multi-objective Optimization, Multidisciplinary Design Optimization, Evolutionary Computation, Self-Organizing Map, Visualization, Data Mining. ABSTRACT Multi-Objective Design Exploration (MODE) is presented to address Multidisciplinary Design Optimization problems. MODE reveals the structure of the design space from the trade-off information and visualizes it as a panorama for Decision Maker. The present form of MODE consists of Kriging Model, Adaptive Range Multi Objective Genetic Algorithms, Analysis of Variance and Self-Organizing Map. The main emphasis of this approach is data mining. The example illustrates the importance of the present approach because brief exploration of the design space could lead to finding design knowledge. In Japan, a 5-year R&D project has been in progress toward the development of environmentally friendly high performance regional jet aircraft under auspices from New Energy Development Organization of Japan (NEDO) since 2003 [1]. In the project, several research programs have been investigated by industry-government-university cooperation [2]. The conceptual image of a regional jet aircraft is shown in Fig. 1. For the success of the project, a practical MDO system for regional jet wing design is required. An MDO system was developed for a clean wing under the project [3]. The MDO system is based on the integration of Computational Fluid Dynamics (CFD) codes and the NASTRAN-based aeroelastic-structural interface code. Moreover, the Kriging model is employed to reduce computational expenses for function evaluations in MOGA. The resulting MDO tool has also been extended to an engine-airframe integration problem [4], which is one of the most important issues in the aircraft design. Shock wave generated at inboard of pylon may lead to flow separation and buffeting (Fig. 2). In order to prevent these phenomena, the lower wing surface near the pylon has been optimized. Based on the results of the above multi-disciplinary optimization, knowledge mining has been attempted by using visualization of the design space. Figure 3 shows the