| Project/Area Number |
11650939
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Aerospace engineering
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| Research Institution | TOHOKU UNIVERSITY |
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Principal Investigator |
OBAYASHI Shiogeru Tohoku Univ., Inst. of Fluid Science, Associate Prof., 流体科学研究所, 助教授 (80183028)
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| Project Period (FY) |
1999 – 2001
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| Project Status |
Completed (Fiscal Year 2001)
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| Budget Amount *help |
¥3,700,000 (Direct Cost: ¥3,700,000)
Fiscal Year 2001: ¥1,200,000 (Direct Cost: ¥1,200,000)
Fiscal Year 2000: ¥1,100,000 (Direct Cost: ¥1,100,000)
Fiscal Year 1999: ¥1,400,000 (Direct Cost: ¥1,400,000)
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| Keywords | Aircraft / Wing Design / Computational Fluid Dynamics / Design Optimization / Multiobjective Optimization / Evolutionary Computation / Self-Organizing Map / Datamining / 航空機設計 / 超音速機 / DOC / 機体サイジング / 翼平面形 / 空力設計 / 空力最適化 / 航空機概念設計 / 最適化 / 遺伝的アルゴリズム / 超音速 |
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| Research Abstract |
Toward aircraft built domestically or developed by Asian Airbus-like consortium, researches have bee conducted for market, Computational Fluid Dynamics (CFD), and design optimization. Market study focused on feasibility of supersonic regional transport, which connects Asian cities within one-day round trip. A conceptual design of supersonic regional jet has been presented. Sophisticated Evolutionary Multiobjective Optimization (EMO) has been developed and applied to supersonic wing design. This research is one of the most realistic EMO applications and has been recognized internationally.
EMO searches many compromised solutions (Pareto solutions) between multiple objective functions simultaneously. The resulting set of solutions reveals design tradeoffs between conflicting design objectives. This method has been applied to supersonic wing design with four design objective and various design tradeoffs have been examined. The tradeoff study is trivial between two objectives : however, it
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will become more difficult as the number of design objectives increases. Therefore, aiming for real-world applications of EMO, visualization of Pareto solutions are studied as post-processing together with the improvement and application of EMO itself. Self-Organizing Map (SOM) has been utilized as a visualization technique of high dimensional space. Datamining of design tradeoffs between multiple design objectives are performed by using SOM of Pareto solutions in the objective function space. SOM is also confirmed to be useful as the datamining tool by mapping the solutions in design variable space because the resulting SOM represents the aerodynamic knowledge in wing design througjh the clusters of design variables.
In addition to these works, researches have been performed for unstructured adjoint approach as an alternative optimization method and for extension of CFD code to fluid-structure interaction toward multidisciplinary design optimization. These activities have been reported at international conferences. Less
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