| Project/Area Number |
10555339
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| Research Category |
Grant-in-Aid for Scientific Research (B).
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| Allocation Type | Single-year Grants |
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| Section | 展開研究 |
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| Research Field |
船舶工学
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| Research Institution | Yokohama National University |
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Principal Investigator |
SUZUKI Kazuo Yokohama National University, Faculty of Engineering, Professor, 工学部, 教授 (80111699)
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| Project Period (FY) |
1998 – 2000
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| Project Status |
Completed (Fiscal Year 2000)
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| Budget Amount *help |
¥11,700,000 (Direct Cost: ¥11,700,000)
Fiscal Year 2000: ¥4,100,000 (Direct Cost: ¥4,100,000)
Fiscal Year 1999: ¥3,200,000 (Direct Cost: ¥3,200,000)
Fiscal Year 1998: ¥4,400,000 (Direct Cost: ¥4,400,000)
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| Keywords | WIG / Panel Method / Nonlinear Programming / Wing Section / Shape Optimization / SQP / 最適翼型 |
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| Research Abstract |
A vehicle based on WIG (Wing In Ground effect) is expected as one of the candidates of future high speed vessels on seaway. As the first study, the shape optimization problem of 2D (2 dimensional) WIG is discussed as a fundamental study with respect to WIG.For this purpose, the panel method is used for the fluid flow analysis around WIG and the nonlinear programming is used as the optimization method. Numerical examples are shown for several optimization problems. An optimized wing section of WIG is tested to verify its aerodynamic characteristics by using an experimental method of WIG devised for a small wind tunnel. As the second problem, Morino's panel method is applied to aerodynamic analyses around a Ram-wing type 3D WIG with special reference to aerodynamic characteristics of its side end plates. Under the consideration of these analyses, aerodynamic shape optimization problems of Ram-wing type WIG are discussed. Numerical examples of optimized wing section are shown, in which the optimizations are carried out by means of the aerodynamic analysis based on the panel method and the nonlinear programming. In both problems, SQP (Sequential Quadratic Programming) technique is used as the optimization method, which is very useful to get the optimum solution under several complex design constraints.
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