• Korean Architects
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• no.4 s.145
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• pp.43-53
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• 1981

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.596-601
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• 2007

A simplified finite element analysis method is proposed to calculate elasto-plastic responses of general hardening materials. The method provides an effective tool to calculate structural elasto-plastic responses. Numerical examples have demonstrated that its computational efficiency is very much higher than that of the incremental elasto-plastic finite element analysis, and computational results are accurate enough to meet the need of engineering practice. Compared with the general elasto-plastic incremental finite element analysis, the proposed method can avoid the incremental iteration of nodal displacements and the constitutive equation integration at each Gauss integral point, and computational results are accurate enough to meet the need of engineering practice.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.3080-3085
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• 2007

Shape optimization of the 3-dimensional WIG airfoil with 3.0-aspect ratio has been performed by using the multi-objective genetic algorithm. The WIG ship effectively floating above the surface by the ram effect and the virtual additional aspect ratio by a ground is one of next-generation and cost-effective transportations. Unlike the airplane flying out of the ground effect, a WIG ship has possibility to capsize because of unsatisfying the static stability. The WIG ship should satisfy aerodynamic properties as well as a static stability. They tend to strong contradict and it is difficult to satisfy aerodynamic properties and static stability simultaneously. It is inevitable that lift force has to scarify to obtain a static stability. Multi-objective optimization technique that the individual objectives are considered separately instead of weighting can overcome the conflict. Due to handling individual objectives, the optimum cannot be unique but a set of nondominated potential solutions: pareto optimum. There are three objectives; lift coefficient, lift-to-drag ratio and static stability. After a few evolutions, the non-dominated pareto individuals can be obtained. Pareto sets are all the set of possible and excellent solution across the design space. At any selections of the pareto set, these are no better solutions in all design space