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IMPROVED MODEL FOR THREE DIMENSIONAL NONLINEAR WATER WAVE FORCE PREDICTION
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作者 Lu Yu-lin Liu Wen-yan Li Bao-yuan Dalian University of Technology,Dalian 116024,P.R.China 《Journal of Hydrodynamics》 SCIE EI CSCD 1990年第1期56-65,共10页
An improved model for numerically predicting nonlinear wave forces exerted on an offshore structure is pro- posed.In a previous work[9],the authors presented a model for the same purpose with an open boundary condi- t... An improved model for numerically predicting nonlinear wave forces exerted on an offshore structure is pro- posed.In a previous work[9],the authors presented a model for the same purpose with an open boundary condi- tion imposed,where the wave celerity has been defined constant.Generally,the value of wave celerity is time-de- pendent and varying with spatial location.With the present model the wave celerity is evaluated by an upwind dif- ference scheme,which enables the method to be extended to conditions of variable finite water depth,where the value of wave celerity varies with time as the wave approaches the offshore structure.The finite difference method incorporated with the time-stepping technique in time domain developed here makes the numerical evolution effec- tive and stable.Computational examples on interactions between a surface-piercing vertical cylinder and a solitary wave or a cnoidal wave train demonstrates the validity of this program. 展开更多
关键词 WAVE PRO IMPROVED MODEL FOR THREE dimensional NONLINEAR WATER WAVE FORCE PREDICTION
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Aerodynamic multi-objective integrated optimization based on principal component analysis 被引量:10
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作者 Jiangtao HUANG Zhu ZHOU +2 位作者 Zhenghong GAO Miao ZHANG Lei YU 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2017年第4期1336-1348,共13页
Based on improved multi-objective particle swarm optimization(MOPSO) algorithm with principal component analysis(PCA) methodology, an efficient high-dimension multiobjective optimization method is proposed, which,... Based on improved multi-objective particle swarm optimization(MOPSO) algorithm with principal component analysis(PCA) methodology, an efficient high-dimension multiobjective optimization method is proposed, which, as the purpose of this paper, aims to improve the convergence of Pareto front in multi-objective optimization design. The mathematical efficiency,the physical reasonableness and the reliability in dealing with redundant objectives of PCA are verified by typical DTLZ5 test function and multi-objective correlation analysis of supercritical airfoil,and the proposed method is integrated into aircraft multi-disciplinary design(AMDEsign) platform, which contains aerodynamics, stealth and structure weight analysis and optimization module.Then the proposed method is used for the multi-point integrated aerodynamic optimization of a wide-body passenger aircraft, in which the redundant objectives identified by PCA are transformed to optimization constraints, and several design methods are compared. The design results illustrate that the strategy used in this paper is sufficient and multi-point design requirements of the passenger aircraft are reached. The visualization level of non-dominant Pareto set is improved by effectively reducing the dimension without losing the primary feature of the problem. 展开更多
关键词 Aerodynamic optimization dimensional reduction Improved multi-objective particle swarm optimization(MOPSO) algorithm Multi-objective Principal component analysis
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