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并行工程技术及优化工序法在模具生产中的应用
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作者 孙先伟 童隽 +1 位作者 陈瑞秋 周传宏 《电加工与模具》 2002年第5期41-44,共4页
介绍了并行工程 (CE)的思想 ,并通过基于DFX的并行工程技术、基于CAD/CAE集成的并行工程方法和优化工序法在实际模具生产中的应用 ,提出了适合于注塑模具并行工程开发的模式来缩短模具生产周期、降低成本、提高效益 。
关键词 并行工程 DFX CAD CAE 优化工序法 模具
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Solving chemical dynamic optimization problems with ranking-based differential evolution algorithms 被引量:3
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作者 Xu Chen Wenli Du Feng Qian 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2016年第11期1600-1608,共9页
Dynamic optimization problems(DOPs) described by differential equations are often encountered in chemical engineering. Deterministic techniques based on mathematic programming become invalid when the models are non-di... Dynamic optimization problems(DOPs) described by differential equations are often encountered in chemical engineering. Deterministic techniques based on mathematic programming become invalid when the models are non-differentiable or explicit mathematical descriptions do not exist. Recently, evolutionary algorithms are gaining popularity for DOPs as they can be used as robust alternatives when the deterministic techniques are invalid. In this article, a technology named ranking-based mutation operator(RMO) is presented to enhance the previous differential evolution(DE) algorithms to solve DOPs using control vector parameterization. In the RMO, better individuals have higher probabilities to produce offspring, which is helpful for the performance enhancement of DE algorithms. Three DE-RMO algorithms are designed by incorporating the RMO. The three DE-RMO algorithms and their three original DE algorithms are applied to solve four constrained DOPs from the literature. Our simulation results indicate that DE-RMO algorithms exhibit better performance than previous non-ranking DE algorithms and other four evolutionary algorithms. 展开更多
关键词 Dynamic optimization Differential evolution Ranking-based mutation operator Control vector parameterization
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Multi-objective optimization of the streamlined head of high-speed trains based on the Kriging model 被引量:17
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作者 YAO ShuanBao GUO DiLong +2 位作者 SUN ZhenXu YANG GuoWei CHEN DaWei 《Science China(Technological Sciences)》 SCIE EI CAS 2012年第12期3495-3509,共15页
As the running speed of high-speed trains increases, aerodynamic drag becomes the key factor which limits the further increase of the running speed and energy consumption. Aerodynamic lift of the trailing car also bec... As the running speed of high-speed trains increases, aerodynamic drag becomes the key factor which limits the further increase of the running speed and energy consumption. Aerodynamic lift of the trailing car also becomes the key force which affects the amenity and safety of the train. In the present paper, a simplified CRH380A high-speed train with three carriages is chosen as the model in order to optimize aerodynamic drag of the total train and aerodynamic lift of the trailing car. A constrained mul- ti-objective optimization design of the aerodynamic head shape of high-speed trains based on adaptive non-dominated sorting genetic algorithm is also developed combining local function three-dimensional parametric approach and central Latin hypercube sampling method with maximin criteria based on the iterative local search algorithm. The results show that local function parametric approach can be well applied to optimal design of complex three-dimensional aerodynamic shape, and the adaptive non-dominated sorting genetic algorithm can be more accurate and efficient to find the Pareto front. After optimization the aerodynamic drag of the simplified train with three carriages is reduced by 3.2%, and the lift coefficient of the trailing car by 8.24%, the volume of the streamlined head by 2.16%; the aerodynamic drag of the real prototype CRH380A is reduced by 2.26%, lift coefficient of the trailing car by 19.67%. The variation of aerodynamic performance between the simplified train and the true train is mainly concentrated in the deformation region of the nose cone and tail cone. The optimization approach proposed in the present paper is simple yet efficient, and sheds lights on the constrained multi-objective engineering optimization design of aerodynamic shape of high-speed trains. 展开更多
关键词 multi-objective optimization KRIGING genetic algorithms aerodynamic shape high-speed trains
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