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Multi-objective optimization of process parameters during low-pressure die casting of AZ91D magnesium alloy wheel castings

机译:AZ91D镁合金轮铸件低压压铸过程中工艺参数的多目标优化

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Multi-objective optimization has been increasingly applied in engineering where optimal decisions need to be made in the presence of trade-offs between two or more objectives. Minimizing the volume of shrinkage porosity, while reducing the secondary dendritic arm spacing of a wheel casting during low-pressure die casting (LPDC) process, was taken as an example of such problem. A commercial simulation software ProCASTTM was applied to simulate the fi lling and solidifi cation processes. Additionally, a program for integrating the optimization algorithm with numerical simulation was developed based on SiPESC. By setting pouring temperature and fi lling pressure as design variables, shrinkage porosity and secondary dendritic arm spacing as objective variables, the multi-objective optimization of minimum volume of shrinkage porosity and secondary dendritic arm spacing was achieved. The optimal combination of AZ91D wheel casting was: pouring temperature 689 °C and fi lling pressure 6.5 kPa. The predicted values decreased from 4.1% to 2.1% for shrinkage porosity, and 88.5 μm to 81.2 μm for the secondary dendritic arm spacing. The optimal results proved the feasibility of the developed program in multi-objective optimization.
机译:多目标优化已越来越多地应用于工程设计中,需要在两个或多个目标之间进行权衡的情况下做出最佳决策。这样的问题的一个例子是,使收缩孔隙率最小化,同时减小了低压压铸(LPDC)过程中车轮铸件的二次枝状臂间距。商业仿真软件ProCASTTM用于模拟填充和固化过程。此外,基于SiPESC开发了将优化算法与数值模拟集成的程序。通过将浇注温度和填充压力作为设计变量,将收缩孔隙率和次生树枝状臂间距作为目标变量,实现了收缩孔隙率和次生树枝状臂间距最小体积的多目标优化。 AZ91D车轮铸件的最佳组合是:浇注温度689°C,填充压力6.5 kPa。收缩孔隙率的预测值从4.1%降低至2.1%,次级树突臂间距的预测值从88.5μm降低至81.2μm。最优结果证明了所开发程序在多目标优化中的可行性。

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