| China is rich in magnesium resources,and its primary magnesium production accounts for more than 80%of the world.Magnesium alloys are praised as one of the"21st Century Green Environmental Protection Projects"due to their low density(The density of pure magnesium is 1.74g/cm~3,which is approximately 2/3 of aluminum alloy and 1/4 of steel.),high specific strength and specific stiffness.Magnesium alloys are the lightest metal engineering structural materials in practical applications.At present,magnesium alloy research usually adopts traditional"trial and error method"to optimize the composition and process,resulting in a long research and development cycle and high production costs,which is not an effective way to the rapid development and application of high-performance magnesium alloy.Therefore,the adoption of a new and efficient method is in an urgent need to promote the upgrading of China's magnesium industry.In this paper,the defect/microstructure simulation and mechanical property prediction of AZ91D magnesium alloy casting process are studied.The finite element software ProCAST is used to analyze the casting defects,microstructure and properties.The T-stub casting is simulated by using the cellular automata model of ProCAST software.MATLAB artificial neural network model is used for predicting the relationship of microstructure and properties.Data transfer through different CAE modules,and an automatic optimization of the casting process are developed based on the SiPESC platform.Firstly,combining ProCAST with SiPESC.OPT,it can realize the process-defect/microstructure optimization simulation prediction.Next,by integrating MATLAB with SiPESC.OPT;defect/microstructure-property module prediction is realized based on the artificial neural network model.And then on the basis of data transfer between the two different modules,input the CAD model to the automatic optimization of process-defect/microstructure-property simulation platform.The program achieved rapid optimization of process-defect/microstructure-property.Finally,the calculation results of the platform were compared and verified based on the existing calculation results.The purpose of this study is to establish an integrated computational platform for magnesium alloy process-defect/microstructure-property,which can cut down the trial cycle,reduce the development cost and improve the quality of castings.And it also can provide preference for the selection of process parameter in high-performance magnesium alloy castings.To facilitate data exchange between different modules and the user's operation in later stage,this paper developed a CAE analysis and integration platform based on the open source software SiPESC.A module for casting process-defect/microstructure-property is especially constructed in this study,and the corresponding user interface design is completed.In addition,the thesis took multi-objective optimization of low-pressure die casting of the magnesium alloy hub is achieved,by setting the pouring temperature(680?~720?)and filling pressure(4.3KPa~8.0KPa)as design variables,and the volume of shrinkage porosity and the secondary dendritic arm spacing are the objectives.It had been found that under the condition of pouring temperature 689?and filling pressure 6.5KPa,the optimization result was evident.The volume of shrinkage porosity and secondary dendritic arm spacing decreased from 4.1%,88.5?m to 2.1%and 81.2?m,respectively.Through the platform,it realized the multi-objective automatic optimization in low-pressure die casting process of AZ91D magnesium alloy wheel. |
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