In order to control the effective stress during the solidification process and avoid the occurrence of thermal cracking

the ProCAST software was used to simulate the temperature field and effective stress of the low pressure casting process of ZL205 Atraction component.Four factors

such as pouring temperature

mold preheat temperature

heat transfer coefficient and mold wall thickness were selected as design parameters.Combined with the results of effective stress prediction

a 4-7-1-1 artificial neural network and genetic algorithm were constructed to optimize the casting process.The results show that the average relative error of neural network prediction reaches 2.9%

presenting strong prediction accuracy.Through genetic optimization

the optimal process parameters are presented as follows:pouring temperature of 688℃

mold preheating temperature of 291℃

mold wall thickness of 150 mm

and the heat transfer coefficient of 1 284 W/（m

2

·K）.It provides reference and guidance for the low pressure casting process of traction structural parts.