Autonomous Optimization of a Solidification Pattern and Its Effect on Porosity and Segregation in Steel Castings

The present paper considers optimization of a solidification pattern of a gravity sand-cast steel part. That is, the choice of proper riser and chill designs has been investigated using genetic algorithms while simultaneously considering their impact on centerline porosity and macrosegregation distribution.

This was accomplished by coupling a casting simulation software package with an optimization module. The casting process of the original casting design was simulated using a transient 3D thermal model incorporated in a commercial simulation software package to determine potential flaws and inadequacies.

After this initial assessment, a new geometrical model was suggested with the redesigned gating system and rearranged chills to obtain better filling and solidification patterns. Based on the improved model, relevant optimization targets and constraints were defined. One multi-objective optimization case with two conflicting objectives was considered in which minimization of the riser volume together with minimization of centerline porosity and elimination of macrosegregation issues were performed.

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