The gravity die casting process for aluminium engine heads is one of the most complex of the casting industry, with high geometrical complexity, highest mechanical properties, lowest porosity levels. In the design of such a process by means of numerical methods, two kinds of problems arise: the first is the correctness of the boundary conditions of the thermal problem, the second is the availability of algorithms for predicting microstructural features, by which the final mechanical properties can be assessed. To assess this problems, a full numerical analysis has been carried out on an 8 cylinders A356 engine head which is in current production, by carefully replicating all the available process monitoring data: die temperatures and gradients, alloy composition and gas content, casting temperature, filling strategy and cooling times. An advanced microstructure module was then run to evaluate the porosity distribution throughout the casting; predicted and experimental values were finally compared.
R. Squatrito, I. Todaro, L. Tomesani (2009). Process modeling and microstructure prediction in gravity die aluminum castings with sand cores. SAN FRANCISCO : TMS.
Process modeling and microstructure prediction in gravity die aluminum castings with sand cores
SQUATRITO, ROSARIO;TODARO, IVAN;TOMESANI, LUCA
2009
Abstract
The gravity die casting process for aluminium engine heads is one of the most complex of the casting industry, with high geometrical complexity, highest mechanical properties, lowest porosity levels. In the design of such a process by means of numerical methods, two kinds of problems arise: the first is the correctness of the boundary conditions of the thermal problem, the second is the availability of algorithms for predicting microstructural features, by which the final mechanical properties can be assessed. To assess this problems, a full numerical analysis has been carried out on an 8 cylinders A356 engine head which is in current production, by carefully replicating all the available process monitoring data: die temperatures and gradients, alloy composition and gas content, casting temperature, filling strategy and cooling times. An advanced microstructure module was then run to evaluate the porosity distribution throughout the casting; predicted and experimental values were finally compared.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.