Abstract
This manuscript presents an advanced modeling methodology developed to accurately simulate the temperature field evolution in the die and wheel in an industrial low-pressure die casting (LPDC) machine employed in the production of A356 automotive wheels. The model was developed in the commercial casting simulation platform ProCAST for a production die operating under production conditions. Key elements in the development of the model included the definition of the resistance to heat transfer across the die/casting interfaces and die/water-cooling channel interfaces. To examine the robustness of the modeling methodology, the model was applied to simulate production and non-production process conditions for a die cooled by a combination of water and air-cooling (Die-A), and to a second die for a different wheel geometry (Die-B) utilizing only water cooling for production conditions. In each case, the model predictions with respect to in-die and in-wheel temperature evolution were compared to industrially derived thermocouple (TC) data, and were found to be in good agreement. Once tuned to the process conditions for Die-A operating under production conditions, no further tuning of the die/casting interface resistance was applied. Additionally, the model results, in terms of the prediction of pockets of solid encapsulated liquid, were used to compare to x-ray images of wheels. This comparison indicated that the model was able to predict clusters of porosity associated with encapsulated liquid with an equivalent radius of ~27 mm.
Highlights
Low-pressure die casting (LPDC) is the primary process adopted to manufacture load-bearing aluminum automotive parts thanks to its ability to produce parts with a good balance of cost-effectiveness and performance [1,2,3,4]
To standardize the model parameters, instead of changing Tenv, proportionally greater heat transfer coefficient (HTC) are used for the non-production process condition. ** Depending on the reference die components, different Tenv are applied at different locations of the surface based on measured data from the production process condition
The model validations for the two process conditions for Die-A are presented in Section 3.1, Section 3.2 and Section 3.3, followed by a comparison of the model predictions with a selection of data obtained from the production process for Die-B (Section 3.4)
Summary
Low-pressure die casting (LPDC) is the primary process adopted to manufacture load-bearing aluminum automotive parts thanks to its ability to produce parts with a good balance of cost-effectiveness and performance [1,2,3,4]. The sophistication of simulations has reached a level whereat the key phenomena, including heat, mass and momentum transport occurring within the LPDC process, can be described Despite this increased capability, few studies appear in the literature focused on commercial wheel production. Hetu et al developed a coupled fluid flow-heat transfer model that was used to simulate the LPDC process for an automotive housing and a wheel [6]. The trend in the casting industry of adopting a computational-based approach to mold design and process control requires highly accurate and robust models that can accurately explore design and process control options [16] This manuscript presents an advanced modeling methodology developed for the industrial LPDC of automotive wheels. The capabilities of the model for Die-A, operating under two different sets of process conditions (production and non-production), and for a second die with a different geometry (Die-B) operating under a third set of conditions (production), are presented in this manuscript by comparing the model results with the in-process derived data
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