Abstract
An integrated precipitation and strengthening model, incorporating the effect of precipitate morphology on precipitation kinetics and yield strength, is developed based on a modified Kampmann–Wagner numerical (KWN) framework with a precipitate shape factor. The optimized model was used to predict the yield strength of Al-Si-Mg-Mn casting alloys produced by vacuum high pressure die casting at various aged (T6) conditions. The solid solution strengthening contribution of Mn, which is a common alloying element to avoid die soldering, was included in the model to increase the prediction accuracy. The experimental results and simulations show good agreement and the model is capable of reliably predicting yield strength of aluminum die castings after T6 heat treatment, providing a useful tool to tailor heat treatment for a variety of applications.
Highlights
Al-Si-Mg-Mn alloys produced by a vacuum high pressure die casting process (HPDC) are commonly used for high integrity structural components in the automotive industry
The coupling of classical nucleation and growth theories (CNGTs) to the PanEngine provides information on phase equilibria and changes in the kinetic parameters with composition and temperature that are critical to the accuracy of the model
It is assumed that the maximum solubility of elements is achieved at the end of the solution heat treatment. α-Al15 (Fe,Mn)3 Si2 phase, which is a common phase constituent in Al-Si-Mg-Mn alloys, was included in phase equilibria calculation at solution heat treatment temperatures along with eutectic Si for accurate prediction of solute contents (Si, Mg, and Mn) that contribute in the aging process
Summary
Al-Si-Mg-Mn alloys produced by a vacuum high pressure die casting process (HPDC) are commonly used for high integrity structural components in the automotive industry. The Kampmann–Wagner numerical (KWN) model [2], based on classical nucleation and growth theories (CNGTs), is the most common analytic method used to simulate the precipitation kinetics, and it allows prediction of the properties of precipitates, such as volume fraction, number density, the evolution of particle size distribution (PSD), and mean precipitate radius (spherical precipitates). A CA-FEA (finite element analysis) model has been developed to predict as-cast yield strength of Al-Si-Mg alloys based on location-specific solidification microstructure including porosity [12]. The accurate consideration of phase equilibria (including all existing phases in the cast alloy microstructure) during solution and aging heat treatment processes using CALPHAD tools and incorporating shape factor in the modeling of precipitation and yield strength are critical.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
