Abstract
A flow stress model which considers the processing conditions for a given alloy composition as well as the microchemistry of the alloy allows for integrated optimization of alloy composition, thermal treatments and forming operations to achieve the desired properties in the most efficient processing route. In the past, a statistical flow stress model for cell forming metals, 3IVM+ (3 Internal Variable Model), has been used for through process modeling of sheet production. However, this model was restricted to a given alloy in the state in which it was calibrated. In this work, the existing 3IVM+ model is augmented with an analytical solute strengthening model which uses input from ab initio simulations. Furthermore, a new particle strengthening model for non-shearable precipitates has been introduced which takes Orowan looping at low temperatures and dislocation climb at high temperatures into account. Hence, the present modeling approach considers the strengthening contributions from solutes, precipitates and forest dislocations. Three case studies on the alloys AA 1110, AA 3003 and AA 8014 are presented to assess the performance of the model in simulating the yield stress and flow stress of Al alloys over a wide range of temperatures and strain rates.
Highlights
Aluminum with its various alloy variations is a first-choice material for a number of lightweight engineering applications
The model presented in this work builds upon the 3IVM+ model, incorporates a solute strengthening model developed by Leyson et al [9,10,11,12] and introduces a new particle strengthening model which captures Orowan looping at low temperatures and dislocation climb at high temperatures
Most commercial aluminum alloys contain particles, such as constituent phases formed during solidification, dispersoids formed during homogenization and fine precipitates formed during age hardening at low temperatures
Summary
Aluminum with its various alloy variations is a first-choice material for a number of lightweight engineering applications. Reliable and efficient manufacturing processes are the main prerequisites to fulfill growing expectations on semi-finished products in a strong field of worldwide competition. From this standpoint, the employment of computer-aided decision-making systems in the process routing or even at a shop floor level are desired. The material properties of aluminum semi-finished products cannot be measured during the production process. To close this data gap, fast statistical material models can be used to compute material properties such as the microstructure and flow stress. Three case studies are presented on industrial aluminum alloys, i.e. AA 1110, AA 3103 and AA 8014, to assess the quality of the simulations of the yield stress and flow stress at different temperatures ranging from 20 °C to 550 °C and for three different strain rates ranging from 0.1 to 10 s−1
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