Luc Neumann

Through-process texture modelling of aluminium alloys

The complete through-process modelling of crystallographic texture evolution during aluminium sheet production is addressed. The texture determining processes deformation and recrystallization are analysed with respect to the underlying mechanisms. The advanced deformation texture model grain interaction (GIA) is coupled to a statistical analytical recrystallization texture model (StaRT). New concepts are described to model nucleation spectra for recrystallization with the GIA model and with a new model for the prediction of in grain orientation gradients. Orientation dependent recovery of the deformed structure is reflected based on substructure information extracted from the GIA model. A finite element (FE) model incorporating dislocation density based work hardening as well as texture serves as a process model to describe the macroscopic production parameters based on microstructural information. More detailed information on this integrative FE model can be found in a second paper presented at this symposium by Neumann et al. The excellent performance of the outlined through-process texture modelling concept is demonstrated in applications for two different aluminium sheet production lines?one laboratory and one industrial process?and displays for the first time the possibility of modelling texture evolution throughout various consecutive processing steps.

Through-process modelling of texture and anisotropy in AA5182

A through-process texture and anisotropy prediction for AA5182 sheet production from hot rolling through cold rolling and annealing is reported. Thermo-mechanical process data predicted by the finite element method (FEM) package T-Pack based on the software LARSTRAN were fed into a combination of physics based microstructure models for deformation texture (GIA), work hardening (3IVM), nucleation texture (ReNuc), and recrystallization texture (StaRT). The final simulated sheet texture was fed into a FEM simulation of cup drawing employing a new concept of interactively updated texture based yield locus predictions. The modelling results of texture development and anisotropy were compared to experimental data. The applicability to other alloys and processes is discussed.

Simulation of casting, homogenization, and hot rolling: consecutive process and microstructure modelling for aluminium sheet production

An overview of simulation of casting, homogenization, and hot rolling of an aluminium alloy is addressed in this paper. The microstructure models used to describe casting, solidification, precipitation (growth and coarsening) during homogenization, deformation texture evolution, and the work hardening behaviour are presented as well as their respective theoretical backgrounds. Emphasis is placed on interfacing the microstructure models with each other between the processing steps. This makes it possible to take into account microstructural changes that occur early during processing during later production steps. Along with this overview, reference will be made to previously presented simulation and experimental results—for validation—where appropriate.

Through-process texture simulation for aluminum sheet fabrication

We introduce a simulation procedure for through-process texture and anisotropy prediction, in particular for AA5182 sheet production from hot rolling through cold rolling and annealing. The FEM package ‘T-Pack’ based on the software LARSTRAN served as a process model. It was combined with physics based microstructure models for deformation texture (GIA), work hardening (3IVM), nucleation texture (ReNuc), and recrystallization texture (StaRT). The terminal sheet texture was used for a FEM simulation of cup drawing. A new concept of interactively updated texture based yield locus predictions was employed. The simulation predictions were compared to experimental data. The procedure can be applied to a wide variety of Aluminum alloys.

Modelling Set Up for Through‐Process Simulation of Aluminium Cup Production

In order to enable metal forming process optimisation through numerical simulation rather than trial and error, it is necessary to develop plasticity models of predictive character. The major disadvantage of frequently used phenomenological plasticity models lies in their limited validity which is defined by the experimental data ranges to which these models are fitted. The concept of phenomenological models may, however, be very successful if the plastic strains are small and if the strain path is not complex. This is often the case in sheet metal forming. Physical plasticity models, on the other hand, capture not only the true physical phenomena occuring during plastic deformation but also have the benefit of a ‘self evolutionary character’ which means that they are able to describe a considered phenomenon even outside of the experimental data range to which they have been adjusted. However, setting up physical models requires a significant amount of research and their adaptation to a specific alloy mak...

Integral Modelling of Texture Evolution in Multiple Pass Hot Rolling of Aluminium Alloys

The interaction of several physically based models for the development of crystallographic texture and microstructure during deformation and recrystallisation is exemplified in two cases of multiple pass hot rolling of commercial aluminium alloys. In this study streamlines output by the FE-code LARSTRAN/SHAPE and a model based on elementary rolling theory have been used respectively to calculate the evolution of material properties during deformation with a dislocation density based flow stress model and a Taylor type deformation texture model which considers grain interaction. To model the texture development during the interpass times between the rolling passes, an analytical recrystallisation model has been applied .

Simulation Of Coupled Processes And Product Properties

The properties of a product result at the end of the production chain. To predict these properties as accurate as feasible every process step has to be described in the exactest way possible. The big challenge for the simulation technique is to realistically depict the actual circumstances in the process chain as well as in the process depth.Usually, simulations are calculated for single process steps of an entire process chain. The aim of recent research is to combine these steps to a complete simulation of a plant even using the calculated results of the previous step as input data for the next one. An useful method to combine simulations and to present the results is the Virtual Reality tool. It offers the possibility to show a three dimensional model of the whole complex plant. Combined with results of logistic simulations the VR‐model can visualize the whole production process. For the combination of calculations at several accuracy levels a hierarchical structure was developed. At selectable parts i...