Joseph M. Fridy

Modeling texture evolution during recrystallization in aluminum

The main aim of this work was to develop a model with predictive capability for microstructural evolution during recrystallization and to identify factors that exert the greatest effect on the development of texture. To achieve this aim, geometric and crystallographic observations from two orthogonal sections through a polycrystal were used as input to the computer simulations, to create a statistically representative three-dimensional model. Assignment of orientations to the grains was performed so as to optimize agreement between the orientation and misorientation distributions of assigned and observed orientations. The microstructures thus created were allowed to evolve using a Monte Carlo simulation. As a demonstration of the model the effects of anisotropy, both in energy and in mobility, stored energy and oriented nucleation (ON) on overall texture development were studied. The results were analyzed with reference to the various established competing theories of ON and oriented growth. The results suggested that all of ON, mobility anisotropy, stored energy and energy anisotropy (listed in order of their relative importance) influence texture development. It was also determined that comparison of simulated and measured textures throughout the recrystallization process is a more severe test of a model than the typical comparison of textures only at the end of the process.

A Microstructure Based Multi‐Site Crack Growth Model

A simple computational method to simulate component failures in engineered structures based on microstructure characteristics has been developed. The computational model deals directly with a large set of cracks in a defined geometrical region, and is capable of tracking the simultaneous growth and interaction of those cracks, including crack-tip shielding and link-up, until final failure. The Multi-Site Crack Growth (MSCG) tool is designed to start from either an initial uncracked state where cracks may nucleate from cracked particles or other microstructural features, or from an initial cracked state such as might be expected at a percentage of fatigue life expended. Alternatively, the input can be expected crack nucleation sites from microstructure simulations. The MSCG tool is designed based on microstructural origins of fatigue cracks, and the statistical distributions of microstructural parameters. Thus it is possible to extend this framework to corrosion-fatigue. The computational algorithms used enable rapid calculation of the complete crack growth geometry for the current loading cycle, including the current number of cracks, the maximum crack length, the average crack length, and the total cracked area. This makes application to life predictions possible as crack length, area, and number distribution are predicted for given number of load cycles. Example simulations of crack nucleation from large second phase particles will be given.

Modeling Recrystallization in Aluminum Using Input from Experimental Observations

A model has been constructed for the microstructural evolution that occurs during the annealing of aluminum alloys. Geometric and crystallographic observations from two orthogonal sections through a polycrystal using automated Electron Back-Scatter Diffraction (EBSD) were used as an input to the computer simulations to create a statistically representative threedimensional model. The microstructure is generated using a voxel-based tessellation technique. Assignment of orientations to the grains is controlled to ensure that both texture and nearest neighbor relationships match the observed distributions. The microstructures thus obtained are allowed to evolve using a Monte-Carlo simulation. Anisotropic grain boundary properties are used in the simulations. Nucleation is done in accordance with experimental observations on the likelihood of occurrences in particular neighborhoods. We will present the effect of temperature on the model predictions.

Image Processing to Automate Mesh Generation

Abstract. Finite element modeling is now a standard approach used in the industry to minimize costly trials and help reduce the overall lead time in product and process design. However, building surface/solid models defining the product shape and generating finite element meshes for analyses still require a significant amount of the engineers’ time. In this paper, we present a new method for automatically generating a finite element mesh directly from bitmap images obtained from an artist’s concept of a label for an embossed aluminum beverage can, and demonstrate its application towards the building of tooling mesh models used in the modeling of the embossing process. This approach completely eliminates the need for creating a surface/solid model, thus resulting in a dramatic reduction in the time required for process design.