Technical capabilities of the Center include advanced computing resources ranging from high-end work stations to emerging massively parallel computers, a wide range of commercial and in-house simulation software, and state-of-the-art preprocessing and postprocessing tools. Center staff have broad expertise in modeling heat and fluid flow, solidification processes, deformation processes, heat treatment and distortion, residual stresses, and macro-micro structural modeling.
User centers also provide experimental capabilities to facilitate understanding of the behavior of processes. Testing and benchmarking of a model can be pursued simultaneously. The expertise and diversity of experience available in the Oak Ridge Complex have made complex, multidisciplinary projects successful. For example, Oak Ridge researchers developed an information and advisory system that materials scientists, mathematicians, process control engineers, and the end user can use for flawless design, analysis, and production. This process integrates modeling, simulation, process characterization, and process control.
MAJOR THRUSTS
REPRESENTATIVE PROJECTS
Department of Transportation Car Crash Simulation. Oak Ridge researchers developed an algorithm for increased accuracy that incorporated large-deformation, nonlinear, and temperature-dependent material processes. A parallel version of an important design code was also developed.
Recrystallization Modeling. Oak Ridge researchers improved the process for a multistory furnace strip mill and evaluated and optimized alloy additions for an energy-efficient process with uniform product and performance.
Details. Steel is composed of individual microcrystals, or grains. Material properties of steel are highly dependent on grain size and structure. When steel is cold rolled, the existing grains become highly deformed and contain large amounts of strain energy. If the steel is heated to a sufficiently high temperature, new grains will grow that have no strain energy. This process is called recrystallization. The numerical method uses the Monte Carlo technique to model the coalescence of steel microcrystals. The Monte Carlo calculation can determine the growth of both grains and recrystallized grains simultaneously. Results were obtained for four stages in recrystallization: cold-rolled grains with considerable strain energy, approximately 50% recrystallization, approximately 80% recrystallization, and 100% recrystallization.
Neural Networks. Oak Ridge researchers reduced the number of design iterations for reach near-net shape for complex parts, optimized the forming process, adapted the developed method for a wide variety of materials (for both government and industry) and improved the environmental friendliness of the forming processes.
Porosity and Microstructure Prediction in Shaped Casting.
Oak Ridge researchers calculated thermal gradients, solidification rates, and
fraction solid distribution. The modeling process yields microstructure
evolution, porosity distribution, hot tearing susceptibility, and
castability maps.