Advanced Computational Research in Materials Processing for Design and Manufacturing
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Begun in 1973, the Review of Progress in Quantitative Nondestructive Evaluation (QNDE) is the premier international NDE meeting designed to provide an interface between research and early engineering through the presentation of current ideas and results focused on facilitating a rapid transfer to engineering development.
This site provides free, public access to papers presented at the annual QNDE conference between 1983 and 1999, and abstracts for papers presented at the conference since 2001.
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Abstract
Advanced mathematical techniques and computer simulation play a major role in providing enhanced understanding of conventional and advanced materials processing operations. Development and application of mathematical models and computer simulation techniques can provide a quantitative understanding of materials processes and will minimize the need for expensive and time consuming trial- and error-based product development. As computer simulations and materials databases grow in complexity, high performance computing and simulation are expected to play a key role in supporting the improvements required in advanced material syntheses and processing by lessening the dependence on expensive prototyping and re-tooling. Many of these numerical models are highly compute-intensive. It is not unusual for an analysis to require several hours of computational time on current supercomputers despite the simplicity of the models being studied. For example, to accurately simulate the heat transfer in a 1-m3 block using a simple computational method requires 1012 arithmetic operations per second of simulated time. For a computer to do the simulation in real time would require a sustained computation rate 1000 times faster than that achievable by current supercomputers. Massively parallel computer systems, which combine several thousand processors able to operate concurrently on a problem, are expected to provide orders of magnitude increase in performance. This paper briefly describes advanced computational research in materials processing at ORNL. Continued development of computational techniques and algorithms utilizing the massively parallel computers will allow the simulation of conventional and advanced materials processes in sufficient generality.