Error estimation improves multiscale models
Posted April 16, 2007
J. Tinsley Oden has a favorite quote from German science philosopher Hans Reichenbach: “If error is corrected whenever it is recognized as such, the path of error is the path of truth.”
“That’s sort of our mantra,” says Oden, director of the Institute for Computational Engineering and Sciences at the University of Texas. He and his research group are refining methods that estimate the error of mathematical models underlying computers simulations of physical systems, such as the molecular structure of materials. Knowing the error allows researchers to adapt the model to control error or change the model’s scales of time and space for more precision.
The ability to compute multiple scales is becoming more important as scientists investigate how the behavior of atoms and molecules affects the materials and processes they make up. Such understanding is vital to creating smaller, faster electronics, curing disease and addressing other problems.
However, “The development of models that function over many temporal and spatial scales is one of the most challenging aspects facing modern computation,” says Oden, who is an associate vice president for research and holds multiple appointments at Texas. “Virtually all the methods that have been proposed to transcend scale argue that the analyst has some insight and knows when a result is valid at one scale or needs information at another, ” Oden adds. “This very often is not the case.”
“Our hope is to bring some rigor to this process and let the analyst get an estimate of the error at each scale,” Oden says.
