INSIGHTS: Multiscale modeling and simulation

By Hanchen Huang Department of Mechanical, Aerospace, and Nuclear Engineering, Rensselaer Polytechnic Institute

Hanchen Huang is professor of mechanical and nuclear engineering at the Rensselaer Polytechnic Institute. His research group studies the evolution of nanostructures during fabrication, mechanical deformation, radiation exposure, and aging.
* Huang's biography

Large machines, such as airplanes and nuclear reactors, are many meters in size and operate for many years, yet their performances depend on the fundamental mechanics of atoms and electrons. This dependence is even more pronounced for machines made of nanostructured materials. Therefore, modeling and simulation of engineering problems must address multiple scales in both size and time.

To fully realize the greatest potential of multiscale modeling and simulation in science and technology requires synergies in three aspects.

The first synergy is among researchers of mathematical and physical (or biological) sciences. The advancement of modeling and simulation methods relies on smart mathematics for realization in computers, and on physics for meaningful representations of reality. Professional societies such as the U.S. Association of Computational Mechanics and federal agencies such as the National Science Foundation (NSF) have actively promoted crossfertilization between computational mathematicians and physical scientists. Continuing and strengthening such cross-fertilization will be very beneficial.

The second synergy is between scientists and engineers, and it has been in practice among the modeling and simulation teams at the U.S. Department of Energy national laboratories. The integration of mission-oriented engineering research and discoveryoriented scientific exploration maximizes the potential impacts of multiscale modeling and simulation.

The third synergy is between modelers and experimentalists. The term “computer experiments” may have been coined with good intentions. However, modeling and computer simulations offer their greatest

potential when accompanied by experimental validation or when motivated by experimental observation. The engagement of experimentalists in multiscale modeling and simulations deserves particular attention and cannot be overemphasized.

These RPI images, showing self-organized branching that occurs during materials synthesis, illustrate science-based conceptualization (left), a rendering based on predictive simulation (center), and experimental validation (microscopy image, right).
(Reference: Wang, Huang, Kesapragada, and Gall, Nano Letters 2005)

Augmenting these synergies is computational capacity. Having the world’s eight most powerful computers, the U.S. should undoubtedly be in the leading position. Indeed, supercomputers such as Red Storm at Sandia and the IBM Blue Gene at Rensselaer Polytechnic Institute have proven to be enabling tools for multiscale modeling and simulation.

Equipped with the three synergies and the necessary computational capacity, the modeling and simulation community will be in a good position to address the challenging issues of both time and size scales. The issue of multiple time scales is probably the most challenging and can also be the most rewarding. The issue of multiple size scales has been the focus of intensive efforts, and the moment is ripe for the transition from demonstration of methods to their application in realistic engineering environments.

Although its full potential has yet to be realized, modeling and simulation has an important future role in the advancement of science and technology. Its impacts should be at three levels. At the first level, it provides interpretation to experimental tests and observations. At a higher level, it offers insights to scientific and engineering exploration. At the highest level, multiscale modeling and simulation is predictive and leads to scientific discovery and science-based engineering and design.