All across America, trucks and tractor-trailers are transporting industrial explosives such as munitions, rocket motors, and dynamite on nearly every artery of the country’s interstate and highway system. America’s track record in transporting these materials is about as safe as they come, but accidents can happen. Thanks to the University of Tennessee’s (UT’s) Cray XT5 Kraken supercomputer and a research team from the University of Utah, accidents may soon become better understood, and hopefully, a near impossibility.
The team is using the processing power of Kraken to simulate burning and detonation processes in transportable explosives. Recent simulations have led the team to believe that the key to preventing these types of detonations is to pack the trucks transporting the explosives in such a way that temperatures and pressures are vented so as to avoid a chain-reaction explosion-to-detonation scenario.
The difference in burning — or deflagration — and detonation is a crucial one. In deflagration, the rate of burning is strictly limited by the transfer of heat to each individual device. Detonation, however, is a phenomenon that occurs as the result of a shock wave that moves 1 million times faster than deflagration and in the end is approximately 1 million times more devastating.
Team members are scaling up the models for explosions and detonations. That scaling up means simulating whole truckloads. For now, the team is simulating only a few explosives at a time, a daunting task even with Kraken’s 100,000-plus computing cores. This computing power especially comes in handy when dealing with detonations, in which the team believes that the phenomenon ultimately results from very fine-scale behaviors.
This modeling across scales is what the team refers to as “continuum-level science.” Because of the relationships between the different scales, this type of problem specifically requires a system such as Kraken, which has the necessary processing power for simulating explosions and detonations from their microscopic beginnings to their larger cataclysmic finales.
The team is using Uintah, a general-purpose scientific computing and engineering software, to model a full-truckload detonation. The software was developed with support from DOE, the DoD, and the National Institutes of Health. The simulations have given the group the computational knowledge to expand its algorithms to ensure that its codes continue to scale to tomorrow’s even larger computing architectures.