Supercomputing Targets Cleaner Combustion
Leadership-class supercomputers, like the Department of Energy systems, are instrumental in meeting the challenges of the 21st century. A team of scientists and mathematicians at the DOE’s Lawrence Berkeley National Laboratory are using these powerful number crunchers together with sophisticated algorithms to create cleaner combustion technologies.
The United States relies on the combustion of fossil fuels for more than 80 percent of its energy needs. The national economic engine as well as the standard of living are tied to this combustion process to drive all manner of transportation and provide home energy needs. But the burning of fossil fuels is also the number one source of anthropogenic climate change, so advances in cleaner combustion are critical to our future.
Despite the prevalence of combustion, the chemical process is not very well understood, but that’s changing thanks in part to the work of researchers at Berkeley and other DOE labs. Applied mathematicians and combustion scientists at Berkeley are using supercomputers to model this complex process with the intent of developing cleaner-burning, more efficient devices.
A recent article at Berkeley Lab by Jon Bashor discusses one such technology, called the low-swirl burner, which was developed by Robert Cheng in Berkeley Lab’s Environmental Energy Technologies Division. The device imparts a gentle spin to the fuel and air mixture, which causes it to spread out and burn at a lower temperature than in conventional burners. Lower flame temperatures are associated with increased efficiency and reduced levels of nitrogen oxides (NOx) and greenhouse gases. Reducing NOx compounds is a worthy goal since they have been implicated in emphysema, bronchitis, asthma and heart disease.
The article explains the difficulty with simulating practical-scale combustion devices like the low-swirl burner. “The fuel is often turbulent, the combustion process may involve hundreds of species and thousands of chemical reactions, and the processes involved can span milliseconds to minutes and microns to meters,” Bashor writes.
Just several years ago, the tools that were available for this purpose failed to support the necessary complexity. So scientists and mathematicians at CCSE developed new software tools and algorithms that cut computational costs for combustion simulations by a factor of 10,000. At the same time the number of variables used to represent the solution has increased from hundreds of thousands to more than a billion. The upshot is it’s now possible to produce 3D simulations with a remarkable level of complexity and fidelity.
The new software tools are based on adaptive mesh refinement (AMR), a grid-based system that rations computing by directing maximum processing power to where it’s needed most.
Now the research team is focused on adapting the design of the device to burn hydrogen, which while not a renewable resource as it is currently obtained, does not itself release greenhouse gases. Burning hydrogen does still release a very low amount of NOx, however, and the project seeks to reduce the amount further. The team is using the DOE’s National Energy Research Scientific Computing (NERSC) Center supercomputers to help achieve this goal.
“In order to develop clean, energy-efficient systems, we need a continuous feedback loop from the flame to the lab and back again,” Cheng said. “This is the missing link that computation at NERSC provides.”
Combustion science has benefitted from an increase in processing power as well as the development of better algorithms. In addition to the work being done at Berkeley lab, there are similar projects at Argonne National Laboratory (led by scientists from General Electric) and at Sandia National Laboratories (using a supercomputer at Oak Ridge National Laboratory). All these teams are studying combustion with the intention of reducing fuel consumption and pollutants.