Nuclear reactors 'evolve' inside supercomputers
- 09:48 09 June 2006
- NewScientist.com news service
Nuclear reactors could be built more efficiently using supercomputers to artificially "evolve" designs, say engineers from the US Department of Energy's Oak Ridge National Laboratory in Tennessee.
They have found they can speed up the extremely complex process of designing a reactor and generate novel designs from scratch by simulating natural selection.
Designing a nuclear reactor normally involves input from various specialists and the resulting structure can be uniquely influenced by this collaborative process.
"The design that comes out of this lengthy process is typically sub-optimal," says Louis Qualls, a nuclear systems specialist at Oak Ridge National Laboratory. "If you started with a different person, or designed pieces in a different order, you would get a different system."
Qualls and his colleagues were looking for a more efficient design approach and found inspiration in biological evolution. They used software tools known as genetic algorithms to evolve different reactor designs. Similar algorithms are already used in many different fields to evolve highly efficient solutions to particular problems.
The algorithms they created first produce a population of reactor designs by randomising all the different design factors involved. Each design is then tested in a simulation for its "fitness", measuring its performance efficiency, running cost, safety and other parameters.
The designs that perform best are singled out for survival. They are mutated and recombined to create the next generation of designs. After many cycles, the potential of the most refined designs is evaluated by engineers.
"[Simulated evolution] will come up with some systems we would just never have thought of," Qualls says. "It won't replace the experts or come up with a finished design, but it makes it possible to consider options they wouldn't have had otherwise."
The parameters used to decide which designs survive can also be tweaked to meet different overall criteria. "If I were a businessman I'd want to make the most profit," explains Qualls. "But a safety engineer would want one that is least likely to break down."
Qualls's team has used the approach to help design the reactor for a NASA spacecraft designed to one day travel to the asteroid belt. In this case, weight was the main design concern.
Andy Keane, an independent genetic algorithms expert at Southampton University, UK, says this approach has already proven useful in other fields of engineering.
But for very complex problems, such as nuclear reactor design, he says it is important to combine genetic algorithms with sophisticated methods of simulation and analysis. "Research is now focused on integrating genetic algorithms with other techniques and more powerful computation," Keane says. "This means we can produce more complete designs."