Boost in computing power
stoking a nuclear revival
(page 3 of 4)
Models could move to that predictive-science base with petascale and exascale computing. That could mean replacing crude safety margins with “conservative safety margins derived from a better-educated design, a science-based design,” Rosner says. “You’re not reducing any aspect of safety. You’re using a better understanding of how things work to replace overdesign.” He likens it to the auto industry, which used lots of heavy steel to make cars safe. Today’s vehicles are lighter and more efficient but safer, thanks to new systems and a better understanding of materials and forces.
Predictive models also could help cut the time – and cost – to prototype and build new reactor designs, Rosner says. For example, engineers must test new fuel rod designs or fuel compositions to see how they exhaust themselves, a process that takes years. The data are used to fine-tune models. “It’s extremely expensive to do those experiments,” Smith says. With predictive modeling, “we’re on the verge of being able to compute those kinds of things. The fuel designers are looking at this and salivating.”
Modeling also can help devise new, less-expensive modular reactors, with parts manufactured in a single facility and transported to a site for installation. Taken together, Rosner says, these efforts can help “break the cost curve” that makes new nuclear plants hugely expensive.
Besides enabling revolutionary designs, predictive models can help existing nuclear plants continue operating longer and at higher power. “We’re in the midst of a major program of life extension,” Rosner says, raising questions about the durability of major plant components like containment and pressure vessels. With the right models, researchers can gauge how materials withstand reactor conditions.
Building on current models
Scientists already are building models that can calculate many nuclear plant processes and properties, including fluid flow and neutron transport in a fuel assembly. “That’s huge, because you now have ways of looking inside the pin bundle that have never been possible before,” Rosner says. Researchers could computationally test designs before prototyping.
DOE’s Consortium for Advanced Simulation of Light Water Reactors (CASL), based at Oak Ridge National Laboratory (ORNL), is designed to build simulation capabilities that help utilities maximize existing reactors. CASL researchers plan to do that by improving fundamental reactor models, says CASL researcher Jess Gehin, ORNL senior nuclear research and development manager, moving them from approximations to high-fidelity, coupled-physics representations.
The petascale computers now available give researchers much of the capacity needed to do that, CASL leader Doug Kothe says. “Exascale opens up a lot of interesting possibilities. An operational core model is going to be memory intensive – it’s not just flops. More and more memory allows you to use more and more complex physical models and fewer assumptions, hence, at least potentially, less error.”