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Construction of ITER reactor begins

ITER will avoid worst of heat-related damage, simulations show

Image credit: ITER

Researchers at the US Department of Energy’s Princeton Plasma Physics Laboratory have used computer simulations to predict the heat-related damage caused to ITER, the international tokamak currently under construction in France.

Nuclear fusion is most often artificially induced using facilities called tokamaks. These use a magnetic field to confine plasma at million-degree temperatures in the shape of a doughnut and are considered the most promising candidate for a practical nuclear fusion reactor.

The ITER reactor, which is under construction in Provence, France, is designed to create and sustain a plasma of 500MW (thermal power) for 20 minutes, while just 50MW of thermal power are injected into the reactor. This would demonstrate the principle of producing more thermal power than is used to heat the plasma; a hugely significant step towards commercial nuclear fusion.

Fusion reactors are extreme environments which essentially contain miniature stars and they have to contend with many challenges. Among these is the extreme heat-load; the amount of thermal energy that must be added to maintain the extreme temperature necessary for fusion. These loads flow against the walls of divertor plates, which extract waste heat from the reactor and can cause serious damage to the facility.

The Princeton researchers used high-performance computers and artificial intelligence tools to predict the heat-load width for the ITER while it operates at full power. They produced a forecast that was over six times wider – and far less damaging – than those predicted using a simple extrapolation based on present tokamaks.

“If the simple extrapolation to full-power ITER from today’s tokamaks were correct, no known material could withstand the extreme heat load without some difficult preventive measures,” said Professor Choong-Seock Chang, who lead the team. “An accurate formula can enable scientists to operate ITER in a more comfortable and cost-effective way toward its goal of producing 10 times more fusion energy than the input energy.”

In 2017, the same team used its XGC plasma turbulence code and the Titan supercomputer to forecast a heat-load width for ITER at full power that was, as now, six times wider than expected. The difference between these predictions and previous predictions can be accounted for by parameters in the simple extrapolations that treated plasma as a fluid without considering particle motion; the XGC code produced simulations of trillions of particles on extreme-scale computers. The disparity suggested that there may have been hidden parameters that the fluid model failed to account for.

The team have performed more refined simulations on the Summit computer at Oak Ridge National Laboratory to ensure that their 2017 findings were not in error. They also performed simulations on current tokamaks, including the Joint European Torus in Oxfordshire, to compare the Titan and Summit findings. The results in these cases agreed with the narrow heat-load width forecasts from simple extrapolations, suggesting that there are indeed hidden parameters to account for.

Chang’s team then used supervised machine learning to identify these parameters. This identified that the hidden parameter is related to the orbiting of plasma particles around the tokamak’s magnetic field lines (gyromotion). This provided a suggestion of a different formula which forecasts a far wide and less dangerous heat-load width than the XGC code had derived from experimental results in present tokamaks.

“This exercise exemplifies the necessity for high-performance computing, by not only producing high-fidelity understanding and prediction, but also improving the analytic formula to be more accurate and predictive,” said Chang. “It is found that the full-power ITER edge plasma is subject to a different type of turbulence than the edge in present tokamaks due to the large size of the ITER edge plasma compared to the gyromotion radius of particles.”

The researchers then verified the AI-suggested formula through three further ITER simulations on the Summit and Theta supercomputers.

“If this formula is validated experimentally, this will be huge for the fusion community and for ensuring that ITER’s divertor can accommodate the heat exhaust from the plasma without too much complication,” Chang said.

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