Since nuclear experiments are costly and require extensive safety precautions, the nuclear industry relies heavily on modeling and simulation of nuclear systems. The state-of-the-art simulation tool for steady-state neutron transport is Monte Carlo, a probabilistic approach to solving for the distribution of neutrons. Although it is the most accurate tool available, it is very computationally expensive. Monte Carlo is even more burdensome when coupled to other physics, which allows us to properly capture feedback effects from density and temperature changes. Nonetheless, it is imperative to do such coupling because nuclear reactor designs rely on these intrinsic feedback mechanisms to ensure passive safety.
Besides coupling Monte Carlo with other physics codes, there is an additional hurdle to overcome for time-dependent simulations. These are a few of the reasons why nuclear reactor simulations are a target of exascale computing initiatives. This talk will cover several coupling schemes that create feasible runtimes for coupled time-dependent Monte Carlo simulations. In particular, we will give consideration to high-order/low-order schemes where Monte Carlo and diffusion solvers are paired to deliver accurate results in efficient time.
The most promising of these high-order/low-order schemes is the frequency transform method, which has been used for the first time to efficiently model a multiple-second transient problem with Monte Carlo. As the low-order method computes time-dependent and spatially dependent neutronics information, it also computes frequencies that describe the rate of change of neutron and delayed precursor concentrations. These frequencies are used in Monte Carlo shape-function calculations as an approximation for the time derivatives. Our results show the success of the frequency transform method on prescribed transients and its significant improvement compared to existing methods. Ongoing work is being conducted to show how this method can also be successful when coupled to a thermal-fluids solver in self-propagating transients.
