FEniCSx-OpenMC Coupling for Neutronic Calculation with Temperature Feedback

The state of an operating nuclear reactor depends on several interdependent physical phenomena, which can be considered simultaneously by modelling the system using a multi-physics (MP) approach. MP allows a higher level of detail of the system’s properties at the expense of code complexity and computational burden, whereas, in the past, single-physics codes were dominant due to the limited computational resources, and the coupling effects were typically introduced using correlations or boundary conditions to the problem. In the context of nuclear reactors, the fundamental coupling is between neutron physics and thermal hydraulics, as their interaction directly affects the power and temperature profiles, which are quantities of interest during both the design and safety analysis phases. Due to the recent improvements in computational capabilities, the MP approach has become feasible, focusing the efforts on the development of interfaces between different single-physics numerical codes (in most cases, already validated and verified) to catch the MP coupling. This work focuses on developing a tool capable of determining the temperature profile of a characteristic fuel pin of a PWR when the power generated by the system is known: this test case is interesting because the thermal feedback effects produce a shift in the power peak compared to the middle of the rod,which a well-known phenomenon in nuclear reactor pins. This tool is developed in a Python environment, using the open-source library FEniCSx for the thermal-hydraulic analysis and the OpenMC Monte Carlo code to describe the fissionable system; this choice has been made to have the whole code inside a single open-source environment which, compared to state-of-the-art proprietary codes, offer higher accessibility and community feedback. In the coupling, an explicit method is applied whose convergence is based on a Picard scheme, using an adaptive relaxation scheme: this strategy is one of the most adopted techniques due to its simplicity; however, monolithic approaches can be also adopted which may give better results even though the implementation phase is more challenging. The proposed coupling approach can predict the peak shift in the power density as per the literature, thus more efforts can be made to extend the current model to more complex cases.