Laboratory for Reactor Physics and Thermal-Hydraulics (LRT)

For water-cooled nuclear reactors, a loss of coolant accident constitutes one of the key scenarios to be evaluated for the design of the plant and associated safety systems. Even if these accidents are not expected to occur at all during reactor lifetime, their potential consequences include the heat up of the fuel in the reactor core. For the recovery of the plant to safe conditions, safety systems are in place to inject water in order to reflood the core and to quench the high temperature fuel. The two-phase flow behaviour during this reflooding phase is extremely complex. In particular, the prediction of the behaviour of small liquid droplets generated as the quench front propagates upwards has a significant effect on the fuel temperatures in the upper regions of the reactor core. In collaboration with the US Nuclear Regulatory Commission (NRC), we have been working to improve our modelling of the droplet behaviour and their impact on key safety parameters.

During the last decades, computing power has been subject to tremendous progress due to the shrinking of transistor size as predicted by Moore’s law. However, as we approach the physical limits of this scaling, alternative techniques have to be deployed to increase computing performance. In this regard, the next big advance is envisioned to be the usage of approximate computing hardware based on field-programmable gate arrays and/or digital-analogue in-memory circuits. Such approximate computing can provide disproportional gain (x1000) in energy efficiency and/or execution time for acceptable loss of simulation accuracy. This could be highly beneficial in order to accelerate computational intensive simulations such as reactor core analyses with higher resolution multi-physics models. On the other hand, the execution of programming codes on low-precision hardware may result in inadequate outcomes due to quality degradation and/or algorithm divergence. To address these questions, studies on the stability and the performance of advanced reactor simulation algorithms as function of reduced floating-point arithmetic precision are being conducted at the laboratory for reactor physics and thermal-hydraulics. Results obtained so far indicate a large room for the acceleration of nuclear engineering applications using mixed-precision hardware. Therefore, research is now being enlarged towards assessing multiprecision computing methods for reactor core simulations with higher spatial resolution.

Data science (DS) and artificial intelligence (AI) methods opens up an immense range of new opportunities and challenges in the context of continuously enhancing the complex methodologies used as basis for nuclear safety assessments. To this aim, following discussions in the ETSON Technical Board on Reactor Safety, the PSI laboratory for reactor physics and thermal-hydraulics organized on October 20-21, 2022, an international workshop to review and discuss DS/AI within ETSON, the network of European research and expert organizations providing scientific support to national nuclear authorities. With close to 40 participants, the workshop, organized as a hybrid meeting, allowed to put in evidence that similarly as at PSI, a wide and growing range of developments with integration of DS/AI methods are currently taking place in order to complement and/or inform nuclear safety analysis methodologies.