STARS Highlights

After several years of loyal and reliable services during heavy duty operation in a reactor, nuclear fuel must be discharged and go into retirement. For Switzerland, the final place of retirement is planned to consist of a deep geological repository where the used nuclear fuel will be disposed. Before the repository is constructed, the used fuel will need to be stored in wet pools and/or dry storage casks.

During all this time, safe handling of the fuel will remain the top priority for operators and regulators. To gain better knowledge on the relevant phenomena which could potentially affect the fuel thermo-mechanics and safety characteristics during long storage periods as well as to allow predicting their evolution, simulation models are being developed at PSI within the DRYstars project.

A first milestone was recently achieved with the development of models coupled to state-of-the-art fuel performance codes for each of the three main categories of phenomena considered as having high safety relevance for storage, namely helium behaviour, creep behaviour and hydrogen behaviour.

A safe, economical and environmental friendly disposal of used nuclear fuel represents an essential objective of relevance for all. This guides the approach under development at the laboratory for reactor physics and thermal-hydraulics. Establish higher resolution simulation methods to gain more detailed knowledge on the content of each single nuclear fuel rod ever irradiated in a reactor. Thereafter, use this knowledge to explore optimization approaches that could potentially enlarge the range of disposal options allowing to fulfill the highest level of safety standards while reducing economical costs and geological footprints at the same time.

All matter in the universe is made of atoms and all atoms are made of particles. Spontaneous changes within atoms as well as collisions between atoms and surrounding particles are nuclear reaction processes guided by nuclear physics laws. To simulate these processes using computer models, probabilities for the various involved nuclear reactions are required. This is precisely the role of nuclear data: supply the computational models with evaluated quantities representing these nuclear reaction probabilities.

Through this, nuclear data can effectively be seen as the fundamental link between nature and any computer simulation involving nuclear reactions. It is thus of primary importance to continuously improve knowledge on nuclear data. In that context, researchers at the laboratory for reactor physics and thermal-hydraulics have recently focused on the development and application of Bayesian frameworks combining both differential and integral experiments for the improvement of nuclear data. By considering the different experiments together, the aim is to achieve enhancements of the nuclear data evaluations while preserving the basic nuclear physics sum rules.

Nuclear reactors are complex systems with inherent stochastic behaviour. In simple words, the behaviour of various reactor processes are continuously fluctuating over their mean values, even under normal operation and steady-state conditions. The detailed and systematic analysis of this noisy behaviour can reveal valuable information about the operating status of the studied nuclear reactor. More importantly, designed modifications of the reactor’s operation or even unexpected deviations from the normal performance can be identified using advanced signal analysis techniques. The STARS program, at the Laboratory for Reactor Physics and Thermal-Hydraulics (LRT) in PSI, based on a tight collaboration with the Swiss nuclear industry, has developed a well-established signal analysis methodology, being continuously improved since more than two decades. The latest enhancements of the PSI signal analysis methodology allow a deeper understanding of the underlying mechanisms that drive the reactor’s operation, and can provide better insight on the root-cause of possible disturbances or malfunctions. Recently, the latest STARS activities in advanced signal analysis techniques were culminated by an international recognition through a special distinction from the AIP Chaos Journal.

Spent fuel management is becoming one of the major concerns in many countries with a nuclear program. The radiation aspect as well as the safe and economical part of the long-term storage of the spent nuclear fuel has to be evaluated with a high degree of confidence. To assist such project from the neutronic simulation side, a new method is proposed to systematically calculate at the same time canister loading curves and radiation sources, based on the inventory information from an in-core fuel management system.

Global sensitivity analysis (GSA) is routinely applied in engineering to determine the sensitivity of a simulation output to the input parameters. Typically, GSA methods require the code output to be a scalar. In the context of thermal-hydraulic system code, however, simulation outputs are often not scalar but time-dependent (e.g. temperature profile). How to perform GSA on these outputs?

Noise appears in many areas of science, and commonly has an unwanted and disturbing nature by deteriorating signals’ quality. Therefore, various techniques have been developed over the years for separating noise from pure signals. However, noise has a key role in signal analysis of nuclear reactors as its’ appropriate assessment can be used not only for exploring the normal and dynamic behaviour of nuclear cores, but also for identifying and detecting possible anomalies of reactor systems. State of the art methods have been recently implemented within the well-established signal analysis methodology of the STARS program, at the Laboratory for Reactor Physics and Thermal-Hydraulics (LRT), for investigating nuclear reactor noise and getting a better insight on analysing reactors’ operation.

Spent fuel characterization is necessary to improve nuclear fuel design, optimize core refueling patterns and manage the handling, transport and storage of spent fuel assemblies. The experimental characterization of spent fuels includes measuring their gamma and neutron emissions typically with high-purity Germanium and He-3 detectors. In the past few years, however, efforts to develop efficient and low-cost, fast and thermal, neutron detectors have guided the research to the development of new scintillation detectors. These scintillators offer good efficiency, fast-timing properties, and good pulse shape discrimination capabilities for dual gamma and neutron detection. Within the Laboratory for Reactor Physics and Thermal-Hydraulics (LRT), a preliminary analysis was performed through Monte Carlo simulations to design a measurement unit at the HOTLAB based on new scintillators for the detection of fast neutrons emitted by spent fuel. This semester work of Marianna Papadionysiou was presented at the ANS Student conference in April and received two awards for "Best Detection and Measurement" and "Best Overall Research".

The main threat to the reactor pressure vessel (RPV) operational safety is certainly the radiation damage that hardens and embrittles the steel it is made of. Four decades of research worldwide have allowed understanding and monitoring the phenomena that come into play. At the computational level, a simulation platform, PERFORM-60, has the ambitious aim of predicting the steel evolution for most RPV and operational conditions. It was initially elaborated in the frame of the EU project of the same acronym and is currently further developed to be the end-product of the on-going H2020 EU project SOTERIA. As a contribution of the Laboratory for Reactor Physics and Systems Behaviour (LRS) to SOTERIA, the platform has been rigorously assessed for the first time since its release on a real case study of a Swiss RPV. This critical assessment has been acknowledged by the community and serves as basis for improvements and future developments of the platform within SOTERIA.