Scientific Highlights LRT

The entire study is an investigation into the self-similarity behavior ^[1] of first and second order statistical quantities derived from a large-scale jet flow taken from one of the experiments in the PANDA facility using the Proper Orthogonal Decomposition (POD).

What is presented, are the merits, the potential and the characteristics of the corresponding underlying POD analysis. Proper Orthogonal Decomposition (POD) is a mathematical framework to extract large-scale structures which are otherwise eventually masked by the complexity of the fully turbulent flow; example: the meandering of a jet which is not so obvious for the original data.

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.

Between the years 2015 and 2019, PSI coordinated a project investigating the pebble bed high temperature gas-cooled (HTGR) reactor aside with molten salt reactor (MSR) concepts and the use of thorium fuel. The project involved different groups from the ETH domain and the main purpose is to build-up the specific know-how in Switzerland that is necessary to provide in-depth information to decision makers and identify research needs for the future. Several key aspects of both HTGR and MSR reactors were addressed in this research project. These include economic and accident phenomenology studies of the HTGR, fuel cycle optimization of both MSR and HTGR, as well as a study on waste volume reduction of the pebble bed reactors.

In nuclear safety analyses, the assessment of hydrogen release, distribution, and mitigation in the containment has high relevance, because under certain postulated scenarios, combustible mixture could form and hydrogen explosions could damage safety systems.

Safety analyses is carried out using advanced computational tools that have been assessed and validated through a variety of the analyses based experiments representative of the phenomena postulated in the containment and obtained in highly instrumented thermal-hydraulics facilities.

The OECD/NEA HYMERES project (www.psi.ch/en/teg/projects) was carried out to create an experimental database consisting in 24 PANDA tests and 9 MISTRA (CEA, France) tests devoted to phenomena with high relevance in nuclear safety. In two PANDA tests identified as HP6_1 and HP6_2) was investigated the effect of complex natural circulation in a PWR two-room type containment, on the hydrogen distribution, during postulated accidents [1]. The PANDA test specifications have been determined based on scoping analyses with the GOTHIC and APROS advanced computational tools [2].

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?

The Accident at the Fukushima Daiichi Nuclear Power Station, which occurred in March 2011, had a very strong impact on the nuclear community. Three reactors suffered core damage and fission products were released to the environment. Paul Scherrer Institute (PSI) has participated in an Organisation for Economic Cooperation and Development (OECD) project, Benchmark Study of the Accident at the Fukushima (BSAF). The project aimed to evaluate and analyse the accident progression, likely end-state of the reactor core after the accidents, and the release of radioactivity to the environment. PSI has concentrated on the analysis of unit 3 using MELCOR 2.1. Hundreds of calculations have been performed and a plausible scenario which predicted remarkably well the main signatures has been selected.