The purpose of this paper is to quantify the influence of turbulence in collision statistics by separately studying the impacts of computational domain sizes, eddy dissipation rates (EDRs), and droplet sizes and eventually to develop an accurate parameterization of collision kernels. Direct numerical simulations (DNS) were performed with a relatively wide range of EDRs and Taylor microscale Reynolds numbers R l . EDR measures the turbulence intensity levels. DNS model studies have simulated homogeneous turbulence in a small domain in the cloud's adiabatic core. Clouds clearly have much larger scales than current DNS can simulate. For this reason, it is emphasized that R l obtained from current DNS is fundamentally only a measure of the computational domain size for a given EDR and cannot completely describe the physical properties of cloud turbulence. Results show that the collision statistics are independent of the domain sizes and hence of the computational R l for droplet sizes no bigger than 25 mm as long as the droplet separation distance, which is on the order of the Kolmogorov scale in real clouds, is resolved. Instead, they are found to be highly correlated with EDRs and droplet sizes, and this correlation is used to formulate an improved parameterization scheme. The new scheme well represents the turbulent geometric collision kernel with a relative uncertainty of 14%. A comparison between different parameterizations is made, and the formulas proposed here are shown to improve the fit to the collision statistics.

In order to enhance the safety standards and culture of Liquid Metal Fast Reactors (LMFR), it's important to provide the system designers with accurate information and data. Because of a general lack of experimental data relating to accident scenarios, such as loss of flow (pump breaking down) or loss of heat sink (heat exchanger malfunction), the use of numerical simulations (e.g. thermal-hydraulics analysis) remains a valid support in predicting coolant flow and thermal behaviour in such scenarios. Historically, the primary computational tool to study the reactor's behaviour are System Thermal-Hydraulic (STH) codes. These were initially designed and validated to be used for Light Water Reactors (LWRs) but have recently been adopted for application of liquid metals as coolant in LMFRs. The advantage of using STH codes is that they require relatively low computational efforts as they are often 1D and/or use a relatively coarse nodalization in 3D. The drawback though is that no details of the flow and temperature fields are resolved. With the increase in computer power and capacity, and the advancements being made in numerical modelling, nowadays it is possible to resolve the full flow and thermal fields of the reactor on a, relatively, fine and detailed scale using Computational Fluid Dynamics (CFD). This has as clear advantage that the flow and thermal fields can be studied in detail. However, to simulate accident scenario's occurring in a nuclear reactor, long transients have to be simulated, which costs a lot of computational power and time if a CFD code is used. Multi-scale modelling combines the best of both worlds; it uses CFD where detailed solutions are desired and STH codes where 1D solutions give accurate enough solutions, allowing the simulation time to remain manageable. The focus of this paper is on multi-scale modelling of the Italian CIRColazione Eutettico (CIRCE) heavy liquid-metal pool-type facility built at ENEA Brasimone. Within the European Horizon 2020 projects called SESAME (thermal hydraulics Simulations and Experiments for the Safety Assessment of MEtal cooled reactors) and MYRTE (MYRRHA Research and Transmutation Endeavour), several experiments are designed in the CIRCE facility to mimic hypothetical accident scenarios occurring inside a liquid metal cooled reactor. Results coming from the foreseen experimental campaigns are, where possible, used to assess and improve the developed models. Two different models of the CIRCE facility are created. At NRG, the CFD code CFX is coupled with the STH code SPECTRA, while at UniPi, Fluent is used for the CFD calculations and a modified version of RELAP5 (RELAP5/Mod3.3) is adopted for the STH calculations. Modelling and coupling strategies for both models are discussed in the present paper. Furthermore, simulation results of both models are compared with each other, both for steady-state cases representing experiments at full power, as well as Protected Loss Of Heat sink and Loss Of Flow (PLOH + LOF) accident scenarios. Special attention is paid to ...

No abstract

No abstract

No abstract