Abstract
MYRRHA is a flexible fastspectrum research reactor under design at SCKCEN. The reactor is cooled with Lead Bismuth Eutectic (LBE). A temperature limit of 400°C was determined to mitigate the corrosion problems related to the cladding stainless steel in contact with LBE. This constraint is the basis for defining the main goal of the thesis; to study the maximum cladding surface temperature and the corresponding uncertainties under the normal operation of MYRRHA.
This study develops a subchannel model in the software Matlab, applicable for hexagonal wire wrapped fuel assemblies. It is used to obtain the maximum cladding surface temperature as an output. This model is validated using experimental data. Some uncertain effects are considered, namely the power distribution, the flow distribution, the heat transfer coefficient, the coolant properties and the geometrical tolerances. These inputs are used to obtain a relevant output distribution using Monte Carlo simulations. Sensitivity indices are computed using Monte Carlo integration.
Later, this study investigates the thermalhydraulic behaviour of the fuel bundle using CFD simulations in the software ANSYS CFX. It focuses on the effect of the axialradial power profile and the size of the fuel assembly. The results are compared to experiments and the subchannel model.
The subchannel model is found to overestimate the experimental maximum surface cladding temperature for a 19pins bundle with homogeneous heating. Compared to CFD results, the model is also conservative for the 19pins with homogeneous heating, but representative for the 19pins with axial power profile and optimistic for the 37pins with axial power profile. Nevertheless, the output distributions obtained with Monte Carlo’s computations comprise all CFD results. The Monte Carlo estimated standard deviation is of the order of 10°C. From the sensitivity analysis, it appears that the power uncertainties affect the most the cladding temperature. The heat capacity, heat conductivity and heat transfer coefficient are also important parameters.
The effect of the axial power profile on the 19pins model is a decrease in the maximum surface cladding temperature of about 10°C, for the same total fuel assembly power. Rather small changes in the temperature profile for the 19pins model are observed when introducing the radial profile. Increasing the size of the bundle enhances the effect of the radial profile.
These results help to direct future research and design studies to improve the thermal performance of the reactor. In a different way, this study can also be used to determine maximum input uncertainties in order to remain within the temperature limit. It is advised to carry out more experiments as well as more CFD simulations to further validate these results, but also to improve the subchannel model in order to correctly consider the number of pins. Practically, more simulations with bigger bundles (>19pins), with axial and radial profiles could be tested both numerically and experimentally to improve the knowledge of the local heat transfer coefficient inside the fuel assemblies. This will involve a particular study of the local heat transfer coefficient in larger assemblies and considering power distributions.
This study develops a subchannel model in the software Matlab, applicable for hexagonal wire wrapped fuel assemblies. It is used to obtain the maximum cladding surface temperature as an output. This model is validated using experimental data. Some uncertain effects are considered, namely the power distribution, the flow distribution, the heat transfer coefficient, the coolant properties and the geometrical tolerances. These inputs are used to obtain a relevant output distribution using Monte Carlo simulations. Sensitivity indices are computed using Monte Carlo integration.
Later, this study investigates the thermalhydraulic behaviour of the fuel bundle using CFD simulations in the software ANSYS CFX. It focuses on the effect of the axialradial power profile and the size of the fuel assembly. The results are compared to experiments and the subchannel model.
The subchannel model is found to overestimate the experimental maximum surface cladding temperature for a 19pins bundle with homogeneous heating. Compared to CFD results, the model is also conservative for the 19pins with homogeneous heating, but representative for the 19pins with axial power profile and optimistic for the 37pins with axial power profile. Nevertheless, the output distributions obtained with Monte Carlo’s computations comprise all CFD results. The Monte Carlo estimated standard deviation is of the order of 10°C. From the sensitivity analysis, it appears that the power uncertainties affect the most the cladding temperature. The heat capacity, heat conductivity and heat transfer coefficient are also important parameters.
The effect of the axial power profile on the 19pins model is a decrease in the maximum surface cladding temperature of about 10°C, for the same total fuel assembly power. Rather small changes in the temperature profile for the 19pins model are observed when introducing the radial profile. Increasing the size of the bundle enhances the effect of the radial profile.
These results help to direct future research and design studies to improve the thermal performance of the reactor. In a different way, this study can also be used to determine maximum input uncertainties in order to remain within the temperature limit. It is advised to carry out more experiments as well as more CFD simulations to further validate these results, but also to improve the subchannel model in order to correctly consider the number of pins. Practically, more simulations with bigger bundles (>19pins), with axial and radial profiles could be tested both numerically and experimentally to improve the knowledge of the local heat transfer coefficient inside the fuel assemblies. This will involve a particular study of the local heat transfer coefficient in larger assemblies and considering power distributions.
Original language  English 

Qualification  Master of Science 
Awarding Institution 

Supervisors/Advisors 

Date of Award  20 Jun 2022 
Publisher  
State  Published  23 Jun 2022 