Development of Flow Network Analysis Code for Core of Prismatic Very High Temperature Reactor

Abstract

The core of the prismatic very high temperature reactor (VHTR) consists of hexagonal prismatic fuel blocks and reflector blocks made of graphite. Therefore, there are interstitial gaps between blocks and the gap varies during core cycles due to the neutron-induced shrinkage of the graphite. If the core bypass flow ratio increases, the coolant channel flow is decreased and can then lower the heat removal efficiency, resulting in a locally increased fuel block temperature. Moreover, variations in the size of the gap increase the uncertainty of the core flow distribution. Recently, the computational fluid dynamics (CFD) method has received a great deal of attention as a method for understanding the flow behavior in the VHTR core. However, the large computational cost and time required to implement CFD codes simulating the entire core hinder their application to analysis of the gap effect. An alternative technique is the utilization of a system code, which uses lumped parameter model. The system code has advantages in computational time and cost but, the accuracy is relatively low. Therefore, to analyze flow distribution in the core of VHTR effectively, the flow network analysis code named FastNet (Flow Analysis for Steady-state Network) which uses looped network analysis method was developed in this study. The flow network analysis code presents flow paths as a network of flow resistances, and thus requires the precise relation between the pressure loss and flow rate in given geometry. In the VHTR core, there are three types of flow paths: coolant channel, bypass gap, and cross gap. The coolant channel and the bypass gap can be analyzed using equations that relate the head loss due to friction along given length of channel. However, the relation between the pressure loss and flow rate at the cross gap cannot be analyzed easily because of its complex geometry. Moreover, the cross gap complicates the flow distribution in the connecting flow path between the coolant channel and bypass gap. For these reasons, the cross flow in the VHTR core was studied experimentally to enhance the calculation accuracy of the flow network code using the correlation of the cross flow loss coefficient. Thus, a cross flow experimental facility was constructed to investigate the cross flow phenomena in the core of the VHTR and a series of experiments were carried out under varying flow rates and gap sizes. The results of the experiments were compared with CFD (Computational Fluid Dynamics) analysis results in order to verify its prediction capability for the cross flow phenomena. Good agreement was seen between experimental results and CFD predictions and the local characteristics of the cross flow were investigated. Based on the calculation results, a correlation of pressure loss coefficient across the cross gap was developed and the developed correlation was implemented in FastNet. For heat transfer analysis, since the FastNet allocates 6 cells for one fuel block, the effective thermal conductivity (ETC) model was adopted. In this model, the thermal conductivities of all components in the multiple medium are homogenized to a single ETC in conjunction with the contribution of the radiation heat transfer. Moreover, the maximum fuel temperature model using unit cell was implemented to predict the highest temperature of fuel in a cell. For verification and validation of FastNet, the calculation results were compared with CFD analysis results and experiments data. At first, flow network analysis capability was validated with the SNU multi-block experiment. Then, a single column analysis was simulated and compared with CFD analysis and CORONA calculation results. Finally, a whole core simulation was conducted to evaluate the calculation performance of FastNet and the simulation results were compared with results of CFD analysis and CORONA calculation. FastNet shows the fast calculation speed as well as reliable calculation results. From the V&V results, it can be concluded that FastNet can provide reliable predictions on flow distribution and temperature distribution in the core of prismatic VHTR. Therefore, it is expected that FastNet can contribute to assure the core thermal margin.