Pressure drop modeling and comparisons with experiments for single- and two-phase sodium flow

Data-Driven Reduced-Order Modeling of Convective Heat Transfer in Porous Media

This work presents a data-driven Reduced-Order Model (ROM) for parametric convective heat transfer problems in porous media. The intrusive Proper Orthogonal Decomposition aided Reduced-Basis (POD-RB) technique is employed to reduce the porous medium formulation of the incompressible Reynolds-Averaged Navier–Stokes (RANS) equations coupled with heat transfer. Instead of resolving the exact flow configuration with high fidelity, the porous medium formulation solves a homogenized flow in which the fluid-structure interactions are captured via volumetric flow resistances with nonlinear, semi-empirical friction correlations. A supremizer approach is implemented for the stabilization of the reduced fluid dynamics equations. The reduced nonlinear flow resistances are treated using the Discrete Empirical Interpolation Method (DEIM), while the turbulent eddy viscosity and diffusivity are approximated by adopting a Radial Basis Function (RBF) interpolation-based approach. The proposed method is tested using a 2D numerical model of the Molten Salt Fast Reactor (MSFR), which involves the simulation of both clean and porous medium regions in the same domain. For the steady-state example, five model parameters are considered to be uncertain: the magnitude of the pumping force, the external coolant temperature, the heat transfer coefficient, the thermal expansion coefficient, and the Prandtl number. For transient scenarios, on the other hand, the coastdown-time of the pump is the only uncertain parameter. The results indicate that the POD-RB-ROMs are suitable for the reduction of similar problems. The relative L2 errors are below 3.34% for every field of interest for all cases analyzed, while the speedup factors vary between 54 (transient) and 40,000 (steady-state).

Experimental and CFD Investigation on Flow Behaviors of a NPP Pump under Natural Circulation Condition

Passive safety system is the core feature of advanced nuclear power plant (NPP). It is a research hotspot to fulfill the function of passive safety system by improving the NPP natural circulation capacity. Considering that the flow behaviors of stopped pump pose a significant effect on natural circulation, both experimental and computational fluid dynamics (CFD) methods were performed to investigate the flow behaviors of a NPP centrifugal pump under natural circulation condition with a low flow rate. Since the pump structure may lead to different flows depending on the flow direction, an experimental loop was set up to measure the pressure drop and loss coefficient of the stopped pump for different flow directions. The experimental results show that the pressure drop of reverse direction is significantly greater than that of forward direction in same Reynolds number. In addition, the loss coefficient changes slightly while the Reynolds number is greater than 8 × 104; however, the coefficients show rapid increase with the decrease in Reynolds number under lower Reynolds number condition. According to the experimental data, an empirical correlation of the pump loss coefficient is obtained. A CFD analysis was also performed to simulate the experiment. The simulation provides a good accuracy with the experimental results. Furthermore, the internal flow field distributions are obtained. It is observed that the interface regions of main components in pump contribute to the most pressure losses. Significant differences are also observed in the flow field between forward and reverse condition. It is noted that the local flows vary with different Reynolds numbers. The study shows that the experimental and CFD methods are beneficial to enhance the understanding of pump internal flow behaviors.