A methodology to obtain the directional pressure loss coefficients in a porous media model of an electromagnetically compatible screen of a radio base station model is presented. The directional loss coefficients of this compact model are validated against a detailed computational fluid dynamics model not only by comparing the total pressure drop, but also by evaluating the flow pattern after the screen. The detailed model was validated in an earlier article by the authors. A parametric study is conducted for 174 cases. Seven parameters were investigated: velocity, inlet height, screen porosity, printed circuit board (PCB) thickness, inlet-screen gap, distance between two PCBs and screen thickness. Based on the compact model parametric study, two correlations for the directional loss coefficients are developed as a function of the Reynolds number and the above geometrical parameters. The average disagreement between the compact model that uses the directional loss coefficients from the correlations and the detailed model was of 3% for the prediction of the total pressure drop and less than 6.5% and 9.5% for two coefficients that accurately characterize the flow pattern.
The objective of this paper is to investigate the performance of five well-known turbulence models, in order to find a model that predicts the details of the flow patterns through an electromagnetic compatibility (EMC) screen. The turbulence models investigated in the present study are five different eddy-viscosity models; the standard k-epsilon model, the renormalization group (RNG) k-epsilon model, the realizable k-epsilon model, the standard k-omega model, as well as the shear stress transport k-w model. A steady-state 3-D detailed model, which serves as the most accurate representation of the model, was used in order to evaluate the details of the airflow paths and pressure field. The flow was assumed to be isothermal, turbulent and incompressible. A general model that covers a considerable range of velocities and geometries was validated experimentally by wind tunnel measurements. The result shows that for most of the k-epsilon models used with correct y(+) and mesh strategy, the pressure drop and the velocity field deviation is small compared to experimental data. The k-omega models overpredict the overall pressure drop. When using the RNG k-epsilon model, the total static pressure drop predicted differs around 5%-10% and the average velocity deviation at several locations before and after the screen is around 5%.