CFD Simulation for Understanding the Effects of Wind Direction and Surroundings on Airflow and Air Exchange Rate of a Naturally Ventilated Dairy Building

摘要

Advective heat and mass transfer, due to pressure differences created by wind or buoyancy, dominates the exchange processes in naturally ventilated structures. The air> exchange rate (AER) quantifies this transfer. The airflow patterns including air velocities and turbulences govern the indoor environmental parameters such as temperature, gases and humidity. These patterns form the essential link between the outdoor environment and the buildings microclimate; thus, an understanding of the principlesof air motion is necessary in order to provide the correct quantities of air and the proper distribution patterns to meet the needs of the application. Computational fluid dynamics (CFD) have been applied in very limited studies for naturally ventilatedanimal houses considering wind directions and surrounding buildings. This paper presents isothermal CFD simulations with a naturally ventilated dairy (NVD) barn model to assess the influence of wind direction and surroundings on the AER and indoor and outdoor airflow distributions. A typical NVD building and its surroundings located in Northeast Germany were selected for model development and simulation. ANSYS Workbench 2020R1 platform (ANSYS Inc) was used for creating model geometry, meshing and simulation. Simulations were performed for four wind directions and for a computation model with and without surrounding buildings. The standard kinetic energy (k)-dissipation (e) turbulence model was used for all simulations. In order to improve the quality of CFD calculations, i.e. to make calculations with sufficient accuracy, several important issues (e.g. grid independency and convergence criteria etc) were considered carefully for both the governing equations and the computation. CFD validation was performed with the measured data from a boundary layer wind tunnel under strictly controlled laboratory conditions taking into account full scale measurement. The results showed that the simulated differences in AER between wind directions can go up to 52.2%(without surroundings) and 65.1% (with surroundings). Furthermore, comparing the simulations with and without surrounding buildings showed that neglecting the surroundings can lead to overestimation of the AER with up to 52 %. Further investigations arerequired to understand the airflow pattern and estimate AER in unsteady conditions considering wind directions and surroundings.