Large-eddy simulations of wind-driven cross ventilation, Part1: validation and sensitivity study

TL;DR

This study validates large-eddy simulations for wind-driven cross ventilation in buildings, demonstrating their accuracy and sensitivity to grid resolution and inflow conditions, with implications for sustainable building design.

Contribution

It provides the first comprehensive validation and sensitivity analysis of LES for wind-driven cross ventilation in buildings, highlighting the robustness of mean flow predictions.

Findings

Fine grid resolution improves flow detail accuracy

Inflow turbulence affects instantaneous ventilation variability

Mean ventilation rate predictions are robust to grid and inflow variations

Abstract

Natural ventilation is gaining popularity in response to an increasing demand for a sustainable and healthy built environment, but the design of a naturally ventilated building can be challenging due to the inherent variability in the operating conditions that determine the natural ventilation flow. Large-eddy simulations (LES) have significant potential as an analysis method for natural ventilation flow, since they can provide an accurate prediction of turbulent flow at any location in the computational domain. However, the simulations can be computationally expensive, and few validation and sensitivity studies have been reported. The objectives of this study are to validate LES of wind-driven cross-ventilation and to quantify the sensitivity of the solution to the grid resolution and the inflow boundary conditions. We perform LES for an isolated building with two openings, using three different grid resolutions and two different inflow conditions with varying turbulence intensities. Predictions of the ventilation rate are compared to a reference wind-tunnel experiment available from literature, and we also quantify the age of air and ventilation efficiency. The results show that a sufficiently fine grid resolution is needed to provide accurate predictions of the detailed flow pattern and the age of air, while the inflow condition is found to affect the standard deviation of the instantaneous ventilation rate. However, for the cross-ventilation case modeled in this paper, the prediction of the mean ventilation flow rate is very robust, showing negligible sensitivity to the grid resolution or the inflow characteristics.