airflow network model

Building energy simulation (BES) and Airflow network (AFN) programs generally incorporate wind pressure coefficients (Cp) estimated from secondary sources, namely data bases or analytical models. As these coefficients are influenced by a wide range of parameters, it is difficult to obtain reliable Cp data. This leads to uncertainties in BES-AFN models results, especially for naturally ventilated building studies, where air change rate which strongly depends on Cp, is a key value for thermal comfort and energy consumption results.

Buoyancy-driven natural ventilation in ventilation shafts is investigated with a small scale physical experiment within a duct and CFD simulations of an office building. For a fixed exhaust opening, smaller shafts lead to higher flow rates in upper floors of a multi-storey building with a shared ventilation shaft. These higher flow rates are caused by increased vertical momentum within the smaller shafts that induce flow through upper floors, an effect referred to as the “ejector effect”.

The prevailing paradigm in indoor environment control of office buildings often excludes natural ventilation, due to the fact that its dynamic nature may not be compatible with the close control of mechanical conditioning systems. Due to the potential magnitudes of wind and buoyancy forces in tall buildings, the challenges are greater. This research is concerned with the prospect of purely naturally ventilated tall office buildings. The naturally available driving forces of wind and buoyancy are investigated separately or in combination.