| The potential for natural ventilation in building design to reduce associated building cooling and fan energy consumption makes it an area of great interest. However, its increased use is dependent on the availability of accurate modeling tools to predict its impact on a given building design. This thesis examines the accuracy of four modeling tools to predict ventilation rates across a wide range of natural ventilation scenarios.;Two stand-alone network airflow models (COMIS and CONTAM), as well as two full building simulation tools (EnergyPlus and ESP-r) which have integrated network airflow models, are investigated. These four tools are applied to experimental datasets from literature for various combinations of geometry and natural ventilation driving forces (ex. buoyancy-driven single-sided ventilation, wind-driven cross ventilation). Results show that the four tools are generally similar to each other, but are only able to predict ventilation rates within 35%. Further sensitivity study shows the network airflow model's dependence on several ambiguous parameters, specifically the discharge coefficient.;Further study was conducted using EnergyPlus to model three real naturally ventilated buildings. Accuracy of predicted indoor temperatures as compared to field monitoring data was varied across the three buildings. The experience of modeling these buildings highlighted several deficiencies in the tool's capabilities, as well as incompleteness in the available datasets. |
