Predictive simulations for quantifying ventilation in slum housing in Dhaka, Bangladesh

Pneumonia is the leading cause of death in children under 5, killing 100 children every hour globally. Bangladesh is among the top ten countries with the highest incidence of pneumonia, and there are indications that improved ventilation in slum housing could reduce its occurrence. The objective of this study is to develop and validate a computational framework for predicting the ventilation rate in these slum houses. The framework uses a combination of an integral model, a computational fluid dynamics (CFD) model, and uncertainty quantification methods. The integral model is used to quantify the effect of uncertainties in model parameters such as weather conditions, the home’s material properties, the internal heat loads, and the window discharge coefficients, on the prediction. The 3D CFD model is used to investigate local flow patterns and obtain more accurate inputs used in the integral model. Validation is performed by comparing model predictions to ventilation measurements performed in a Dhaka home. The validated model will be used to design an optimal solution for improving ventilation while maintaining thermal comfort and mitigating privacy and safety concerns.