Paper Conference

Proceedings of Building Simulation 2021: 17th Conference of IBPSA

     

Natural ventilation predictions for a slum house in Dhaka using large-eddy simulations within a multi-fidelity simulation framework with uncertainty quantification

Yunjae Hwang, Catherine Gorle
Stanford University, United States of America

DOI: https://doi.org/10.26868/25222708.2021.30683
Abstract: A previous study in Dhaka, Bangladesh, indicates that there might be an association between the occurrence of pneumonia, the leading cause of death in children under 5, and the presence of cross-ventilation in slum housing. The objective of this research is to establish a validated computational framework to accurately estimate household ventilation rates and support further investigation of this association. The framework leverages a computationally efficient integral model and high-fidelity large-eddy simulations, as well as uncertainty quantification methods. Simulation results for a variety of weather and housing conditions are validated against field measurements of the ventilation rate and indoor temperatures.
Keywords: Natural ventilation, Large eddy simulation (LES), Uncertainty quantification (UQ)
Pages: 3220 - 3227
Paper:
bs2021_30683