Stanford Engineering
Wind Engineering Lab

Natural Ventilation for Improving Health in Slum Homes

bangladesh_slum_area

by Yunjae Hwang

Project timeline: 2017-2022

Motivation & Objectives

Respiratory diseases are a leading cause of death in children under 5. Poor indoor air quality is a major cause of these infections and a preliminary study indicated that there might be an association between the respiratory illnesses and household ventilation. This project is part of large-scale study that more thoroughly investigates this relationship in urban slums of Dhaka, Bangladesh. Our objective is to develop and validate a computational framework for predicting ventilation rates in a variety of housing layouts and weather conditions. This framework will: (1) help identify robust ventilation strategies that will work under a variety of weather conditions, (2) provide ventilation rate estimates that will support analyzing results of RCT studies evaluating the impact of ventilation interventions in slum homes, and (3) support the formulation of global ventilation recommendations.

Computational framework & Results

The framework encompasses two models in different levels of fidelities: a building thermal model and a computational fluid dynamics (CFD) model. The computational predictions are validated by comparing them to field measurements.

The integral model solves for the time-evolution of the volume-averaged indoor air temperature and predicts the ventilation rate using an envelope flow model. The main advantage of this model is its low computational cost (the model runs in 10 seconds on my laptop!), which makes it ideal for uncertainty quantification (UQ). Combined with UQ, the model predicts mean values and 95% confidence intervals for our quantities of interest. However, the model has limitations in terms of capturing the influence of detailed physics such as turbulence and temperature stratification on the ventilation rate.

The CFD model predicts the full 3D velocity and temperature fields with a higher-fidelity representation of the flow physics than the integral model. Large-eddy simulation (LES) support resolving the important effect of turbulence on the ventilation rates. The simulations consider different weather conditions (i.e. temperatures and wind directions). In addition, the model includes not only the target house, but also the surrounding buildings. The LES simulation improves our understanding the complicated flow physics of combined wind- and buoyancy-driven ventilation. Using similarity theory, the simulations support defining building-specific correlations for the natural ventilation flow field, which can then be to formulate a highly accurate and computationally efficient building thermal model.

Related Publications

  • Field measurements and building thermal model with UQ:
    Y. Hwang, L.H. Kwong, S. Munim, F. Nizame, S.P. Luby & C. Gorlé "Modeling ventilation in a low-income house in Dhaka, Bangladesh" (in preparation)
  • LES validation and building-specific correlations for the natural ventilation flow:
    Y. Hwang & C. Gorlé "Large-eddy simulations to define building-specific similarity relationships for natural ventilation flow rates" (submitted to Flow)
  • LES validation of wind-driven cross ventilation:
    Y. Hwang & C. Gorlé "Large-eddy simulations of wind-driven cross ventilation, Part1: validation and sensitivity study" (submitted to Frontiers in Built Environment)
  • LES to analyze different wind-driven cross ventilation configurations:
    Y. Hwang & C. Gorlé "Large-eddy simulations of wind-driven cross ventilation, Part 2: comparison of ventilation performance under different ventilation configurations" (Submitted to Frontiers in Built Environment)

Conference presentations

  • Y. Hwang & C. Gorlé "Similarity theory for wind and buoyancy combined natural ventilation using CFD simulations", 74th APS Division of Fluid Dynamics, Phoenix, AZ, Nov. 21-23, 2021
  • Y. Hwang & C. Gorlé "Natural ventilation predictions for a slum house in Dhaka using large-eddy simulations within a multi-fidelity simulation framework with uncertainty quantification", Building Simulation 2021 Conference, Bruges, Belgium, Sep. 1-3, 2021 
  • Y. Hwang & C. Gorlé "Computational Fluid Dynamics for Modeling Ventilation in a Slum House in Dhaka, Bangladesh", Engineering Mechanics Institute Conference, Virtual, May 25-28, 2021
  • Y. Hwang & C. Gorlé "Large-eddy simulations of combined wind and buoyancy-driven ventilation in a slum house in Dhaka, Bangladesh", 6th American Association for Wind Engineering Workshop, Virtual, May 12-14, 2021
  • Y. Hwang & C Gorlé "A multi-fidelity simulation framework with uncertainty quantification for predicting natural ventilation in a slum house in Dhaka, Bangladesh", 73rd annual APS Division of Fluid Dynamics, Virtual, Nov. 22-24, 2020 [Link]
  • Y. Hwang, M. Hasan, L. Kwong, F.A. Nizame, S. Luby & C. Gorlé, "Modeling ventilation in an urban-slum home in Dhaka, Bangladesh", 72nd annual APS Division of Fluid Dynamics, Seattle, WA, Nov. 23-26, 2019 [Link]
  • Y. Hwang, L. Kwong, J. Forsyth, S. Rahman, F.A. Nizame, S. Luby, & C. Gorlé, "Modeling ventilation in a slum house in Dhaka, Bangladesh" Engineering Mechanics Institute Conference, Pasadena, CA, Jun. 18-21, 2019
  • Y. Hwang, Y. & C. Gorlé, "Predictive simulations for quantifying ventilation in slum housing in Dhaka, Bangladesh", 71st annual APS Division of Fluid Dynamics, Atlanta, GA, Nov. 18-20, 2018 [Link]
  • Y. Hwang, R. Ho, & C. Gorlé, "Predictive simulations for improving ventilation to decrease respiratory illness in slums of Dhaka, Bangladesh" International Symposium on Computational Wind Engineering, Seoul, South Korea, Jun. 18-22, 2018

Acknowledgment

This research was funded by an EVP grant from the Woods Institute for the Environment, as well as by the Stanford Center at the Incheon Global Campus (SCIGC).