Dissertation

Predictive Dynamic CFD Approach to Reducing Airborne Transmission in Naturally Ventilated Hospital Rooms: Impact of Window Opening Angles During Transitional Cold Seasons in China

Yu, Haowei

2025

Overview

The SARS-CoV-2 airborne virus outbreak has once again drawn attention from researchers to the features of viral cross-transmission, particularly the numerous cross-transmissions that took place in hospitals. Autodesk Computational Fluid Dynamics (CFD) is the most widely used simulation software; nevertheless, technical limitations hinder it from effectively reproducing the dispersion and transmission properties of viruses in naturally ventilated rooms under actual conditions. As a result, there is no established way to prevent the spread of viruses across rooms rely only on natural airflow currently. In this thesis, a CFD simulation approach is proposed to investigate the diffusion characteristics of airborne viruses/pollutants in multiple rooms on the same level, considering different window statuses (opening angles). This novel simulation approach combines a window state prediction algorithm and CFD simulation technology. The first approach predicts the window angle based on indoor and outdoor environmental factors obtained from fieldwork measurements. Stepwise polynomial regression has been validated as a novel algorithm that can effectively predict window opening angles. The second approach develops a dynamic CFD model for the target building. The UDF was used to compile dynamic boundary conditions. By combining these two models, more realistic and dynamic characteristics of indoor pollutant dispersion are simulated and extracted. The study found that using this novel CFD simulation framework allows for a relatively accurate description of velocity and concentration fields in naturally ventilated buildings. Specifically, the simulation accuracy for the velocity field is approximately 75%. The accuracy for the concentration field is even higher, with a maximum APE of only 25% and an average prediction accuracy of 97.2%. Furthermore, the study found that if the window opening direction is improperly set, window-opening behavior may lead to severe pollutant dispersion rather than effectively reducing indoor pollutant levels. This study not only clarified the practical application of the window-opening behavior prediction model but also provided a valuable reference for future dynamic CFD simulation studies on buildings with central corridors.

• Publisher: ProQuest Dissertations & Theses
• Subject: Air conditioning / Boundary conditions / Buildings / Built environment / Carbon dioxide / Childrens health / Correlation analysis / COVID-19 / Disease transmission / Epidemics / Epidemiology / Fluid dynamics / Hospitals / Humidity / Medical research / Nosocomial infections / Pollutants / Public health / Severe acute respiratory syndrome coronavirus 2 / Ventilation / Ventilators / Virology / VOCs / Volatile organic compounds
• ISBN: 9798263317263