Excellence in Research: From Geometry to Flow: Predicting Wind Turbulence in Realistic Urban Neighborhoods

This project conducts research that will contribute to predicting wind loads on buildings in realistic urban and suburban environments, ultimately enhancing the resilience of communities against hurricane winds. This research will advance understanding of wind behavior, support societal well-being, and improve national security. Accurate prediction of wind loading is an important first step in assessing the safety and structural integrity of buildings exposed to hurricane winds. One of the main technical challenges today is that predicting wind behavior in realistic urban and suburban environments is difficult without site-specific wind tunnel testing or computational simulations, which are often prohibitively expensive. This project will develop general knowledge of how building arrangements and geometric features influence airflow in realistic neighborhoods. This knowledge will help predict key wind behaviors in built environments without requiring separate wind tunnel testing or computational simulations for every location. The project will also produce wind velocity measurements for different building arrangements, which will be made publicly available to support other researchers working to improve wind-loading predictions. The project will engage students and the broader public, foster interest in science, technology, engineering, and mathematics education, and raise awareness of efforts to improve resilience against hurricane winds. The project has two objectives: to develop geometric representations of realistic urban neighborhoods that account for aerodynamic interactions among buildings and to investigate how these geometric features influence flow characteristics. Various neighborhoods will be selected, and their building arrangements will be characterized computationally. Wind tunnel testing and computational fluid dynamics simulations will then be conducted to evaluate the resulting flow characteristics. These data will be fused to quantify relationships between geometric features, represented through computational geometry, and flow behavior. Once these geometry-to-flow relationships are established, their ability to predict key flow behaviors in neighborhoods beyond the study set will be evaluated, potentially reducing the need for site-specific wind tunnel experiments or computational fluid dynamics simulations. General knowledge of urban aerodynamics has often relied on unrealistic simplifications, such as aligned or staggered rectangular block arrays. This research will instead examine realistic urban environments, develop computational methods to characterize building arrangements while considering aerodynamic interactions, and identify geometric features that cause unfavorable airflow, including high turbulence and velocity amplification. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.