Collaborative Research: Wind Tunnel Modeling of Higher-Order Turbulence and its Effects on Structural Loads and Response

University Of Florida, Gainesville FL

Investigators

Abstract

Wind hazards are among the most destructive and costly natural forces confronting civil infrastructure. To mitigate risk and business interruptions, reduce damage, and save lives it is essential that we understand the basic nature of wind forces. One important tool for assessing wind loads on structures is the Boundary Layer Wind Tunnel (BLWT), which simulates the effects of high intensity wind field on scaled structures in a controlled environment. The University of Florida Boundary Layer Wind Tunnel (UF-BLWT) is a shared-use facility supported by the National Science Foundation (NSF) Natural Hazards Engineering Research Infrastructure (NHERI) program. The UF-BLWT is a state-of-the-art facility capable of rapidly modifying wind behavior in an automated fashion to investigate the effects of terrain on wind fields and resulting forces on structures. This study will conduct a set of novel experiments at the UF-BLWT to understand the influence of terrain variations on peak wind pressures that load structures during storms. The experimental outcomes will provide a precise description of how a building?s surroundings affect wind pressures and enabling engineers to cost effectively design to survive extreme winds. The novel experiments proposed herein will be further leveraged to support unique educational initiatives including a student exchange program between University of Florida and Johns Hopkins University, and a NSF NHERI workshop on advanced cyber-physical, data-driven, and active learning experimental designs applied to BLWT modeling. A trove of data generated through this study will be curated and published for public access, and will serve as a resource for the wind engineering and machine learning communities as well as an educational resource for teaching wind engineering courses. The project will also support the PIs to continue individual outreach activities at their home institutions that include afterschool programs and internships for underprivileged youth. The Boundary Layer Wind Tunnel (BLWT) is a commonly used tool for assessing wind loads on structures. Existing BLWT facilities routinely match first- and second-order wind field models that have been validated with full-scale wind measurements. However, a growing body of evidence suggests that winds in the roughness sublayer and the inertial sublayer exhibit non-Gaussian higher-order properties in both full-scale wind measurements and BLWT wind fields. These non-Gaussian properties can strongly influence peak wind pressures, which govern certain structural limit states and play an important role in design. To date, no systematic study has been conducted to investigate the influence of these higher-order features in a BLWT, let alone understand their connection to the BLWT roughness elements in an effort to control the higher-order properties of mechanically induced turbulence. We propose a BLWT effort derived from two fundamental hypotheses: 1. Second-order equivalent wind fields can possess different higher-order properties and these properties can be linked to surface roughness features; 2. Differences in higher-order properties of the wind field can significantly influence peak pressures and consequently the response of structures. These hypotheses will be tested through a sequence of four tasks that will systematically modify the automated roughness element array (terraformer) unique to the University of Florida BLWT to identify roughness arrays that create second-order equivalent, but higher-order divergent wind fields. Machine learning methods will be employed to identify relationships between roughness element configurations and higher-order statistical properties of the wind field. The effect of these higher-order wind fields on structures will be studied by investigating peak pressures on two low-rise bluff bodies and measuring the dynamic response of a single degree of freedom flexible structure with tunable nonlinear response. 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.