EAGER: Advanced Digital Twin Capability for Turbulent Wind Fields in the NHERI Boundary Layer Wind Tunnel at the University of Florida

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This EArly-concept Grant for Exploratory Research (EAGER) will establish, validate, and disseminate an advanced digital twin capability for the National Science Foundation (NSF)-supported Natural Hazards Engineering Research Infrastructure (NHERI) boundary layer wind tunnel (BLWT) at the University of Florida (UF). Wind tunnel testing remains the most common approach for assessing wind loads on structures and informing wind resistant design to reduce the cost of damage. However, wind tunnel experiments have limitations, such as the measurement resolution and the challenge of obtaining simultaneous records of wind velocity and pressure fields. Numerical simulations, such as Large Eddy Simulation (LES), offer an opportunity to fill in these gaps, but such simulation capabilities are currently not optimally leveraged by the research community. An important barrier is that current numerical modeling capabilities are mostly tailored to stationary, standard neutral wind profiles; in contrast, wind tunnels such as the BLWT at UF are increasingly implementing advanced capabilities to reproduce more complex turbulent wind fields that cause structural damage. This research project will establish numerical simulation capabilities for these complex wind fields. To maximize the potential impact of the project, validation test cases and a corresponding digital twin tool set and tutorial for the simulation capabilities will be defined through structured interviews with the current UF BLWT user base. The resulting digital twin capability will make it possible to jointly leverage numerical and experimental models to improve understanding of the turbulent wind loads that drive damage to buildings and civil infrastructure and to advance wind resilient design. Simulation data and documented source codes will be archived and made publicly available in the NHERI Data Depot (https://www.DesignSafe-ci.org). This EAGER will contribute to the NSF role in the National Windstorm Impact Reduction Program. The specific goal of the research is to establish and disseminate a numerical modeling strategy for reproducing complex turbulent wind fields generated in the UF BLWT. For standard neutral log-law wind fields, inflow boundary conditions commonly employ artificial turbulence generation methods. Since the velocity statistics of artificial turbulence evolve within the computational domain, some form of calibration is required to ensure that the target wind field is correctly reproduced. This calibration challenge is exacerbated when the objective is to model more complex turbulent wind fields, such as the boundary layer with a pronounced roughness sublayer that can be produced in the UF BLWT, which is important for low-rise buildings, where the building is immersed in the roughness sublayer (the roughness height of the boundary layer is on the order of the building height). The first objective of this project is to explore computationally efficient and accurate methods for numerically reproducing these roughness sublayers. Different combinations of artificial turbulence inflow generators, upstream roughness resolving simulations, source term forcing methods, and machine learning approaches will be investigated and validated against experimental data. The second objective of this project is to support broad dissemination of the resulting turbulence generation method by co-designing a digital twin tool set and a tutorial with the BLWT user base. The digital wind tunnel can also help identify optimal measurement locations for physical testing and potentially support data infilling where there are limits on the spatial resolution of physical measurements.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.