Field data collected under the Florida Coastal Monitoring Program (FCMP) during recent hurricane seasons on prototype buildings has revealed that measured pressure coefficients exceeded the provisions of building codes and that wind damage occurred at wind speeds well below the design wind speeds presented in these codes. Because the current code provisions for wind loads are based on the reduction of many wind tunnel observations into a few numbers, the question arises as to what constitutes a proper wind tunnel simulation of the flow in the atmospheric surface layer and associated wind loads on low-rise structures and what procedures should be followed in translating pressure coefficients as measured in these simulations to full scale applications. The objective of the proposed research is to determine whether generic wind tunnel simulations of low-rise structures can predict wind loads under hurricane conditions. This will be achieved by contrasting full scale peak pressure and wind load coefficients measured during recent hurricane seasons with model scale measurements with the same probability of non-exceedence. The comparison will be based on a probabilistic procedure that will be employed to obtain the distribution of peak pressure and load coefficients from single sample records. Different methods will be implemented and compared to determine the parameters of the probability distribution function of the peaks. The different limiting factors, including effects of turbulence intensity and differences between open and suburban terrain exposures, will also be addressed. The recent measurements conducted in Florida provide a unique database that can be used to assess the reliability of simulated wind loads. The proposed effort provides a probabilistic approach for contrasting full and model scale pressure and wind load coefficients. This approach redefines a peak wind load as measured in a single record by associating a non-exceedence probability with its value. The intellectual merit of this project is that it will enable a better comparison of field data with data from wind tunnel simulations. With respect to broader impacts, the proposed research will contribute to a more reliable prediction of wind loads and thus to the goal of reducing losses due to wind damage. The project team will work with the Institute for Business and Home Safety, a non-profit U.S. corporation established to support research and promote construction techniques for loss reduction from natural hazards. The project team will also work with the Multicultural Academic Opportunities Program (MAOP) at Virginia Tech to enable involvement by undergraduate and graduate students from underrepresented groups in this wind research.
Intellectual Impact: Wind storms, such hurricanes and tornadoes, pose dangerous threats to human lives and are an enormous drain on the economy. Their damage to buildings usually starts with the failure of structural components that are subjected to extreme wind loads. In the first part of this work, we aim at enhancing the ability to predict extreme wind loads because having those estimates is very important to mitigate losses caused by severe wind storms. Two questions arise: First, what constitutes an extreme load especially in wind tunnel measurements on building models or numerical simulations? Second, how would those compare to full-scale loads? In this work, we investigate the characteristics of extreme loads on low-rise structures through analysis of full-scale and numerical data. We used a probabilistic approach to characterize peak loads as measured on a subject house during Hurricane Ivan on 2004. Time series of pressure coefficients collected on the roof of that house were analyzed. Rather than using peak values, which could vary due to the stochastic nature of the data, a probabilistic analysis was performed to determine the probability of non-exceedence of specific values of pressure coefficients and associated wind loads. The results show that the time series of the pressure coefficients follow a three-parameter Gamma distribution, while the peak pressure follows a two-parameter Gumbel distribution. The results of the analysis were contrasted with the design values as suggested by the ASCE 7. it should be noted that results from one subject house and one storm are not sufficient to judge standard wind provisions. By providing a basis for contrasting design value and full scale data, the analysis presented here can certainly be used in future investigations for assessing wind loads on structures. As more advances are made in the fields of computing power and tools, we should be able to develop better capabilities to numerically predict wind loads on structures and examine different approaches to reduce and control the effects of extreme loads. In the second part of this work, we performed numerical simulations of the flow over a surface-mounted prism as a simplified example for the flow over a low-rise structure. A Direct Numerical Simulation (DNS) code is developed to solve the unsteady two-dimensional incompressible Navier-Stokes equations of the flow past the prism. The pressure coefficients are then computed on the prism surface in order to assess the wind loads. The code was written on a parallel platform using the Message Passing Interface (MPI) library. We used the simulations to study the effects of inflow disturbances on the extreme loads on structures. The sensitivities of extreme loads, based on the probabilistic approach developed above, on a surface mounted prism to variations in incident gust parameters were determined. The results showed that the extreme loads are most sensitive to the transverse amplitude of the disturbance. Furthermore, because the separated flow over sharp edges is responsible for the extreme pressure peaks, we investigated the use of active and passive control strategies to reduce wind loads. The studied active flow control strategies included blowing, suction, and synthetic jets. We implemented them by using different flux injections, different slot locations and different angles. The results showed that one could achieve a reduction of nearly 25%. For passive control, we mounted a flexible membrane on the top of the prism. The results showed that this strategy is as efficient as the active control approach, in terms of reducing extreme loads. Borader Impact: The broader impact of the performed work can be classified into two components. The developed probabilistic approach for estimating extreme wind loads on structures can be used in many other applications where significant time variations are expected. For instance, it can be expanded to determine the internal stresses in a structure when subjected to such loads. The numerical simulations were performed on a basic structure but the developed code can be used for other applications. Also, the results of flow control of the separation region can be implemented in other applications where flow separation from sharp edges is encountered. To our knowledge, the passive control approach by using a membrane has not been suggested before.
