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1. Research Experiences for Undergraduates (REU), NHERI 2023: Mayfield Clothing Mill Deviation Analysis and Conversion of Point Cloud Model to FEM

   https://doi.org/10.17603/ds2-f3pq-dn68  

   Whitesides, Elanor; Kaushal, Saanchi Singh; Napolitano, Rebecca; Wartman, Joseph (January 2023, Designsafe-CI)

   Point cloud models of the Mayfield Clothing Mill, a tornado-damaged historic masonry building, are analyzed to understand any possible structural deviations. A point cloud alignment and deviation analysis workflow are described. Cloud2FEM, a point cloud to finite element model (FEM) conversion software, is utilized to generate a FEM for the Clothing Mill. The resulting FEM can be used for structural analysis purposes and be simulated under load conditions to study the structure’s response. 

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2. Processed data and the final point clouds for the historic masonry structures in Mayfield, Kentucky:RAPID: Mayfield, KY Post-Tornado Building Reconnaissance

   https://doi.org/10.17603/ds2-atmx-gp96  

   Kaushal, Saanchi Singh; Gutierrez Soto, Mariantonieta; Napolitano, Rebecca (January 2023, Designsafe-CI)

   The process of generating a comprehensive point cloud from the raw data collected at Mayfield involved three distinct steps. Firstly, Pix4D was utilized to process and analyze the data. This was followed by the utilization of Register 360 to further refine and align the collected data. Finally, Cyclone was used to complete the point cloud generation process, ensuring that the resulting point cloud was as detailed and accurate as possible. The combination of these three steps allowed for the creation of a comprehensive point cloud that could be utilized for a variety of applications, ranging from surveying and mapping to construction and design.Damage reconnaissance of historical buildings affected by tornado loading 

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3. Probabilistic simulation of tornado-like loading on a low-rise building based on laboratory testing

   Wu, Xinyang; Zuo, Delong (August 2023, 16th International Conference on Wind Engineering)

   Tornadoes can cause severe damage to buildings, but it is difficult to measure tornado loading on structures due to limitation of equipment. To enable investigations of tornado effects on buildings, this paper presents a method that can be used to numerically simulate nonstationary, non-Gaussian tornado-like loading based on laboratory testing. An illustrative application shows that the proposed method can successfully simulate tornado-like loading that is statistically similar to the loading measured in experiments. 

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4. Research Experiences for Undergraduates (REU), NHERI 2022: Post-Tornado Historic Masonry Building Reconstruction

   https://doi.org/10.17603/ds2-s0g7-ed50  

   Patelski, Keely; Kaushal, Saanchi Singh; Napolitano, Rebecca (January 2022, Designsafe-CI)

   Models of 12 historic masonry buildings damaged by an EF4 tornado were created by combining Unmanned Aerial Vehicle Structure-from-Motion (UAV-SfM) and Light Detection and Ranging (LiDAR) point clouds. The building models can be used for a myriad of purposes, such as structural analysis. Additionally, the point cloud combination workflow can be applied to other projects. 

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5. Mobile Radar Observations of the Evolving Debris Field Compared with a Damage Survey of the Shawnee, Oklahoma, Tornado of 19 May 2013

   https://doi.org/10.1175/MWR-D-19-0215.1  

   Wakimoto, Roger M.; Wienhoff, Zachary; Bluestein, Howard B.; Bodine, David J.; Kurdzo, James M. (May 2020, Monthly Weather Review)

   A detailed damage survey is combined with high-resolution mobile, rapid-scanning X-band polarimetric radar data collected on the Shawnee, Oklahoma, tornado of 19 May 2013. The focus of this study is the radar data collected during a period when the tornado was producing damage rated EF3. Vertical profiles of mobile radar data, centered on the tornado, revealed that the radar reflectivity was approximately uniform with height and increased in magnitude as more debris was lofted. There was a large decrease in both the cross-correlation coefficient ( ρ hv ) and differential radar reflectivity ( Z DR ) immediately after the tornado exited the damaged area rated EF3. Low ρ hv and Z DR occurred near the surface where debris loading was the greatest. The 10th percentile of ρ hv decreased markedly after large amounts of debris were lofted after the tornado leveled a number of structures. Subsequently, ρ hv quickly recovered to higher values. This recovery suggests that the largest debris had been centrifuged or fallen out whereas light debris remained or continued to be lofted. Range–height profiles of the dual-Doppler analyses that were azimuthally averaged around the tornado revealed a zone of maximum radial convergence at a smaller radius relative to the leading edge of lofted debris. Low-level inflow into the tornado encountering a positive bias in the tornado-relative radial velocities could explain the existence of the zone. The vertical structure of the convergence zone was shown for the first time. 

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