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Creators/Authors contains: "Roueche, D.B."

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  1. This study presents a framework for global sensitivity analysis of wind uplift resistance in wood-frame residential structures. The vertical load path is modeled probabilistically as an assemblage of connections, with resistance distributions based on connection design capacity and cumulative dead load. An established sensitivity analysis approach is applied to the load path resistance model to evaluate the influence of the input parameter set on the system resistance, which is taken as the resistance of the weakest connection in series. A preliminary analysis illustrates the potential of the framework as a useful tool for assessing the relative importance of structural attributes for wind resistance, adaptable to any arbitrary vertical load path and parameter set. The framework also facilitates the evaluation of the relative vulnerability of different load path configurations from structure to structure. 
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  2. This study describes a hybrid framework for post-hazard building performance assessments. The framework relies upon rapid imaging data collected by regional scout teams being integrated into broader data platforms that are parsed by virtual teams of hazards engineers to efficiently create robust performance assessment datasets. The study also pilots a machine-in-the-loop approach whereby deep learning and computer vision-based models are used to automatically define common building attributes, enabling hazard engineers to focus more of their efforts on precise damage quantification and other more nuanced elements of performance assessments. The framework shows promise, but to achieve optimal accuracy of the automated methods requires regional tuning. 
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