Systematic Study of the Failure of a Light-Frame Wood Roof in a Tornado

Abstract

Tornadoes are a particularly devastating natural hazard that affect communities across the United States, particularly the Midwest and South. They are unique from an engineering point-of-view due to their very low probability of occurrence but often highly destructive consequences. The 2011 season was particularly devastating to the Southeastern portion of the U.S. This paper presents a single case study of a 2012 tornado that struck a single large rural light-frame wood house with an unconventional roof system. A fragility methodology was used as a tool to probabilistically study the loss of the roof system, and bound an Enhanced Fujita (EF) scale rating of the tornado. The tornado was initially rated as an EF3 tornado by the U.S. National Weather Service. However, following a detailed site inspection verified with numerical structural models, the tornado was downgraded to an EF2 tornado. As expected, the use of nail connections in a roof-to-wall connection resulted in a weaker link compared to a hurricane clip. The approach presented in this paper can be used as a supplement to the EF rating provided by U.S. National Weather Service meteorologists when unusual conditions in either the structure or surroundings exists.

Stochastic Modeling of Uncertainties in the Wind Load Pressure on Residential Buildings Using Different Stochastic Techniques

“…Several probabilistic analyses of the wind load im-pacts on building and infrastructure were investigated in the literature including wind hazard induced by tornados [13][14][15] and hurricanes [16][17][18][19]. Additionally, multiple numerical and experimental studies in the literature focus on propagating uncertainties in wind damage models using fragility functions to describe the probabilistic performance of buildings and infra-structure [9,13,[20][21][22][23]. Most all of these functions are using Monte Carlo simulation (MCS) to propagate uncertainties in the wind demand and capacity parameters based on a specific number of simulations.…”