Abstract

An increasing threat of global terrorism has led to concerns about bombings of buildings, which could cause minor to severe structural damage. After such an event, it is important to rapidly assess the damage to the building to ensure safe and efficient emergency response. Current methods of visual inspection and non-destructive testing are expensive, subjective, and time consuming for emergency responders' usage immediately after an attack. On the other hand, vibration-based damage detection methods with wireless smart sensors could provide rapid assessment of structural characteristics with low cost. For blast analysis, structural response is usually determined using a simplified SDOF version of the undamaged structure, such as used in a Pressure-Impulse (P-I) Diagram, or using more complex FEM (finite element method) models. However, the simplified models cannot take into account damage caused by blast focus at a specific location or on a specific element, which may induce local failure leading to potential progressive collapse, and the more complex FEM models take too long to derive applicable results to be effective for a rapid structural assessment. In this paper, a new method to incorporate vibration-based damage detection methods to calculate the multi degree of freedom structural stiffness for determining structural condition is provided to create a framework for the rapid structural condition assessment of buildings after a terrorist attack. The stiffness parameters are generated from the modal analysis of the measured vibration on the building, which are then used in a numerical simulation to determine its structural response from the blast. The calculated structural response is then compared to limit conditions that have been developed from ASCE blast design codes to determine the damage assessment. A laboratory-scale building frame has been employed to validate the developed use of experimentally determined stiffness by comparing the P-I diagram using the experimental stiffness with that from numerical models. The reasonable match between the P-I diagrams from the numerical models and the experiments shows the positive potential of the method. The framework and examples of how to develop a rapid condition assessment are presented.

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