Investigating Fire Collapse Early Warning Systems for Portal Frames

In recent years, firefighter accidents and people injured by the collapse of steel structures during a fire have occurred frequently, which has attracted the attention of the National Emergency Management Department and the Fire and Rescue Bureau. It is urgent to carry out research on early warning systems for building collapse during a fire. Existing early warning methods mainly use characteristic parameters such as temperature, vibration, and structural deformation. Due to the complexity of an actual fire, it is difficult to accurately predict the critical temperature of fire−induced instability in columns and the failure mode after the instability, and there are deviations in the collapse warnings. In this study, changes in ultrasonic transverse and longitudinal wave velocities at high temperatures are used to monitor the stiffness degradation of columns in fire in real time and improve the accuracy of early warning systems. In this study, four common collapse modes of portal frames are obtained by using the results of parametric numerical analysis. According to key displacements and the displacement rates of simple key measuring points, the elastic modulus threshold of a three−level early warning for portal frame collapse with different collapse modes is obtained. Combined with an ultrasonic experiment, the theoretical relationships between the transverse and longitudinal wave velocities and the elastic modulus of steel at high temperatures are verified, and the relationship between the transverse and longitudinal wave velocities and the overall damage of the portal frame is further constructed; then, a new early warning method for portal frame stability during a fire is proposed. Based on the change in wave velocity, a three-level early warning index for predicting portal frame stability during a fire is determined. When the collapse mode of a portal frame is an overall inward collapse, transverse and longitudinal wave velocities are reduced to 2635 m/s and 5308 m/s, respectively. At a second-level warning, they are reduced to 2035 m/s and 4176 m/s, respectively. At 1504 m/s and 3030 m/s, respectively, third-level warnings are issued. This research shows that the real−time monitoring of wave velocities provides an effective way for early warning systems to identify structural collapse. The proposed early warning method can be used as a quick and efficient early warning system for the collapse of portal frames during a fire, and its accuracy and applic