Modal‐based identification method of fire damage in reinforced concrete T‐beams using support vector machine and firefly algorithm

Abstract

To determine the degree of fire damage in reinforced concrete (RC) T-beams, a damage identification method based on an improved support vector machine and firefly algorithm (FA-SVM) is proposed herein. First, based on the fire test of 10 simply supported beams, a refined finite element model of simply supported T-beams was established. A modal analysis of the simply supported beams was performed to obtain a sample library of the input and output parameters for the FA-SVM identification network. Subsequently, the trained FA-SVM identification network was used to predict the fire exposure duration of the samples. The sectional temperature during the fire exposure duration could be calculated by using the finite element model, and the bending stiffness and bending capacity of the simply supported beams after exposure to the fire were calculated. The test sample results were similar to the experimental results of the simply supported beams exposed to fire for 60, 90, and 120 min, which demonstrated the feasibility and effectiveness of the proposed method. Finally, a three-step method for fire damage identification suitable for RC continuous beams was developed based on the FA-SVM identification network. An example calculation analysis of three-span continuous beams was performed, and the results demonstrated accuracy of the identification results. The identification sample magnitude was significantly reduced using this method, which can be conveniently used in practical engineering applications.