Application of Carrera unified formulation to predict the flexural response of the composite floor systems at elevated temperatures: Development of the hybrid population-based metaheuristic algorithms

This study investigates the application of Carrera unified formulation (CUF) to predict the flexural response of composite floor systems subjected to elevated temperatures. The accurate assessment of such systems is critical for ensuring the structural integrity of buildings during fire events or other extreme thermal conditions. CUF, known for its flexibility and efficiency in structural analysis, is utilized to develop high-fidelity models capable of capturing the complex behavior of composite floor systems under thermal stress. The formulation allows for the inclusion of various structural components and material properties, enabling a comprehensive analysis of flexural behavior. To enhance the accuracy and reliability of the predictions, the CUF-based models are validated using hybrid population-based metaheuristic algorithms. These algorithms combine the strengths of multiple optimization techniques, effectively navigating the complex solution space associated with thermal-structural interactions. The hybrid approach ensures a robust solution by minimizing errors in the prediction of flexural response, thus addressing the limitations of conventional methods. Results demonstrate that CUF, when integrated with metaheuristic algorithms, provides a powerful tool for predicting the flexural response of composite floor systems at elevated temperatures. The hybrid validation process confirms the model's ability to achieve high accuracy, offering valuable insights for designing fire-resistant composite structures. This research establishes a novel framework for coupling advanced structural formulations with metaheuristic optimization, contributing to safer and more resilient building designs under extreme thermal conditions.