DEVELOPING THE THERMO - ELASTIC FINITE ELEMENT APPROACH WITH APPLICATIONS TO FRAMEWORKS USING AI

The thermo-elastic behaviour of frameworks plays a crucial role in various engineering applications, including aerospace, civil structures, and mechanical systems. Accurately predicting the response of these frameworks under thermal and mechanical loads is essential for ensuring their structural integrity and performance. This paper presents a novel approach that combines the power of thermo-elastic finite element analysis (FEA) with artificial intelligence (AI) techniques to improve the accuracy and efficiency of simulations in the framework design and analysis process. The proposed approach utilizes the fundamental principles of FEA to discretize the framework into small elements, allowing for the representation of complex geometries and material behaviour. Within each element, the governing equations for thermal and mechanical deformation are established based on the laws of conservation of energy and linear elasticity. These equations are solved numerically using established finite element methods to obtain the framework's response under given loading conditions. Incorporating AI techniques into the thermo-elastic finite element approach enhances its predictive capabilities and efficiency. AI algorithms, such as machine learning and deep learning, can be employed to learn complex patterns and relationships from large datasets, enabling the development of accurate constitutive models for the framework materials. These models capture the non-linear behaviour, hysteresis, and time-dependent effects often encountered in real-world applications. AI-based techniques can optimize the framework's design and performance by automating the iterative process of parameter tuning and shape optimization. Genetic algorithms, neural networks, and other AI optimization algorithms can be integrated into the framework analysis workflow to efficiently search for optimal design configurations while satisfying specific constraints and objectives. The developed thermo-elastic finite element approach with AI applications offers significant benefits to engineers and designers. It provides a robust and accurate framework analysis tool that considers both thermal and mechanical effects. By harnessing the power of AI, it enables improved material characterization, faster simulations, and more effective design optimization. The proposed approach has the potential to revolutionize the field of framework design and analysis by facilitating the development of innovative and efficient structures in various industries.