Computational Modelling of Heat Transfer in Advanced Engineering Systems

Abstract

Computational Heat Transfer (CHT) is an essential tool for analyzing and optimizing thermal performance in advanced engineering systems such as aerospace vehicles, power plants, electronic devices, automotive systems, manufacturing processes, and renewable energy technologies. By integrating mathematical models, numerical methods, and computer simulations, CHT enables the study of conduction, convection, and radiation in complex systems where analytical solutions are difficult to obtain. Techniques such as Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA), Finite Volume Methods (FVM), and Finite Difference Methods (FDM) provide accurate thermal predictions while reducing the need for costly experiments. These methods are widely used to investigate multi-physics phenomena, including fluid flow, turbulence, phase change, combustion, and thermal stresses. Numerical simulations help improve energy efficiency, identify thermal hotspots, and support virtual prototyping. This study presents a computational framework for heat transfer modeling that includes governing equations, discretization methods, solution procedures, and validation techniques. Comparative analysis shows that advanced numerical algorithms improve prediction accuracy and computational efficiency. The results highlight the importance of computational modeling for thermal design optimization and energy management. Furthermore, emerging technologies such as Artificial Intelligence (AI), Machine Learning (ML), and High-Performance Computing (HPC) are expected to enhance the accuracy and scalability of future heat transfer simulations.