Numerical Analysis of Heat Transfer in Stainless Steel Blade with Short Fin Configurations Using C Programming

Abstract

This research focuses on the computational analysis of heat flow at the root of a stainless steel blade equipped with short fins, with the assumption of negligible heat loss. The study aims to employ Artificial Intelligence (AI) techniques in C programming to model and simulate the heat transfer phenomenon. By utilizing C's numerical computing libraries and AI algorithms, such as machine learning and optimization techniques, the objective is to accurately predict the heat distribution at the blade root under various operating conditions. This research contributes to the advancement of computational methods for heat transfer analysis in engineering applications, particularly in the optimization of blade designs for enhanced thermal performance. This study delves into the intricate dynamics of thermodynamics fins and heat transfer phenomena, with a focus on utilizing C programming for analysis and exploration. Fins, as integral components in engineering systems, play a pivotal role in enhancing heat dissipation efficiency by increasing surface area. The research investigates the fundamental principles governing heat transfer mechanisms, encompassing conduction, convection, and radiation, within the context of fin structures. Mathematical models, including the one-dimensional heat conduction equation, serve as foundational frameworks for understanding heat transfer in fins. Leveraging C's robust numerical computing libraries, such as NumPy and SciPy, enables the implementation of Finite Difference Methods (FDM) for solving heat conduction equations numerically. Additionally, the study explores the application of Computational Fluid Dynamics (CFD) simulations to provide comprehensive insights into fluid flow and heat transfer interactions around fins. Furthermore, optimization techniques facilitated by C's optimization libraries are employed to optimize fin designs for maximizing heat transfer efficiency. Through C programming, this research endeavours to advance our understanding of thermodynamics fins and heat transfer processes, offering practical insights for engineering applications and system design optimization.