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While machining materials changes and deformation of grain structure take place. This deformation of the grains affects the thermal properties of the material leading to orthotropic thermo-physical property. Typical materials like Ti-6Al-4 V having high hardness which are extensively used in many critical applications especially medical implants, requires study of such properties for proper fitment, sustainability and longevity. As a large amount of heat is produced during machining hence, in depth idea of the distribution of temperature in the product is highly necessary to design an optimally cooling strategy, to control the thermo-physical property of the material. In this present work, 2D material domain has been modelled to numerically predict the distribution of temperature, aided with Finite Difference scheme using Python. The differential equation governing the heat conduction and the boundary conditions have been are discretized, which are solved using an iterative method. The effect of different orthotropic thermo-physical property on heat conduction for Ti-4Al-4 V alloy have been demonstrated using the temperature distribution plots. The results can be used for deciding both the machining parameters as well as post-machining operations like cooling strategies.

Python assisted numerical analysis of heat conduction for an orthotropic material