# Influence of Micro-Textures on Cutting Insert Heat Dissipation
## 2 System Design and Implementation
### Numeric Study  
The numerical thermal-fluid-solid coupling study is conducted to investigate the proposed device's effectiveness and linearity, by using a pressure-based solver from ANSYS-Fluent(r), solving the momentum, continuity, and energy equations. This involved determining the optimal dimensions of the internal fluid flow channels, maximizing the coolant temperature gradient, between inlet and outlet, and obtaining a uniform distribution of the cutting insert surface temperature, keeping its top surface below 100 \({}^{\circ}\)C to avoid latent heat absorption. The final dimensions of the flow channels and the core geometry were obtained after a few iterations. The average and standard deviations values for mass density and thermal properties of the materials, considered for the numerical simulations, are indicated in Table 1. For the analysis' sake of simplicity, the thermal conductivity of the materials is assumed to be constant and independent of the temperature. The numerical simulation requires the knowledge of real thermal properties to achieve an effective and reliable solution. This involves the selection of the fluid thermal properties, the heat power input, coolant fluid mass flow rate, the initial temperatures, and the definition of the thermal boundary conditions. Given that the water is the basis of the commonly used cutting fluids, about 95%, its thermal properties are assumed for the numerical simulations. The heat power generation of 93.07 MW/m\({}^{3}\) was defined for each resistive electric element to simulate the electric input power of 50 W. A constant fluid mass flow rate of 15.6 g/s was defined to avoid exceeding the specified temperature limit of 100 \({}^{\circ}\)C at the top insert surface. The inlet water temperature was considered constant at 15.2 \({}^{\circ}\)C and the room temperature at 20.3 \({}^{\circ}\)C. Natural convection plays a key role in the temperature distribution throughout the device. The average value convection coefficient of 25 W/m\({}^{2}\).K was equally assumed for all the surfaces and thermal conductance of 11,000 W/m\({}^{2}\).K was considered between all components [41]. The values of natural \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Component** & **Material** & **Mass Density [kg/m\({}^{3}\)]** & **Specific Heat** & **Thermal Conductivity** \\  & & **[J/kg.K]** & **[W/m.K]** \\ \hline Main body & AISI 1010 Steel & 7849.80 \(\pm\) 50.00 & 442.63 \(\pm\) 20.00 & 56.59 \(\pm\) 6.00 \\ Top chamber & Aluminium 6082-t6 & 2699.80 \(\pm\) 30.00 & 899.82 \(\pm\) 18.00 & 171.97 \(\pm\) 3.00 \\ Heat sources & Aluminium 6082-t6 & 2699.80 \(\pm\) 30.00 & 899.82 \(\pm\) 18.00 & 171.97 \(\pm\) 3.00 \\ Cutting insert & WC-Co 90-10 & 14,550.00 \(\pm\) 150.00 & 209.00 \(\pm\) 4.00 & 89.50 \(\pm\) 3.50 \\ Support seat & WC-Co 90-10 & 14,550.00 \(\pm\) 150.00 & 209.00 \(\pm\) 4.00 & 89.50 \(\pm\) 3.50 \\ Main stud & AISI 1015 & 7849.80 \(\pm\) 50.00 & 442.63 \(\pm\) 20.00 & 52.02 \(\pm\) 2.00 \\ Nut & AISI 1015 & 7849.80 \(\pm\) 50.00 & 442.63 \(\pm\) 20.00 & 52.02 \(\pm\) 2.00 \\ Core & PET-G & 1339.10 \(\pm\) 50.00 & 1199.00 \(\pm\) 50.00 & 0.17 \(\pm\) 0.0065 \\ Guide pin & AISI 304 Stainless Steel & 7954.30 \(\pm\) 105.00 & 473.62 \(\pm\) 20.00 & 14.92 \(\pm\) 1.50 \\ Resistive element & AISI 304 Stainless Steel & 7954.30 \(\pm\) 105.00 & 473.62 \(\pm\) 20.00 & 14.92 \(\pm\) 1.50 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Materials mass density and thermal properties. convection coefficient and thermal conductance were later fine-tuned to reproduce the experimental device response. The final values were obtained by applying the heuristic method. After a few iterations, a new convection coefficient of 10 W/m\({}^{2}\).K was considered for the main body (1) and 20 W/m\({}^{2}\).K for the support seat (2), main stud (4), top chamber (5), and nut (14).