Analytical Heat Transfer Model to Predict Friction Surfacing Process Parameters

The goal of this research is to develops a low-order heat transfer model to predict deposition temperature during friction surfacing, aiding in the selection of process parameters for uniform deposits with strong bonds to the substrate. A steady-state, zero-dimensional analytical model uses a thermal resistance network to predict the interface temperature. Sensitivity analysis shows that heat power input, axial (forge) force, and the friction coefficient have the largest influence on temperature predictions. Of the machine parameters one can set, spindle speed has a similar influence on predicted temperature as axial (forge) force. Based on the sensitivity analysis of the measured temperatures, it is observed that an increase in spindle speed from the nominal value leads to a more significant temperature rise (e.g., 155 K for a 100% increase in spindle speed). In contrast, an increase in traverse feed rate from the nominal value results in a temperature drop (e.g., 26 K for a 50% increase in feed rate), highlighting the profound influence of spindle speed on the interface temperature. Simulation of multi-layer deposits showed that in order to maintain a constant interface temperature, the greatest change in process parameters (e.g., spindle speed) must be implemented between the first and second layers. Future work will validate the model with multi-layer tests to optimize deposition temperature and morphology.