A novel three-dimensional profile prediction method integrated with particle acceleration simulation and layer stacking in cold spray additive manufacturing

Abstract

In cold spray additive manufacturing (CSAM), predicting the deposit profile is a critical prerequisite for subsequent path planning. Unlike other additive manufacturing (AM) technologies, which achieve high single-track resolution through precise energy input, CSAM still faces challenges in shape control. While some previous models can predict thin coatings, they are unsuitable for complete CSAM workpieces or cold spray (CS) repairing of irregular damaged zones. Therefore, we proposed a new combined 3D method based on the particle acceleration simulation and the layer stacking principle, taking critical velocity (v_cr) as the regulation of deposition efficiency (DE) into consideration. The predicted profile is deduced by the integral equation containing various process parameters, namely particle distribution, particle height, nozzle traversing speed and the number of stacking layers. The effects of different influencing factors on deposit profile during CSAM were investigated, including nozzle cross-section shape, spray angle, standoff distance, nozzle traversing speed and scanning step. Results show that this new method overcomes the limitations of spatially symmetric particle distribution and adds up the critical velocity criterion (CVC) to ground the simulation ‌in virtue of solid physical principle. It provides real-time profile prediction feedback for nozzle path planning within a short time, offering a visual reference for complex spraying scenarios without requiring pre-experiments.