A Physics-Guided Parameter Estimation Framework for Cold Spray Additive Manufacturing Simulation

Coatings, Journal Year: 2025, Volume and Issue: 15(4), P. 364 - 364

Published: March 21, 2025

This work presents a physics-guided parameter estimation framework for cold spray additive manufacturing (CSAM), focusing on simulating and validating deposit profiles across diverse process conditions. The proposed model employs two-zone flow representation: quasi-constant velocity near the nozzle exit followed by an exponentially decaying free jet to capture particle acceleration impact dynamics. comprehensive approach numerically integrating drag-dominated trajectories predict formation with high accuracy. physics-based incorporates both operational geometric parameters ensure robust prediction capabilities. Operational include angle, standoff distance, traverse speed, powder feed rate, while factors encompass design characteristics such as diameter divergence angle. Validation is performed using 36 experimentally measured of commercially pure titanium powder. simulator shows excellent agreement experimental data, achieving global root mean square error (RMSE) 0.048 mm coefficient determination R2=0.991, improving absolute more than 40% relative neural network-based approach. Sensitivity analyses reveal that geometry, critical strongly modulate amplitude shape deposit. Notably, decreasing or angle significantly increases local deposition rates, increasing distance dampens velocities, thereby reducing height. Although partial differential equation (PDE)-based entails moderate increase in computational time—about 50 s per run, roughly 2.5 times longer simpler empirical models—this remains practical most optimization tasks. Beyond its accuracy, PDE-based simulation framework’s principal advantage lies minimal reliance sampling data. It can readily be adapted new materials untested parameters, making it powerful predictive tool design. study underscores simulator’s potential guiding selection, reliability offering deeper physical insights into formation.

Language: Английский

The influence of process parameters on flow-field characteristics and coating properties in nanocomposite spray deposition

Journal of Manufacturing Processes, Journal Year: 2025, Volume and Issue: 141, P. 1716 - 1728

Published: March 28, 2025

Language: Английский