Additive Manufacturing - Visualizing Melt Pool Dynamics

Version 1.0.2 (45,8 KB) von Hui Yang
This toolbox includes codes and example to visualize melt pools that are sensed and measured in the Laser powder bed fusion (LPBF) procecess
38 Downloads
Aktualisiert 7. Okt 2024

Lizenz anzeigen

% This toolbox includes codes and the example to visualize melt pools that
% are sensed and measured in the Laser powder bed fusion (LPBF) process.
% LPBF is a key technology of additive manufacturing that enables the fab-
% rication of metal parts with complex geometry through a multi-layer process..
% Melt-pool morphological characteristics are eminent indicators for
% manufacturing process stability and part quality.
% Author: Dr. Hui Yang and Dr. Siqi Zhang
% Affiliation:
% The Pennsylvania State University
% 310 Leohard Building, University Park, PA
% Email: yanghui@gmail.com
% If you find this toolbox useful, please cite the following paper:
% [1] Zhang, S., Yang, H., Yang, Z., & Lu, Y. (2024). Engineering-Guided
% Deep Learning of Melt-Pool Dynamics for Additive Manufacturing Quality
% Monitoring. Journal of Computing and Information Science in Engineering,
% 24(10). DOI: 10.1115/1.4066026
% [2] Zhang, S., Lu, Y., & Yang, H. (2024). Multiscale basis modeling of
% 3D melt-pool morphological variations for manufacturing process monitoring.
% The International Journal of Advanced Manufacturing Technology, 1-12.
% DOI: 10.1007/s00170-024-13377-2

Zitieren als

Hui Yang (2025). Additive Manufacturing - Visualizing Melt Pool Dynamics (https://de.mathworks.com/matlabcentral/fileexchange/173645-additive-manufacturing-visualizing-melt-pool-dynamics), MATLAB Central File Exchange. Abgerufen.

Zhang, Siqi, et al. “Engineering-Guided Deep Learning of Melt-Pool Dynamics for Additive Manufacturing Quality Monitoring.” Journal of Computing and Information Science in Engineering, vol. 24, no. 10, ASME International, Aug. 2024, doi:10.1115/1.4066026.

Mehrere Stile anzeigen

Zhang, Siqi, et al. “Multiscale Basis Modeling of 3D Melt-Pool Morphological Variations for Manufacturing Process Monitoring.” The International Journal of Advanced Manufacturing Technology, Springer Science and Business Media LLC, Mar. 2024, doi:10.1007/s00170-024-13377-2.

Mehrere Stile anzeigen
Kompatibilität der MATLAB-Version
Erstellt mit R2015a
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Version Veröffentlicht Versionshinweise
1.0.2

modified title

1.0.1

adding the youtube video links

1.0.0