Estimating the Parameters of Laser Processing of Diamonds Using the Finite Element Method and Artificial Neural Networks
https://doi.org/10.35596/1729-7648-2023-21-4-40-45
Abstract
This paper provides the simulation of laser processing of diamonds by using a combination of artificial neural networks and the finite element method. The training data array and the data array for testing neural networks were generated in ANSYS. The calculations were performed for 600 types of input parameters, 60 of which were used to test artificial neural networks. The influence of the parameters of neural network models on the accuracy of determining temperatures in the laser processing area were studied. The parameters of neural networks were established that provide acceptable results in predicting temperatures generated by laser radiation in diamonds. The results obtained can be used to determine the technological parameters of the laser processing of diamonds.
About the Authors
V. A. Emelyanov
Joint-Stock Company “INTEGRAL” – Manager Holding Company “INTEGRAL”
Belarus
Belarus
Victor A. Emelyanov - Dr. of Sci. (Tech.), Professor, Corr. Member of the National Academy of Sciences of Belarus.
Minsk
E. B. Shershnev
Francisk Skorina Gomel State University
Belarus
Belarus
Evgeny B. Shershnev - Cand. of Sci., Associate Professor, Head of the Department of General Physics.
246019, Gomel, Sovietskaya St., 104
Yu. V. Nikitjuk
Francisk Skorina Gomel State University
Belarus
Belarus
Yuri V. Nikitjuk - Cand. of Sci., Associate Professor, Vice Rector for Academic Affairs.
246019, Gomel, Sovietskaya St., 104
S. I. Sokolov
Francisk Skorina Gomel State University
Belarus
Belarus
Sokolov Sergey Ivanovich - Senior Lecturer at the Department of General Physics.
246019, Gomel, Sovietskaya St., 104. Tel.: +375 232 50-38-17
I. Y. Aushev
University of Civil Protection of the Ministry for Emergency Situations of the Republic of Belarus
Belarus
Belarus
Igor Y. Aushev - Cand. of Sci., Associate Professor, Professor at the Department of Industrial Safety.
Minsk
References
1. Mityagin A. Y., Altukhov A. A., Mityagina A. B. (2009) Technology and Equipment for Processing Diamond Materials of Modern Technology. Technology and Design in Electronic Equipment. (1), 53–58 (in Russian).
2. Shkadov A. I., Bocharov A. M. (ed.) (1997) Physical Foundations of Laser Processing of Diamonds. Physical Bases of Laser Diamond Processing. 3, 288 (in Russian).
3. Retukhin G. E., Koshcheev A. G., Fain I. V., Shershnev E. B. (2001) Dimensional Processing of Gem Diamonds by Q-Switched YAG: ND Laser Radiation. Proceedings of the National Academy of Sciences of Belarus. Physical-Technical Series. (1), 73–77 (in Russian).
4. Bessmeltsev V. P., Bulushev E. D. (2014) Optimization of Laser Microprocessing Modes. Avtometriya. 50 (6), 3–21 (in Russian).
5. Parandoush P., Hossain A. (2014) A Review of Modeling and Simulation of Laser Beam Machining. International Journal of Machine Tools and Manufacture. (85), 135–145.
6. Shalupaev S. V., Shershnev E. B., Nikitjuk Y. V., Sviridova V. V. (2001) Dependence of the Diamond Laser Processing Efficiency on Crystallographic Directions. SPIE. 4358, 329–333.
7. Shershnev E. B., Nikityuk Y. V., Shershnev A. E. (2011) Simulation of Laser Processing of Diamond Crystals. Proceedings of Francisk Skorina Gomel State University. (6), 164–168 (in Russian).
8. Shershnev E. B., Nikityuk Y. V., Shershnev A. E., Sokolov S. I. (2015) Features of the Formation of Thermoelastic Fields During Laser Processing of Diamond Crystals. Problems of Physics, Mathematics and Technics. (1), 38–40 (in Russian).
9. Emelyanov V. A., Shershnev E. B., Nikitjuk Y. V., Sokolov S. I., Aushev I. Y. (2022) Optimization of Laser Processing of Diamonds. Problems of Physics, Mathematics and Technics. (4), 30–36.
10. Bakhtiyari A. N., Wang Z., Wang L., Zheng H. (2021) A Review on Applications of Artificial Intelligence in Modeling and Optimization of Laser Beam Machining. Optics & Laser Technology. 135, 1–18.
11. Yousef B. F., Knopf G. K., Bordatchev E. V., Nikumb S. K. (2003) Neural Network Modeling and Analysis of the Material Removal Process During Laser Machining. International Journal of Advanced Manufacturing Technology. 22 (1–2), 41–53.
12. Ismail M., Okamoto Y., Okado A. (2013) Neural Network Modeling for Prediction of Weld Bead Geometry in Laser Microwelding. Advances in Optical Technologies. 7.
13. Kadri M. B., Nisar S., Khan S. Z., Khan W. A. (2015) Comparison of ANN and Finite Element Model for the Prediction of Thermal Stresses in Diode Laser Cutting of Float Glass. Optik – Int. J. Light Electron Optics. 126 (19), 1959–1964.
14. Kant R., Joshi S. N., Dixit U. S. (2015) An Integrated FEM-ANN Model for Laser Bending Process with Inverse Estimation of Absorptivity. Mech Adv Mater Mod Process. (1), 6.
15. Nikitjuk Y., Bayevich G., Myshkovets V., Maximenko A., Aushev I. (2022). Characterization of Laser Welding of Steel 30XГCH2A by Combining Artificial Neural Networks and Finite Element Method. Research and Education: Traditions and Innovations. INTER-ACADEMIA 2021. Lecture Notes in Networks and Systems. 422. Springer, Singapore. https://doi.org/10.1007/978-981-19-0379-3_28.
16. Nikityuk Y. V., Serdyukov A. N., Prokhorenko V. A., Aushev I. Y. (2021) Application of Artificial Neural Networks and the Finite Element Method to Determine the Processing Parameters of Quartz Sol-Gel Glasses with Elliptical Laser Beams. Problems of Physics, Mathematics and Technics. (3), 30–36 (in Russian).
17. Nikitjuk Y. V., Serdyukov A. N., Aushev I. Y. (2022) Determination of the Parameters of Two-Beam Laser Splitting of Silicate Glasses Using Regression and Neural Network Models. Journal of the Belarusian State University. Physics. 5–43.
18. Nikityuk Y. V. et al. (2022) Application of the Finite Element Method and Artificial Neural Networks to Determine the Parameters of Laser Processing of Steel 12Х18Н9Т. Bulletin. Sukhoi State Technical University of Gomel. (1), 48–55 (in Russian).
19. Bokii G. B., Bezrukov G. N., Klyuev Y. A. et аl. (1986) Natural and Synthetic Diamonds. Moscow, Nauka Publ. 221 (in Russian).
20. Novikov N. V. et al. (1987) Physical Properties of Diamond. Kiev, Navukova Dumka Publ. 201 (in Russian).
21. Golovko V. A., Krasnoproshin V. V. (2017) Neural Network Technologies for Data Processing: Teaching Manual. Minsk, BSU Publ. 263 (in Russian).
22. François Chollet (2018) Deep Learning with Python. St. Petersburg, Peter Publ. 400.
Review
For citations:
Emelyanov V.A., Shershnev E.B., Nikitjuk Yu.V., Sokolov S.I., Aushev I.Y. Estimating the Parameters of Laser Processing of Diamonds Using the Finite Element Method and Artificial Neural Networks. Doklady BGUIR. 2023;21(4):40-45. https://doi.org/10.35596/1729-7648-2023-21-4-40-45
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