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پایش برخط دینامیک حوضچه مذاب در روکشکاری لیزری با استفاده از شبیهسازی عددی و مشخصهیابی طیفی | ||
| نشریه مهندسی مکانیک امیرکبیر | ||
| دوره 56، شماره 9، 1403، صفحه 1275-1302 اصل مقاله (2.9 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22060/mej.2025.23511.7774 | ||
| نویسندگان | ||
| محمدجواد ترکمنی* 1؛ ابراهیم غلامی2؛ سعید باطبی2 | ||
| 1مرکز ملی علوم و فنون لیزر ایران، تهران، ایران | ||
| 2گروه فیزیک، دانشکده علوم، دانشگاه گیلان، رشت، ایران | ||
| چکیده | ||
| پایش برخط و کنترل دینامیک حوضچه مذاب، نقش کلیدی در تعیین کیفیت لایههای روکش شده در فرایندهای ساخت افزایشی لیزری ایفا میکند. این پژوهش رویکردی ترکیبی از شبیهسازی عددی با مدل گلداک و پایش لحظهای با طیفسنجی فروشکست القایی لیزری را در فرایند روکشکاری لیزری آلیاژ اینکونل 718 بر روی زیرلایه استیل 304 ارائه میدهد. مدلسازی دقیق دینامیک حرارتی حوضچه مذاب در 64 نمونه روکش انجام شده و ابعاد سطح مقطع روکش و درصد آمیختگی با اندازهگیریهای تجربی اعتبارسنجی شده است. جهت کاهش خطای مدل، از مشخصه یابی طیفی برای پایش لحظهای تغییرات حوضچه مذاب استفاده شد که اطلاعات دقیقی از دمای موضعی حوضچه مذاب و همچنین ترکیب عناصر آن را ارائه داد. دمای پلاسمای استخراجشده از خطوط کروم در پنجره طیفی 400 تا 500 نانومتر، بطور موثر تغییرات دمای حوضچه مذاب را بر اساس پارامترهای ورودی ردیابی کرده، درحالیکه نسبت شدت نیکل (طول موج 361/93 نانومتر) به آهن (طول موج 382/94 نانومتر) آمیختگی لایه روکش را کمیسازی نمود. این رویکرد، امکان کالیبراسیون پویای پارامترهای ورودی فرایند را فراهم کرده و کیفیت یکنواخت لایه روکش را بر اساس کنترل لحظهای تغییرات دمای حوضچه مذاب و درجه آمیختگی تضمین میکند. | ||
| کلیدواژهها | ||
| پایش برخط؛ ساخت افزایشی لیزری؛ روکشکاری لیزری؛ دینامیک حوضچه مذاب؛ طیفسنجی | ||
| عنوان مقاله [English] | ||
| In-Situ Monitoring of Melt Pool Dynamics in Laser Cladding using Numerical Simulation and Spectral Diagnostics | ||
| نویسندگان [English] | ||
| Mohammad Javad Torkamany1؛ Ebrahim Gholami2؛ Saeed Batebi2 | ||
| 1Iranian National Center for Laser Science and Technology | ||
| 2Department of Physics, University of Guilan | ||
| چکیده [English] | ||
| Online Monitoring and Control of melt pool dynamics play a crucial role in determining the quality of clad layers in laser additive manufacturing processes. This study presents a hybrid approach that combines numerical simulation using the Goldak model with real-time monitoring via Laser-Induced Breakdown Spectroscopy (LIBS) in the laser cladding process of Inconel 718 alloy on 304 stainless steel substrate. The precise modeling of the thermal dynamics of the melt pool was performed on 64 cladding samples, and the cross-sectional dimensions and dilution percentage were validated against experimental measurements. To minimize model error, spectral characterization was employed for real-time monitoring of melt pool variations, providing highly accurate data on local melt pool temperature and elemental composition. The plasma temperature extracted from chromium emission lines in the spectral window of 400 to 500 nm effectively tracked the melt pool temperature variations based on input parameters, while the intensity ratio of nickel (wavelength 361.93 nm) to iron (wavelength 382.94 nm) quantified the dilution of the clad layer. This approach enables dynamic calibration of process input parameters, ensuring uniform clad quality through real-time control of the melt pool. | ||
| کلیدواژهها [English] | ||
| Online Monitoring, Laser Additive Manufacturing, Laser Cladding, Melt Pool Dynamics, Laser-Induced Breakdown Spectroscopy | ||
| مراجع | ||
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[1] C. Kusuma, The effect of laser power and scan speed on melt pool characteristics of pure titanium and Ti-6Al-4V alloy for selective laser melting, (2016). [2] S. Liao, S. Webster, D. Huang, R. Council, K. Ehmann, J. Cao, Simulation-guided variable laser power design for melt pool depth control in directed energy deposition, Additive Manufacturing, 56 (2022) 102912. [3] J. Trejos-Taborda, L. Reyes-Osorio, C. Garza, P. del Carmen Zambrano-Robledo, O. Lopez-Botello, Finite element modeling of melt pool dynamics in laser powder bed fusion of 316L stainless steel, The International Journal of Advanced Manufacturing Technology, 120(5) (2022) 3947-3961. [4] Y. Xu, D. Zhang, J. Deng, X. Wu, L. Li, Y. Xie, R. Poprawe, J.H. Schleifenbaum, S. Ziegler, Numerical simulation in the melt pool evolution of laser powder bed fusion process for Ti6Al4V, Materials, 15(21) (2022) 7585. [5] X. Kaikai, G. Yadong, Z. Qiang, Numerical simulation of dynamic analysis of molten pool in the process of direct energy deposition, The International Journal of Advanced Manufacturing Technology, 124(7) (2023) 2451-2461. [6] J. Goldak, A. Chakravarti, M. Bibby, A new finite element model for welding heat sources, Metallurgical transactions B, 15 (1984) 299-305. [7] T. Kik, Computational techniques in numerical simulations of arc and laser welding processes, Materials, 13(3) (2020) 608. [8] P. Li, Y. Fan, C. Zhang, Z. Zhu, W. Tian, A. Liu, Research on heat source model and weld profile for fiber laser welding of A304 stainless steel thin sheet, Advances in Materials Science and Engineering, 2018(1) (2018) 5895027. [9] Y. Zhang, S. Li, G. Chen, J. Mazumder, Experimental observation and simulation of keyhole dynamics during laser drilling, Optics & Laser Technology, 48 (2013) 405-414. [10] E. Mirkoohi, D.E. Seivers, H. Garmestani, S.Y. Liang, Heat source modeling in selective laser melting, Materials, 12(13) (2019) 2052. [11] A. Kiran, Y. Li, J. Hodek, M. Brázda, M. Urbánek, J. Džugan, Heat source modeling and residual stress analysis for metal directed energy deposition additive manufacturing, Materials, 15(7) (2022) 2545. [12] M.H. Farshidianfar, A. Khajepour, A. Gerlich, Real-time control of microstructure in laser additive manufacturing, The International Journal of Advanced Manufacturing Technology, 82 (2016) 1173-1186. [13] W.-W. Liu, Z.-J. Tang, X.-Y. Liu, H.-J. Wang, H.-C. Zhang, A review on in-situ monitoring and adaptive control technology for laser cladding remanufacturing, Procedia Cirp, 61 (2017) 235-240. [14] U. Fantz, Basics of plasma spectroscopy, Plasma sources science and technology, 15(4) (2006) S137. [15] D.W. Hahn, N. Omenetto, Laser-induced breakdown spectroscopy (LIBS), part II: review of instrumental and methodological approaches to material analysis and applications to different fields, Applied spectroscopy, 66(4) (2012) 347-419. [16] Y. Zhang, G.S. Hong, D. Ye, K. Zhu, J.Y. Fuh, Extraction and evaluation of melt pool, plume and spatter information for powder-bed fusion AM process monitoring, Materials & Design, 156 (2018) 458-469. [17] M. Schmidt, P. Huke, C. Gerhard, K. Partes, In-Line Observation of Laser Cladding Processes via Atomic Emission Spectroscopy, Materials, 14(16) (2021) 4401. [18] J.J. Valdiande, J. Mirapeix, J. Nin, E. Font, C. Seijas, J.M. Lopez-Higuera, Laser metal deposition on-line monitoring via plasma emission spectroscopy and spectral correlation techniques, IEEE Journal of Selected Topics in Quantum Electronics, 27(6) (2021) 1-8. [19] V. Lednev, P. Sdvizhenskii, A.Y. Stavertiy, M.Y. Grishin, R. Tretyakov, R. Asyutin, S. Pershin, Online and in situ laser-induced breakdown spectroscopy for laser welding monitoring, Spectrochimica Acta Part B: Atomic Spectroscopy, 175 (2021) 106032. [20] V.N. Lednev, P.A. Sdvizhenskii, R.D. Asyutin, R.S. Tretyakov, M.Y. Grishin, A.Y. Stavertiy, S.M. Pershin, In situ multi-elemental analysis by laser induced breakdown spectroscopy in additive manufacturing, Additive Manufacturing, 25 (2019) 64-70. [21] R. Wang, D. Garcia, R.R. Kamath, C. Dou, X. Ma, B. Shen, H. Choo, K. Fezzaa, H.Z. Yu, Z. Kong, In situ melt pool measurements for laser powder bed fusion using multi sensing and correlation analysis, Scientific reports, 12(1) (2022) 13716. [22] T. Moges, Z. Yang, K. Jones, S. Feng, P. Witherell, Y. Lu, Hybrid modeling approach for melt-pool prediction in laser powder bed fusion additive manufacturing, Journal of Computing and Information Science in Engineering, 21(5) (2021) 050902. [23] S. Mondal, D. Gwynn, A. Ray, A. Basak, Investigation of melt pool geometry control in additive manufacturing using hybrid modeling, Metals, 10(5) (2020) 683. [24] P.K. Nalajam, R. Varadarajan, A hybrid deep learning model for layer-wise melt pool temperature forecasting in wire-arc additive manufacturing process, IEEE Access, 9 (2021) 100652-100664. [25] G. Fuchs, High temperature alloys, Kirk‐Othmer Encyclopedia of Chemical Technology, (2000). [26] J. Rafiei, A.R. Ghasemi, Development of thermo-mechanical simulation of WC/Inconel 625 metal matrix composites laser cladding and optimization of process parameters, International Journal of Thermal Sciences, 198 (2024) 108883. [27] M.I. Al Hamahmy, I. Deiab, Review and analysis of heat source models for additive manufacturing, The International Journal of Advanced Manufacturing Technology, 106 (2020) 1223-1238. [28] N. Nguyen, Y. Mai, S. Simpson, A. Ohta, Analytical Approximate Solution for Double Ellipsoidal Heat Source in Finite Thick Plate, Welding journal, 83(3) (2004) 82. [29] A. Lundbäck, H. Alberg, P. Henrikson, Simulation and validation of TIG-welding and post weld heat treatment of an Inconel 718 plate, in: International Seminar on Numerical Analysis of Weldability: 29/09/2003-01/10/2003, Techn. Univ. TYG, 2005, pp. 683-696. [30] J. James, J. Spittle, S. Brown, R. Evans, A review of measurement techniques for the thermal expansion coefficient of metals and alloys at elevated temperatures, Measurement science and technology, 12(3) (2001) R1. [31] A.H. Committee, Properties and selection: nonferrous alloys and special-purpose materials, in, ASM international, 1990. [32] D. Raj, S.R. Maity, B. Das, Optimization of process parameters of laser cladding on AISI 410 using MEREC integrated MABAC method, Arabian Journal for Science and Engineering, 49(8) (2024) 10725-10739. [33] V.N. Lednev, P.A. Sdvizhenskii, R.D. Asyutin, R.S. Tretyakov, M.Y. Grishin, A.Y. Stavertiy, A.N. Fedorov, S.M. Pershin, In situ elemental analysis and failures detection during additive manufacturing process utilizing laser induced breakdown spectroscopy, Optics Express, 27(4) (2019) 4612-4628. [34] G. Cristoforetti, A. De Giacomo, M. Dell'Aglio, S. Legnaioli, E. Tognoni, V. Palleschi, N. Omenetto, Local thermodynamic equilibrium in laser-induced breakdown spectroscopy: beyond the McWhirter criterion, Spectrochimica Acta Part B: Atomic Spectroscopy, 65(1) (2010) 86-95. [35] F. Anabitarte, A. Cobo, J.M. Lopez-Higuera, Laser‐induced breakdown spectroscopy: fundamentals, applications, and challenges, International Scholarly Research Notices, 2012(1) (2012) 285240. [36] G. Dalton, R.A. Dragoset, J.R. Fuhr, D.E. Kelleher, S.A. Kotochigova, W.C. Martin, P.J. Mohr, A. Musgrove, K. Olsen Podobedova, NIST atomic spectra database, NIST SPECIAL PUBLICATION SP, (1998) 12-15. | ||
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