MOLECULAR DYNAMICS SIMULATION STUDY OF LIQUID-ASSISTED LASER BEAM MACHINING PROCESS

S James and VA Menon and M Parmar, PROCEEDINGS OF THE ASME 13TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE, 2018, VOL 4, V004T03A032 (2018).

Liquid Assisted Laser Beam Micromachining (LA-LBMM) process is advanced machining process which can overcome the limitations of traditional laser beam machining processes. LA-LBMM process uses a layer of a liquid medium such as water above the substrate surface during the application of laser beam. During LA-LBMM process, the liquid medium is used both in static mode in which the water is still or in a dynamic mode in which the water flows over the substrate with a specific velocity. Experimental studies on LA-LBMM process have shown that the cavity machined has a better surface finish due to a reduction. in the amount of re-deposition and recast material. While LA-LBMM process promises significant improvement in laser-based micromachining applications, the process mechanisms involved in LA-LBMM process is not well understood. In the past, finite element simulation studies on LA-LBMM process is studied which could only find the temperature distribution on the substrate during machining. A clear understanding of the role of water medium during the LA-LBMM process is lacking. This research involves the use of Molecular Dynamics (MD) simulation technique to investigate the complex and dynamic mechanisms involved in the LA-LBMM process both in static and dynamic mode. The results of the MD simulation are compared with those of Laser Beam Micromachining (LBMM). The study revealed that machining during LA-LBMM process showed higher removal compared with LBMM process. The LA-LBMM process in dynamic mode showed lesser material removal compared with static mode as the flowing water carrying the heat away from the machining zone. Formation of nanoscale bubbles along with shockwave propagation is observed during the simulation of LA-LBMM process. The findings of this study provide further insights to strengthen the knowledge base of LA-LBMM process.

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