Journal of South China University of Technology(Natural Science Edition) ›› 2023, Vol. 51 ›› Issue (12): 53-63.doi: 10.12141/j.issn.1000-565X.220832

Special Issue: 2023年机械工程

• Mechanical Engineering • Previous Articles     Next Articles

Structural Optimization and Flow Field Characteristics of Large Format SLM Forming Bin

LIU Guoyong1,2 ZHANG Wenpeng1 ZHANG Tongxin1 ZHU Dongmei1 ZENG Xinxi1   

  1. 1.School of Mechanical Engineering,University of Science and Technology Beijing,Beijing 100083,China
    2.Shunde Innovation School,University of Science and Technology Beijing,Foshan 528399,Guangdong,China
  • Received:2022-12-28 Online:2023-12-25 Published:2023-05-09
  • About author:刘国勇(1969-),男,博士,副教授,主要从事多物理场耦合建模与优化、机械装备力学行为研究。E-mail:gy_liu666@ustb.edu.cn
  • Supported by:
    the Postdoctoral Innovative Talent Support Program(BX20190032)

Abstract:

To study the distribution of soot particles and the efficiency of fume extraction inside the SLM (selective laser melting) forming bin, this research analyzed the flow law of shielding gas and soot particles in the forming bin with Fluent discrete phase model (DPM) based on the established model of the large-format porous wind wall forming bin. Then multi-objective genetic algorithm (MOGA) was used to optimize the structure of the porous wind wall forming bin. The length of air inlet P1, the radius of wind wall hole P2, the length of conical protection plate P3 and the shaft length of wind wall hole P4 were taken as optimization variables, and the average flow velocity of shielding gas in the middle section of the forming bin, the concentration difference of smoke particles at the inlet and outlet of the forming bin and the maximum concentration of smoke particles in the entire forming bin were taken as optimization objectives. The response surfaces and sensitivity analysis results of each optimization variable and optimization target were obtained, and the optimization target before and after optimization was compared. The results show that for the four optimized variables, the order of influence on the flow velocity of the shielding gas in the middle section of the forming bin is P2>P4>P3>P1; the order of influence on the concentration difference of inlet and outlet particles is P2>P4>P1>P3; the order of influence on the maximum particle concentration in the porous air wall forming bin is P2>P1>P3>P4; the pore size of the porous wind wall plays a key role in the flow of dust particles in the forming bin. Through multi-objective genetic algorithm, the optimized length of gas inlet is 358 mm, the radius of wind wall hole is 20 mm, the length of conical protection plate is 589 mm, and the shaft length of wind wall hole is 6 mm. Compared with that before the optimization of the structure of the forming bin, the flow velocity of the shielding gas in the middle section of the forming bin after the optimization increases by 11.3%; the concentration difference between the inlet and outlet particles decreases by 16.8%; the maximum particle concentration in space decreases by 23.9%; the trend of outward diffusion of soot particles decreases, and the flow velocity of the shielding gas passing 30 mm above the forming table increases by 21%, indicating that the shielding gas can carry the soot particles out of the forming bin more efficiently.

Key words: CFD, structural design, soot, selective laser melting, multi-objective optimization

CLC Number: