• Title/Summary/Keyword: 원뿔 절두체

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A PARAMETRIC STUDY OF CONICAL FRUSTUM GEOMETRY FOR IMPROVEMENT OF COOLING PERFORMANCE OF VORTEX TUBE (Vortex Tube 성능 개선을 위한 절두체의 형상 매개변수에 대한 연구)

  • Koo, H.B.;Park, J.Y.;Sohn, D.Y.;Choi, Y.H.
    • Journal of computational fluids engineering
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    • v.20 no.4
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    • pp.7-13
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    • 2015
  • Vortex tube is a thermal static device that separates compressed air into hot and cold streams. In general, the cooling efficiency of vortex tubes is lower than that of traditional air conditioning equipment and vortex tubes are mainly used for industrial spot cooling applications because of their quick responses. In this study, conical frustums are employed in the nozzle chamber to improve the cooling performance. Conical frustums can be used to decrease the ineffective mass fraction that directly passes through the cold exit without energy separation. The shape optimization of conical frustums has been performed using full factorial design. It is found that the height of frustums has the largest main effects on the cooling performance. Computational results show that the cooling performance can be increased by about 10% within the considered range of the design parameters. This is because the ineffective mass fraction toward the cold exit is decreased by about 20%.

Optimization of Process Parameters of Incremental Sheet Forming of Al3004 Sheet Using Genetic Algorithm-BP Neural Network (유전 알고리즘-BP신경망을 이용한 Al3004 판재 점진성형 공정변수에 대한 최적화 연구)

  • Yang, Sen;Kim, Young-Suk
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.1
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    • pp.560-567
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    • 2020
  • Incremental Sheet Forming (ISF) is a unique sheet-forming technique. The process is a die-less sheet metal manufacturing process for rapid prototyping and small batch production. In the forming process, the critical parameters affecting the formability of sheet materials are the tool diameter, step depth, feed rate, spindle speed, etc. This study examined the effects of these parameters on the formability in the forming of the varying wall angle conical frustum model for a pure Al3004 sheet with 1mm in thickness. Using Minitab software based on Back Propagation Neural Network (BPNN) and Genetic Algorithm (GA), a second order mathematical prediction model was established to predict and optimize the wall angle. The results showed that the maximum forming angle was 87.071° and the best combination of these parameters to give the best performance of the experiment is as follows: tool diameter of 6mm, spindle speed of 180rpm, step depth of 0.4mm, and feed rate of 772mm/min.