DOI QR코드

DOI QR Code

고체분말/액체연료의 과도혼합 농도 분포 측정

Measurements of Transient Mixing Concentrations between Solid Powder and Liquid Fuel

  • 도덕희 (한국해양대학교 기계에너지시스템공학부) ;
  • 염주호 (한국해양대학교 대학원) ;
  • 조경래 (한국해양대학교 기계에너지시스템공학부) ;
  • 민성기 (국방과학연구소 제1기술연구본부 5부) ;
  • 김명호 (국방과학연구소 제1기술연구본부 5부) ;
  • 유경원 (국방과학연구소 제1기술연구본부 5부) ;
  • 유남현 (경남대학교 해양시스템유합기술연구센터)
  • Doh, Deoghee (Div. of Mech. and Energy Systems Eng., Korea Maritime Univ.) ;
  • Yum, Jooho (Graduate School of Korea Maritime Univ.) ;
  • Cho, Gyeongrae (Div. of Mech. and Energy Systems Eng., Korea Maritime Univ.) ;
  • Min, Seongki (Agency for Defense Development, The 1st R&D Institute-5) ;
  • Kim, Myungho (Agency for Defense Development, The 1st R&D Institute-5) ;
  • Ryu, Gyongwon (Agency for Defense Development, The 1st R&D Institute-5) ;
  • Yoo, Namhyun (Ocean System Convergence Technology Research Center(KOSTEC), Kyungnam Univ.)
  • 투고 : 2012.09.28
  • 심사 : 2012.12.31
  • 발행 : 2012.12.31

초록

Concentration fields of solid powder in a liquid fuel were quantitatively measured by a visualization technique. The measurement system consists of a camcoder and three LCD monitors. The solid powder (glass powder) were filled in a head tank which was installed over a main mixing tank ($D{\times}H$, $310{\times}370mm$). The main mixing tank was filled with JetA1 fuel oil. With a sudden opening of the upper tank by pressurized nitrogen gas with 1.9 bar, the solid powder were poured into the JetA1 oil. An impeller type agitator was being rotated in the mixing with 700 rpm for the enhancements of mixing. Uniform visualization for the mixing flow field was made by the light from the three LCD monitors, and the visualized images were captured by the camcoder. The color images captured by the camcoder The color information of the captured images was decoded into three principle colors R, G, and B to get quantitattive relations between the concentrations of the solid powder and the colors. To get better fitting for the strong non-linearity between the concentration and the color, a neural network which has strong fitting performances was used. Analyses on the transient mixing of the solid powders were quantitatively made.

키워드

참고문헌

  1. Y. C. Pak, J. H. Choi and S. H. Oh, "The Effects of Silica-Alumina Type Inorganic Compounds on the Pyrolysis Reaction of EVA to Produce Fuel-Oil", Trans. of the Korean Hydrogen and New Energy Society, 2011, Vol. 22, No. 5, pp. 706-713.
  2. H. H. Hu, "Direct Simulation of Flows of Solid-liquid Mixtures", International Journal of Multiphase Flow, Vol. 22, No. 2, 1996, pp. 335-352. https://doi.org/10.1016/0301-9322(95)00068-2
  3. A. Ochieng, A. E. Lewis, "Nickel Solids Concentration Distribution in a Stirred Tank", Minerals Engineering, Vol. 19, 2006, pp. 180-189. https://doi.org/10.1016/j.mineng.2005.09.028
  4. S. Hosseini, D. Patel, F. Ein-Zozaffari, M. Mehrvar, "Study of Solid-liquid Mixing in Agitated Tanks Through Electrical Resistance Tomography", Chemical Engineering Science, Vol. 65, 2010, pp. 1375-1384.
  5. Y. Hongbin, J. N. Koster, "Radioscopic Visualization of Melting, Alloying and Solidification of Pure Al and Al-u, Journal of Alloys and Compounds", Vol. 352, 2003, pp. 175-189. https://doi.org/10.1016/S0925-8388(02)01123-4
  6. T. Kobayashi, H. Tai, S. Kato, "Measurement Method of Particle Concentration and Acoustic Properties in Suspension using a Focused Ultrasonic Impulse Radiated from a Planoconcave Transducer", Ultrasonics, Vol. 44, 2006, pp. e491-e496. https://doi.org/10.1016/j.ultras.2006.05.028
  7. R. Angst, M. Kraume, "Experimental Investigations of Stirred Solid/Liquid Systems in Three Different Scales: Particle Distribution and Power Consumption", Chemical Engineering Science, 2006, Vol. 61, pp. 2864-2870. https://doi.org/10.1016/j.ces.2005.11.046
  8. E. H. Jeong and K. C. Kim, "A Study on the Mixing Characteristics in a Rushton Turbine Reactor by a Laser Induced Fluorescence Method", KSME(B), Vol. 26, No. 8, 2002, pp. 1145-1152. https://doi.org/10.3795/KSME-B.2002.26.8.1145
  9. D. E. Rumelhart, G. E. Hinton and R. J. Williams, "Learning Representations by Back-Propagating Errors", Nature, 1986, pp. 323-333.
  10. D.H. Doh, T. Kobayashi, and T. Saga, "Particle Imaging Thermometry and Velocimetry using Liquid Crystal; A Color-to-Temperature Calibration Method using a Neural Network, SEISAN-KENKYU, Institude of Industrial Science and Tech. Univ. of Tokyo, 1995, Vol. 47, No. 9, pp. 20-23.
  11. J. H. Yum, D. H. Doh, G. R. Cho, S. K. Min, M. H. Kim, G. W. Ryu, "Measurements on Transient Mixing Concentrations of Two Fuel Oils using a Quantitative Flow Visualization Technique", Trans. of Korean Hydrogen and New Energy Society, Vol. 23, No. 4, 2012, pp. 354-372. https://doi.org/10.7316/KHNES.2012.23.4.364