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Mining, Metallurgy & Exploration

, Volume 36, Issue 6, pp 1101–1114 | Cite as

The Order of Kinetic Models, Rate Constant Distribution, and Maximum Combustible Recovery in Gilsonite Flotation

  • Ataallah BahramiEmail author
  • Fatemeh Kazemi
  • Yousef Ghorbani
  • Jafar Abdolahi Sharif
Article
  • 48 Downloads

Abstract

Kinetic models are the most important tool for predicting and evaluating the performance of flotation circuits. Gilsonite is a natural fossil resource similar to an oil asphalt, high in asphaltenes. Here, in order to determine the kinetic order and flotation rate of a gilsonite sample, flotation experiments were carried out in both rougher and cleaner stages. Experiments were conducted using the combinations of oil–MIBC and gas oil–pine oil, with one test without collector and frother. Five kinetic models were applied to the data obtained from the flotation tests using MATLAB software. Statistical analysis showed that the results of the experiment with oil–MIBC were highly in compliance with all models. Kinetic constants (k) were calculated as 0.1548 (s−1) and 0.0450 (s−1) for rougher and cleaner stages, respectively. Rougher and cleaner tests without collector and frother also matched all models well (R2 > 0.98), with k values of 0.2163 (s−1) and 0.284 (s−1), respectively. The relationship between flotation rate constant, maximum combustible recovery, and particle size showed that the maximum flotation combustible recovery and flotation rate were obtained in the size range of −250 + 106 μm in the rougher and cleaner stages. The combustible recovery and flotation rate were higher in the rougher flotation process than in the cleaner stage.

Keywords

Flotation Kinetic models Gilsonite Bitumen  Asphaltum Iran 

Notes

Compliance with Ethical Standards

Conflict of Interest

On behalf of all authors, the corresponding author (Ataallah Bahrami) states that there is no conflict of interest.

References

  1. 1.
    Sripriya R, Rao PVT, Choudhury BR (2003) Optimization of operating variables of fine coal flotation using a combination of modified flotation parameters and statistical techniques. Int J Miner Process 68(1–4):109–127.  https://doi.org/10.1016/S0301-7516(02)00063-7 CrossRefGoogle Scholar
  2. 2.
    Zhang H, Liu J, Cao Y, Wang Y (2013) Effects of particle size on lignite reverse flotation kinetics in the presence of sodium chloride. Powder Technol 246:658–663.  https://doi.org/10.1016/j.powtec.2013.06.033 CrossRefGoogle Scholar
  3. 3.
    Mao L, Yoon RH (1997) Predicting flotation rates using a rate equation derived from first principles. Int J Miner Process 51(1–4):171–181.  https://doi.org/10.1016/S0301-7516(97)00025-2 CrossRefGoogle Scholar
  4. 4.
    Lynch AJ, Johnson NW, Manlapig EV, Thorne CG (1981) Mineral and coal flotation circuits, their simulation and control. Elsevier Scientific Publishing Company, New YorkGoogle Scholar
  5. 5.
    Arbiter N (1951) Flotation rates and flotation efficiency. Trans AIME 190:791–769Google Scholar
  6. 6.
    Ek C (1992) Flotation kinetics. In: Innovation in flotation technology. Springer, Dordrecht, pp 183–210.  https://doi.org/10.1007/978-94-011-2658-8_8 CrossRefGoogle Scholar
  7. 7.
    Klimpel RR (1980) Selection of chemical reagents for flotation. In: Mular AL, Bhappu RB (eds) Mineral processing plant design. AIME, New York, pp 907–934Google Scholar
  8. 8.
    Imaizumi T, Inoue T (1963) Kinetic considerations of froth flotation. In: 6th international mineral processing congress, Cannes, pp 581–593Google Scholar
  9. 9.
    Klassen VI, Mokrousov VA (1963) An introduction to the theory of flotation. Butterworths, LondonGoogle Scholar
  10. 10.
    Trahar WJ, Warren LJ (1976) The floatability of very fine particles—a review. Int J Miner Process 3:103–131.  https://doi.org/10.1016/0301-7516(76)90029-6 CrossRefGoogle Scholar
  11. 11.
    Drzymala J, Ratajczak T, Kowalczuk P (2017) Kinetic separation curves based on process rate considerations. Physicochemical problems of mineral processing 53(2):983–995 http://hdl.handle.net/11250/2464431 Google Scholar
  12. 12.
    Gharai M, Venugopal R (2016) Modeling of flotation process—an overview of different approaches. Miner Process Extr Metall Rev 37(2):120–133.  https://doi.org/10.1080/08827508.2015.1115991 CrossRefGoogle Scholar
  13. 13.
    Bu X, Xie G, Peng Y, Ge L, Ni C (2017) Kinetics of flotation. Order of process, rate constant distribution and ultimate recovery. Physicochemical Problems of Mineral Processing 53(1):342–365.  https://doi.org/10.5277/ppmp170128 CrossRefGoogle Scholar
  14. 14.
    Guanghua A, Yang X, Li X (2017) Flotation characteristics and flotation kinetics of fine wolframite. Powder Technol 305:377–381.  https://doi.org/10.1016/j.powtec.2016.09.068 CrossRefGoogle Scholar
  15. 15.
    Albijanic B, Subasinghe N, Park CH (2015) Flotation kinetic models for fixed and variable pulp chemical conditions. Miner Eng 78:66–68.  https://doi.org/10.1016/j.mineng.2015.04.010 CrossRefGoogle Scholar
  16. 16.
    Helms JR, Kong X, Salmon E, Hatcher PG, Schmidt-Rohr K, Mao J (2012) Structural characterization of gilsonite bitumen by advance nuclear magnetic resonance spectroscopy and ultrahigh resolution mass spectrometry revealing pyrrolic and aromatic rings substituted with aliphatic chains. J of organic Geochemistry 44:21–36.  https://doi.org/10.1016/j.orggeochem.2011.12.001 CrossRefGoogle Scholar
  17. 17.
    Li K, Vasiliu M, Mcalpine CR, Yang Y, Dixon DA, Voorhees KJ, Batzle M, Liberatore MW, Herring AM (2015) Further insights into the structure and chemistry of the gilsonite asphaltene from a combined theoretical and experimental approach. Fuel.  https://doi.org/10.1016/j.fuel.2015.04.029 CrossRefGoogle Scholar
  18. 18.
    Kazemi F (2017) Site Selection of gilsonite ore Dressing Plant, Based on Industrial Specification of Mine (Kermanshah). Master of Science Thesis in Mining Engineering, Faculty of Engineering- Urmia University, IranGoogle Scholar
  19. 19.
    Tripp BT, White ER (2006) Gilsonite. In: Kogel JE, Trivedi NC, Barker JM, Krukowski ST (eds) Industrial minerals and rocks: commodities, markets, and uses. Society for Mining, Metallurgy, and Exploration, Littleton, pp 481–493Google Scholar
  20. 20.
    Jahanian HR, Shafabakhsh G, Divandari H (2017) Performance evaluation of hot mix asphalt (HMA) containing bitumen modified with gilsonite. Constr Build Mater 131:156–164CrossRefGoogle Scholar
  21. 21.
    Velez JS, Velásquez S, Giraldo D (2016) Mechanical and rheumatic properties of gilsonite/carbon black/natural rubber compounds cured using conventional and efficient vulcanization systems. Polym Test 56:1–9CrossRefGoogle Scholar
  22. 22.
    Ameri M, Mansourian A, Ashani SS, Yadollahi G (2011) Technical study on the Iranian gilsonite as an additive for modification of asphalt binders used in pavement construction. Constr Build Mater 25(3):1379–1387CrossRefGoogle Scholar
  23. 23.
    Kok BV, Yilmaz M, Guler M (2011) Evaluation of high temperature performance of SBS + gilsonite modified binder. Fuel 90(10):3093–3099CrossRefGoogle Scholar
  24. 24.
    Muganda S, Zanin M, Grano SR (2011) Benchmarking flotation performance: single minerals. Int J Miner Process 98(3–4):182–194.  https://doi.org/10.1016/j.minpro.2010.12.001 CrossRefGoogle Scholar
  25. 25.
    Tao D (2005) Role of bubble size in flotation of coarse and fine particles—a review. Sep Sci Technol 39(4):741–760.  https://doi.org/10.1081/SS-120028444 CrossRefGoogle Scholar
  26. 26.
    Vapur H, Bayat O, Uçurum M (2010) Coal flotation optimization using modified flotation parameters and combustible recovery in a Jameson cell. Energy Convers Manag 51:1891–1897.  https://doi.org/10.1016/j.enconman.2010.02.019 CrossRefGoogle Scholar
  27. 27.
    Ni C, Xie G, Jin M, Peng Y, Xia W (2016) The difference in flotation kinetics of various size fractions of bituminous coal between rougher and cleaner flotation processes. Powder Technol 292:210–216.  https://doi.org/10.1016/j.powtec.2016.02.004 CrossRefGoogle Scholar
  28. 28.
    Welsby SDD, Vianna SM, Franzidis JP (2010) Assigning physical significance to floatability components. Int J Miner Process 97(1–4):59–67.  https://doi.org/10.1016/j.minpro.2010.08.002 CrossRefGoogle Scholar
  29. 29.
    Shahbazi B, Rezai B, Javad Koleini SM (2010) Bubble–particle collision and attachment probability on fine particles flotation. Chem Eng Process Process Intensif 49(6):622–627.  https://doi.org/10.1016/j.cep.2010.04.009 CrossRefGoogle Scholar
  30. 30.
    Jameson GJ (2010) Advances in fine and coarse particle flotation. Can Metall Q 49(4):325–330.  https://doi.org/10.1179/cmq.2010.49.4.325 CrossRefGoogle Scholar
  31. 31.
    Schubert H (2008) On the optimization of hydrodynamics in fine particle flotation. Miner Eng 21(12–14):930–936.  https://doi.org/10.1016/j.mineng.2008.02.012 CrossRefGoogle Scholar
  32. 32.
    Xia W, Xie G, Liang C, Yang J (2014) Flotation behavior of different size fractions of fresh and oxidized coals. Powder Technol 267:80–85.  https://doi.org/10.1016/j.powtec.2014.07.017 CrossRefGoogle Scholar

Copyright information

© Society for Mining, Metallurgy & Exploration Inc. 2019

Authors and Affiliations

  • Ataallah Bahrami
    • 1
    Email author
  • Fatemeh Kazemi
    • 2
  • Yousef Ghorbani
    • 3
  • Jafar Abdolahi Sharif
    • 1
  1. 1.Department of Mining EngineeringUrmia UniversityUrmiaIran
  2. 2.University of KashanKashanIran
  3. 3.Mineral Processing and Extractive Metallurgy Department of Civil, Environmental and Natural Resources EngineeringLulea University of TechnologyLuleaSweden

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