Skip to main content
SpringerLink
Log in

Modeling and Optimization of the Oil Agglomeration Parameters of Low-Calorific Value Lignite by Box–Behnken Design (BBD) Method

  • Original Article
  • Published:
Transactions of the Indian Institute of Metals Aims and scope Submit manuscript

Abstract

In this study, optimization of oil agglomeration parameters of Beyşehir-Bayavşar lignite using Box–Behnken design (BBD) was investigated. BBD model predicted responses, the coefficient of determination R2 for the percentage of ash% and combustible recovery% (CR) of the agglomerates was obtained as 0.97 and 0.90, respectively. These results showed a good correlation between the calculated and observed values. The estimated the percentage of ash content and CR% values were determined as 15.81% and 73.73%, respectively. The best results were obtained in test 22, the zeta potential value was − 11.61 mV, the contact angle was 107°, and the calorific value was 4702 kcal/kg at pH 3.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  1. Mehrotra V P, Sastry K V S, and Morey B W, Int J Miner Process 11 (1983) 175. https://doi.org/10.1016/0301-7516(83)90025-X

    Article  CAS  Google Scholar 

  2. Sahinoglu E, and Uslu T, Fuel Process Technol 128 (2014) 211. https://doi.org/10.1016/j.fuproc.2014.07.015

    Article  CAS  Google Scholar 

  3. Kumar S, Chary G H V C, and Dastidar M, Fuel 141 (2015) 9. https://doi.org/10.1016/j.fuel.2014.09.119

    Article  CAS  Google Scholar 

  4. Cebeci Y, and Sonmez I, Fuel 85 (2006) 289. https://doi.org/10.1016/j.fuel.2005.07.017

    Article  CAS  Google Scholar 

  5. Rao T C, Vanangamudi M, and Rao K H, Int J Miner Process 9 (1982) 235. https://doi.org/10.1016/0301-7516(82)90030-8

    Article  CAS  Google Scholar 

  6. Bensley C N, Swanson A R, and Nicol S K, Int J Miner Process 4 (1977) 173. https://doi.org/10.1016/0301-7516(77)90024-2

    Article  CAS  Google Scholar 

  7. Chary G H V C, and Dastidar M, Fuel 98 (2012) 259. https://doi.org/10.1016/j.fuel.2012.03.027

    Article  CAS  Google Scholar 

  8. Aslan N, Fuel 109 (2013) 373. https://doi.org/10.1016/j.fuel.2013.02.069

    Article  CAS  Google Scholar 

  9. Capes C E, AIME 2 (1980) 1442.

    CAS  Google Scholar 

  10. Keller D V, and Burry W, Colloids Surf 22 (1987) 37. https://doi.org/10.1016/0166-6622(87)80004-5

    Article  CAS  Google Scholar 

  11. Capes C E, and Jonasson K A, Surfactant Sci Ser 32 (1988) 1.

    Google Scholar 

  12. Gurses A, Doymus K, and Bayrakceken S, Fuel 75 (1996) 1175. https://doi.org/10.1016/0016-2361(96)00077-4

    Article  CAS  Google Scholar 

  13. Sahinoglu E, and Uslu T, Energy Convers Manag 49 (2008) 3684. https://doi.org/10.1016/j.enconman.2008.06.026

    Article  CAS  Google Scholar 

  14. Skarvelakis C, Hazi M, and Antonini G, Sep Sci Technol 30 (1995) 2519. https://doi.org/10.1080/01496399508021399

    Article  CAS  Google Scholar 

  15. Yadav A M, Nikkam S, and Gajbhiye P, Energy Sour Part A 38 (2016) 3612. https://doi.org/10.1080/15567036.2016.1196271

    Article  CAS  Google Scholar 

  16. Carbini P, Ciccu R, Ghiani M, and Satta F, Coal Prep 11 (1992) 11. https://doi.org/10.1080/07349349208905204

    Article  CAS  Google Scholar 

  17. Garcia A B, Vega J M G, and Martinez-Tarazona M R, Fuel 74 (1995) 1692. https://doi.org/10.1016/0016-2361(95)00149-Y

    Article  CAS  Google Scholar 

  18. Valdes A F, and Garcia A B, Fuel 85 (2006) 607. https://doi.org/10.1016/j.fuel.2005.08.011

    Article  CAS  Google Scholar 

  19. Unal I, and Aktas Z, Fuel Process Technol 69 (2001) 141. https://doi.org/10.1016/S0378-3820(00)00137-5

    Article  CAS  Google Scholar 

  20. Duzyol S, Powder Technol 274 (2015) 1. https://doi.org/10.1016/j.powtec.2015.01.011

    Article  CAS  Google Scholar 

  21. Chary G H V C, and Dastidar M, Fuel 106 (2013) 285. https://doi.org/10.1016/j.fuel.2012.12.002

    Article  CAS  Google Scholar 

  22. Labuschagne B C J, Coal Prep 3 (1986) 1. https://doi.org/10.1080/07349348608905270

    Article  CAS  Google Scholar 

  23. Guy D W, Crawford R J, and Mainwaring D E, Fuel 71 (1992) 935. https://doi.org/10.1016/0016-2361(92)90245-J

    Article  CAS  Google Scholar 

  24. Ozkan A, Aydogan S, and Yekeler M, Int J Miner Process 76 (2005) 83. https://doi.org/10.1016/j.minpro.2004.12.003

    Article  CAS  Google Scholar 

  25. Unal I, and Ersan G M, Fuel Process Technol 87 (2005) 71. https://doi.org/10.1016/j.fuproc.2005.08.001

    Article  CAS  Google Scholar 

  26. Sahinoglu E, and Uslu T, Fuel Process Technol 116 (2013) 332. https://doi.org/10.1016/j.fuproc.2013.07.016

    Article  CAS  Google Scholar 

  27. Ferreira S L C, Bruns R E, Ferreira H S, Matos G D, David J M, Brandao G C, da Silva E P, Portugal L A, dos Reis P S, Souza A S, and dos Santos W N L, Anal Chim Acta 597 (2007) 179.

    Article  CAS  Google Scholar 

  28. Talib N A A, Salam F, Yusof N A, Ahmad S A A, and Sulaiman Y, J Electroanal Chem 787 (2017) 1. https://doi.org/10.1016/j.jelechem.2017.01.032

    Article  CAS  Google Scholar 

  29. Yadav A M, Nikkam S, Gajbhiye P, and Tyeb M H, Int J Miner Process 163 (2017) 55. https://doi.org/10.1016/j.minpro.2017.04.009

    Article  CAS  Google Scholar 

  30. Yadav A M, Chaurasia R C, Suresh N, and Gajbhiye P, Fuel 220 (2018) 826. https://doi.org/10.1016/j.fuel.2018.02.040

    Article  CAS  Google Scholar 

  31. Chary G H V C, and Dastidar M, Fuel 89 (2010) 2317. https://doi.org/10.1016/j.fuel.2009.12.016

    Article  CAS  Google Scholar 

  32. Aslan N, and Unal I, Fuel 88 (2009) 490. https://doi.org/10.1016/j.fuel.2008.10.039

    Article  CAS  Google Scholar 

  33. Aslan N, and Unal I, Fuel Process Technol 92 (2011) 1157. https://doi.org/10.1016/j.fuproc.2010.05.029

    Article  CAS  Google Scholar 

  34. Agacayak T, and Duzyol S, J Int Sci Publ Mater Methods Technol 12 (2018) 179.

    Google Scholar 

  35. Duzyol S, Part Sci Technol 3 (2018) 351. https://doi.org/10.1080/02726351.2016.1248264

    Article  CAS  Google Scholar 

  36. He J, Zhu L, Liu C, and Bai Q, Fuel 254 (2019) 115560. https://doi.org/10.1016/j.fuel.2019.05.143

    Article  CAS  Google Scholar 

  37. Shukla D, and Venugopal R, Powder Technol 346 (2019) 316. https://doi.org/10.1016/j.powtec.2019.02.001

    Article  CAS  Google Scholar 

  38. Polat S, and Sayan P, Adv Powder Technol 30 (2019) 2396. https://doi.org/10.1016/j.apt.2019.07.022

    Article  CAS  Google Scholar 

  39. Bagheri A R, Ghaedi M, Asfaram A, Jannesar R, and Goudarzi A, Ultrason Sonochem 35 (2017) 112. https://doi.org/10.1016/j.ultsonch.2016.09.008

    Article  CAS  Google Scholar 

  40. Box G E B, Hunter W G, and Hunter J S, Statistics for experimenters, Willey, New York (1978).

    Google Scholar 

  41. Montgomery D C, Design and analysis of experiments, Wiley, New York (2001).

    Google Scholar 

  42. Yildiz N, Ates C, Yilmaz M, Demir D, Yildiz A, and Calimli A, Green Process Synth 3 (2014) 259. https://doi.org/10.1515/gps-2014-0024

    Article  CAS  Google Scholar 

  43. Korbahti B K, and Tasyurek S, Environ Sci Pollut Res 22 (5), (2015) 3265. https://doi.org/10.1007/s11356-014-3101-7

    Article  CAS  Google Scholar 

  44. Souzaa A S, Walter N L, Santos D, and Sergio L C F, Spectrochim Acta Part B 60 (2005) 737. https://doi.org/10.1016/j.sab.2005.02.025

    Article  CAS  Google Scholar 

  45. Joglekar A M, and May A T, Cereal Foods World 32 (1987) 857.

    Google Scholar 

  46. Vazifeh Y, Jorjani E, and Bagherian A, Trans Nonferrous Met Soc China 20 (2010) 2371. https://doi.org/10.1016/S1003-6326(10)60657-7

    Article  CAS  Google Scholar 

  47. Leong Y K, and Boger D V, J Colloid Interface Sci 136 (1990) 249. https://doi.org/10.1016/0021-9797(90)90095-6

    Article  CAS  Google Scholar 

  48. Duzyol S, and Sensogut C, Fuel Process Technol 137 (2015) 333. https://doi.org/10.1016/j.fuproc.2015.03.021

    Article  CAS  Google Scholar 

  49. Ozdemir O, Taran E, Hampton M A, Karakashev S I, and Nguyen A V, Int J Miner Process 92 (2009) 177. https://doi.org/10.1016/j.minpro.2009.04.001

    Article  CAS  Google Scholar 

  50. S. Duzyol, C. Sensogut, A.O. Aksu, H.S. Erisir, K. Aspir, Benefication of Tuncbilek lignites by oil agglomeration, in M.E. Bilir, K. Kel, E. Kaymakci (Eds.). Proceedings of the 19th Coal Congress of Turkey, Zonguldak/Turkey. 2014, pp. 237–244.

  51. Duzyol S, CU J Fac Eng Archit 31 (2016) 77.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mining Engineering, Konya Technical University, 42250, Konya, Turkey

    Tevfik Agacayak

Authors
  1. Tevfik Agacayak
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tevfik Agacayak.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Agacayak, T. Modeling and Optimization of the Oil Agglomeration Parameters of Low-Calorific Value Lignite by Box–Behnken Design (BBD) Method. Trans Indian Inst Met 76, 2243–2251 (2023). https://doi.org/10.1007/s12666-023-02940-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12666-023-02940-2

Keywords

Search

Navigation