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Prediction and optimization of hydrogen yield and energy conversion efficiency in a non-catalytic filtration combustion reactor for jet A and butanol fuels

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Abstract

Hydrogen production is one of main subjects in fuel cells. The traditional method of synthesis gas production is based on fuel reforming using catalysts. The main problem of these methods is sensitivity and fast degradation of catalysts especially when fuels with high sulfur content are used. A new technique for hydrogen production is fuel-reforming using non-catalytic filtration combustion in porous media reactors. Various experimental works have been carried out to increase hydrogen production under different operating conditions such as inlet fuel velocity and equivalence ratio. First, we investigated the ability of adaptive neuro fuzzy inference system (ANFIS) for predicting the filtration combustion characteristics. Four distinct ANFIS models were developed for estimating the hydrogen yield and energy conversion efficiency for fuels of jet A and butanol. Eight different membership functions of dsigmf, gauss2mf, gaussmf, gbellmf, pimf, psigmf, trapmf and trimf were tested for training of the ANFIS networks. The results showed that the RMSE of the best developed ANFIS models for estimating of the hydrogen yield of jet fuel, hydrogen yield of butanol, conversion efficiency of jet fuel and conversion efficiency of butanol were 1.399, 1.213, 0.508 and 2.191, respectively. Moreover the R2 values of 0.998, 0.998, 0.999 and 0.999 were obtained for predicting the above mentioned variables, respectively. In the second step, a novel algorithm based on imperialist competitive algorithm (ICA) was used for optimization of hydrogen yield and energy efficiency. The maximum value of hydrogen yield and energy efficiency was 50.46% and 67.88% for jet A and 47.27% and 96.93% for butanol, respectively. The results showed that the imperialist competitive algorithm is an efficient and powerful algorithm to optimize combustion processes.

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References

  1. H. Pedersen-Mjaanes, L. Chan and E. Mastorakos, Int. J. Hydrogen Energy, 30, 579 (2005).

    Article  CAS  Google Scholar 

  2. C. H. Smith, D. M. Leahey, L. E. Miller and J. L. Ellzey, Proceedings of the Combustion Institute, 33(2), 3317 (2011).

    Article  CAS  Google Scholar 

  3. C. H. Smith, D. I. Pineda, C.D. Zak and J. L. Ellzey, Int. J. Hydrogen Energy, 38(2), 879 (2013).

    Article  CAS  Google Scholar 

  4. R. S. Dhamrat and J. L. Ellzey, Combust. Flame, 144(4), 698 (2006).

    Article  CAS  Google Scholar 

  5. M. J. Dixon, I. Schoegl, C.B. Hull and J.L. Ellzey, Combust. Flame, 154(1–2), 217 (2008).

    Article  CAS  Google Scholar 

  6. S.R. Shabanian, M. Rahimi, A. Amiri, S. Sharifnia and A.A. Alsairafi, Korean J. Chem. Eng., 29(11), 1531 (2012).

    Article  CAS  Google Scholar 

  7. S. S. Bharadwaj and L.D. Schmidt, Fuel Processing Technol., 42(2–3), 109 (1995).

    Article  CAS  Google Scholar 

  8. D. J. Moon, J.W. Ryu, S.D. Lee, B.G. Lee and B.S. Ahn, Appl. Catal. A: Gen., 272(1–2), 53 (2004).

    Article  CAS  Google Scholar 

  9. S. Velu, X. Ma, C. Song, M. Namazian, S. Sethuraman and G. Venkataraman, Energy Fuels, 19(3), 1116 (2005).

    Article  CAS  Google Scholar 

  10. S. L. Lakhapatri and M.A. Abraham, Appl. Catal. A: Gen., 405(1-2), 149 (2011).

    Article  CAS  Google Scholar 

  11. R. Araya, K. Araus, K. Utria and M. Toledo, Int. J. Hydrogen Energy, 39, 7338 (2014), DOI:10.1016/j.ijhydene.2014.02.113.

    Article  CAS  Google Scholar 

  12. C. H. Smith, C.D. Zak, D. Pineda and J. L. Ellzey, Conversion of Jet A to Syngas by Filtration Combustion, 7th US National Technical Meeting of the Combustion Institute Hosted by the Georgia Institute of Technology, Atlanta, GA (2011).

    Google Scholar 

  13. N.A. Kakutkina and V.A. Bunev, Explosion, and Shock Waves, 37(4), 395 (2001).

    Article  Google Scholar 

  14. M. Toledo, F. Gracia, S. Caro, J. Gómez and V. Jovicic, Int. J. Hydrogen Energy, 41, 5857 (2016).

    Article  CAS  Google Scholar 

  15. A. Pastore and E. Mastorakos, Exp. Therm. Fluid Sci., 34, 359 (2010).

    Article  CAS  Google Scholar 

  16. A. Pastore and E. Mastorakos, Fuel, 90, 64 (2011).

    Article  CAS  Google Scholar 

  17. S.R. Shabanian, M. Rahimi, A. Khoshhal and A.A. Alsairafi, Iranian J. Chem. Chem. Eng. (IJCCE), 29(4), 161 (2010).

    CAS  Google Scholar 

  18. R. Beigzadeh, M. Rahimi and S.R. Shabanian, Fluid Phase Equilib., 331, 48 (2012).

    Article  CAS  Google Scholar 

  19. L. Guoneng, Z. Hao, Q. Xinping and C. Kefa, Chinese J. Chem. Eng., 16(2), 292 (2008).

    Article  Google Scholar 

  20. P. Glarborg, J. A. Miller and R. J. Kee, Combust. Flame, 65(2), 177 (1986).

    Article  CAS  Google Scholar 

  21. S. H. Riazi, H. Heydari, E. Ahmadpour, A. Gholami and S. Parvizi, J. Natural Gas Sci. Eng., 18, 377 (2014).

    Article  CAS  Google Scholar 

  22. M.A. Ahmadi, M. Ebadi, A. Shokrollahi and S. M. J. Majidi, Appl. Soft Computing, 13(2), 1085 (2013).

    Article  Google Scholar 

  23. M.A. Ahmadi, J. Petroleum Exploration and Production Technol., 1(2), 99 (2011).

    Article  CAS  Google Scholar 

  24. S.M. Berneti and M. Shahbazian, Int. J. Comput. Applications, 26(10), 47 (2011).

    Article  Google Scholar 

  25. S. Zendehboudi, M. A. Ahmadi, O. Mohammadzadeh, A. Bahadori and I. Chatzis, Ind. Eng. Chem. Res., 52(17), 6009 (2013).

    Article  CAS  Google Scholar 

  26. M. Abolhasani, A. Karami and M. Rahimi, Numerical Heat Transfer, Part A, 67, 1282 (2015).

    Article  Google Scholar 

  27. N. Fitriyani, S.D.N. Nahdliyah and T.R. Biyanto, Operational Optimization of Binary Distillation Column to Achieve Product Quality using Imperialist Competitive Algorithm (ICA), 6th International Annual Engineering Seminar (InAES), Yogyakarta, Indonesia (2016).

    Book  Google Scholar 

  28. M. A. Al Dossary and H. Nasrabadi, J. Petroleum Sci. Eng., 147, 237 (2016).

    Article  Google Scholar 

  29. R. Rajabioun, E. Atashpaz-Gargarif and C. Lucas, Colonial Competitive Algorithm as a Tool for Nash Equilibrium Point Achievement, In: Gervasi O., Murgante B., Laganà A., Taniar D., Mun Y., Gavrilova M.L. (Eds.) Computational Science and Its Applications- ICCSA. Lecture Notes in Computer Science, Springer, Berlin, Heidelberg, 5073, 680 (2008).

    Google Scholar 

  30. H. Sepehri Rad and C. Lucas, Application of Imperialistic Competition Algorithm in Recommender Systems. In 13th international CSI computer conference (CSICC’08), Kish Island, Iran (2008).

    Google Scholar 

  31. A. Maroufmashat, F. Sayedin and S. S. Khavas, Int. J. Hydrogen Energy, 39, 18743 (2014).

    Article  CAS  Google Scholar 

  32. K.K. Justesen, S. J. Andreasen, H.R. Shaker, M. P. Ehmsen and J. Andersen, Int. J. Hydrogen Energy, 38, 10577 (2013).

    Article  CAS  Google Scholar 

  33. K.K. Justesen and S. J. Andreasen, Int. J. Hydrogen Energy, 40, 9505 (2015).

    Article  CAS  Google Scholar 

  34. W. Yaïci and E. Entchev, Renewable Energy, 86, 302 (2016).

    Article  Google Scholar 

  35. V.K. Mishra, S.C. Mishra and D.N. Basu, Numerical Heat Transfer, Part A, 67, 1119 (2015).

    Article  Google Scholar 

  36. V. Bubnovich, L. Henríquez and N. Gnesdilov, Numerical Heat Transfer, Part A, 52, 275 (2007).

    Article  CAS  Google Scholar 

  37. M. Bidabadi, J. Fereidooni, R. Tavakoli and M. Mafi, Korean J. Chem. Eng., 28(2), 461 (2011).

    Article  CAS  Google Scholar 

  38. S.R. Shabanian and A.A. Abdoos, A hybrid soft computing approach based on feature selection for estimation of filtration combustion characteristics, neural computing and application, 2017 (in press), DOI:10.1007/s00521-017-2956-1.

    Google Scholar 

  39. C. H. Smith, C.D. Zak and J. L. Ellzey, Conversion of Bio-butanol to Syngas via Filtration Combustion, 2010 Spring Technical Meeting of the Western States Section of the Combustion Institute hosted by University of Colorado at Boulder, Boulder, CO (2010).

    Google Scholar 

  40. E. Atashpaz-Gargari and C. Lucas, Imperialist competitive algorithm: an algorithm for optimization inspired by imperialistic competition, IEEE Congress on Evolutionary Computation, 4661, Singapore (2007).

    Google Scholar 

  41. J.-S.R. Jang, C.-T. Sun and E. Mizutani, Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence, Prentice-Hall (1996).

    Google Scholar 

  42. J.-S.R. Jang and C.-T. Sun, IEEE Transactions on Neural Networks, 4(1), 156 (1993).

    Article  CAS  Google Scholar 

  43. J. S.R. Jang, ANFIS- adaptive-network-based fuzzy inference system, IEEE Transactions on Systems, Man and Cybernetics, 23(3), 665 (1993).

    Google Scholar 

  44. R. Beigzadeh, M. Hajialyani and M. Rahimi, Korean J. Chem. Eng., 33(5), 1534 (2016).

    Article  CAS  Google Scholar 

  45. S.R. Shabanian, S. lashgari and T. Hatami, Numerical Heat Transfer, Part A, 70(1), 30 (2016).

    Article  Google Scholar 

  46. S.N. Sivanandam and S. N. Deepa, Introduction to Genetic Algorithms, Springer Science and Business Media, New York (2007).

    Google Scholar 

  47. C.C. Yuen, Aatmeeyata, S.K. Guptaf and A.K. Ray, J. Membr. Sci., 176, 177 (2000).

    Article  CAS  Google Scholar 

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Authors and Affiliations

  1. Department of Chemical Engineering, Babol Noshirvani University of Technology, Shariati Ave., Babol, 47148-71167, Iran

    Seyed Reza Shabanian, Sanaz Edrisi & Fatemeh Vahdat Khoram

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  1. Seyed Reza Shabanian
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  2. Sanaz Edrisi
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  3. Fatemeh Vahdat Khoram
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Correspondence to Seyed Reza Shabanian.

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Shabanian, S.R., Edrisi, S. & Khoram, F.V. Prediction and optimization of hydrogen yield and energy conversion efficiency in a non-catalytic filtration combustion reactor for jet A and butanol fuels. Korean J. Chem. Eng. 34, 2188–2197 (2017). https://doi.org/10.1007/s11814-017-0134-x

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  • DOI: https://doi.org/10.1007/s11814-017-0134-x

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