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Original Articles

Analysis and Optimization of Ultrasound-Assisted Alkaline Palm Oil Transesterification by RSM and ANN-GA

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References

  • Abdullah, A. Z., Salamatinia, B., Mootabadi, H., and Bhatia, S. (2009). Current status and policies on biodiesel industry in Malaysia as the world's leading producer of palm oil, Energy Policy, 37, 5440–5448.
  • Adepoju, T. F., and Olawale, O. (2014). Transesterification of CaSO with low amount of free fatty acids and its optimization, Rev. Energy Technol. Policy Res., 1, 20–27.
  • Agarwal, M., Chauhan, G., Chaurasia, S. P., and Singh, K. (2012). Study of catalytic behavior of KOH as homogeneous and heterogeneous catalyst for biodiesel production, J. Taiwan Inst. Chem. Eng., 43, 89–94.
  • Ali, E. N., and Tay, C. I. (2013). Characterization of biodiesel produced from palm oil via base catalyzed transesterification, Proc. Eng., 53, 7–12.
  • Avhad, M. R., and Marchetti, J. M. (2015). A review on recent advancement in catalytic materials for biodiesel production, Renew. Sust. Energy Rev., 50, 696–718.
  • Badday, A. S., Abdullah, A. Z., and Lee, K.-T. (2014). Artificial neural network approach for modeling of ultrasound-assisted transesterification process of crude Jatropha oil catalyzed by heteropolyacid based catalyst, Chem. Eng. Process.: Process Intensif., 75, 31–37.
  • Betiku, E., and Ajala, S. O. (2014). Modeling and optimization of Thevetia peruviana (yellow oleander) oil biodiesel synthesis via Musa paradisiacal (plantain) peels as heterogeneous base catalyst: a case of artificial neural network vs. response surface methodology, Ind. Crops Prod., 53, 314–322.
  • Betiku, E., Okunsolawo, S. S., Ajala, S. O., and Odedele, O. S. (2015). Performance evaluation of artificial neural network coupled with generic algorithm and response surface methodology in modeling and optimization of biodiesel production process parameters from shea tree (Vitellaria paradoxa) nut butter, Renew. Energy, 76, 408–417.
  • Betiku, E., Omilakin, O. R., Ajala, S. O., Okeleye, A. A., Taiwo, A. E., and Solomon, B. O. (2014). Mathematical modeling and process parameters optimization studies by artificial neural network and response surface methodology: a case of non-edible neem (Azadirachta indica) seed oil biodiesel synthesis, Energy, 72, 266–273.
  • Bezerra, M. A., Santelli, R. E., Oliveira, E. P., Villar, L. S., and Escaleira, L. A. (2008). Response surface methodology (RSM) as a tool for optimization in analytical chemistry, Talanta, 76, 965–977.
  • Bharathiraja, B., Chakravarthy, M., Kumar, R. R., Yuvaraj, D., Jayamuthunagai, J., Kumar, R. P., Palani, S. (2014). Biodiesel production using chemical and biological methods – a review of process, catalyst, acyl acceptor, source and process variables, Renew. Sustain. Energy Rev., 38, 368–382.
  • Brito, J. Q. A., Silva, C. S., Almeida, J. S., Korn, M. G. A., Korn, M., and Teixeira, L. S. G. (2012). Ultrasound-assisted synthesis of ethyl esters from soybean oil via homogeneous catalysis, Fuel Process Technol., 95, 33–36.
  • Choudhury, H. A., Chakma, S., and Moholkar, V. S. (2014a). Mechanistic insight into sonochemical biodiesel synthesis using heterogeneous base catalyst, Ultrason. Sonochem., 21, 169–181.
  • Choudhury, H. A., Goswami, P. P., Malani, R. S., and Moholkar, V. S. (2014b). Ultrasonic biodiesel synthesis from crude Jatropha curcas oil with heterogeneous base catalyst: mechanistic insight and statistical optimization, Ultrason. Sonochem., 21, 1050–1064.
  • Daud, N. M., Sheikh Abdullah, S. R., Abu Hasan, H., and Yaakob, Z. (2015). Production of biodiesel and its wastewater treatment technologies: a review, Process Safety Environ. Prot., 94, 487–508.
  • Dhingra, S., Dubey, K., and Bhushan, G. (2014). A polymath approach for the prediction of optimized transesterification process variables of polanga biodiesel, J. Am. Oil Chem. Soc., 91, 641–653.
  • Fayyazi, E., Ghobadian, B., Najafi, G., Hosseinzadeh, B., Mamat, R., and Hosseinzadeh, J. An ultrasound-assisted system for the optimization of biodiesel production from chicken fat oil using a genetic algorithm and response surface methodology, Ultrason. Sonochem., 26, 312–320.
  • Giraldo, S. Y., Rios, L. A., and Suárez, N. (2013). Comparison of glycerol ketals, glycerol acetates and branched alcohol-derived fatty esters as cold-flow improvers for palm biodiesel, Fuel, 108, 709–714.
  • Gnanaprakasam, A., Sivakumar, V. M., Surendhar, A., Thirumarimurugan, M., and Kannadasan, T. (2013). Recent strategy of biodiesel production from waste cooking oil and process influencing parameters: a review, J. Energy, 2013, 10.
  • Gole, V. L., and Gogate, P. R. (2012). A review on intensification of synthesis of biodiesel from sustainable feed stock using sonochemical reactors, Chem. Eng. Process.: Process Intensif., 53, 1–9.
  • Guo, W., Li, H., Ji, G., and Zhang, G. (2012). Ultrasound-assisted production of biodiesel from soybean oil using Brønsted acidic ionic liquid as catalyst, Bioresour. Technol., 125, 332–334.
  • Gupta, M. M., Jin, L., and Homma, N. (2003). Static and Dynamic Neural Networks; From Fundamentals to Advanced Theory, John Wiley & Sons, NJ, Hobokon, New Jersy.
  • Hagan, M. T., and Menhaj, M. (1994). Training feed-forward networks with the Marquardt algorithm, IEEE Trans. Neural Netw., 5, 989–993.
  • Hanh, H. D., Dong, N. T., Okitsu, K., Nishimura, R., and Maeda, Y. (2009). Biodiesel production through transesterification of triolein with various alcohols in an ultrasonic field, Renew. Energy, 34, 766–768.
  • Hui, L. W. (2012). Case study of artificial neural network modeling on catalyzed and enzymatic transesterification process for biodiesel production, J. Appl. Sci. Res., 8, 1672–1681.
  • Laugier, F., Andriantsiferana, C., Wilhelm, A. M., and Delmas, H. (2008). Ultrasound in gas–liquid systems: effects on solubility and mass transfer, Ultrason. Sonochem., 15, 965–972.
  • Levenberg, K. (1944). A method for the solution of certain problems in least squares, Q. Appl. Math., 2, 164–168.
  • Liao, C.-C., and Chung, T.-W. (2011). Analysis of parameters and interaction between parameters of the microwave-assisted continuous transesterification process of Jatropha oil using response surface methodology, Chem. Eng. Res. Des., 89, 2575–2581.
  • MacKay, D. J. C. (1992). Bayesian interpolation, Neural Comput., 4, 415–447.
  • Maran, J. P., and Priya, B. (2015). Comparison of response surface methodology and artificial neural network approach towards efficient ultrasound-assisted biodiesel production from muskmelon oil, Ultrason. Sonochem., 23, 192–200.
  • Michalewicz, Z. (1994). Genetic Algorithms + Data Structures = Evolution Programs, Springer-Verlag, Berlin.
  • Mitchell, M. (1999). An Introduction to Genetic Algorithms, The MIT Press, Cambridge, Massachusetts, London, England.
  • Mootabadi, H., Salamatinia, B., Bhatia, S., and Abdullah, A. Z. (2010). Ultrasonic-assisted biodiesel production process from palm oil using alkaline earth metal oxides as the heterogeneous catalysts, Fuel, 89, 1818–1825.
  • Moradi, G. R., Dehghani, S., Khosravian, F., and Arjmandzadeh, A. (2013). The optimized operational conditions for biodiesel production from soybean oil and application of artificial neural networks for estimation of the biodiesel yield, Renew. Energy, 50, 915–920.
  • Muppaneni, T., Reddy, H. K., Ponnusamy, S., Patil, P. D., Sun, Y., Dailey, P., Deng, S. (2013). Optimization of biodiesel production from palm oil under supercritical ethanol conditions using hexane as co-solvent: a response surface methodology approach, Fuel, 107, 633–640.
  • Nguyen, D., and Widrow, B. (1990). The truck backer-upper: an example of self-learning in neural networks, in: Neural Networks for Control, eds. W. Thomas Miller, III., S. S. Richard, and J. W. Paul, 287–299, MIT Press.
  • Ong, H. C., Mahlia, T. M. I., Masjuki, H. H., and Norhasyima, R. S. (2011). Comparison of palm oil, Jatropha curcas and Calophyllum inophyllum for biodiesel: a review, Renew. Sustain. Energy Rev., 15, 3501–3515.
  • Patil, P. D., Gude, V. G., Mannarswamy, A., Cooke, P., Nirmalakhandan, N., Lammers, P., and Deng, S. (2012). Comparison of direct transesterification of algal biomass under supercritical methanol and microwave irradiation conditions, Fuel, 97, 822–831.
  • Pilli, S., Bhunia, P., Yan, S., LeBlanc, R. J., Tyagi, R. D., and Surampalli, R. Y. (2011). Ultrasonic pretreatment of sludge: a review, Ultrason. Sonochem., 18, 1–18.
  • Prakash Maran, J., and Priya, B. (2015). Modeling of ultrasound assisted intensification of biodiesel production from neem (Azadirachta indica) oil using response surface methodology and artificial neural network, Fuel, 143, 262–267.
  • Rajković, K. M., Avramović, J. M., Milić, P. S., Stamenković, O. S., and Veljković, V. B. (2013). Optimization of ultrasound-assisted base-catalyzed methanolysis of sunflower oil using response surface and artificial neural network methodologies, Chem. Eng. J., 215–216, 82–89.
  • Russell, S., and Norvig, P. (2003). Artificial Intelligence A Modern Approach, 2nd ed., Prentice Hall, Englewood Cliffs, New Jersey.
  • Sajjadi, B., Abdul Aziz, A. R., Baroutian, S., and Ibrahim, S. (2014a). Investigation of convection and diffusion during biodiesel production in packed membrane reactor using 3D simulation, J. Ind. Eng. Chem., 20, 1493–1504.
  • Sajjadi, B., Abdul Aziz, A. R., and Ibrahim, S. (2014b). Investigation, modelling and reviewing the effective parameters in microwave-assisted transesterification, Renew. Sust. Energy Rev., 37, 762–777.
  • Sajjadi, B., Abdul Raman, A. A., Baroutian, S., Ibrahim, S., and Raja Ehsan Shah, R. S. S. (2014c). 3D simulation of fatty acid methyl ester production in a packed membrane reactor, Fuel Process. Technol., 118, 7–19.
  • Salamatinia, B., Mootabadi, H., Bhatia, S., and Abdullah, A. Z. (2010). Optimization of ultrasonic-assisted heterogeneous biodiesel production from palm oil: a response surface methodology approach, Fuel Process. Technol., 91, 441–448.
  • Sarve, A., Sonawane, S. S., and Varma, M. N. (2015). Ultrasound assisted biodiesel production from sesame (Sesamum indicum L.) oil using barium hydroxide as a heterogeneous catalyst: comparative assessment of prediction abilities between response surface methodology (RSM) and artificial neural network (ANN), Ultrason. Sonochem., 26, 218–228.
  • Shahabuddin, M., Kalam, M. A., Masjuki, H. H., Bhuiya, M. M. K., and Mofijur, M. (2012). An experimental investigation into biodiesel stability by means of oxidation and property determination, Energy, 44, 616–622.
  • Shirazi, Y., Farno, E., Majareh, H. S., Sadrzadeh, M., Mohammadi, T., and Kasiri, N. (2012). Effect of operating conditions on PV performance of PVA membranes: experimental and neural network modeling, Sep. Sci. Technol., 47, 1472–1484.
  • Somnuk, K., and Prateepchaikul, G. (2012). Feasibility of using high-intensity ultrasound assisted biodiesel production from mixed crude palm oil in two-step process, Adv. Mater. Res., 46, 875–877.
  • Somnuk, K., Smithmaitrie, P., and Prateepchaikul, G. (2012). Feasibility of using ultrasound-assisted biodiesel production from degummed-deacidified mixed crude palm oil using small-scale circulation, Kasetsart J. (Nat. Sci.), 46, 662–669.
  • Stamenković, O. S., Rajković, K., Veličković, A. V., Milić, P. S., and Veljković, V. B. (2013). Optimization of base-catalyzed ethanolysis of sunflower oil by regression and artificial neural network models, Fuel Process. Technol., 114, 101–108.
  • Stavarache, C., Vinatoru, M., Maeda, Y., and Bandow, H. (2007). Ultrasonically driven continuous process for vegetable oil transesterification, Ultrason. Sonochem., 14, 413–417.
  • Subramani, A., and Muthukumar, K. (2015). Transesterification of palm oil with high free fatty acid content using sodium hydride, Indian Chem. Eng., 57, 1–7.
  • Talebian-Kiakalaieh, A., Amin, N. A. S., Zarei, A., and Noshadi, I. (2013). Transesterification of waste cooking oil by heteropoly acid (HPA) catalyst: optimization and kinetic model, Appl. Energy, 102, 283–292.
  • Thanh, L. T., Okitsu, K., Sadanaga, Y., Takenaka, N., Maeda, Y., and Bandow, H. (2010). Ultrasound-assisted production of biodiesel fuel from vegetable oils in a small scale circulation process, Bioresour. Technol., 101, 639–645.
  • Trakarnpruk, W., and Porntangjitlikit, S. (2008). Palm oil biodiesel synthesized with potassium loaded calcined hydrotalcite and effect of biodiesel blend on elastomer properties, Renew. Energy, 33, 1558–1563.
  • Yaakob, Z., Mohammad, M., Alherbawi, M., Alam, Z., and Sopian, K. (2013). Overview of the production of biodiesel from Waste cooking oil, Renew. Sust. Energy Rev., 18, 184–193.
  • Zarei, A., Amin, N. A. S., Talebian-Kiakalaieh, A., and Zain, N. A. M. (2014). Immobilized lipase-catalyzed transesterification of Jatropha curcas oil: optimization and modeling, J. Taiwan Inst. Chem. Eng., 45, 444–451.

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