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Mathematical modeling of cooking pots’ thermal efficiency using a combined experimental and neural network method

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  • Hannani, S.K.
  • Hessari, E.
  • Fardadi, M.
  • Jeddi, M.K.

Abstract

A mathematical framework to model the heat transfer efficiency of cooking pots is proposed and exploited in this paper. The model consists of combining the experimental results and the statistical data of Residential Energy Consumption Survey (RECS) of Iran with a soft-computing concept such as neural network. Using neural network results, the variations of the efficiency with various parameters have been studied. It is shown that Group Method of Data Handling (GMDH)-type neural network can effectively model and predict thermal efficiency, as a function of important input parameters for a conventional cooking pot. Results show that efficiency increases with increasing diameter to flame ratio, bottom wall curvature, pot wall slope, and overall conductivity. With increasing edge radius and pot height to pot diameter ratio, efficiency decreases. Occupied volume percentage does not have a significant effect on efficiency.

Suggested Citation

  • Hannani, S.K. & Hessari, E. & Fardadi, M. & Jeddi, M.K., 2006. "Mathematical modeling of cooking pots’ thermal efficiency using a combined experimental and neural network method," Energy, Elsevier, vol. 31(14), pages 2969-2985.
    • Handle: RePEc:eee:energy:v:31:y:2006:i:14:p:2969-2985
    DOI: 10.1016/j.energy.2005.11.006
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    References listed on IDEAS

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    1. Akter Lucky, Rahima & Hossain, Ijaz, 2001. "Efficiency study of Bangladeshi cookstoves with an emphasis on gas cookstoves," Energy, Elsevier, vol. 26(3), pages 221-237.
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    Cited by:

    1. Makmool, U. & Jugjai, S. & Tia, S. & Vallikul, P. & Fungtammasan, B., 2007. "Performance and analysis by particle image velocimetry (PIV) of cooker-top burners in Thailand," Energy, Elsevier, vol. 32(10), pages 1986-1995.
    2. Deh Kiani, M. Kiani & Ghobadian, B. & Tavakoli, T. & Nikbakht, A.M. & Najafi, G., 2010. "Application of artificial neural networks for the prediction of performance and exhaust emissions in SI engine using ethanol- gasoline blends," Energy, Elsevier, vol. 35(1), pages 65-69.
    3. Cadavid, Francisco J. & Cadavid, Yonatan & Amell, Andrés A. & Arrieta, Andrés E. & Echavarría, Juan D., 2014. "Numerical and experimental methodology to measure the thermal efficiency of pots on electrical stoves," Energy, Elsevier, vol. 73(C), pages 258-263.
    4. Belén Bonet-Sánchez & Iulen Cabeza-Gil & Begoña Calvo & Jorge Grasa & Carlos Franco & Sergio Llorente & Miguel A. Martínez, 2022. "A Combined Experimental-Numerical Investigation of the Thermal Efficiency of the Vessel in Domestic Induction Systems," Mathematics, MDPI, vol. 10(5), pages 1-15, March.
    5. Sedighi, Mohammadreza & Salarian, Hesamoddin, 2017. "A comprehensive review of technical aspects of biomass cookstoves," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 656-665.

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