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A novel approach for estimating heat transfer coefficients of ethylene glycol–water mixtures

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Abstract

Ethylene glycol–water mixtures (EGWM) are vital for cooling engines in automotive industry. Scarce information is available in the literature for estimating the heat transfer coefficients (HTC) of EGWM using knowledge-based estimation techniques such as adaptive neuro-fuzzy inference systems (ANFIS) and artificial neural networks (ANN) which offer nonlinear input–output mapping. In this paper, the supervised learning methods of ANFIS and ANN are exploited for estimating the experimentally determined HTC. This original research fulfills the preceding modeling efforts on thermal properties of EGWM and HTC applications in the literature. An experimental test setup is designed to compute HTC of mixture over a small circular aluminum heater surface, 9.5 mm in diameter, placed at the bottom 40-mm-wide wall of a rectangular channel 3 mm × 40 mm in cross section. Measurement data are utilized as the train and test data sets of the estimation process. Prediction results have shown that ANFIS provide more accurate and reliable approximations compared to ANN. ANFIS present correlation factor of 98.81 %, whereas ANN estimate 87.83 % accuracy for test samples.

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Authors and Affiliations

  1. R&D and Satellite Design Department, TURKSAT AS, Golbasi, 06839, Ankara, Turkey

    Murat Bulut

  2. Vocational School of Technical Sciences, Baskent University, 06530, Ankara, Turkey

    Haydar Ankishan

  3. Electronics Engineering Department, Ankara University, Tandogan, 06100, Ankara, Turkey

    Erdem Demircioglu

  4. Faculty of Computer and Informatics, Sakarya University, Serdivan, 54187, Sakarya, Turkey

    Seckin Ari

  5. R&D Department, Prime Ministry of Turkey, Kizilay, 06573, Ankara, Turkey

    Orhan Sengul

Authors
  1. Murat Bulut
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  2. Haydar Ankishan
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  3. Erdem Demircioglu
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  4. Seckin Ari
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  5. Orhan Sengul
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Correspondence to Erdem Demircioglu.

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Bulut, M., Ankishan, H., Demircioglu, E. et al. A novel approach for estimating heat transfer coefficients of ethylene glycol–water mixtures. Neural Comput & Applic 25, 115–121 (2014). https://doi.org/10.1007/s00521-013-1453-4

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  • DOI: https://doi.org/10.1007/s00521-013-1453-4

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