Abstract
Cooling towers and chillers are the basis of modern refrigeration systems of large facilities, such as oil refineries, power plants and large commercial buildings. The increasing concerns about the scarcity of water and energy resources require careful optimization processes to achieve energy efficiency in industrial buildings. Energy efficiency oriented optimizations require mathematical models of real equipment that compose the refrigeration systems. In this paper, we present a complete model cooling towers and corresponding fans based on Merkel’s and Braun’s methods. We prove that proposed model is accurate and faithful to the real cooling cells in modern refrigeration systems. The obtained value of mean square error when applying the model and comparing the obtained results to the actual ones is minimal, hence validated the proposed model.
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References
Alpina: Torres de resfriamento de água. Tech. rep., Alpina S/A Indústria e Comércio, São Bernardo do Campo, SP (1978)
Braun, J.E., Klein, S.A., Mitchel, J.W.: Effectiveness models cooling towers cooling coils. ASHRAE Trans. 95(2), 164–174 (1989)
Fahmy, A.A., Shouman, L.A.: Deterministic study on the optimum performance of counter flow cooling tower. Int. J. Sci. Eng. Res. 3(6), 1–5 (2012)
Kern, D.Q.: Process Heat Transfer. McGraw-Hill Book Company Inc., Tokyo (1983)
Khan, J.R., Zubair, S.M.: An improved design and rating analyses of counter flow wet cooling towers. J. Heat Trans. 123, 770–778 (2001)
Kloppers, J.C., Kroger, D.G.: A critical cooling tower performance evaluation. In: 12th IAHR Symposium in Cooling Towers and Heat Exchangers, UTS, pp. 108–115 (2001)
Kloppers, J.C., Kroger, D.G.: Cooling tower performance: a critical evaluation of the Merkel assumptions. Res. Dev. J. Incorporated SA Mech. Eng. 20(1), 24–29 (2004)
Leontaritis, I.J., Billings, S.A.: Model selection and validation methods for non-linear systems. Int. J. Control 45(1), 311–341 (1987)
Lu, L., Cai, W.: A universal engineering model for cooling towers. In: International Refrigeration and Air Conditioning Conference, Indiana, USA (2002)
Merkel, F.: Verdunstungskuhlung, pp. 576–583. VDI Forschungsarbeiten, Berlin (1925)
Nedjah, N., Mourelle, L.M., Lizarazu, M.S.D.: Mathematical modeling of chiller-based refrigeration systems for energy efficiency optimization. In: Gervasi, O., et al., B.M. (eds.) International Conference on Computational Science and Its Applications, pp. 1–18 (2022, accepted)
Poppe, M., Rogener, H.: Berechnung von ruckkuhlwerken, VDI-Warmeatlas (1991). pp. 1001–1015
Seber, G.A.F., Wild, C.J.: Nonlinear Regression. Willey-Interscience, Hoboken (2003)
Sutherland, J.W.: Analysis of mechanical draught counter flow air water cooling tower. J. Heat Trans. 105, 576–583 (1983)
Yu, K., Hung, Y., Hsieh, S., Hung, S.: Chiller energy saving optimization using artificial neural networks. J. Appl. Sci. 16(11), 3008–3014 (2011). https://doi.org/10.3923/jas.2011.3008.3014
Acknowledgments
This work is supported by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq - Brazil) and by Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro (FAPERJ - Brazil 203.111/2018). We are most grateful for their continuous financial support.
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Nedjah, N., de Macedo Mourelle, L., Lizarazu, M.S.D. (2022). Mathematical Modeling of Cooling Towers-Based Refrigeration Systems for Energy Efficiency Optimization. In: Gervasi, O., Murgante, B., Misra, S., Rocha, A.M.A.C., Garau, C. (eds) Computational Science and Its Applications – ICCSA 2022 Workshops. ICCSA 2022. Lecture Notes in Computer Science, vol 13377. Springer, Cham. https://doi.org/10.1007/978-3-031-10536-4_20
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