Abstract
In this study, experiments were conducted for the flow of R-134a condensing in an enhanced inclined tube at a saturation condensing temperature of 40 °C. The enhanced tube had a helix angle of 14° with a mean internal diameter of 8.71 mm. The mass velocities were varied from 200 to 600 kg m−2 s−1, while the inclination angles were varied from − 90° to + 90°. It was found that the inclination angle had a considerable effect on the flow patterns and the thermal performance. It was also found that the maximum heat transfer coefficients were obtained at tube inclinations of between − 15° and − 5° (downward flows). By using the experimental data and artificial neural networks (ANN), a model was proposed to predict the heat transfer coefficients during condensation inside the enhanced inclined tube. By using four statistical criteria, the performance of the proposed model was examined against experimental data, and it was found that ANN was a useful tool for the prediction of the heat transfer coefficients based on the effective parameters of vapour quality, mass velocity and inclination angle.
Similar content being viewed by others
Abbreviations
- \(A_{\text{cs}}\) :
-
Test section cross-sectional area (m2)
- \(A_{\text{i}}\) :
-
Internal surface area (m2)
- e :
-
Fin height (m)
- G :
-
Mass velocity (kg m−2 s−1)
- h :
-
Heat transfer coefficient (W m−2 K−1)
- L t :
-
Heat transfer length of test section (m)
- \(Q^{.}\) :
-
Heat transfer rate (W)
- T :
-
Temperature (K)
- T sat :
-
Saturation temperature (K)
- \(\bar{T}_{\text{w,i}}\) :
-
Average wall inner temperature (K)
- x :
-
Vapour mass fraction (−)
- \(\beta\) :
-
Inclination angle (°)
- a:
-
Actual
- pred:
-
Predicted
- r, in:
-
Inlet refrigerant temperature
- r, out:
-
Outlet refrigerant temperature
- w, test:
-
Water side of the test section
- EF:
-
Enhancement factor
- MAE:
-
Mean absolute error
- MP:
-
Membership function
- MRE:
-
Mean relative error
- RMSE:
-
Root-mean-square error
- MSE:
-
Mean squared error
- MAPE:
-
Mean absolute percentage error
- R :
-
Correlation coefficient
- R 2 :
-
Coefficient of determination
- RMSE:
-
Root-mean-square error
References
Cavallini A, Censi G, Col DD, Doretti L, Rossetto L, Longo GA. Heat transfer coefficients of HFC refrigerants during condensation at high temperature inside an enhanced tube. In: 9th international refrigeration and air conditioning conference, Purdue, USA, 2002, paper 563.
Briggs A, Kelemenis C, Rose JW. Heat transfer and pressure drop measurements for in-tube condensation of CFC-113 using microfin tubes and wire inserts. Exp Heat Transf. 2000;13(3):163–81.
Cavallini A, Del Col D, Doretti L, Longo GA, Rossetto L. Heat transfer and pressure drop during condensation of refrigerants inside horizontal enhanced tubes. Int J Refrig. 2000;23(1):4–25.
Li W, Tang W, Chen J, Zhu H, Kukulka DJ, He Y, Sun Z, Du J, Zhang B. Convective condensation in three enhanced tubes with different surface modifications. Exp Thermal Fluid Sci. 2018;97:79–88.
Wang HS, Honda H. Condensation of refrigerants in horizontal microfin tubes: comparison of prediction methods for heat transfer. Int J Refrig. 2003;26(4):452–60.
Guo S-P, Wu Z, Li W, Kukulka D, Sundén B, Zhou X-P, Wei J-J, Simon T. Condensation and evaporation heat transfer characteristics in horizontal smooth, herringbone and enhanced surface EHT tubes. Int J Heat Mass Transf. 2015;85:281–91.
Kukulka DJ, Smith R, Li W. Comparison of tubeside condensation and evaporation characteristics of smooth and enhanced heat transfer 1EHT tubes. Appl Therm Eng. 2015;89:1079–86.
Ewim DRE, Meyer JP. Condensation heat transfer coefficients of enhanced tubes. In: 3rd Southern African solar energy conference, South Africa, 11–13 May 2015.
Mohseni SG, Akhavan-Behabadi MA. Visual study of flow patterns during condensation inside a microfin tube with different tube inclinations. Int Commun Heat Mass Transfer. 2011;38(8):1156–61.
Zhang J, Li W, Minkowycz W. Numerical simulation of R410A condensation in horizontal microfin tubes. Numer Heat Transf Part A: Appl. 2017;71(4):361–76.
Diani A, Campanale M, Cavallini A, Rossetto L. Low GWP refrigerants condensation inside a 24 mm ID microfin tube. Int J Refrig. 2018;86:312–21.
Colombo LPM, Lucchini A, Muzzio A. Flow patterns, heat transfer and pressure drop for evaporation and condensation of R134a in microfin tubes. Int J Refrig. 2012;35(8):2150–65.
Jung D, Cho Y, Park K. Flow condensation heat transfer coefficients of R22, R134a, R407C, and R410A inside plain and microfin tubes. Int J Refrig. 2004;27(1):25–32.
Han D, Lee KJ. Experimental study on condensation heat transfer enhancement and pressure drop penalty factors in four microfin tubes. Int J Heat Mass Transf. 2005;48(18):3804–16.
Zhang J, Zhou N, Li W, Luo Y, Li S. An experimental study of R410A condensation heat transfer and pressure drops characteristics in microfin and smooth tubes with 5 mm OD. Int J Heat Mass Transf. 2018;125:1284–95.
Bashar MK, Nakamura K, Kariya K, Miyara A. Experimental study of condensation heat transfer and pressure drop inside a small diameter microfin and smooth tube at low mass flux condition. Appl Sci. 2018;8(11):2146.
Li G, Huang L, Tao L. Experimental investigation of refrigerant condensation heat transfer characteristics in the horizontal microfin tubes. Appl Therm Eng. 2017;123:1484–93.
Adelaja AO, Dirker J, Meyer JP. Experimental study of the pressure drop during condensation in an inclined smooth tube at different saturation temperatures. Int J Heat Mass Transf. 2017;105:237–51.
Lyulin Y, Marchuk I, Chikov S, Kabov O. Experimental study of laminar convective condensation of pure vapor inside an inclined circular tube. Microgravity Sci Technol. 2011;23(4):439–45.
Lips S, Meyer JP. Experimental study of convective condensation in an inclined smooth tube. Part I: inclination effect on flow pattern and heat transfer coefficient. Int J Heat Mass Transf. 2012;55(1):395–404.
Meyer JP, Dirker J, Adelaja AO. Condensation heat transfer in smooth inclined tubes for R134a at different saturation temperatures. Int J Heat Mass Transf. 2014;70:515–25.
Ewim DRE, Meyer JP, Noori Rahim Abadi SMA. Condensation heat transfer coefficients in an inclined smooth tube at low mass fluxes. Int J Heat Mass Transf. 2018;123:455–67.
Romero-Méndez R, Lara-Vázquez P, Oviedo-Tolentino F, Durán-García HM, Pérez-Gutiérrez FG, Pacheco-Vega A. Use of artificial neural networks for prediction of the convective heat transfer coefficient in evaporative mini-tubes. Ingeniería, Investigación y Tecnología. 2016;17(1):23–34.
Ricardo R-M, Manuel H-LJ, Martín D-GH, Arturo P-V. Use of artificial neural networks for prediction of convective heat transfer in evaporative units. Ingeniería, Investigación y Tecnología. 2014;15(1):93–101.
Díaz G, Sen M, Yang KT, McClain RL. Simulation of heat exchanger performance by artificial neural networks. HVAC&R Res. 1999;5(3):195–208.
Zendehboudi A, Li X. A robust predictive technique for the pressure drop during condensation in inclined smooth tubes. Int Commun Heat Mass Transf. 2017;86:166–73.
Zendehboudi A, Li X. Robust predictive models for estimating frost deposition on horizontal and parallel surfaces. Int J Refrig. 2017;80:225–37.
Wang Q, Xie G, Zeng M, Luo L. Prediction of heat transfer rates for shell-and-tube heat exchangers by artificial neural networks approach. J Therm Sci. 2006;15(3):257–62.
Azizi S, Ahmadloo E. Prediction of heat transfer coefficient during condensation of R134a in inclined tubes using artificial neural network. Appl Therm Eng. 2016;106:203–10.
Xie G, Sunden B, Wang Q, Tang L. Performance predictions of laminar and turbulent heat transfer and fluid flow of heat exchangers having large tube-diameter and large tube-row by artificial neural networks. Int J Heat Mass Transf. 2009;52(11):2484–97.
Yaïci W, Entchev E. Performance prediction of a solar thermal energy system using artificial neural networks. Appl Therm Eng. 2014;73(1):1348–59.
Islamoglu Y. A new approach for the prediction of the heat transfer rate of the wire-on-tube type heat exchanger—use of an artificial neural network model. Appl Therm Eng. 2003;23(2):243–9.
Balcilar M, Dalkilic AS, Aroonrat K, Wongwises S. Neural network based analyses for the determination of evaporation heat transfer characteristics during downward flow of R134a inside a vertical smooth and corrugated tube. Arab J Sci Eng. 2014;39(2):1271–90.
Jafari Nasr MR, Habibi Khalaj A, Mozaffari SH. Modeling of heat transfer enhancement by wire coil inserts using artificial neural network analysis. Appl Therm Eng. 2010;30(2):143–51.
Scalabrin G, Condosta M, Marchi P. Mixtures flow boiling: modeling heat transfer through artificial neural networks. Int J Therm Sci. 2006;45(7):664–80.
Hamdan MA, Abdelhafez EA, Hamdan AM, Haj Khalil RA. Heat transfer analysis of a flat-plate solar air collector by using an artificial neural network. J Infrastruct Syst. 2016;22(4):A4014004.
Xie G, Wang Q, Zeng M, Luo L. Heat transfer analysis for shell-and-tube heat exchangers with experimental data by artificial neural networks approach. Appl Therm Eng. 2007;27(5–6):1096–104.
Zhao N, Li Z. Experiment and artificial neural network prediction of thermal conductivity and viscosity for alumina-water nanofluids. Materials. 2017;10(5):552.
Shojaeefard MH, Zare J, Tabatabaei A, Mohammadbeigi H. Evaluating different types of artificial neural network structures for performance prediction of compact heat exchanger. Neural Comput Appl. 2017;28(12):3953–65.
Kamar HM, Ahmad R, Kamsah NB, Mohamad Mustafa AF. Artificial neural networks for automotive air-conditioning systems performance prediction. Appl Therm Eng. 2013;50(1):63–70.
Yang K-T. Artificial neural networks (ANNs): a new paradigm for thermal science and engineering. J Heat Transf. 2008;130(9):1–19.
Balcilar M, Dalkilic A, Wongwises S. Artificial neural network techniques for the determination of condensation heat transfer characteristics during downward annular flow of R134a inside a vertical smooth tube. Int Commun Heat Mass Transf. 2011;38(1):75–84.
Tan CK, Ward J, Wilcox SJ, Payne R. Artificial neural network modelling of the thermal performance of a compact heat exchanger. Appl Therm Eng. 2009;29(17):3609–17.
Kamble LV, Pangavhane DR, Singh TP. Artificial neural network based prediction of heat transfer from horizontal tube bundles immersed in gas–solid fluidized bed of large particles. J Heat Transf. 2015;137(1):012901-1–9.
Tandiroglu A. Artificial neural network approach for transient forced convective heat transfer optimization. Int J Mech Eng Appl. 2016;4(6):212–25.
Ng BC, Darus IZM, Jamaluddin H, Kamar HM. Application of adaptive neural predictive control for an automotive air conditioning system. Appl Therm Eng. 2014;73(1):1244–54.
Verma TN, Nashine P, Singh DV, Singh TS, Panwar D. ANN: prediction of an experimental heat transfer analysis of concentric tube heat exchanger with corrugated inner tubes. Appl Therm Eng. 2017;120:219–27.
Akasaka R, Tanaka K, Higashi Y. Thermodynamic property modeling for 2,3,3,3-tetrafluoropropene (HFO-1234yf). Int J Refrig. 2010;33(1):52–60.
Mohanraj M, Jayaraj S, Muraleedharan C. Applications of artificial neural networks for refrigeration, air-conditioning and heat pump systems—a review. Renew Sustain Energy Rev. 2012;16(2):1340–58.
Mohanraj M, Jayaraj S, Muraleedharan C. Applications of artificial neural networks for thermal analysis of heat exchangers—a review. Int J Therm Sci. 2015;90:150–72.
Hu Q, So AT, Tse W, Ren Q. Development of ANN-based models to predict the static response and dynamic response of a heat exchanger in a real MVAC system. In: Journal of Physics: conference series, IOP Publishing, 2005.
Çebi A, Akdoğan E, Celen A, Dalkilic A. Prediction of friction factor of pure water flowing inside vertical smooth and microfin tubes by using artificial neural networks. Heat Mass Transf. 2017;53(2):673–85.
Azizi S, Ahmadloo E, Awad MM. Prediction of void fraction for gas–liquid flow in horizontal, upward and downward inclined pipes using artificial neural network. Int J Multiph Flow. 2016;87:35–44.
Ghajar AJ, Bhagwat SM. Gas-liquid two phase flow phenomenon in near horizontal upward and downward inclined pipe orientations. Int J Mech Aerospace, Ind Mechatron Eng. 2014;8(6):1039–53.
Boostani M, Karimi H, Azizi S. Heat transfer to oil-water flow in horizontal and inclined pipes: experimental investigation and ANN modeling. Int J Therm Sci. 2017;111:340–50.
Noori Rahim Abadi SMA, Mehrabi M, Meyer JP. Prediction and optimization of condensation heat transfer coefficients and pressure drops of R134a inside an inclined smooth tube. Int J Heat Mass Transf. 2018;124:953–66.
Adelaja AO, Dirker J, Meyer JP. Convective condensation heat transfer of R134a in tubes at different inclination angles. Int J Green Energy. 2016;13(8):812–21.
Abadi SNR, Meyer J, Dirker J. Numerical simulation of condensation inside an inclined smooth tube. Chem Eng Sci. 2018;182:132–45.
Abadi SNR, Mehrabi M, Meyer JP, Dirker J. Effect of saturation temperature on the condensation of R134a inside an inclined smooth tube. Int J Refrig. 2018;94:186–204.
Abadi SMA, Meyer JP, Dirker J. Effect of inclination angle on the condensation of R134a inside an inclined smooth tube. Chem Eng Res Design. 2018;132:346–57.
Caniere H, T’Joen C, Willockz A, De Paepe M, Christians M, Van Rooyen E, Liebenberg L, Meyer JP. Horizontal two-phase flow characterization for small diameter tubes with a capacitance sensor. Meas Sci Technol. 2007;18:2898.
Ji T, Liebenberg L, Meyer JP. Heat transfer enhancement during condensation in smooth tubes with helical wire inserts. Heat Transf Eng. 2009;30(5):337–52.
Liebenberg L, Meyer JP. A review of flow pattern-based predictive correlations during refrigerant condensation in horizontally smooth and enhanced tubes. Heat Transf Eng. 2008;29(1):3–19.
Liebenberg L, Thome JR, Meyer JP. Flow visualization and flow pattern identification with power spectral density distributions of pressure traces during refrigerant condensation in smooth and micro-fin tubes. J Heat Transf. 2005;127(3):209–20.
Lips S, Meyer JP. Two-phase flow in inclined tubes with specific reference to condensation: a review. Int J Multiph Flow. 2011;37(8):845–59.
Lips S, Meyer JP. Effect of gravity forces on heat transfer and pressure drop during condensation. Microgravity Sci Technol. 2011;24(3):157–64.
Lips S, Meyer JP. Experimental study of convective condensation in an inclined smooth tube Part II: inclination effect on pressure drops and void fractions. Int J Heat Mass Transf. 2012;55:405–12.
Olivier JA, Liebenberg L, Thome JR, Meyer JP. Heat transfer, pressure drop, and flow pattern recognition during condensation inside smooth, helical micro-fin, and herringbone tubes. Int J Refrig. 2007;30:609–23.
Olivier SP, Meyer JP, De Paepe M, De Kerpel K. The influence of inclination angle on void fraction and heat transfer during condensation inside a smooth tube. Int J Multiph Flow. 2016;80:1–14.
Suliman R, Liebenberg L, Meyer JP. Improved flow pattern map for accurate prediction of the heat transfer coefficients during condensation of R-134a in smooth horizontal tubes and within the low-mass flux range. Int J Heat Mass Transf. 2009;52(25–26):5701–11.
Ewim DRE, Meyer JP. Pressure drop during condensation at low mass fluxes in smooth horizontal and inclined tubes. Int J Heat Mass Transf. 2019;133:686–701.
Meyer JP, Ewim DRE. Heat transfer coefficients during the condensation of low mass fluxes in smooth horizontal tubes. Int J Multiph Flow. 2018;99:485–99.
Ewim DRE, Kombo R, Meyer JP. Flow pattern and experimental investigation of heat transfer coefficients during the condensation of R134a at low mass fluxes in a smooth horizontal tube. In: 12th international conference on heat transfer, fluid mechanics and thermodynamics (HEFAT), Costa del Sol, Malaga, Spain, 2016, pp 264–269.
Adelaja AO, Ewim DRE, Dirker J, Meyer JP. Experimental investigation on pressure drop and friction factor in tubes at different inclination angles during the condensation of R134a. In: Proceedings of the 15th international heat transfer conference, Kyoto, Paper IHTC15-9363, 2014, pp 10–15.
Adelaja AO, Ewim DR, Dirker J, Meyer JP. Experimental investigation on pressure drop and friction factor in tubes at different inclination angles during the condensation of R134A. In: Proceedings of the 15th international heat transfer conference, Kyoto, paper IHTC15-9363, 2014, pp 10–15.
Adelaja AO, Ewim DRE, Dirker J, Meyer JP. Heat transfer, void fraction and pressure drop during condensation inside inclined smooth and microfin tubes. Exp Therm Fluid Sci. 2019;109:109905.
Thome JR. Condensation inside tubes. Eng Data Book. 2006;III(1979):1–27.
Géron A. Neural networks and deep learning. https://www.oreilly.com/library/view/neural-networks-and/9781492037354/ch01.html. Accessed 30th Aug 2019.
Al Shamisi MH, Assi AH, Hejase HA. Using MATLAB to develop artificial neural network models for predicting global solar radiation in Al Ain City–UAE, Engineering education and research using MATLAB, IntechOpen2011.
Acknowledgements
The funding obtained from Tshwane University of Technology, NRF, TESP, Stellenbosch University/the University of Pretoria, SANERI/SANEDI, CSIR, TUT, EEDSM Hub and NAC is acknowledged and duly appreciated.
Author information
Authors and Affiliations
Corresponding authors
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Ewim, D.R.E., Adelaja, A.O., Onyiriuka, E.J. et al. Modelling of heat transfer coefficients during condensation inside an enhanced inclined tube. J Therm Anal Calorim 146, 103–115 (2021). https://doi.org/10.1007/s10973-020-09930-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10973-020-09930-2