Applying Machine Learning in CFD to Study the Impact of Thermal Characteristics on the Aerodynamic Characteristics of an Airfoil

Document Type : Regular Article


1 Department of Mechanical Engineering, University of Kufa, Najaf, Iraq

2 Department of Mechanical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran

3 Institute for Energy Research, Jiangsu University, Zhenjiang, 212013, P.R. China

4 School of the Environment and Safety Engineering, Institute for Energy Research, Jiangsu University, Zhenjiang, 212013, P.R. China

5 Department of Sustainable and Renewable Energy Engineering, University of Sharjah, Sharjah 27272, United Arab Emirates



A computational fluid dynamic (CFD) and machine learning approach is used to investigate heat transfer on NASA airfoils of type NACA 0012. Several different models have been developed to examine the effect of laminar flow, Spalart flow, and Allmaras flow on the NACA 0012 airfoil under varying aerodynamic conditions. Temperature conditions at high and low temperatures are discussed in this article for different airfoil modes, which are porous mode and non-porous mode. Specific parameters included permeability of 11.36 x 10-10 m2, porosity of 0.64, an inertia coefficient of 0.37, and a temperature range between 200 K and 400 K. The study revealed that a temperature increase can significantly increase lift-to-drag. Additionally, employing both a porous state and temperature differentials further contributes to enhancing the lift-to-drag coefficient. The neural network also successfully predicted outcomes when adjusting the temperature, particularly in scenarios with a greater number of cases. Nevertheless, this study assessed the accuracy of the system using a SMOTER model. It has been shown that the MSE, MAE, and R for the best performance validation of the testing case were 0.000314, 0.0008, and 0.998960, respectively, at K = 3. However, the study shows that epoch values greater than 2000 increase computational time and cost without improving accuracy. This indicates that the SMOTER model can be used to classify the testing case accurately; however, higher epoch values are not necessary for optimal performance. 


Main Subjects

Ahmed, S., Kamal, K., Ratlamwala, T. A. H., Mathavan, S., Hussain, G., Alkahtani, M., & Alsultan, M. B. M. (2022). Aerodynamic analyses of airfoils using machine learning as an alternative to RANS simulation. Applied Sciences, 12(10), 5194.
Bekka, N., Bessaïh, R., Sellam, M., & Chpoun, A. (2009). Numerical study of heat transfer around the small scale airfoil using various turbulence models, numer. Numerical Heat Transfer, Part A: Applications, 56, 946–969.
Bergman, T. L., Lavine, A. S., Incropera, F. P., & DeWitt, D. P. (2011). Introduction to heat transfer. John Wiley & Sons.
Bhatnagar, S., Afshar, Y., Pan, S., Duraisamy, K., & Kaushik, S. (2019). Prediction of aerodynamic flow fields using convolutional neural networks. Computational Mechanics, 64(2), 525-545.
Burns, T., & Muller, T. (1982). Experimental studies of the eppler 61 airfoil at low reynolds numbers. 20th Aerospace Sciences Meeting.
Chen, Z., Shi, Z., Chen, S., & Yao, Z. (2022). Stall flutter suppression of NACA 0012 airfoil based on steady blowing. Journal of Fluids and Structures, 109, 103472.
Crivellini, A., & D’Alessandro, V. (2014). Spalart–allmaras model apparent transition and rans simulations of laminar separation bubbles on airfoils. International Journal of Heat and Fluid Flow, 47, 70-83.
Ethiraj, L., & Pillai, S. N. (2021). Effect of trailing-edge modification over aerodynamic characteristics of NACA 0020 airfoil. Wind and Structures, 33(6), 463-470.
Eucken, A. (1940). Allgemeine gesetzmäßigkeiten für das wärmeleitvermögen verschiedener stoffarten und aggregatzustände. Forschung auf dem Gebiet des Ingenieurwesens A, 11(1), 6-20.
Fahland, G., Stroh, A., Frohnapfel, B., Atzori, M., Vinuesa, R., Schlatter, P., & Gatti, D. (2021). Investigation of blowing and suction for turbulent flow control on airfoils. 59(11), 4422-4436.
Ferziger, J. H., Perić, M., & Street, R. L. (2002). Computational methods for fluid dynamics. Berlin: springer, 3, 196-200.
Grasmeyer, J., & Keennon, M. (2001). Development of the black widow micro air vehicle. 39th Aerospace Sciences Meeting and Exhibit.
Hinz, D. F., Alighanbari, H., & Breitsamter, C. (2013). Influence of heat transfer on the aerodynamic performance of a plunging and pitching NACA0012 airfoil at low Reynolds numbers. Journal of Fluids and Structures, 37, 88-99.
Jordaan, H., Stephan Heyns, P., & Hoseinzadeh, S. (2021). Numerical development of a coupled one-dimensional/three-dimensional computational fluid dynamics method for thermal analysis with flow maldistribution. Journal of Thermal Science and Engineering Applications, 13(4).
Kim, J., Rusak, Z., & Koratkar, N. (2003). Small-Scale Airfoil aerodynamic efficiency improvement by surface temperature and heat transfer. Aerospace Research Central, 41(11), 2105-2113.
Lage, J. L., Antohe, B. V., & Nield, D. A. (1997). Two types of nonlinear pressure-drop versus flow-rate relation observed for saturated porous media. Journal of Fluids Engineering, 119(3), 700-706. %J Journal of Fluids Engineering
Landrum, D., & Macha, J. (1987). Influence of a heated leading edge on boundary layer growth, stability, and transition. 19th AIAA, Fluid Dynamics, Plasma Dynamics, and Lasers Conference.
Li, X. K., Liu, W., Zhang, T. J., Wang, P. M., & Wang, X. D. (2019). Analysis of the effect of vortex generator spacing on boundary layer flow separation control. Applied Sciences, 9(24), 5495.
Liepmann, H. W., & Fila, G. H. (1947). Investigations of effects of surface temperature and single roughness elements on boundary-layer transition (No. NACA-TR-890).
Liu, Y., Zhu, Y., Li, D., Huang, Z., & Bi, C. (2023). Computational simulation of mass transfer in membranes using hybrid machine learning models and computational fluid dynamics. Case Studies in Thermal Engineering, 47, 103086.
Llorente, E., & Ragni, D. (2020). Trailing-edge serrations effect on the performance of a wind turbine. Renewable Energy, 147, 437-446.
Mabey, D. G. (1990). Effects of heat transfer on aerodynamics and possible implications for wind tunnel tests. Progress in Aerospace Sciences, 27(4), 267-303.
Mueller, T. J., & B. Jansen, J. (1982). Aerodynamic measurements at low reynolds numbers. 12th Aerodynamic Testing Conference.
Norton, D. J., Macha, J. M., & Young, J. C. (1973). Surface Temperature Effect on Subsonic Stall. Aerospace Research Central, 10(9), 581-587.
O'Meara, M. M., & Mueller, T. J. (1987). Laminar separation bubble characteristics on an airfoil at low Reynolds numbers. Aerospace Research Central, 25(8), 1033-1041.
Oosedo, A., Abiko, S., Konno, A., & Uchiyama, M. (2017). Optimal transition from hovering to level-flight of a quadrotor tail-sitter UAV. Autonomous Robots, 41(5), 1143-1159.
Raghunathan, S., & Mitchell, D. (1995). Computed effects of heat transfer on the transonic flow over an aerofoil. Aerospace Research Central, 33(11), 2120-2127.
Samiee, A., Djavareshkian, M. H., Feshalami, B. F., & Esmaeilifar, E. (2018). Improvement of airfoils aerodynamic efficiency by thermal camber phenomenon at low reynolds number. Journal of Aerospace Technology and Management, 10.
Selimefendigil, F., & Öztop, H. F. (2021). Thermoelectric generation in bifurcating channels and efficient modeling by using hybrid CFD and artificial neural networks. Renewable Energy, 172, 582-598.
Seyhan, M., Sarioglu, M., & Akansu, Y. E. (2021). Influence of leading-edge tubercle with amplitude modulation on NACA 0015 airfoil. Aerospace Research Central, 59(10), 3965-3978.
Silva, D. d., & Malatesta, V. (2020). Numerical simulation of the boundary layer control on the NACA 0015 airfoil through vortex generators. Journal of Aerospace Technology and Management, 12.
Stock, H. W. (2002). Wind tunnel–flight correlation for laminar wings in adiabatic and heating flow conditions. Aerospace Science and Technology, 6(4), 245-257.
Sutherland, W. (1893). LII. The viscosity of gases and molecular force. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science, 36(223), 507-531.
Wang, L., Alam, M. M., Rehman, S., & Zhou, Y. (2022). Effects of blowing and suction jets on the aerodynamic performance of wind turbine airfoil. Renewable Energy, 196, 52-64.
Yan, Y., Avital, E., Williams, J., & Cui, J. (2019). CFD analysis for the performance of micro-vortex generator on aerofoil and vertical axis turbine. Journal of Renewable and Sustainable Energy, 11(4).
Zadorozhna, D. B., Benavides, O., Grajeda, J. S., Ramirez, S. F., & de la Cruz May, L. (2021). A parametric study of the effect of leading edge spherical tubercle amplitudes on the aerodynamic performance of a 2D wind turbine airfoil at low Reynolds numbers using computational fluid dynamics. Energy Reports, 7, 4184-4196. 
  • Received: 05 September 2023
  • Revised: 05 November 2023
  • Accepted: 28 November 2023
  • Available online: 30 January 2024