Article Sidebar

Download
PDF
Statistic
Read Counter : 221 Download : 106

Downloads

Download data is not yet available.

Main Article Content

Abstract

Finding possible solutions where there are multiple conflicting objectives to be simultaneously satisfied is a challenging situation. Multi-objective optimisation of a rear spoiler on a generic road vehicle model is carried out by using adjoint-based optimisation coupled with Computational Fluid Dynamics. The study aims to reduce the vehicle drag and increase vehicle downforce simultaneously by optimising the shape of the spoiler, by allowing the deformation to achieve the most optimised shape assuming no manufacturing constraint. The OpenFOAM software was used for the solver. A strategy for multi-objective optimisation was proposed by assigning appropriate objective function weight, leading to some possible solutions and Pareto front of the proposed design family. Five optimisation solutions of the non-dominated solution Pareto front resulting from the spoiler shape optimisation are presented, explaining the trade-off between conflicting drag and downforce objectives on the vehicle model. The baseline geometry of the simulation is in good agreement with the experimental measurement. The analysis of the shape changes in the proposed optimisation is deeply investigated in terms of the optimised geometry deformation, velocity contour comparison, recirculating region on the base, pressure coefficient comparison and stream-wise velocity component at the slant region of the model. The adjoint-based optimisation method in the presence study can handle multiple objective optimisations and generate possible optimised spoiler shapes to reduce drag and increase downforce. Free deformation of the shape yields in the unique shapes of the spoiler, enabling to manipulate of the base flow at the rear of the vehicle model.

Keywords

Adjoint Multi-objective optimization Ahmed body Spoiler Aerodynamics

Article Details

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

References

  1. L. Martinelli and A. Jameson, “Computational aerodynamics: solvers and shape optimization,” Journal of heat transfer, vol. 135, no. 1, p. 11002, 2013, doi: 10.1115/1.4007649.
  2. S. N. Skinner and H. Zare-Behtash, “State-of-the-art in aerodynamic shape optimisation methods,” Applied Soft Computing, vol. 62, pp. 933–962, 2018, doi: 10.1016/j.asoc.2017.09.030.
  3. C. Othmer, “Adjoint methods for car aerodynamics,” Journal of Mathematics in Industry, vol. 4, no. 1, p. 6, 2014, doi: 10.1186/2190-5983-4-6.
  4. G. Gunadi, H. Sofyan, A. Yudianto, W. Setiawan, F. Julianto, and U. Aminudin, “On the options for bus aerodynamic profile optimization,” in AIP Conference Proceedings, 2023, vol. 2671, no. 1, doi: 10.1063/5.0117392.
  5. A. Altaf, A. A. Omar, and W. Asrar, “Passive drag reduction of square back road vehicles,” Journal of Wind Engineering and Industrial Aerodynamics, vol. 134, pp. 30–43, 2014, doi: 10.1016/j.jweia.2014.08.006.
  6. R. P. Putra, D. Yuvenda, M. Setyo, A. Andrizal, and M. Martias, “Body City Car Design of Two Passengers Capacity: A Numerical Simulation Study,” Automotive Experiences, vol. 5, no. 2, pp. 163–172, Apr. 2022, doi: 10.31603/ae.6304.
  7. M. Szudarek, A. Piechna, and J. Piechna, “Feasibility Study of a Fan-Driven Device Generating Downforce for Road Cars,” Energies, vol. 15, no. 15, p. 5549, 2022, doi: 10.3390/en15155549.
  8. Z. Arifin et al., “Aerodynamic Characteristics of Ahmed Body with Inverted Airfoil Eppler 423 and Gurney Flap on Fastback Car,” Automotive Experiences, vol. 5, no. 3, pp. 355–370, 2022, doi: 10.31603/ae.7067.
  9. C. Baker, F. Cheli, A. Orellano, N. Paradot, C. Proppe, and D. Rocchi, “Cross-wind effects on road and rail vehicles,” Vehicle system dynamics, vol. 47, no. 8, pp. 983–1022, 2009, doi: 10.1080/00423110903078794.
  10. A. Yudianto, W. Setiawan, F. Julianto, and U. Aminudin, “Aerodynamic study of vehicles in formation under crosswind,” in AIP Conference Proceedings, 2023, vol. 2671, no. 1, doi: 10.1063/5.0114571.
  11. A. Yudianto, I. W. Adiyasa, and A. Yudantoko, “Aerodynamics of Bus Platooning under Crosswind,” Automotive Experiences, vol. 4, no. 3, pp. 119–130, 2021.
  12. S.-Y. Cheng, K.-Y. Chin, and S. Mansor, “Experimental study of yaw angle effect on the aerodynamic characteristics of a road vehicle fitted with a rear spoiler,” Journal of Wind Engineering and Industrial Aerodynamics, vol. 184, pp. 305–312, 2019, doi: 10.1016/j.jweia.2018.11.033.
  13. J.-F. Beaudoin and J.-L. Aider, “Drag and lift reduction of a 3D bluff body using flaps,” Experiments in fluids, vol. 44, no. 4, pp. 491–501, 2008, doi: 10.1007/s00348-007-0392-1.
  14. J.-L. Aider, J.-F. Beaudoin, and J. E. Wesfreid, “Drag and lift reduction of a 3D bluff-body using active vortex generators,” Experiments in fluids, vol. 48, pp. 771–789, 2010, doi: 10.1007/s00348-009-0770-y.
  15. G. Pujals, S. Depardon, and C. Cossu, “Drag reduction of a 3D bluff body using coherent streamwise streaks,” Experiments in fluids, vol. 49, pp. 1085–1094, 2010, doi: 10.1007/s00348-010-0857-5.
  16. A. Thacker, S. Aubrun, A. Leroy, and P. Devinant, “Effects of suppressing the 3D separation on the rear slant on the flow structures around an Ahmed body,” Journal of Wind Engineering and Industrial Aerodynamics, vol. 107, pp. 237–243, 2012, doi: 10.1016/j.jweia.2012.04.022.
  17. J. Howell, A. Sheppard, and A. Blakemore, “Aerodynamic drag reduction for a simple bluff body using base bleed,” SAE transactions, pp. 1085–1091, 2003.
  18. W. Yi, W. SaGong, and H.-C. Choi, “Drag reduction of a three-dimensional car model using passive control device,” in Proceedings of the KSME Conference, 2007, pp. 2868–2872.
  19. R. Lohner, O. Soto, and C. Yang, “An adjoint-based design methodology for CFD optimization problems,” in 41st Aerospace Sciences Meeting and Exhibit, 2003, p. 299, doi: 10.2514/6.2003-299.
  20. R. Askari, P. Shoureshi, M. R. Soltani, and A. Khajeh Fard, “Adjoint-Based Design Optimization of S-Shaped Intake Geometry,” in ASME International Mechanical Engineering Congress and Exposition, 2017, vol. 58349, p. V001T03A008, doi: 10.1115/IMECE2017-71884.
  21. C. Hinterberger and M. Olesen, “Automatic geometry optimization of exhaust systems based on sensitivities computed by a continuous adjoint CFD method in OpenFOAM,” SAE Technical Paper, 2010.
  22. E. de Villiers and C. Othmer, “Multi-objective adjoint optimization of intake port geometry,” SAE Technical Paper, 2012.
  23. E. M. Papoutsis-Kiachagias, V. G. Asouti, K. C. Giannakoglou, K. Gkagkas, S. Shimokawa, and E. Itakura, “Multi-point aerodynamic shape optimization of cars based on continuous adjoint,” Structural and Multidisciplinary Optimization, vol. 59, pp. 675–694, 2019, doi: 10.1007/s00158-018-2091-3.
  24. E. M. Papoutsis-Kiachagias, N. Magoulas, J. Mueller, C. Othmer, and K. C. Giannakoglou, “Noise reduction in car aerodynamics using a surrogate objective function and the continuous adjoint method with wall functions,” Computers & Fluids, vol. 122, pp. 223–232, 2015, doi: 10.1016/j.compfluid.2015.09.002.
  25. A. Yudianto, U. Aminudin, W. Setiawan, and F. Julianto, “Aerodynamic investigation of misaligned four-vehicle platoon,” in AIP Conference Proceedings, 2023, vol. 2671, no. 1, doi: 10.1063/5.0114577.
  26. A. Yudianto, H. Sofyan, and N. A. Fauzi, “Aerodynamic characteristics of overtaking bus under crosswind: CFD investigation,” CFD Letters, vol. 14, no. 8, pp. 20–32, 2022, doi: 10.37934/cfdl.14.8.2032.
  27. A. Yudianto, M. Solikin, S. Sutiman, Z. Arifin, Iw. Adiyasa, and A. Yudantoko, “Aerodynamic investigation of extremely efficient vehicles under side wind conditions,” Revista Facultad de Ingeniería Universidad de Antioquia, no. 109, pp. 79–88, 2023, doi: 10.17533/udea.redin.20221107.
  28. S. R. Ahmed, G. Ramm, and G. Faltin, “Some salient features of the time-averaged ground vehicle wake,” SAE transactions, pp. 473–503, 1984.
  29. E. M. Papoutsis-Kiachagias and K. C. Giannakoglou, “Continuous adjoint methods for turbulent flows, applied to shape and topology optimization: industrial applications,” Archives of Computational Methods in Engineering, vol. 23, no. 2, pp. 255–299, 2016, doi: 10.1007/s11831-014-9141-9.
  30. A. Bueno-Orovio, C. Castro, F. Palacios, and E. Zuazua, “Continuous adjoint approach for the Spalart-Allmaras model in aerodynamic optimization,” AIAA journal, vol. 50, no. 3, pp. 631–646, 2012, doi: 10.2514/1.J051307.
  31. S. Nadarajah and A. Jameson, “A comparison of the continuous and discrete adjoint approach to automatic aerodynamic optimization,” in 38th Aerospace sciences meeting and exhibit, 2000, p. 667, doi: 10.2514/6.2000-667.
  32. S. Thomas and O. Carsten, “Adjoint optimization for vehicle external aerodynamics,” International Journal of Automotive Engineering, vol. 7, no. 1, pp. 1–7, 2016, doi: 10.20485/jsaeijae.7.1_1.
  33. P. He, C. A. Mader, J. R. R. A. Martins, and K. J. Maki, “An aerodynamic design optimization framework using a discrete adjoint approach with OpenFOAM,” Computers & Fluids, vol. 168, pp. 285–303, 2018, doi: 10.1016/j.compfluid.2018.04.012.
  34. P. Spalart and S. Allmaras, “A one-equation turbulence model for aerodynamic flows,” in 30th aerospace sciences meeting and exhibit, 1992, p. 439.
  35. I. S. Kavvadias, E. M. Papoutsis-Kiachagias, and K. C. Giannakoglou, “On the proper treatment of grid sensitivities in continuous adjoint methods for shape optimization,” Journal of Computational Physics, vol. 301, pp. 1–18, 2015, doi: 10.1016/j.jcp.2015.08.012.
  36. F. Massarwi and G. Elber, “A B-spline based framework for volumetric object modeling,” Computer-Aided Design, vol. 78, pp. 36–47, 2016, doi: 10.1016/j.cad.2016.05.003.
  37. J. R. R. A. Martins and A. Ning, Engineering design optimization. Cambridge University Press, 2021.
  38. Y. Sawaragi, H. Nakayama, and T. Tanino, “Theory of Multiobjective Optimization. Elsevier,” 1985.
  39. J. C. Meza, “Steepest descent,” Wiley Interdisciplinary Reviews: Computational Statistics, vol. 2, no. 6, pp. 719–722, 2010.