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Research Article

Aerodynamic multi-objective optimization on train nose shape using feedforward neural network and sample expansion strategy

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Article: 2226187 | Received 16 Mar 2023, Accepted 05 Jun 2023, Published online: 22 Jun 2023

References

  • Dai, Z. Y., Li, T., Zhang, W. H., & Zhang, J. Y. (2023). Research progress of aerodynamic multi-objective optimization on high-speed train nose shape. Computer Modeling in Engineering & Sciences, 1–29. https://doi.org/10.32604/cmes.2023.028677
  • Deb, K., & Jain, H. (2013). An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, Part I: Solving problems with box constraints. IEEE Transactions on Evolutionary Computation, 18(4), 577–601. https://doi.org/10.1109/TEVC.2013.2281535
  • Fluent Inc. (2021). FLUENT user's guide. https://ansyshelp.ansys.com
  • Guo, Z. J., Liu, T. H., Hemida, H., Chen, Z. W., & Liu, H. (2020). Numerical simulation of the aerodynamic characteristics of double unit train. Engineering Applications of Computational Fluid Mechanics, 14(1), 910–922. https://doi.org/10.1080/19942060.2020.1784798
  • Han, Y. D., & Yao, S. B. (2017). Scale effect analysis in aerodynamic performance of high-speed train. Journal of Zhejiang University (Engineering Science), 51(12), 2383–2391. https://doi.org/10.3785/j.issn.1008-973X.2017.12.010
  • Johnson, M. E., Moore, L. M., & Ylvisaker, D. (1990). Minimax and maximin distance designs. Journal of Statistical Planning and Inference, 26(2), 131–148. https://doi.org/10.1016/0378-3758(90)90122-B
  • Krajnović, S. (2009). Shape optimization of high-speed trains for improved aerodynamic performance. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 223(5), 439–452. https://doi.org/10.1243/09544097JRRT251
  • Lee, J., & Kim, J. (2007). Kriging-based approximate optimization of high-speed train nose shape for reducing micropressure wave. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 221(2), 263–270. https://doi.org/10.1243/0954409JRRT110
  • Li, H. Q., Zhang, Q. H., & Chen, X. Q. (2021a). Deep learning-based surrogate model for flight load analysis. Computer Modeling in Engineering & Sciences, 128(2), 605–621. https://doi.org/10.32604/cmes.2021.015747
  • Li, R., Xu, P., Peng, Y., & Ji, P. (2016). Multi-objective optimization of a high-speed train head based on the FFD method. Journal of Wind Engineering and Industrial Aerodynamics, 152, 41–49. https://doi.org/10.1016/j.jweia.2016.03.003
  • Li, T., Dai, Z. Y., Yu, M. G., & Zhang, W. H. (2021b). Numerical investigation on the aerodynamic resistances of double-unit trains with different gap lengths. Engineering Applications of Computational Fluid Mechanics, 15(1), 549–560. https://doi.org/10.1080/19942060.2021.1895321
  • Li, T., Liang, H., Zhang, J., & Zhang, J. Y. (2023). Numerical study on aerodynamic resistance reduction of high-speed train using vortex generator. Engineering Applications of Computational Fluid Mechanics, 17(1), e2153925. https://doi.org/10.1080/19942060.2022.2153925
  • Liang, H., Sun, Y., Li, T., & Zhang, J. (2022). Influence of marshalling length on aerodynamic characteristics of urban emus under crosswind. Journal of Applied Fluid Mechanics, 16, 9–20. https://doi.org/10.47176/JAFM.16.01.1338
  • Liu, Y. K., Yang, W. C., Deng, E., Wang, Y. W., He, X. H., Huang, Y. M., & Chen, Z. W. (2023). Aerodynamic impacts of high-speed trains on city-oriented noise barriers: A moving model experiment. Alexandria Engineering Journal, 68, 343–364. https://doi.org/10.1016/j.aej.2023.01.041
  • Muñoz-Paniagua, J., & García, J. (2019). Aerodynamic surrogate-based optimization of the nose shape of a high-speed train for crosswind and passing-by scenarios. Journal of Wind Engineering and Industrial Aerodynamics, 184, 139–152. https://doi.org/10.1016/j.jweia.2018.11.014
  • Muñoz-Paniagua, J., García, J., & Crespo, A. (2014). Genetically aerodynamic optimization of the nose shape of a high-speed train entering a tunnel. Journal of Wind Engineering and Industrial Aerodynamics, 130, 48–61. https://doi.org/10.1016/j.jweia.2014.03.005
  • Park, J. S. (1994). Optimal Latin-hypercube designs for computer experiments. Journal of Statistical Planning and Inference, 39(1), 95–111. https://doi.org/10.1016/0378-3758(94)90115-5
  • Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning representations by back-propagating errors. Nature, 323(6088), 533–536. https://doi.org/10.1038/323533a0
  • Sun, Z. K., Wang, T. T., & Wu, F. (2020). Numerical investigation of influence of pantograph parameters and train length on aerodynamic drag of high-speed train. Journal of Central South University, 27(4), 1334–1350. https://doi.org/10.1007/s11771-020-4370-6
  • Sun, Z. X., Song, J. J., & An, Y. R. (2010). Optimization of the head shape of the CRH3 high speed train. Science China Technological Sciences, 53(12), 3356–3364. https://doi.org/10.1007/s11431-010-4163-5
  • Tian, H. Q. (2019). Review of research on high-speed railway aerodynamics in China. Transportation Safety and Environment, 1(1), 1–21. https://doi.org/10.1093/tse/tdz014
  • Wang, Tiantian, Zhu, Yu, Tian, Xudong, Shi, Fangcheng, Zhang, Lei, & Lu, Yibin. (2022). Design method of the variable cross-section tunnel focused on improving passenger pressure comfort of trains intersecting in the tunnel. Building and Environment, 221, 109336. http://dx.doi.org/10.1016/j.buildenv.2022.109336
  • Xiang, Z. R., Zhi, J. Y., Huang, J. H., Kang, H. J., Li, T., Gao, P. F., & Li, F. (2019). A systematic approach for streamlined head form design and evaluation of Chinese high-speed train. International Journal of Rail Transportation, 7(2), 117–139. https://doi.org/10.1080/23248378.2018.1501776
  • Yao, S. B., Guo, D. L., Sun, Z., & Yang, G. W. (2015). A modified multi-objective sorting particle swarm optimization and its application to the design of the nose shape of a high-speed train. Engineering Applications of Computational Fluid Mechanics, 9(1), 513–527. https://doi.org/10.1080/19942060.2015.1061557
  • Yao, S. B., Guo, D. L., & Yang, G. W. (2012). Three-dimensional aerodynamic optimization design of high-speed train nose based on GA-GRNN. Science China Technological Sciences, 55(11), 3118–3130. https://doi.org/10.1007/s11431-012-4934-2
  • Yao, S. B., Guo, D. L., & Yang, G. W. (2013). Aerodynamic optimization of high-speed train based on RBF mesh deformation. Chinese Journal of Theoretical and Applied Mechanics, 45(6), 982–986. https://doi.org/10.6052/0459-1879-13-111
  • Yao, Z., Zhang, N., Chen, X., Zhang, C., Xia, H., & Li, X. (2020). The effect of moving train on the aerodynamic performances of train-bridge system with a crosswind. Engineering Applications of Computational Fluid Mechanics, 14(1), 222–235. https://doi.org/10.1080/19942060.2019.1704886
  • Zhang, L., Li, T., & Zhang, J. Y. (2021). Research on aerodynamic shape optimization of trains with different dimensional design variables. International Journal of Rail Transportation, 9(5), 479–501. https://doi.org/10.1080/23248378.2020.1817803
  • Zhang, L., Wang, Z. W., Wang, Q., Mo, J. L., Feng, J., & Wang, K. Y. (2023). The effect of wheel polygonal wear on temperature and vibration characteristics of a high-speed train braking system. Mechanical Systems and Signal Processing, 186, 109864. https://doi.org/10.1016/j.ymssp.2022.109864