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An Algorithm for Calculating Blasting Parameters of the Complex Surrounding Rock Tunnel Undercrossing Nearby Roadbed

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Russian Physics Journal Aims and scope

Traditionally, when the algorithm for calculating the tunnel blasting parameter based on theory of damage mechanics and explosive theory is used, the complexity of rock surrounding tunnel is not taken into account, and the result obtained are not optimized, thereby leading to low accuracy of the calculated parameter. In the present work, an algorithm for calculating the blasting parameters of tunnels in complex surrounding underground subgrade is studied based on genetic support vector regression. By calculating the internal stress of the complex surrounding rock, the vibration velocity parameters affecting the stability of the surrounding rock are obtained. The parameter calculation model has been developed using the ANSYS-DYNA numerical simulation software. The model is also used to obtain the complex surrounding rock pressure parameters. A coupling method based on genetic support vector regression is used to optimize the parameter. Experimental results show that the proposed method is practicable and provides accurate results. It can be used to quickly calculate the tunnel blasting parameter.

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References

  1. H. R. Ansari and A. Gholami, Fluid Phase Equilibria, 402, No. 3, 124–132 (2015).

    Article  Google Scholar 

  2. D. J. Armaghani, E. T. Mohamad, M. Hajihassani, et al., Eng. Comput., 32, No. 1, 109–121 (2016).

    Article  Google Scholar 

  3. M. Bobyr, H. Altenbach, and O. Khalimon, Arch. Appl. Mech., 85, No. 4, 455–468 (2015).

    Article  ADS  Google Scholar 

  4. B. Borogayary, A. K. Das, and A. J. Nath, J. Environ. Biol., 39, No. 1, 67–71 (2018).

    Article  Google Scholar 

  5. H. B. Wang, H. Jia, Y. Xu, Q. Zong, and J. G. Fu, Chin. Saf. Prod. Sci. Technol., 1, No. 05, 47–52 (2015).

    Google Scholar 

  6. C. Conti, C. Colombo, M. Realini, et al., J. Raman Spectrosc., 46, No. 5, 476–482 (2015).

    Article  ADS  Google Scholar 

  7. A. H. Fakeeha, A. A. Ibrahim, W. U. Khan, et al., Arab. J. Chem., 11, No. 3, 405–414 (2018).

    Article  Google Scholar 

  8. C. Fernandez-Lozano, F. Cedrón, D. Rivero, et al., Eng. Comput., 33, No. 4, 995–1005 (2016).

    Article  Google Scholar 

  9. Efi Foufoula-Georgiou, Z. Takbiri, J. A. Czuba, et al., Water Resour. Res., 51, No. 8, 6649–6671 (2015).

    Article  ADS  Google Scholar 

  10. Y. Zheng and C. Qiu, Mod. Tunn. Tech., 15, No. 3, 740–764 (2016).

    Google Scholar 

  11. R. Guadalupe Sanchez-Duarte, M. Del Rosario Martinez-Macias, M. Araceli Correa-Murrieta, et al., Rev. Int. De Contaminacion Ambiental, 33, No. SI, 93–98 (2017).

    Article  Google Scholar 

  12. M. A. Hoque, F. M. Hassan, A. M. Jauhar, et al., ACS Sustain. Chem. Eng., 6, No. 1, 93–98 (2018).

    Article  Google Scholar 

  13. H. F. Jin, Water Conservancy Constr. Manage., 71, Nos. 5–8, 1087–1092 (2017).

    Google Scholar 

  14. N. Iyit, Open Chemistry, 16, No. 1, 377–385 (2018).

    Article  Google Scholar 

  15. A. M. Kalteh, Water Resour. Manag., 30, No. 2, 747–766 (2016).

    Article  ADS  Google Scholar 

  16. Z. Li, C. Han, and T. Gu, Energ. Sour., Part B: Econ. Plan. Policy, 13, No. 2, 137–140 (2018).

    Article  Google Scholar 

  17. A. M. P. Mcdonnell, P. W. Boyd, R. K. O. Buessele, Global Biogeochem. Cycles, 29, No. 2, 175–193 (2015).

    Article  ADS  Google Scholar 

  18. P. Mostaghimi, J. R. Percival, D. Pavlidis, et al., Math. Geosci., 47, No. 4, 417–440 (2015).

    Article  MathSciNet  Google Scholar 

  19. P. Phantong, T. Machikowa, P. Saensouk, and N. Muangsan, Emir. J. Food Agric., 30, No. 2, 157–164 (2018).

    Google Scholar 

  20. J. Safaei-Ghomi, N. Enayat-Mehri, and F. Eshteghal, J. Saudi Chem. Soc., 22, No. 4, 485–495 (2018).

    Article  Google Scholar 

  21. Z. M. Sawan, Inf. Process. Agric., 5, No. 1, 134–148 (2018).

    MathSciNet  Google Scholar 

  22. M. Wang, D. Q. Zhang, J. Su, et al., J. Clean. Prod., 179, 12–23 (2018).

    Article  Google Scholar 

  23. R. A. Mohammad, K. R. Abolghasem, et al., Pet. Explor. Dev., 20, No. 4, 710–715 (2019).

    Google Scholar 

  24. Z. Wang, L. Miao, R. Wang, et al., Tumu Gongcheng Xuebao/Ch. Civ. Eng. J., 47, No. 5, 133–138 (2014).

    MathSciNet  Google Scholar 

  25. P. H. Weidlich, M. Schnedler, V. Portz, et al., J. Appl. Phys., 118, No. 3, 113–117 (2015).

    Article  Google Scholar 

  26. H. B. Zhao, Y. Long, X. H. Li, et al., KSCE J. Civ. Eng., 20, No. 1, 431–439 (2016).

    Article  Google Scholar 

  27. G. Zhong, Y. Lou, and Y. Fu, J. Beijing Inst. Technol. (Engl. Ed.), 26, No. 3, 324–333 (2017).

    Google Scholar 

  28. G. F. Attia, A. M. Abdelaziz, and I. N. Hassan, Appl. Math. Nonlinear Sci., 2, No. 1, 151–156 (2017).

    Article  Google Scholar 

  29. A. Q. Baig, M. Naeem, and W. Gao, Appl. Math. Nonlinear Sci., 3, No. 1, 33–40 (2018).

    Article  MathSciNet  Google Scholar 

  30. C. Mi, Y. Shen, W. J. Mi, and Y. F. Huang, J. Coast. Res., 73, 28–34 (2015).

    Article  Google Scholar 

  31. N. Y. Aksoy, Appl. Math. Nonlinear Sci., 5, No. 1, 211–220 (2020).

    Article  MathSciNet  Google Scholar 

  32. S. Goyal, P. Garg, and V. N. Mishra, Appl. Math. Nonlinear Sci., 4, No. 1, 163–168 (2019).

    Article  MathSciNet  Google Scholar 

  33. A. Atangana and S. Jain, Physica A, 512, 330–351 (2018).

    Article  ADS  MathSciNet  Google Scholar 

  34. S. Jain and A. Atangana, Int. J. Biomath., 11, No. 08, 87–105 (2018).

    Article  Google Scholar 

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Correspondence to Li-Cai Zhao.

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Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Fizika, No. 4, pp. 85–95, April, 2021.

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Zhao, LC., Chen, SS. An Algorithm for Calculating Blasting Parameters of the Complex Surrounding Rock Tunnel Undercrossing Nearby Roadbed. Russ Phys J 64, 657–670 (2021). https://doi.org/10.1007/s11182-021-02376-5

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  • DOI: https://doi.org/10.1007/s11182-021-02376-5

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