Advertisement

Improved radial movement optimization to determine the critical failure surface for slope stability analysis

  • Liangxing Jin
  • Qixuan Feng
Original Article
  • 98 Downloads

Abstract

Slope stability analysis usually requires the determination of the critical failure surface. In this paper, a new global optimization algorithm, based on radial movement optimization, is proposed to search the non-circular critical failure surface of a slope. Factors of safety of the slip surfaces are determined using the Spencer method. Nonlinear equations from the Spencer method are solved using the Newton–Raphson method. The data structure of the radial movement algorithm is further optimized to overcome the instability and inaccuracy of the original method. By considering the self-feedback of the particles, the particle swarm can inherit the information of its own particles. The proposed method is validated by examples taken from the literature. The results show that the improved radial movement optimization algorithm can be successfully applied to slope stability analysis, and it has better performance than other global optimization algorithms.

Keywords

Slope stability Non-circular critical failure surface Improved radial movement optimization Factor of safety 

Notes

Acknowledgements

This research was funded by the Fundamental Research Funds for the Central Universities of Central South University (No. 2018zzts674).

References

  1. Arai K, Tagyo K (1985) Determination of noncircular slip surface giving the minimum factor of safety in slope stability analysis. Soils Found 25(1):43–51CrossRefGoogle Scholar
  2. Baker R (1980) Determination of the critical slip surface in slope stability computations. Int J Numer Anal Meth Geomech 4(4):333–359CrossRefGoogle Scholar
  3. Baker R, Garber M (1978) Theoretical analysis of the stability of slopes. Géotechnique 28(4):395–411CrossRefGoogle Scholar
  4. Celestino TB, Duncan JM (1981) Simplified search for non-circular slip surface. In: Proceeding of 10th international conference on soil mechanics and foundation engineering, Stockholm, Sweden pp 391–394Google Scholar
  5. Cheng YM (2003) Location of critical failure surface and some further studies on slope stability analysis. Comput Geotech 30(3):255–267CrossRefGoogle Scholar
  6. Cheng YM, Li L, Chi SC, Wei WB (2007) Particle swarm optimization algorithm for the location of the critical non-circular failure surface in two-dimensional slope stability analysis. Comput Geotech 34(2):92–103CrossRefGoogle Scholar
  7. Cheng YM, Liang L, Chi SC, Wei WB (2008) Determination of the critical slip surface using artificial fish swarms algorithm. J Geotech Geoenviron Eng 134(2):244–251CrossRefGoogle Scholar
  8. Denatale JS (1991) Rapid identification of critical slip surfaces: structure. J Geotech Eng 117(10):1568–1589CrossRefGoogle Scholar
  9. Gao W (2015a) Slope stability analysis based on immunised evolutionary programming. Environ Earth Sci 74(4):3357–3369CrossRefGoogle Scholar
  10. Gao W (2015b) Stability analysis of rock slope based on an abstraction ant colony clustering algorithm. Environ Earth Sci 73(12):7969–7982CrossRefGoogle Scholar
  11. Gao W, Wang X, Dai S, Chen DL (2016) Study on stability of high embankment slope based on black hole algorithm. Environ Earth Sci 75(20):1381CrossRefGoogle Scholar
  12. Greco VR (1996) Efficient Monte Carlo technique for locating critical slip surface. J Geotech Eng 122(7):517–525CrossRefGoogle Scholar
  13. Hermanus B, Gerhard H, Albert G (2003) Global search for critical failure surface in slope stability analysis. Eng Optim 35(1):51–65CrossRefGoogle Scholar
  14. Kahatadeniya KS, Nanakorn P, Neaupane KM (2009) Determination of the critical failure surface for slope stability analysis using ant colony optimization. Eng Geol 108(1–2):133–141CrossRefGoogle Scholar
  15. Li KS, White W (2010) Rapid evaluation of the critical slip surface in slope stability problems. Int J Numer Anal Methods Geomech 11(5):449–473CrossRefGoogle Scholar
  16. Li SJ, Liu YX, He X, Liu YJ (2003) Global search algorithm of minimum safety factor for slope stability analysis based on annealing simulation. Chin J Rock Mechan Eng 22(2):236–240 (in Chinese)Google Scholar
  17. Liu SY, Shao LT, Li HJ (2015) Slope stability analysis using the limit equilibrium method and two finite element methods. Comput Geotech 63(63):291–298CrossRefGoogle Scholar
  18. Liu LL, Cheng YM, Wang XM (2016) Genetic algorithm optimized Taylor Kriging surrogate model for system reliability analysis of soil slopes. Landslides 14:535–546CrossRefGoogle Scholar
  19. Mahrami M, Rahmani R, Seyedmahmoudian M, Mashayekhi R, Karimi H, Hosseini E (2016) A hybrid metaheuritic technique developed for hourly load forecasting. Complexity 21(S1):521–532CrossRefGoogle Scholar
  20. Malkawi AIH, Hassan WF, Sarma SK (2001) Global search method for locating general slip surface using monte carlo techniques. J Geotech Geoenviron Eng 127(8):688–698CrossRefGoogle Scholar
  21. Manouchehrian A, Gholamnejad J, Sharifzadeh M (2014) Development of a model for analysis of slope stability for circular mode failure using genetic algorithm. Environ Earth Sci 71(3):1267–1277CrossRefGoogle Scholar
  22. Mccombie P, Wilkinson P (2002) The use of the simple genetic algorithm in finding the critical factor of safety in slope stability analysis. Comput Geotech 29(8):699–714CrossRefGoogle Scholar
  23. Ngugen VU (1985) Determination of critical slope failure surface. J Geotech Eng 194(5):238–250CrossRefGoogle Scholar
  24. Pan ZF, Jin LX, Chen WS (2016) Improved radial movement optimization algorithm for slope stability analysis. Rock and Soil Mech 37(07): 2079–2084 (in Chinese)Google Scholar
  25. Rahmani R, Yusof R (2014) A new simple, fast and efficient algorithm for global optimization over continuous search-space problems. Appl Math Comput 248(C):287–300Google Scholar
  26. Seyedmahmoudian M, Horan B, Rahmani R, Oo AMT, Stojcevski A (2016) Efficient photovoltaic system maximum power point tracking using a new technique. Energies 9(3):147CrossRefGoogle Scholar
  27. Solati S, Habibagahi G (2006) A genetic approach for determining the generalized interslice forces and the critical non-circular slip surface. Iran J Sci Technol Trans B Eng 30(1):1–20Google Scholar
  28. Sun J, Li J, Liu Q (2008) Search for critical slip surface in slope stability analysis by spline-based GA method. J Geotech Geoenviron Eng 134(2):252–256CrossRefGoogle Scholar
  29. Vanithasri M, Balamurugan R, Lakshminarasimman L (2016) Modified radial movement optimization (MRMO) technique for estimating the parameters of fuel cost function in thermal power plants. Eng Sci Technol Int J 19(4):2035–2042CrossRefGoogle Scholar
  30. Wan W, Cao P, Feng T, Yuan HP (2005) Improved genetic algorithm freely searching for dangerous slip surface of slope. J Cent South Univ Technol 12(6):749–752CrossRefGoogle Scholar
  31. Wen SJ, Li Y, Chen X (2011) Stability analysis of slope with arbitrary sliding surface on multi strata using minimum potential energy principle. Adv Mater Res 250-3:2588–2591CrossRefGoogle Scholar
  32. Yamagami T, Ueta Y (1988) Search for noncircular slip surfaces by the Morgenstern-Price method. In: Proceedings. 6th international conference numerical methods in geomech, pp 1335–1340Google Scholar
  33. Zhang GX, Liu BC (2002) Analysis of slope slip surface and stability by the potential slip surface theory. China Civ Eng J 35(6):82–85 (in Chinese)Google Scholar
  34. Zhou XP, Cheng H (2013) Analysis of stability of three-dimensional slopes using the rigorous limit equilibrium method. Eng Geol 160(12):21–33CrossRefGoogle Scholar
  35. Zhu DY, Lee CF, Qian QH, Zou ZS, Sun F (2001) A new procedure for computing the factor of safety using the Morgenstern–Price method. Can Geotech J 38(4):882–888CrossRefGoogle Scholar
  36. Zolfaghari AR, Heath AC, Mccombie PF (2005) Simple genetic algorithm search for critical non-circular failure surface in slope stability analysis. Comput Geotech 32(3):139–152CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Civil EngineeringCentral South UniversityChangshaPeople’s Republic of China

Personalised recommendations