Research article Special Issues

Deformation and failure analysis of heterogeneous slope using nonlinear spatial probabilistic finite element method

  • Received: 08 July 2024 Revised: 21 August 2024 Accepted: 28 August 2024 Published: 11 September 2024
  • MSC : 65D20, 65D30, 74C10, 74S05

  • Slope failures in hilly terrain impact the social and economic balance of the community. The major reasons for these slope failures are steeper slopes, climate factors, seismic activity, nearby excavations, and construction. Natural slopes show significant heterogeneity due to the inherent randomness in material properties and geometric nonlinearities. Effective slope stability analysis solutions can be achieved by incorporating probabilistic approaches. We present a comprehensive method to develop and analyze a heterogeneous two-dimensional slope model, utilizing a non-linear-spatial-probabilistic-finite element method under a plane strain condition. The developed slope model encompasses geometrical and material nonlinearity with a uniform random distribution over the space. Also, the present slope model integrates the Mohr-Coulomb's constitutive model for elastoplastic analysis to capture more realistic and complex behavior. A benchmark soil slope problem was modeled using the spatial probabilistic finite element method, comprising all six material properties with uniform spatial uncertainties. These material properties are elastic modulus, unit weight, cohesion, friction angle, and dilation angle. During the numerical simulation, the detailed deformations, stress patterns, strain patterns, potential pre-failure zone, and failure characteristics of heterogeneous slopes were achieved under self-weight and step loading sequences. Nodal failure and probability of nodal failure were introduced as two novel quantitative parameters for more insights into failure investigations. The testbench slope model was subjected to self-weight load and external 100-step loading sequences with a loading increment of -0.1 kN/m. The percentage probability of nodal failure was obtained at 40.46% considering uniformly distributed material uncertainties with a 10% coefficient of variation. The developed testbench slope model was also simulated for different values of the coefficient of variation (ranging from 0% to 50%) and comparatively investigated. The detailed deformation patterns, thorough profiles of stresses-strains, failure zones, and failure characteristics provided valuable insights into geotechnical engineering practices.

    Citation: Peeyush Garg, Pradeep Kumar Gautam, Amit Kumar Verma, Gnananandh Budi. Deformation and failure analysis of heterogeneous slope using nonlinear spatial probabilistic finite element method[J]. AIMS Mathematics, 2024, 9(10): 26339-26370. doi: 10.3934/math.20241283

    Related Papers:

    [1] P. Pirmohabbati, A. H. Refahi Sheikhani, H. Saberi Najafi, A. Abdolahzadeh Ziabari . Numerical solution of full fractional Duffing equations with Cubic-Quintic-Heptic nonlinearities. AIMS Mathematics, 2020, 5(2): 1621-1641. doi: 10.3934/math.2020110
    [2] SAIRA, Wenxiu Ma, Suliman Khan . An efficient numerical method for highly oscillatory logarithmic-algebraic singular integrals. AIMS Mathematics, 2025, 10(3): 4899-4914. doi: 10.3934/math.2025224
    [3] Kai Wang, Guicang Zhang . Curve construction based on quartic Bernstein-like basis. AIMS Mathematics, 2020, 5(5): 5344-5363. doi: 10.3934/math.2020343
    [4] Taher S. Hassan, Amir Abdel Menaem, Hasan Nihal Zaidi, Khalid Alenzi, Bassant M. El-Matary . Improved Kneser-type oscillation criterion for half-linear dynamic equations on time scales. AIMS Mathematics, 2024, 9(10): 29425-29438. doi: 10.3934/math.20241426
    [5] Dexin Meng . Wronskian-type determinant solutions of the nonlocal derivative nonlinear Schrödinger equation. AIMS Mathematics, 2025, 10(2): 2652-2667. doi: 10.3934/math.2025124
    [6] Samia BiBi, Md Yushalify Misro, Muhammad Abbas . Smooth path planning via cubic GHT-Bézier spiral curves based on shortest distance, bending energy and curvature variation energy. AIMS Mathematics, 2021, 6(8): 8625-8641. doi: 10.3934/math.2021501
    [7] Chunli Li, Wenchang Chu . Remarkable series concerning (3nn) and harmonic numbers in numerators. AIMS Mathematics, 2024, 9(7): 17234-17258. doi: 10.3934/math.2024837
    [8] Beatriz Campos, Alicia Cordero, Juan R. Torregrosa, Pura Vindel . Dynamical analysis of an iterative method with memory on a family of third-degree polynomials. AIMS Mathematics, 2022, 7(4): 6445-6466. doi: 10.3934/math.2022359
    [9] A. Palanisamy, J. Alzabut, V. Muthulakshmi, S. S. Santra, K. Nonlaopon . Oscillation results for a fractional partial differential system with damping and forcing terms. AIMS Mathematics, 2023, 8(2): 4261-4279. doi: 10.3934/math.2023212
    [10] Tongzhu Li, Ruiyang Lin . Classification of Möbius homogeneous curves in R4. AIMS Mathematics, 2024, 9(8): 23027-23046. doi: 10.3934/math.20241119
  • Slope failures in hilly terrain impact the social and economic balance of the community. The major reasons for these slope failures are steeper slopes, climate factors, seismic activity, nearby excavations, and construction. Natural slopes show significant heterogeneity due to the inherent randomness in material properties and geometric nonlinearities. Effective slope stability analysis solutions can be achieved by incorporating probabilistic approaches. We present a comprehensive method to develop and analyze a heterogeneous two-dimensional slope model, utilizing a non-linear-spatial-probabilistic-finite element method under a plane strain condition. The developed slope model encompasses geometrical and material nonlinearity with a uniform random distribution over the space. Also, the present slope model integrates the Mohr-Coulomb's constitutive model for elastoplastic analysis to capture more realistic and complex behavior. A benchmark soil slope problem was modeled using the spatial probabilistic finite element method, comprising all six material properties with uniform spatial uncertainties. These material properties are elastic modulus, unit weight, cohesion, friction angle, and dilation angle. During the numerical simulation, the detailed deformations, stress patterns, strain patterns, potential pre-failure zone, and failure characteristics of heterogeneous slopes were achieved under self-weight and step loading sequences. Nodal failure and probability of nodal failure were introduced as two novel quantitative parameters for more insights into failure investigations. The testbench slope model was subjected to self-weight load and external 100-step loading sequences with a loading increment of -0.1 kN/m. The percentage probability of nodal failure was obtained at 40.46% considering uniformly distributed material uncertainties with a 10% coefficient of variation. The developed testbench slope model was also simulated for different values of the coefficient of variation (ranging from 0% to 50%) and comparatively investigated. The detailed deformation patterns, thorough profiles of stresses-strains, failure zones, and failure characteristics provided valuable insights into geotechnical engineering practices.



    We consider the following family of nonlinear oscillators

    yzz+k(y)y3z+h(y)y2z+f(y)yz+g(y)=0, (1.1)

    where k, h, f0 and g0 are arbitrary sufficiently smooth functions. Particular members of (1.1) are used for the description of various processes in physics, mechanics and so on and they also appear as invariant reductions of nonlinear partial differential equations [1,2,3].

    Integrability of (1.1) was studied in a number of works [4,5,6,7,8,9,10,11,12,13,14,15,16]. In particular, in [15] linearization of (1.1) via the following generalized nonlocal transformations

    w=F(y),dζ=(G1(y)yz+G2(y))dz. (1.2)

    was considered. However, equivalence problems with respect to transformations (1.2) for (1.1) and its integrable nonlinear subcases have not been studied previously. Therefore, in this work we deal with the equivalence problem for (1.1) and its integrable subcase from the Painlevé-Gambier classification. Namely, we construct an equivalence criterion for (1.1) and a non-canonical form of Ince Ⅶ equation [17,18]. As a result, we obtain two new integrable subfamilies of (1.1). What is more, we demonstrate that for any equation from (1.1) that satisfy one of these equivalence criteria one can construct an autonomous first integral in the parametric form. Notice that we use Ince Ⅶ equation because it is one of the simplest integrable members of (1.1) with known general solution and known classification of invariant curves.

    Moreover, we show that transformations (1.2) preserve autonomous invariant curves for equations from (1.1). Since the considered non-canonical form of Ince Ⅶ equation admits two irreducible polynomial invariant curves, we obtain that any equation from (1.1), which is equivalent to it, also admits two invariant curves. These invariant curves can be used for constructing an integrating factor for equations from (1.1) that are equivalent to Ince Ⅶ equation. If this integrating factor is Darboux one, then the corresponding equation is Liouvillian integrable [19]. This demonstrates the connection between nonlocal equivalence approach and Darboux integrability theory and its generalizations, which has been recently discussed for a less general class of nonlocal transformations in [20,21,22].

    The rest of this work is organized as follows. In the next Section we present an equivalence criterion for (1.1) and a non-canonical form of the Ince Ⅶ equation. In addition, we show how to construct an autonomous first integral for an equation from (1.1) satisfying this equivalence criterion. We also demonstrate that transformations (1.2) preserve autonomous invariant curves for (1.1). In Section 3 we provide two examples of integrable equations from (1.1) and construct their parametric first integrals, invariant curves and integrating factors. In the last Section we briefly discuss and summarize our results.

    We begin with the equivalence criterion between (1.1) and a non-canonical form of the Ince Ⅶ equation, that is [17,18]

    wζζ+3wζ+ϵw3+2w=0. (2.1)

    Here ϵ0 is an arbitrary parameter, which can be set, without loss of generality, to be equal to ±1.

    The general solution of (1.1) is

    w=e(ζζ0)cn{ϵ(e(ζζ0)C1),12}. (2.2)

    Here ζ0 and C1 are arbitrary constants and cn is the Jacobian elliptic cosine. Expression (2.2) will be used below for constructing autonomous parametric first integrals for members of (1.1).

    The equivalence criterion between (1.1) and (2.1) can be formulated as follows:

    Theorem 2.1. Equation (1.1) is equivalent to (2.1) if and only if either

    (I)25515lgp2qy+2352980l10+(3430q6667920p3)l514580qp310q276545lgqppy=0, (2.3)

    or

    (II)343l5972p3=0, (2.4)

    holds. Here

    l=9(fgygfy+fgh3kg2)2f3,p=gly3lgy+l(f23gh),q=25515gylp25103lgppy+686l58505p2(f23gh)l+6561p3. (2.5)

    The expression for G2 in each case is either

    (I)G2=126l2qp2470596l10(1333584p3+1372q)l5+q2, (2.6)

    or

    (II)G22=49l3G2+9p2189pl. (2.7)

    In all cases the functions F and G1 are given by

    F2=l81ϵG32,G1=G2(f3G2)3g. (2.8)

    Proof. We begin with the necessary conditions. Substituting (1.2) into (2.1) we get

    yzz+k(y)y3z+h(y)y2z+f(y)yz+g(y)=0, (2.9)

    where

    k=FG31(ϵF2+2)+3G21Fy+G1FyyFyG1,yG2Fy,h=G2Fyy+(6G1G2G2,y)Fy+3FG2G21(ϵF2+2)G2Fy,f=3G2(Fy+FG1(ϵF2+2))Fy,g=FG22(ϵF2+2)Fy. (2.10)

    As a consequence, we obtain that (1.1) can be transformed into (2.1) if it is of the form (2.9) (or (1.1)).

    Conversely, if the functions F, G1 and G2 satisfy (2.10) for some values of k, h, f and g, then (1.1) can be mapped into (2.1) via (1.2). Thus, we see that the compatibility conditions for (2.10) as an overdertmined system of equations for F, G1 and G2 result in the necessary and sufficient conditions for (1.1) to be equivalent to (2.1) via (1.2).

    To obtain the compatibility conditions, we simplify system (2.10) as follows. Using the last two equations from (2.10) we find the expression for G1 given in (2.8). Then, with the help of this relation, from (2.10) we find that

    81ϵF2G32l=0, (2.11)

    and

    567lG32+(243lgh81lf281gly+243lgy)G27l2=0,243lgG2,y+324lG3281glyG2+2l2=0, (2.12)

    Here l is given by (2.5).

    As a result, we need to find compatibility conditions only for (2.12). In order to find the generic case of this compatibility conditions, we differentiate the first equation twice and find the expression for G22 and condition (2.3). Differentiating the first equation from (2.12) for the third time, we obtain (2.6). Further differentiation does not lead to any new compatibility conditions. Particular case (2.4) can be treated in the similar way.

    Finally, we remark that the cases of l=0, p=0 and q=0 result in the degeneration of transformations (1.2). This completes the proof.

    As an immediate corollary of Theorem 2.1 we get

    Corollary 2.1. If coefficients of an equation from (1.1) satisfy either (2.3) or (2.4), then an autonomous first integral of this equation can be presented in the parametric form as follows:

    y=F1(w),yz=G2wζFyG1wζ. (2.13)

    Here w is the general solution of (2.1) given by (2.2). Notice also that, formally, (2.13) contains two arbitrary constants, namely ζ0 and C1. However, without loss of generality, one of them can be set equal to zero.

    Now we demonstrate that transformations (1.2) preserve autonomous invariant curves for equations from (1.1).

    First, we need to introduce the definition of an invariant curve for (1.1). We recall that Eq (1.1) can be transformed into an equivalent dynamical system

    yz=P,uz=Q,P=u,Q=ku3hu2fug. (2.14)

    A smooth function H(y,u) is called an invariant curve of (2.14) (or, equivalently, of (1.1)), if it is a nontrivial solution of [19]

    PHy+QHu=λH, (2.15)

    for some value of the function λ, which is called the cofactor of H.

    Second, we need to introduce the equation that is equivalent to (1.1) via (1.2). Substituting (1.2) into (1.1) we get

    wζζ+˜kw3ζ+˜hw2ζ+˜fwζ+˜g=0, (2.16)

    where

    ˜k=kG32gG31+(G1,yhG1)G22+(fG1G2,y)G1G2F2yG22,˜h=(hFyFyy)G22(2fG1G2,y)G2Fy+3gG21FyF2yG22,˜f=fG23gG1G22,˜g=gFyG22. (2.17)

    An invariant curve for (2.16) can be defined in the same way as that for (1.1). Notice that, further, we will denote wζ as v.

    Theorem 2.2. Suppose that either (1.1) possess an invariant curve H(y,u) with the cofactor λ(y,u) or (2.16) possess an invariant curve ˜H(w,v) with the cofactor ˜λ(w,v). Then, the other equation also has an invariant curve and the corresponding invariant curves and cofactors are connected via

    H(y,u)=˜H(F,FyuG1u+G2),λ(y,u)=(G1u+G2)˜λ(F,FyuG1u+G2). (2.18)

    Proof. Suppose that ˜H(w,v) is an invariant curve for (2.16) with the cofactor ˜λ(w,v). Then it satisfies

    v˜Hw+(˜kv3˜hv2˜fv˜g)˜Hv=˜λ˜H. (2.19)

    Substituting (1.2) into (2.19) we get

    uHy+(ku3hu2fug)H=(G1u+G2)˜λ(F,FyuG1u+G2)H. (2.20)

    This completes the proof.

    As an immediate consequence of Theorem 2.2 we have that transformations (1.2) preserve autonomous first integrals admitted by members of (1.1), since they are invariant curves with zero cofactors.

    Another corollary of Theorem 2.2 is that any equation from (1.1) that is connected to (2.1) admits two invariant curves that correspond to irreducible polynomial invariant curves of (2.1). This invariant curves of (2.1) and the corresponding cofactors are the following (see, [23] formulas (3.18) and (3.19) taking into account scaling transformations)

    ˜H=±i2ϵ(v+w)+w2,˜λ=±2ϵw2. (2.21)

    Therefore, we have that the following statement holds:

    Corollary 2.2. If coefficients of an equation from (1.1) satisfy either (2.3) or (2.4), then is admits the following invariant curves with the corresponding cofactors

    H=±i2ϵ(FyuG1u+G2+F)+F2,λ=(G1u+G2)(±2ϵF2). (2.22)

    Let us remark that connections between (2.1) and non-autonomous variants of (1.1) can be considered via a non-autonomous generalization of transformations (1.2). However, one of two nonlocally related equations should be autonomous since otherwise nonlocal transformations do not map a differential equation into a differential equation [5].

    In this Section we have obtained the equivalence criterion between (1.1) and (2.1), that defines two new completely integrable subfamilies of (1.1). We have also demonstrated that members of these subfamilies posses an autonomous parametric first integral and two autonomous invariant curves.

    In this Section we provide two examples of integrable equations from (1.1) satisfying integrability conditions from Theorem 2.1.

    Example 1. One can show that the coefficients of the following cubic oscillator

    yzz12ϵμy(ϵμ2y4+2)2y3z6μyyz+2μ2y3(ϵμ2y4+2)=0, (3.1)

    satisfy condition (2.3) from Theorem 2.1. Consequently, Eq (3.1) is completely integrable and its general solution can be obtained from (2.2) by inverting transformations (1.2). However, it is more convenient to use Corollary 2.1 and present the autonomous first integral of (3.1) in the parametric form as follows:

    y=±wμ,yz=w(ϵw2+2)wζ2wζ+w(ϵw2+2), (3.2)

    where w is given by (2.2), ζ is considered as a parameter and ζ0, without loss of generality, can be set equal to zero. As a result, we see that (3.1) is integrable since it has an autonomous first integral.

    Moreover, using Corollary 2.2 one can find invariant curves admitted by (3.1)

    H1,2=y4[(2±ϵμy2)2(2ϵμy2)+2(ϵμy22ϵ)u]2μ2y2(ϵμ2y4+2)4u,λ1,2=±2(μy2(ϵμ2y4+2)2u)(2ϵμy22)y(ϵμ2y4+2) (3.3)

    With the help of the standard technique of the Darboux integrability theory [19], it is easy to find the corresponding Darboux integrating factor of (3.1)

    M=(ϵμ2y4+2)94(2ϵu2+(ϵμ2y4+2)2)34(μy2(ϵμ2y4+2)2u)32. (3.4)

    Consequently, equation is (3.1) Liouvillian integrable.

    Example 2. Consider the Liénard (1, 9) equation

    yzz+(biyi)yz+ajyj=0,i=0,4,j=0,,9. (3.5)

    Here summation over repeated indices is assumed. One can show that this equation is equivalent to (2.1) if it is of the form

    yzz9(y+μ)(y+3μ)3yz+2y(2y+3μ)(y+3μ)7=0, (3.6)

    where μ is an arbitrary constant.

    With the help of Corollary 2.1 one can present the first integral of (3.6) in the parametric form as follows:

    y=32ϵμw22ϵw,yz=77762ϵμ5wwζ(2ϵw2)5(2ϵwζ+(2ϵw+2ϵ)w), (3.7)

    where w is given by (2.2). Thus, one can see that (3.5) is completely integrable due to the existence of this parametric autonomous first integral.

    Using Corollary 2.2 we find two invariant curves of (3.6):

    H1=y2[(2y+3μ)(y+3μ)42u)](y+3μ)2[(y+3μ)4yu],λ1=6μ(uy(y+3μ)4)y(y+3μ), (3.8)

    and

    H2=y2(y+3μ)2y(y+3μ)4u,λ2=2(2y+3μ)(u2y(y+3μ)4)y(y+3μ). (3.9)

    The corresponding Darboux integrating factor is

    M=[y(y+3μ)4u]32[(2y+3μ)(y+3μ)42u]34. (3.10)

    As a consequence, we see that Eq (3.6) is Liouvillian integrable.

    Therefore, we see that equations considered in Examples 1 and 2 are completely integrable from two points of view. First, they possess autonomous parametric first integrals. Second, they have Darboux integrating factors.

    In this work we have considered the equivalence problem between family of Eqs (1.1) and its integrable member (2.1), with equivalence transformations given by generalized nonlocal transformations (1.2). We construct the corresponding equivalence criterion in the explicit form, which leads to two new integrable subfamilies of (1.1). We have demonstrated that one can explicitly construct a parametric autonomous first integral for each equation that is equivalent to (2.1) via (1.2). We have also shown that transformations (1.2) preserve autonomous invariant curves for (1.1). As a consequence, we have obtained that equations from the obtained integrable subfamilies posses two autonomous invariant curves, which corresponds to the irreducible polynomial invariant curves of (2.1). This fact demonstrate a connection between nonlocal equivalence approach and Darboux and Liouvillian integrability approach. We have illustrate our results by two examples of integrable equations from (1.1).

    The author was partially supported by Russian Science Foundation grant 19-71-10003.

    The author declares no conflict of interest in this paper.



    [1] A. K. Turner, Social and environmental impacts of landslides, Innov. Infrastruct. Solut., 3 (2018), 70. https://doi.org/10.1007/s41062-018-0175-y doi: 10.1007/s41062-018-0175-y
    [2] P. Lacroix, A. L. Handwerger, G. Bièvre, Life and death of slow-moving landslides, Nat. Rev. Earth Environ., 1 (2020), 404–419. https://doi.org/10.1038/s43017-020-0072-8 doi: 10.1038/s43017-020-0072-8
    [3] S. T. McColl, Landslide causes and triggers, In: Landslide hazards, risks, and disasters, 2 Eds., Amsterdam: Elsevier, 2022, 13–41. https://doi.org/10.1016/B978-0-12-818464-6.00011-1
    [4] R. Paranunzio, M. Chiarle, F. Laio, G.. Nigrelli, L. Turconi, F. Luino, New insights in the relation between climate and slope failures at high-elevation sites, Theor. Appl. Climatol., 137 (2019), 1765–1784. https://doi.org/10.1007/s00704-018-2673-4 doi: 10.1007/s00704-018-2673-4
    [5] J. F. Shroder, L. Cvercková, K. L. Mulhern, Slope-failure analysis and classification: Review of a century of effort, Phys. Geogr., 26 (2005), 216–247. https://doi.org/10.2747/0272-3646.26.3.216 doi: 10.2747/0272-3646.26.3.216
    [6] M. J. Froude, D. N. Petley, Global fatal landslide occurrence from 2004 to 2016, Nat. Hazards Earth Syst. Sci., 18 (2018), 2161–2181. https://doi.org/10.5194/nhess-18-2161-2018 doi: 10.5194/nhess-18-2161-2018
    [7] A. Braathen, L. H. Blikra, S. S. Berg, F. Karlsen, Rock-slope failures in Norway; type, geometry, deformation mechanisms and stability, Norw. J. Geol., 84 (2004), 67–88.
    [8] J. M. Duncan, State of the art: limit equilibrium and finite-element analysis of slopes, Journal of Geotechnical Engineering, 122 (1996), 577–596. https://doi.org/10.1061/(ASCE)0733-9410(1996)122:7(577) doi: 10.1061/(ASCE)0733-9410(1996)122:7(577)
    [9] Y. H. Huang, Slope stability analysis by the limit equilibrium method: Fundamentals and methods, Reston: ASCE Press, 2013. https://doi.org/10.1061/9780784412886
    [10] W. F. Chen, Limit analysis and soil plasticity, Burlington: Elsevier, 2013.
    [11] B. Leshchinsky, S. Ambauen, Limit equilibrium and limit analysis: comparison of benchmark slope stability problems, J. Geotech. Geoenviron., 141 (2015), 04015043. https://doi.org/10.1061/(ASCE)GT.1943-5606.0001347 doi: 10.1061/(ASCE)GT.1943-5606.0001347
    [12] A. Burman, S. P. Acharya, R. Sahay, D. Maity, A comparative study of slope stability analysis using traditional limit equilibrium method and finite element method, Asian Journal of Civil Engineering, 16 (2015), 467–492.
    [13] R. K. H. Ching, D. G. Fredlund, Some difficulties associated with the limit equilibrium method of slices, Can. Geotech. J., 20 (1983), 661–672. https://doi.org/10.1139/t83-074 doi: 10.1139/t83-074
    [14] S. Ullah, M. U. Khan, G. Rehman, A brief review of the slope stability analysis methods, Geological Behavior, 4 (2020), 73–77. https://doi.org/10.26480/gbr.02.2020.73.77 doi: 10.26480/gbr.02.2020.73.77
    [15] Y. N. Zheng, L. F. Zheng, H. Y. Zhan, Q. F. Huang, C. J. Jia, Z. Li, Study on failure mechanism of soil–rock slope with FDM-DEM method, Sustainability, 14 (2022), 17015. https://doi.org/10.3390/su142417015 doi: 10.3390/su142417015
    [16] Z. Y. Yin, J. C. Teng, H. L. Wang, Y. F. Jin, A MATLAB-based educational platform for analysis of slope stability, Comput. Appl. Eng. Educ., 30 (2022), 575–588. https://doi.org/10.1002/cae.22474 doi: 10.1002/cae.22474
    [17] G. R. Lindfield, J. E. T. Penny, Numerical methods: using MATLAB, 3 Eds., New York: Academic Press, 2012. https://doi.org/10.1016/C2010-0-67189-6
    [18] L. Y. Zhang, W. M. Shi, Y. R. Zheng, The slope stability analysis by FEM under the plane strain condition, Chinese Journal of Geotechnical Engineering, 24 (2002), 487–490.
    [19] F. Darve, F. Laouafa, Plane strain instabilities in soil: application to slopes stability, In: Numerical models in geomechanics, Boca Raton: CRC Press, 2020, 85–90. https://doi.org/10.1201/9781003078548-16
    [20] E. M. Dawson, W. H. Roth, Slope stability analysis with FLAC, In: FLAC and numerical modeling in geomechanics, Boca Raton: CRC Press, 2020, 3–9. https://doi.org/10.1201/9781003078531-2
    [21] Y. L. Tan, J. J. Cao, W. X. Xiang, W. Z. Xu, J. W. Tian, Y. Gou, Slope stability analysis of saturated–unsaturated based on the GEO-studio: a case study of Xinchang slope in Lanping County, Yunnan Province, China, Environ. Earth Sci., 82 (2023), 322. https://doi.org/10.1007/s12665-023-11006-x doi: 10.1007/s12665-023-11006-x
    [22] A. Torok, A. Barsi, G. Bogoly, T. Lovas, Á. Somogyi, P. Görög, Slope stability and rockfall assessment of volcanic tuffs using RPAS with 2-D FEM slope modelling, Nat. Hazards Earth Syst. Sci., 18 (2018), 583–597. https://doi.org/10.5194/nhess-18-583-2018 doi: 10.5194/nhess-18-583-2018
    [23] R. Singh, R. K. Umrao, T. N. Singh, Hill slope stability analysis using two and three dimensions analysis: A comparative study, J. Geol. Soc. India, 89 (2017), 295–302. https://doi.org/10.1007/s12594-017-0602-2 doi: 10.1007/s12594-017-0602-2
    [24] D. V. Griffiths, G. A. Fenton, Probabilistic slope stability analysis by finite elements, J. Geotech. Geoenviron., 130 (2004), 507–518. https://doi.org/10.1061/(ASCE)1090-0241(2004)130:5(507) doi: 10.1061/(ASCE)1090-0241(2004)130:5(507)
    [25] J. M. Duncan, Factors of safety and reliability in geotechnical engineering, J. Geotech. Geoenviron., 126 (2000), 307–316. https://doi.org/10.1061/(ASCE)1090-0241(2000)126:4(307) doi: 10.1061/(ASCE)1090-0241(2000)126:4(307)
    [26] K. Farah, M. Ltifi, T. Abichou, H. Hassis, Comparison of different probabilistic methods for analyzing slope stability, Int. J. Civ. Eng., 12 (2014), 264–268.
    [27] V. Renaud, M. A. Heib, Probabilistic slope stability analysis: A novel distribution for soils exhibiting highly variable spatial properties, Probabilist. Eng. Mech., 76 (2024), 103586. https://doi.org/10.1016/j.probengmech.2024.103586 doi: 10.1016/j.probengmech.2024.103586
    [28] M. Matsuo, K. Kuroda, Probabilistic approach to design of embankments, Soils Found., 14 (1974), 1–17. https://doi.org/10.3208/sandf1972.14.2_1 doi: 10.3208/sandf1972.14.2_1
    [29] A. Alfredo, H. Wilson, Probability concepts in engineering planning and design, New York: John Wiley & Sons, 1975.
    [30] E. E. Alonso, Risk analysis of slopes and its application to slopes in Canadian sensitive clays, Geotechnique, 26 (1976), 453–472. https://doi.org/10.1680/geot.1976.26.3.453 doi: 10.1680/geot.1976.26.3.453
    [31] E. H. Vanmarcke, Reliability of earth slopes, Journal of the Geotechnical Engineering Division, 103 (1977), 1247–1265. https://doi.org/10.1061/AJGEB6.00005 doi: 10.1061/AJGEB6.00005
    [32] O. Ditlevsen, P. Bjerager, Methods of structural systems reliability, Struct. Saf., 3 (1986), 195–229. https://doi.org/10.1016/0167-4730(86)90004-4 doi: 10.1016/0167-4730(86)90004-4
    [33] H. El-Ramly, N. R. Morgenstern, D. M. Cruden, Probabilistic slope stability analysis for practice, Can. Geotech. J., 39 (2002), 665–683. https://doi.org/10.1139/t02-034 doi: 10.1139/t02-034
    [34] O. D. Ditlevsen, H. O. Madsen, Structural reliability methods, Chichester: John Wiley & Sons, 1996.
    [35] I. E. Zevgolis, A. V. Deliveris, N. C. Koukouzas, Probabilistic design optimization and simplified geotechnical risk analysis for large open pit excavations, Comput. Geotech., 103 (2018), 153–164. https://doi.org/10.1016/j.compgeo.2018.07.024 doi: 10.1016/j.compgeo.2018.07.024
    [36] C. Obregon, H. Mitri, Probabilistic approach for open pit bench slope stability analysis–A mine case study, Int. J. Min. Sci. Techno., 29 (2019), 629–640. https://doi.org/10.1016/j.ijmst.2019.06.017 doi: 10.1016/j.ijmst.2019.06.017
    [37] V. Merrien-Soukatchoff, T. Korini, A. Thoraval, Use of an integrated discrete fracture network code for stochastic stability analyses of fractured rock masses, Rock Mech. Rock Eng., 45 (2012), 159–181. https://doi.org/10.1007/s00603-011-0136-7 doi: 10.1007/s00603-011-0136-7
    [38] L. J. Wu, H. X. Zhang, X. H. Yang, F. R. Wang, A second-order finite difference method for the multi-term fourth-order integral–differential equations on graded meshes, Comp. Appl. Math., 41 (2022), 313. https://doi.org/10.1007/s40314-022-02026-7 doi: 10.1007/s40314-022-02026-7
    [39] X. H. Yang, Z. M. Zhang, Analysis of a new NFV scheme preserving DMP for two-dimensional sub-diffusion equation on distorted meshes, J. Sci. Comput., 99 (2024), 80. https://doi.org/10.1007/s10915-024-02511-7 doi: 10.1007/s10915-024-02511-7
    [40] W. Wang, H. X. Zhang, Z. Y. Zhou, X. H. Yang, A fast compact finite difference scheme for the fourth-order diffusion-wave equation, Int. J. Comput. Math., 101 (2024), 170–193. https://doi.org/10.1080/00207160.2024.2323985 doi: 10.1080/00207160.2024.2323985
    [41] X. H. Yang, W. L. Qiu, H. X. Zhang, L. Tang, An efficient alternating direction implicit finite difference scheme for the three-dimensional time-fractional telegraph equation, Comput. Math. Appl., 102 (2021), 233–247. https://doi.org/10.1016/j.camwa.2021.10.021 doi: 10.1016/j.camwa.2021.10.021
    [42] M. L. Napoli, M. Barbero, E. Ravera, C. Scavia, A stochastic approach to slope stability analysis in bimrocks, Int. J. Rock Mech. Min., 101 (2018), 41–49. https://doi.org/10.1016/j.ijrmms.2017.11.009 doi: 10.1016/j.ijrmms.2017.11.009
    [43] I. Molchanov, Foundations of stochastic geometry and theory of random sets, In: Stochastic geometry, spatial statistics and random fields, Berlin: Springer, 2012, 1–20. https://doi.org/10.1007/978-3-642-33305-7_1
    [44] D. V. Griffiths, J. S. Huang, G. A. Fenton, Influence of spatial variability on slope reliability using 2-D random fields, J. Geotech. Geoenvirong., 135 (2009), 1367–1378. https://doi.org/10.1061/(ASCE)GT.1943-5606.0000099 doi: 10.1061/(ASCE)GT.1943-5606.0000099
    [45] A. M. Afrapoli, M. Osanloo, Determination and stability analysis of ultimate open-pit slope under geomechanical uncertainty, Int. J. Min. Sci. Techno., 24 (2014), 105–110. https://doi.org/10.1016/j.ijmst.2013.12.018 doi: 10.1016/j.ijmst.2013.12.018
    [46] H. Shen, S. M. Abbas, Rock slope reliability analysis based on distinct element method and random set theory, Int. J. Rock Mech. Min., 61 (2013), 15–22. https://doi.org/10.1016/j.ijrmms.2013.02.003 doi: 10.1016/j.ijrmms.2013.02.003
    [47] R. G. Ghanem, P. D. Spanos, Stochastic finite elements: A spectral approach, New York: Dover Publications, 2003. https://doi.org/10.1007/978-1-4612-3094-6
    [48] X. Li, Q. L. Liao, J. M. He, In-situ tests and a stochastic structural model of rock and soil aggregate in the Three Gorges Reservoir area, China, Int. J. Rock Mech. Min., 41 (2004), 702–707. https://doi.org/10.1016/j.ijrmms.2004.03.122 doi: 10.1016/j.ijrmms.2004.03.122
    [49] B. Pandit, G. Tiwari, G. M. Latha, G. L. S. Babu, Stability analysis of a large gold mine open-pit slope using advanced probabilistic method, Rock Mech. Rock Eng., 51 (2018), 2153–2174. https://doi.org/10.1007/s00603-018-1465-6 doi: 10.1007/s00603-018-1465-6
    [50] S. Sharma, I. Roy, Slope failure of waste rock dump at Jayant opencast mine, India: A case study, International Journal of Applied Engineering Research, 10 (2015), 33006–33012.
    [51] M. R. Bishwal, P. Sen, M. Jawed, Characterization of shear strength properties of spoil dump based on their constituent material, International Journal of Applied Engineering Research, 12 (2017), 8590–8594.
    [52] C. Oggeri, R. Vinai, Characterisation of geomaterials and non-conventional waste streams for their reuse as engineered materials, E3S Web of Conferences, 2020, 06002. https://doi.org/10.1051/e3sconf/202019506002 doi: 10.1051/e3sconf/202019506002
    [53] I. E. Zevgolis, Geotechnical characterization of mining rock waste dumps in central Evia, Greece, Environ. Earth Sci., 77 (2018), 566. https://doi.org/10.1007/s12665-018-7743-5 doi: 10.1007/s12665-018-7743-5
    [54] I. E. Zevgolis, A. I. Theocharis, A. V. Deliveris, N. C. Koukouzas, C. Roumpos, A. M. Marshall, Geotechnical characterization of fine-grained spoil material from surface coal mines, J. Geotech. Geoenviron., 147 (2021), 04021050. https://doi.org/10.1061/(ASCE)GT.1943-5606.0002550 doi: 10.1061/(ASCE)GT.1943-5606.0002550
    [55] K. Arai, K. Tagyo, Determination of noncircular slip surface giving the minimum factor of safety in slope stability analysis, Soils Found., 25 (1985), 43–51. https://doi.org/10.3208/sandf1972.25.43 doi: 10.3208/sandf1972.25.43
    [56] S. H. Li, L. Z. Wu, An improved salp swarm algorithm for locating critical slip surface of slopes, Arab. J. Geosci., 14 (2021), 359. https://doi.org/10.1007/s12517-021-06687-2 doi: 10.1007/s12517-021-06687-2
    [57] J. Singh, A. K. Verma, H. Banka, R. Kumar, A. Jaiswal, Optics-based metaheuristic approach to assess critical failure surfaces in both circular and non-circular failure modes for slope stability analysis, Rock Mechanics Bulletin, 3 (2024), 100084. https://doi.org/10.1016/j.rockmb.2023.100084 doi: 10.1016/j.rockmb.2023.100084
    [58] A. R. Kashani, R. Chiong, S. Mirjalili, A. H. Gandomi, Particle swarm optimization variants for solving geotechnical problems: review and comparative analysis, Arch. Computat. Methods Eng., 28 (2021), 1871–1927. https://doi.org/10.1007/s11831-020-09442-0 doi: 10.1007/s11831-020-09442-0
    [59] J. Singh, H. Banka, A. K. Verma, Locating critical failure surface using meta-heuristic approaches: A comparative assessment, Arab. J. Geosci., 12 (2019), 307. https://doi.org/10.1007/s12517-019-4435-8 doi: 10.1007/s12517-019-4435-8
    [60] Z. Y. Xiao, B. Tian, X. C. Lu, Locating the critical slip surface in a slope stability analysis by enhanced fireworks algorithm, Cluster Comput., 22 (2019), 719–729. https://doi.org/10.1007/s10586-017-1196-6 doi: 10.1007/s10586-017-1196-6
    [61] N. Himanshu, A. Burman, V. Kumar, Assessment of optimum location of non-circular failure surface in soil slope using unified particle swarm optimization, Geotech. Geol. Eng., 38 (2020), 2061–2083. https://doi.org/10.1007/s10706-019-01148-w doi: 10.1007/s10706-019-01148-w
    [62] O. C. Zienkiewicz, R. L. Taylor, J. Z. Zhu, The finite element method: its basis and fundamentals, Oxford: Butterworth-Heinemann, 2013. https://doi.org/10.1016/C2009-0-24909-9
    [63] K. H. Huebner, D. L. Dewhirst, D. E. Smith, T. G. Byrom, The finite element method for engineers, 4 Eds., New York: John Wiley & Sons, 2001.
    [64] H. Nguyen‐Xuan, S. Bordas, H. Nguyen‐Dang, Smooth finite element methods: convergence, accuracy and properties, Int. J. Numer. Meth. Eng., 74 (2008), 175–208. https://doi.org/10.1002/nme.2146 doi: 10.1002/nme.2146
    [65] P. Duxbury, X. K. Li, Development of elasto-plastic material models in a natural coordinate system, Comput. Method. Appl. M., 135 (1996), 283–306. https://doi.org/10.1016/0045-7825(95)00950-7 doi: 10.1016/0045-7825(95)00950-7
    [66] L. E. Baker, R. S. Sandhu, Application of Elasto-Plastic analysis in rock mechanics by finite element method, The 11th U.S. Symposium on Rock Mechanics (USRMS), Berkeley, California,, 1969.
    [67] H. Zheng, D. F. Liu, C. G. Li, Slope stability analysis based on elasto‐plastic finite element method, Int. J. Numer. Meth. Eng., 64 (2005), 1871–1888. https://doi.org/10.1002/nme.1406 doi: 10.1002/nme.1406
    [68] X. H. Yang, H. X. Zhang, The uniform l1 long-time behavior of time discretization for time-fractional partial differential equations with nonsmooth data, Appl. Math. Lett., 124 (2022), 107644. https://doi.org/10.1016/j.aml.2021.107644 doi: 10.1016/j.aml.2021.107644
    [69] X. H. Yang, H. X. Zhang, Q. Zhang, G. W. Yuan, Z. Q. Sheng, The finite volume scheme preserving maximum principle for two-dimensional time-fractional Fokker–Planck equations on distorted meshes, Appl. Math. Lett., 97 (2019), 99–106. https://doi.org/10.1016/j.aml.2019.05.030 doi: 10.1016/j.aml.2019.05.030
  • This article has been cited by:

    1. Dmitry I. Sinelshchikov, Linearizabiliy and Lax representations for cubic autonomous and non-autonomous nonlinear oscillators, 2023, 01672789, 133721, 10.1016/j.physd.2023.133721
    2. Jaume Giné, Xavier Santallusia, Integrability via algebraic changes of variables, 2024, 184, 09600779, 115026, 10.1016/j.chaos.2024.115026
    3. Meryem Belattar, Rachid Cheurfa, Ahmed Bendjeddou, Paulo Santana, A class of nonlinear oscillators with non-autonomous first integrals and algebraic limit cycles, 2023, 14173875, 1, 10.14232/ejqtde.2023.1.50
    4. Jaume Giné, Dmitry Sinelshchikov, Integrability of Oscillators and Transcendental Invariant Curves, 2025, 24, 1575-5460, 10.1007/s12346-024-01182-x
  • Reader Comments
  • © 2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(1126) PDF downloads(100) Cited by(0)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog