# Finite Analytic Method for One-Dimensional Nonlinear Consolidation under Time-Dependent Loading

Authors: Dawei Cheng; Wenke Wang; Xi Chen; Zaiyong Zhang
Journal: Shock and Vibration
 (2017)

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## Abstract

For one-dimensional (1D) nonlinear consolidation, the governing partial differential equation is nonlinear. This paper develops the finite analytic method (FAM) to simulate 1D nonlinear consolidation under different time-dependent loading and initial conditions. To achieve this, the assumption of constant initial effective stress is not considered and the governing partial differential equation is transformed into the diffusion equation. Then, the finite analytic implicit scheme is established. The convergence and stability of finite analytic numerical scheme are proven by a rigorous mathematical analysis. In addition, the paper obtains three corrected semianalytical solutions undergoing suddenly imposed constant loading, single ramp loading, and trapezoidal cyclic loading, respectively. Comparisons of the results of FAM with the three semianalytical solutions and the result of FDM, respectively, show that the FAM can obtain stable and accurate numerical solutions and ensure the convergence of spatial discretization for 1D nonlinear consolidation.


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## Body

## 1. Introduction

In geotechnical engineering, subsoil is subjected to complicated time-dependent loading paths which are induced by different vibration sources, such as wave action, groundwater level cyclic variation, filling and discharging in silos and tanks, vehicular traffic, blast, and earthquake. In these vibration sources, such as waves, changes in water table, loading and unloading in the granary and water towers, and vehicle traffic can cause regular time-dependent loading paths [1, 2]. However, time-dependent loading paths induced by blast, earthquake, and so on are irregular [1, 3]. Many discriminant methods, just like the waveform spectrum analysis, multivariate statistical methods, and soft computing techniques, can identify these vibration sources [4, 5].Based on the cyclic loading classification discriminant criteria proposed by Zienkiewicz and Bettess [6], these relatively regular time-dependent loading paths, induced by wave action, groundwater level cyclic variation, and so forth, are considered as low frequency cyclic loadings. Three effects, including the soil movement inertia force and relative movement inertia force between pore water and soil skeleton, can be ignored in soil consolidation behavior under low frequency loadings. Many methods can be used to simulate these low frequency cyclic loadings, such as suddenly imposed constant loading, single ramp loading, rectangular cyclic loading, triangle cyclic loading, and trapezoidal cyclic loading [7–9]. A period of trapezoidal cyclic loadings includes four phases: loading phase, the maximum load phase, unloading phase, and rest phase, respectively. It is well known that when the duration time of the maximum loading phase is 0, the trapezoidal cyclic loading will be transformed into the triangle cyclic loading. However, when the duration time of loading and unloading phase is 0, the trapezoidal cyclic loading will be transformed into the rectangular cyclic loading [10]. Therefore, this paper will discuss the trapezoidal cyclic loading as a result of its flexibility. In addition, the suddenly imposed constant loading is a basic load form and the single ramp loading is the simplest time-dependent loading path. Thus, both of them are also discussed.The problem of consolidation under time-dependent loading has received attention by various authors [11–13]. Based on the linear relationship of the soil’s constitutive relation, Terzaghi and Fröhlich [11] extended Terzaghi’s linear consolidation theory to various cases of time-dependent loading following a single ramp loading. Olson [12] presented charts for 1D consolidation for the case of simple ramp loading assuming a constant consolidation coefficient. Favaretti and Soranzo [13] derived solutions for common types of cyclic loadings. However, soil’s constitutive relationships are actually nonlinear [10, 14]. The coefficient of compressibility decreases with increasing effective stress. In addition, the permeability coefficient decreases with void ratio decrease.Davis and Raymond [14] developed a nonlinear theory of consolidation assuming the relationship between void ratio and the logarithm of effective stress to conform to linear law, and the decrease in permeability coefficient is proportional to the compressibility. Xie et al. [10] derived a semianalytical solution for trapezoidal cyclic loading by assuming the validity of Davis’s nonlinear theory of consolidation. Razouki et al. [15] derived an analytical solution for consolidation under haversine cyclic loading based on the same assumption. Geng et al. [7] developed a semianalytical method to solve 1D consolidation behavior taking into account the relationship between void ratio and the logarithm of linear effective stress responses. Research has revealed that a stress-strain relation curve is more aligned with the hyperbolic model for certain types of soil, such as soft clay [16, 17]. Shi et al. [18] derived a semianalytical solution for consolidation under suddenly imposed constant loading, taking into account the stress-strain relation curve with a hyperbolic model and the decrease in permeability coefficient being proportional to the decrease in compressibility. Zhang et al. [19] adopted the same assumption, deriving a semianalytical solution for consolidation under trapezoidal cyclic loading. But, for simplifying nonlinear consolidation model, the assumptions of constant initial effective stress are often used, such as Davis’s model and Zhang’s model, which does not conform to practical condition and limits the application of those models in various initial conditions.It is worth noting that the governing partial differential equation is nonlinear partial differential equation. It is difficult to obtain analytical solution, except under specific conditions. So developing numerical solutions for solving complex realistic problems is necessary. As a methodology, the finite analytic method (FAM) was first introduced to mainly solve heat conduction and Navier–Strokes equations [20, 21]. The combination, under FAM of the numerical method and analytical method, gives higher precision, good numerical stability, and fast convergence and is widely employed in fluid mechanics and groundwater dynamics [22–25].In this paper, FAM is first developed to solve the governing partial differential equation of 1D nonlinear consolidation, taking into account the stress-strain behavior expressed by a hyperbolic model and where the permeability coefficient is proportional to compressibility. Then three corrected semianalytical solutions undergoing suddenly imposed constant loading, single ramp loading, and trapezoidal cyclic loading are, respectively, obtained, without the assumption of constant initial effective stress. Finally, the numerical solution of FAM is compared with these three semianalytical solutions and the numerical solution of finite difference method (FDM), respectively.


## 2. The Governing Partial Differential Equation of 1D Nonlinear Consolidation

Modify Terzaghi’s hypothesis as follows [19]:(a) According to results of oedometer tests, the stress-strain relation curve is fitted with a hyperbolic model [16, 17]:(1)σ′ε=E+nσ′,where σ′ is the effective stress; ε is the vertical strain; E is the initial elastic modulus; n=1/εf is the reciprocal of the final vertical strain. When n equals zero, the stress-strain relationship is linear.(b) According to results of oedometer tests, the coefficient of consolidationCv varies much less than the compressibility coefficient αv and may be taken as constant; that is, the decrease in permeability coefficient k is proportional to the decrease in compressibility coefficient αv [14]. The coefficient of consolidation Cv is constant; that is,(2)Cv=k1+e0αv=const,where e0 is the initial void ratio.(c) The initial effective stress is constant; that is,(3)σ0′=∫0Lγ′zdzL=12γ′L,where γ′ is the soil effective gravity and L is the depth of the calculation.(d) Imposed loadings change with time.Other assumptions are the same as those in Terzaghi’s theory.Based on the abovementioned assumptions, except hypothesis (c), the governing partial differential equation of 1D consolidation for time-dependent loading [19] can be established as follows:(4)-CvE1E+nσ′2∂2u∂z2-2nE+nσ′3∂σ′∂z∂u∂z=EE+nσ′2∂σ′∂t,where u is excess pore-water pressure and z is the height beneath the upper boundary.Note that hypothesis (c) means that the initial effective stress is the same for every point in depth, which does not conform to practical condition and limits the application of (4) in various initial conditions. Thus, hypothesis (c) will not be considered in the paper.By the principle of effective stress, this becomes(5)σ′=qt-u,whereq(t) is cyclic loading.By defining a new parameterω,(6)ω=1+e0σ′E+nσ′-1+e0qtE+nqt,(4) can be simplified to the following form:(7)Cv∂2ω∂z2=∂ω∂t+Rt,where R(t)=(E1+e0/[E+nq(t)]2)(dq(t)/dt).


## 3. Finite Analytic Scheme

In the FAM, the modeling domain of (7) can be discretized into small elements by using the spatial discretization Δz (Figure 1). A typical FAM element ej with the space step 2Δz in a given time interval Δt=tn-tn-1 is shown in Figure 1. The origin of local coordinates is symbolized by O. Therefore, the local element is(8)ej=-Δz≤z≤Δz,0≤t≤Δt.Figure 1
Domain and local element of finite analytical method.The space term is treated as the implicit scheme of the time term in local elementej. The unsteady term ∂ω/∂t takes the values at point O at the nth time step. R(t) also takes the values at the nth time step. At the (n+1)th time step, (7) can be written as follows:(9)Cv∂2ω∂z2n+1=∂ω∂tOn+Rtn,where (∂2ω/∂z2)n+1 indicates the values of the element at (n+1)th time step; ∂ω/∂tOn indicates the unsteady term taking the values at point O at the nth time step; R(t)n indicates thatR(t) takes the values at the nth time step.The unsteady term∂ω/∂t is approximated by (ωOn+1-ωOn)/Δt, and (9) can be normalized as follows:(10)∂2ω∂z2n+1≈1CvωOn+1-ωOnΔt+Rtt=nΔt,where ωOn+1 and ωOn indicate the unsteady term taking the values at point O at the (n+1)th and nth time step, respectively; R(t)t=nΔt indicates thatR(t) takes the values at the nth time step.Here,(11)f=1CvωOn+1-ωOnΔt+RnΔt.At the(n+1)th time step, (11) can be written as follows:(12)∂2ω∂z2n+1=f.The general solution of (12) is(13)ωn+1z=fz22+c1z+c2,where the constants c1 and c2 can be specified by two nodal values of ω at the nth time step (Wn and En in Figure 1); that is,(14)ωW=fΔz22-c1Δz+c2z=-Δz,ωE=fΔz22+c1Δz+c2z=Δz.Solving a system of equations composed of (14), the constants c1 and c2 are(15)c1=ωE-ωW2Δz,c2=ωE+ωW2-f2Δz2.Substituting (15) into (13) and letting the value of z be zero,(16)ωOn+1=ωE+ωW2-f2Δz2.Substituting (11) into (16),(17)ωOn+1=12+Δz2/CvΔtωE+12+Δz2/CvΔtωW+Δz2/CvΔt2+Δz2/CvΔtωOn-Δz2/Cv2+Δz2/CvΔtRnΔt.Supposingλ=Δz2/CvΔt, the local analytical solution for the element ej is then written as follows:(18)ωOn+1=12+λωE+12+λωW+λ2+λωOn-λΔt2+λRnΔt.This local analytical solution evaluated at the interior nodej of the element ej at the nth time step is(19)ωjn+1=12+λωj-1n+1+12+λωj+1n+1+λ2+λωjn-λΔt2+λRnΔt.Equation (19) is the FAM implicit scheme of the governing partial differential equation of 1D nonlinear consolidation. A set of algebraic equations can be formed from (19), which can be solved by the method of forward elimination and backward substitution. Associated with boundary conditions, the algebraic equations are solved iteratively for the variable ωjn (n=1,2,3,…,N, j=1,2,3,…,M). Here,N is the number of total time steps, andM is the number of total nodes in the domain. The excess pore-water at the node j and the nth time step is obtained by applying an inversion transformation for (5) and (6).


## 4. The Convergence and Stability of the FAM Scheme

### 4.1. Convergence of Finite Analytical Numerical Scheme

Errors of the FAM implicit scheme (19) are found by using (10). To demonstrate the convergence of FAM, the following equation is used to replace ∂ω/∂t in (9):(20)∂ω∂tjn=ωjn-ωjn-1Δt+OΔt.Here, O(Δt) is truncation error. ωjn represents the exact solution and ω~jn represents finite analytic numerical solution at the node j and the nth time step, respectively. The error between the exact solution ωjn and finite analytic numerical solution ω~jn can be written as εjn; thus,(21)εjn=ωjn-ω~jn.ω
j
n should satisfy the following:(22)ωjn=12+λωj-1n+12+λωj+1n+λ2+λωjn-1-λΔt2+λRnΔt+OΔt.Andω~jn should satisfy the following:(23)ω~jn=12+λω~j-1n+12+λω~j+1n+λ2+λω~jn-1-λΔt2+λRnΔt.Substituting (22) and (23) into (21),(24)εjn=12+λεj-1n+12+λεj+1n+λ2+λεjn-1+OΔt.Because the coefficients in (24) are positive,(25)εjn≤12+λεj-1n+12+λεj+1n+λ2+λεjn-1+Zjn-1,where Zjn-1=O(Δt).It can be shown that(26)εmaxn≤12+λεmaxn-1+12+λεmaxn-1+λ2+λεmaxn-1+Zmaxn-1,where(27)εmaxn-1=max⁡εj-1n-11≤j≤N-1,Zmaxn-1=max⁡Zjn-11≤j≤N-1,and that(28)εmaxn≤εmaxn-1+Zmaxn-1n=1,2,…,M.Because the finite analytical equation and the partial differential equation have the same initial condition, namely, n=1, the finite analytical solution is consistent with the exact solution. That is, εmax0=0.From (27), the following expressions can be obtained:(29)εmax1≤εmax0+Zmax0=Zmax0,εmax2≤εmax1+Zmax1≤Zmax0+Zmax1,⋮εmaxM≤εmaxM-1+ZmaxM-1≤Zmax0+Zmax1+⋯+ZmaxM-1.Therefore,(30)εmaxM≤M·Zmax=M·max⁡OΔt,where(31)Zmax=max⁡Zmaxn1≤n≤M.WhenΔt→0, εmaxM→0, thus ω~jn→ωjn. Thus, it revealed that the finite analytical scheme has uniform convergence.


### 4.2. Stability of the Finite Analytical Numerical Scheme

The stability of finite analytical scheme (19) can be proven as follows. Let ωn=ω0nω1n⋯ωmnT; taking account of calculation error, ω0 becomes ω0∗ and ωn becomes ωn∗. Thus, the error of any term is(32)ejn=ωjn-ωjn∗.From (19), the error ejn fits with(33)-1λej-1n+1+2+λλejn+1-1λej+1n+1=ejn.It can be proven that the error at(n+1)th time step ejn+1 is between the error at the node 0 and the (n+1)th time step e0n+1, the error at the node m and the (n+1)th time step emn+1, and the extreme of the error in nth time step ejn; that is, (34)mn≤ejn+1≤Mn,where(35)mn=min⁡e0n+1,ejn,emn+1,Mn=max⁡e0n+1,ejn,emn+1.Equation (34) can be proven as follows. Assume ekn+1=minj⁡ejn+1. When k=0 or k=m, there is ejn+1≥mn clearly. When 0<k<m, taking into account (33),(36)ekn+1=ekn+1λek-1n+1+ek+1n+1-2ekn+1≥ekn+1λekn+1+ekn+1-2ekn+1=ekn≥mn.Evidenced by the same token,ekn+1≤Mn.The finite analytical equation and the partial differential equation have the same boundary condition, namely,e0n=emn=0, and taking into account (34),(37)minj⁡ejn≤ejn+1≤maxj⁡ejn.Therefore,(38)en+1∞=maxj⁡ejn+1≤maxj⁡ejn=en∞.The following expression can be obtained:(39)en+1∞≤en∞≤⋯≤e0∞.Equation (39) reveals that the finite analytical scheme (19) is unconditionally stable.


## 4.1. Convergence of Finite Analytical Numerical Scheme

Errors of the FAM implicit scheme (19) are found by using (10). To demonstrate the convergence of FAM, the following equation is used to replace ∂ω/∂t in (9):(20)∂ω∂tjn=ωjn-ωjn-1Δt+OΔt.Here, O(Δt) is truncation error. ωjn represents the exact solution and ω~jn represents finite analytic numerical solution at the node j and the nth time step, respectively. The error between the exact solution ωjn and finite analytic numerical solution ω~jn can be written as εjn; thus,(21)εjn=ωjn-ω~jn.ω
j
n should satisfy the following:(22)ωjn=12+λωj-1n+12+λωj+1n+λ2+λωjn-1-λΔt2+λRnΔt+OΔt.Andω~jn should satisfy the following:(23)ω~jn=12+λω~j-1n+12+λω~j+1n+λ2+λω~jn-1-λΔt2+λRnΔt.Substituting (22) and (23) into (21),(24)εjn=12+λεj-1n+12+λεj+1n+λ2+λεjn-1+OΔt.Because the coefficients in (24) are positive,(25)εjn≤12+λεj-1n+12+λεj+1n+λ2+λεjn-1+Zjn-1,where Zjn-1=O(Δt).It can be shown that(26)εmaxn≤12+λεmaxn-1+12+λεmaxn-1+λ2+λεmaxn-1+Zmaxn-1,where(27)εmaxn-1=max⁡εj-1n-11≤j≤N-1,Zmaxn-1=max⁡Zjn-11≤j≤N-1,and that(28)εmaxn≤εmaxn-1+Zmaxn-1n=1,2,…,M.Because the finite analytical equation and the partial differential equation have the same initial condition, namely, n=1, the finite analytical solution is consistent with the exact solution. That is, εmax0=0.From (27), the following expressions can be obtained:(29)εmax1≤εmax0+Zmax0=Zmax0,εmax2≤εmax1+Zmax1≤Zmax0+Zmax1,⋮εmaxM≤εmaxM-1+ZmaxM-1≤Zmax0+Zmax1+⋯+ZmaxM-1.Therefore,(30)εmaxM≤M·Zmax=M·max⁡OΔt,where(31)Zmax=max⁡Zmaxn1≤n≤M.WhenΔt→0, εmaxM→0, thus ω~jn→ωjn. Thus, it revealed that the finite analytical scheme has uniform convergence.


## 4.2. Stability of the Finite Analytical Numerical Scheme

The stability of finite analytical scheme (19) can be proven as follows. Let ωn=ω0nω1n⋯ωmnT; taking account of calculation error, ω0 becomes ω0∗ and ωn becomes ωn∗. Thus, the error of any term is(32)ejn=ωjn-ωjn∗.From (19), the error ejn fits with(33)-1λej-1n+1+2+λλejn+1-1λej+1n+1=ejn.It can be proven that the error at(n+1)th time step ejn+1 is between the error at the node 0 and the (n+1)th time step e0n+1, the error at the node m and the (n+1)th time step emn+1, and the extreme of the error in nth time step ejn; that is, (34)mn≤ejn+1≤Mn,where(35)mn=min⁡e0n+1,ejn,emn+1,Mn=max⁡e0n+1,ejn,emn+1.Equation (34) can be proven as follows. Assume ekn+1=minj⁡ejn+1. When k=0 or k=m, there is ejn+1≥mn clearly. When 0<k<m, taking into account (33),(36)ekn+1=ekn+1λek-1n+1+ek+1n+1-2ekn+1≥ekn+1λekn+1+ekn+1-2ekn+1=ekn≥mn.Evidenced by the same token,ekn+1≤Mn.The finite analytical equation and the partial differential equation have the same boundary condition, namely,e0n=emn=0, and taking into account (34),(37)minj⁡ejn≤ejn+1≤maxj⁡ejn.Therefore,(38)en+1∞=maxj⁡ejn+1≤maxj⁡ejn=en∞.The following expression can be obtained:(39)en+1∞≤en∞≤⋯≤e0∞.Equation (39) reveals that the finite analytical scheme (19) is unconditionally stable.


## 5. Semianalytical Solution of Governing Differential Equation

The analytical model fitting with all assumptions except hypothesis (c) mentioned in Section2 is shown in Figure 2. The depth of the soft clay with permeable top and bottom is 2L. Time-dependent loading q(t) is imposed on top of the soft clay.Figure 2
1D foundation model.According to definition, in Figure2, the initial and boundary conditions of the problem are(40)uz,0=q0if0≤z≤2L,t=0,u0,t=0ifz=0,t>0,u2L,t=0ifz=2L,t>0.By using (6), the transform of (40) is(41)ωz,0=Q0if0≤z≤2L,t=0,ω0,t=0ifz=0,t>0,ω2L,t=0ifz=2L,t>0,where (42)Qt=1+e0σ′E+nσ′-1+e0qtE+nqt.When hypothesis (c) is not considered, the general solution of the problem is modified as(43)u=ωz,tE+nqt2nωz,tE+nqt-E1+e0.The average degrees of consolidation of the soil defined in pore-water pressureUp can be given by(44)Up=∫02Lσ′-σ0′dz∫02Lσf′-σ0′dz=∫02Lqt-udz∫02Lqudz=qtqu-12Lqu∫02Lωz,tE+nqt2nωz,tE+nqt-E1+e0dz,where(45)ωz,t=-∑m=1∞4mπe-Cvmπ/2L2tsin⁡mπz2L·∫0tRτeCvmπ/2L2τdτ-Q0m=1,3,5,….The average degrees of consolidationUp can be approximately written as follows:(46)Up=∫02Lσ′-σ0′dz∫02Lσf′-σ0′dz=∫02Lqt-udz∫02Lqudz=qt-1/2L∑j=1j=2L/ΔzujΔzqu.According to (43) and (44), the exact expression of ω(z,t) is the key to obtaining excess pore-water pressure and average degrees of consolidation for different time-dependent loadings. The following sections will discuss each of ω(z,t) under suddenly imposed constant loading, single ramp loading, and trapezoidal cyclic loading.(a) Suddenly Imposed Constant Loading
(47)
q
t
=
q
u
.Therefore,(48)Q0=-1+e0quE+nqu.Substituting (47) and (48) into (45), (49)ωz,t=∑m=1∞4mπsin⁡mπz2L·e-Cvmπ/2L2t1+e0quE+nqum=1,3,5,….Substituting (49) into (43) and (44) or (46), the excess pore-water pressure and average degrees of consolidation can be obtained for suddenly imposed constant loading.(b) Single Ramp Loading
(50)
q
t
=
q
u
t
0
t
,
i
f
t
≤
t
0
,
q
u
,
i
f
t
>
t
0
.Therefore,(51)Q0=0.From (7) and (50),(52)Rt=E1+e0qu/t0E+nqu/t0t2,t≤t0,0,t>t0.The semianalytical solution to the problem is(53)ωz,t=-∑m=1∞4mπsin⁡mπz2LEi1,-bdc-Ei1,-dtc+bc·tbcd+b2d-edtc+b/cbc+ebd/ctc2+bcae-dtc+b/cbc2tc+b,ift≤t0,-∑m=1∞4mπsin⁡mπz2LEi1,-bdc-Ei1,-dt0c+bc·t0bcd+b2d-edt0c+b/cbc+ebd/ct0c2+bcae-dt+t0c+b/cbc2t0c+b,ift>t0,m=1,3,5,…,where(54)a=E1+e0qut0,b=E,c=nqut0,d=Cvmπ2L2,Eia1,b1=∫1∞e-xb1x-a1dx,a
1 and b1 are nonzero constants.Substituting (53) into (43) and (44) or (46), the excess pore-water pressure and average degrees of consolidation can be obtained for single ramp loading.(c) Trapezoidal Cyclic Loading (Figure3)
(55)
q
t
=
q
u
α
t
0
t
-
N
-
1
β
t
0
,
i
f
N
-
1
β
t
0
≤
t
≤
N
-
1
β
+
α
t
0
,
q
u
,
i
f
N
-
1
β
+
α
t
0
≤
t
≤
N
-
1
β
+
1
-
α
t
0
,
-
q
u
α
t
0
t
-
N
-
1
β
t
0
-
t
0
,
i
f
N
-
1
β
+
1
-
α
t
0
≤
t
≤
N
-
1
β
+
1
t
0
,
0
,
i
f
N
-
1
β
+
1
t
0
≤
t
≤
N
β
t
0
,where qu is the maximum value of loading during a cycle period; βt0 is the period of the loading; α,β are loading factors;N is the cycle number.Figure 3
Trapezoidal cyclic loading.Therefore,(56)Q0=0.From (7) and (50),(57)Rt=E1+e0qu/αt0E+nqu/αt0t-N-1βt02,ifN-1βt0≤t≤N-1β+αt0,0,ifN-1β+αt0≤t≤N-1β+1-αt0,-E1+e0qu/αt0E-nqu/αt0t-N-1β+1t02,ifN-1β+1-αt0≤t≤N-1β+1t0,0,ifN-1β+1t0≤t≤Nβt0.The semianalytical solution for consolidation under the loading case is shown in the Appendix. It is clear that the form of the solution is complex. Compared with the semianalytical solution (A.1), the general solution, obtained by using (45) and (57), can be easier to program.


## 6. Comparison between Results from FAM and Semianalytical Solutions

The numerical solution of FAM is compared with the semianalytical solution for different loading cases. The value of constant parameters from [26] are Cv=5.789×10-3 m2/day, E=1.6878×106 Pa, n=3.3, e0=1.1167, 2L=6.4 m, and t=800 days. In the FAM, the time step Δt is 0.1 days.(a) Suddenly Imposed Constant Loading Case. For the suddenly imposed constant loading case, qu=2×105 Pa. The duration of loading is 800 days. The average degrees of consolidation Up is calculated by using (46), adopting the same space step Δz for FAM and the semianalytical solution. ω(z,t) is calculated by using (49). The number of terms in the series is 20. Curves of the average degrees of consolidation Up versus time factor Tv (shown in (58)) for different methods with different space steps Δz are plotted in Figure 4 (ASM indicates “semianalytical solution method” in the figure). Comparison between the result of FAM and the semianalytical solution shows a negligible gap, indicating that the method proposed in this paper has sufficient precision.(58)Tv=CvtL-2.Figure 4
U
p versus Tv curves for constant loading.In order to investigate the accuracy of this result further, the percentage deviation ofUp between FAM and semianalytical solutions is evaluated. To illustrate the difference of Up between the two, 21 data points of the percentage deviation of Up are chosen at regular intervals for each data group plotted in Figure 5. The percentage deviation decreases with decreasing space step Δz, demonstrating that, under the same conditions, a smaller space step is helpful in enhancing the precision of calculation. However, there is a clear side effect: the amount of calculation increases. Considering the precision and the amount of calculation, Δz=0.2 m is selected in the next two loading cases: single ramp loading case and trapezoidal cyclic loading case.Figure 5
Percentage deviation ofUp between the FAM and the semianalytical solution versus Tv curves for constant loading.(b) Single Ramp Loading Case. In the single ramp loading case, qu=2×105 Pa. The value of q(t) increases linearly from 0 to qu during the loading increase phase t0. In this section, the influence of the loading increase (phase t0) is discussed. The loading increasing (phase t0) is 141.5, 283, and 424.5 days, respectively, and the value of q(t) remains constant. Further ω(z,t) is calculated by using (53) in the semianalytical solution. In order to avoid overflow, the number of terms in the series is 6. The curves of the average degrees of consolidation Up versus time factor Tv for different methods with different loading increase periods are plotted in Figure 6. As shown in Figure 6, Up increases with increasing Tv, but there is a turning point after which the rate of increase slows down. For the different loading increase (period t0), the degree of consolidation with a short loading increase is higher than the degree of consolidation with a long loading increase period. Figure 6 also shows that the agreement between the curves obtained by using the FAM and the semianalytical solutions is quite remarkable. To illustrate the difference of Up between the FAM and the semianalytical solution under single ramp loading case, 21 data points of the percentage deviation of Up are chosen at regular intervals for each data group plotted in Figure 7. Figure 7 shows that the percentage deviation of Up between the FAM and the semianalytical solution changes with increasing Tv. Although there are differences in different loading increase period cases, the percentage deviation of Up is generally negligible.Figure 6
U
p versus Tv curves for single ramp loading.Figure 7
Percentage deviation ofUp between the FAM and the semianalytical solution versus Tv curves for single ramp loading.(c) Trapezoidal Cyclic Loading Case. In the trapezoidal cyclic loading case, the maximum value of loading qu during a cycle period is 2 × 105 Pa. The period of the loading is written as βt0. t0 is a loading period of 141.5 days. The loading factors α and β are 0.3 and 1.0, 0.3 and 1.2, 0.3 and 2.4, and 0.5 and 1.2, which represent trapezoidal cyclic loading without a rest period, trapezoidal cyclic loading with 0.2t0 rest period, trapezoidal cyclic loading with 1.4t0 rest period, and triangularly cyclic loading with a 0.2t0 rest period, respectively. Here, ω(z,t) is calculated by using (45) in the semianalytical solution. In order to avoid overflow, the number of terms in the series is 10. The curves of the average degrees of consolidation Up versus time factor Tv with different loading factors α and β for different methods are plotted in Figure 8, showing that Up tends to be fluctuating while increasing with increasing Tv. To illustrate the difference of Up between the FAM and the semianalytical solution under trapezoidal cyclic loading case, 21 data points of the percentage deviation of Up are chosen at regular intervals for each data group plotted in Figure 8. The comparison between the result of FAM and the semianalytical solution shows a negligible gap in Figure 8. The percentage deviation of Up between the FAM and the semianalytical solution for trapezoidal cyclic loading is plotted in Figure 9, indicating that fluctuation deviation is small in range in terms of percent and is, thus, negligible.Figure 8
U
p versus Tv curves for trapezoidal cyclic loading.Figure 9
Percentage deviation ofUp between the FAM and the semianalytical solution versus Tv curves for trapezoidal cyclic loading.


## 7. Convergence of the Spatial Discretization for FAM

Proving the convergence of the spatial discretization by a mathematical approach is difficult. To further explore the convergence of the spatial discretization, a 1D nonlinear consolidation in the trapezoidal cyclic loading case was introduced as an example. The initial and boundary conditions are as follows:(59)uz,0=104z,if0≤z≤L,t=0,u0,t=0,ifz=0,t>0,∂uL,t∂z=0,ifz=L,t>0.By using (6), the transform of (59) is(60)ωz,0=-2.1167z168.78-3.3z,if0≤z≤L,t=0,ω0,t=0,ifz=0,t>0,∂ωL,t∂t=0,ifz=L,t>0.In this example, a soft clay layer with permeable top and impermeable bottom under initial excess pore-water pressure triangular distribution is introduced, wherequ = 2 × 105 Pa, t0=141.5 days, α=0.3, and β=1.2. The values of the constant parameters are the same as those in Section 6. However, for the case, the analytical solution is difficult to be obtained. But it is easy to solve by numerical method, such as FAM and FDM. For comparison, the space step Δz is set to 0.1, 0.2, 0.4, and 0.8 m by FAM, respectively. To achieve good solutions as comparison, the space step Δz is adopted to 0.1 m by FDM. The space step has influence on degree of consolidation calculated value of Up. To avoid this, the excess pore-water pressure u calculated by FAM with different space steps is compared with FDM with specific space step Δz=0.1 m, shown in Figure 10. It reveals that the results of FAM matches well with the result of FDM, even if Δz is 0.8 m. Therefore, FAM can ensure the convergence of spatial discretization.Figure 10
Comparison between the results of FAM and the results of FDM.
(a)
FDMΔz=0.1 m; FAM Δz=0.1 m
(b)
FDMΔz=0.1 m; FAM Δz=0.2 m
(c)
FDMΔz=0.1 m; FAM Δz=0.4 m
(d)
FDMΔz=0.1 m; FAM Δz=0.8 m


## 8. Conclusions

This paper develops the finite analytic method (FAM) for solving a 1D nonlinear consolidation undergoing time-dependent loading. The study shows that FAM is very efficient and convenient in simulating the nonlinear consolidation. The following conclusions can be drawn from this research:(1)
The governing partial differential equation with nonhomogeneous character can be transformed into the diffusion equation, where the FAM uses an analytical solution in small local elements to formulate the algebraic representation of the 1D nonlinear consolidation undergoing time-dependent loading.(2)
The FAM is a combination of analytical solution and numerical approach. The finite analytical scheme has uniform convergence and is unconditionally stable for 1D nonlinear consolidation. Therefore, FAM can obtain smooth and high-precision solutions.(3)
The comparison between the results of FAM and the semianalytical solution of the 1D nonlinear consolidation undergoing suddenly imposed constant loading, single ramp loading, and trapezoidal cyclic loading indicates that FAM can obtain stable and accurate numerical solutions.(4)
The comparison between the results of FAM with different space steps and the results of FDM with a small space step indicates that FAM can ensure the convergence of spatial discretization.



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*Source: 4071268-2017-03-30.xml*