Case report Special Issues

Bryozoan limestone experience—the case of Stevns Klint

  • Received: 20 February 2019 Accepted: 29 April 2019 Published: 20 May 2019
  • Bryozoan limestone is a formation of Danian limestone, generally found underlying the younger Copenhagen formation and above the Cretaceous chalk. The mineralogy between the Danian and Cretaceous formations is similar, resulting in similar mechanical responses of the matrix material. The mineralogy of the mentioned formations generally includes calcareous minerals with variable contents of flint (siliceous materials) and irregularly a small content of other materials. The distinctive feature of the matrix material of these formations is primarily the type of porosity reflecting the originating organisms and depositional history. Our database includes Bryozoan limestone data collected on major infrastructure projects between Sjælland (Denmark) and Skåne (Sweden), such as Malmø Citytunnel, as well as from a number of smaller investigation campaigns. The database includes borehole registrations, geological descriptions, classification tests and basic strength tests. Further knowledge collection includes results of wireline logging, advanced laboratory tests etc. In the latest campaign on the Bryozoan limestone, the site and material are investigated for the design of the rock anchors at the UNESCO site of Stevns Klint. The article presents a part of the interpretation of the mechanical behavior of Bryozoan limestone aided by the use of the existing database.

    Citation: Nataša Katić, Joakim S. Korshøj, Helle F. Christensen. Bryozoan limestone experience—the case of Stevns Klint[J]. AIMS Geosciences, 2019, 5(2): 163-183. doi: 10.3934/geosci.2019.2.163

    Related Papers:

    [1] Amira Khelifa, Yacine Halim . Global behavior of P-dimensional difference equations system. Electronic Research Archive, 2021, 29(5): 3121-3139. doi: 10.3934/era.2021029
    [2] Najmeddine Attia, Ahmed Ghezal . Global stability and co-balancing numbers in a system of rational difference equations. Electronic Research Archive, 2024, 32(3): 2137-2159. doi: 10.3934/era.2024097
    [3] Bin Wang . Random periodic sequence of globally mean-square exponentially stable discrete-time stochastic genetic regulatory networks with discrete spatial diffusions. Electronic Research Archive, 2023, 31(6): 3097-3122. doi: 10.3934/era.2023157
    [4] Tran Hong Thai, Nguyen Anh Dai, Pham Tuan Anh . Global dynamics of some system of second-order difference equations. Electronic Research Archive, 2021, 29(6): 4159-4175. doi: 10.3934/era.2021077
    [5] Wedad Albalawi, Fatemah Mofarreh, Osama Moaaz . Dynamics of a general model of nonlinear difference equations and its applications to LPA model. Electronic Research Archive, 2024, 32(11): 6072-6086. doi: 10.3934/era.2024281
    [6] Merve Kara . Investigation of the global dynamics of two exponential-form difference equations systems. Electronic Research Archive, 2023, 31(11): 6697-6724. doi: 10.3934/era.2023338
    [7] Qianhong Zhang, Shirui Zhang, Zhongni Zhang, Fubiao Lin . On three-dimensional system of rational difference equations with second-order. Electronic Research Archive, 2025, 33(4): 2352-2365. doi: 10.3934/era.2025104
    [8] Chang Hou, Hu Chen . Stability and pointwise-in-time convergence analysis of a finite difference scheme for a 2D nonlinear multi-term subdiffusion equation. Electronic Research Archive, 2025, 33(3): 1476-1489. doi: 10.3934/era.2025069
    [9] Nouressadat Touafek, Durhasan Turgut Tollu, Youssouf Akrour . On a general homogeneous three-dimensional system of difference equations. Electronic Research Archive, 2021, 29(5): 2841-2876. doi: 10.3934/era.2021017
    [10] Ling Xue, Min Zhang, Kun Zhao, Xiaoming Zheng . Controlled dynamics of a chemotaxis model with logarithmic sensitivity by physical boundary conditions. Electronic Research Archive, 2022, 30(12): 4530-4552. doi: 10.3934/era.2022230
  • Bryozoan limestone is a formation of Danian limestone, generally found underlying the younger Copenhagen formation and above the Cretaceous chalk. The mineralogy between the Danian and Cretaceous formations is similar, resulting in similar mechanical responses of the matrix material. The mineralogy of the mentioned formations generally includes calcareous minerals with variable contents of flint (siliceous materials) and irregularly a small content of other materials. The distinctive feature of the matrix material of these formations is primarily the type of porosity reflecting the originating organisms and depositional history. Our database includes Bryozoan limestone data collected on major infrastructure projects between Sjælland (Denmark) and Skåne (Sweden), such as Malmø Citytunnel, as well as from a number of smaller investigation campaigns. The database includes borehole registrations, geological descriptions, classification tests and basic strength tests. Further knowledge collection includes results of wireline logging, advanced laboratory tests etc. In the latest campaign on the Bryozoan limestone, the site and material are investigated for the design of the rock anchors at the UNESCO site of Stevns Klint. The article presents a part of the interpretation of the mechanical behavior of Bryozoan limestone aided by the use of the existing database.


    Difference equations are the essentials required to understand even the simplest epidemiological model: the SIR-susceptible, infected, recovered-model. This model is a compartmental model, which results in the basic difference equation used to measure the actual reproduction number. It is this basic model that helps us determine whether a pathogen is going to die out or whether we end up having an epidemic. This is also the basis for more complex models, including the SVIR, which requires a vaccinated state, which helps us to estimate the probability of herd immunity.

    There has been some recent interest in studying the qualitative analysis of difference equations and system of difference equations. Since the beginning of nineties there has be considerable interest in studying systems of difference equations composed by two or three rational difference equations (see, e.g., [4,5,6,2,8,9,11,10,14,15,17,19,20] and the references therein). However, given the multiplicity of factors involved in any epidemic, it will be important to study systems of difference equations composed by many rational difference equations, which is what we will do in this paper.

    In [2], Devault et al. studied the boundedness, global stability and periodic character of solutions of the difference equation

    xn+1=p+xnmxn (1)

    where m{2,3,}, p is positive and the initial conditions are positive numbers.

    In [20], Zhang et al. investigated the behavior of the following symmetrical system of difference equations

    xn+1=A+ynmyn,yn+1=A+xnmxn (2)

    where the parameter A is positive, the initial conditions xi,yi are arbitrary positive numbers for i=m,m+1,,0 and mN. While this study is good, we note that the authors did not investigate various device properties, such as the stability nature, the rate of convergence and the asymptotic behavior.

    Complement of the work above, in [8], Gümüş studied the global asymptotic stability of positive equilibrium, the rate of convergence of positive solutions and he presented some results about the general behavior of solutions of system (2). Our aim in this paper is to generalize the results concerning equation (1) and system (2) to the system of p nonlinear difference equations

    x(1)n+1=A+x(2)nmx(2)n,x(2)n+1=A+x(3)nmx(3)n,,x(p)n+1=A+x(1)nmx(1)n,n,m,pN0 (3)

    where A is a nonnegative constant and x(j)m,x(j)m+1,,x(j)1,x(j)0,j=1,2,,p are positive real numbers.

    The remainder of the paper is organized as follows. In Section (2), we introduce some definitions and notations that will be needed in the sequel. Moreover, we present, in Theorem (2.4), a result concerning the linearized stability that will be useful in the main part of the paper. Section (3) discuses the behavior of positive solutions of system (3) via semi-cycle analysis method. Furthermore, Section (4) is devoted to study the local stability of the equilibrium points and the asymptotic behavior of the solutions when 0A<1,A=1 and A>1. In Section (5), we turn our attention to estimate the rate of convergence of a solution that converges to the equilibrium point of the system (3) in the region of parameters described by A>1. Some numerical examples are carried out to support the analysis results in Section (6). Section (7) summarizes the results of this work, draws conclusions and give some interesting open problems for difference equations theory researchers.

    In this section we recall some definitions and results that will be useful in our investigation, for more details see [3,7,14,13].

    Definition 2.1. (see, [14]) A 'string' of sequential terms {x(j)μ,,x(j)ν}, μ1, ν+ is said to be a positive semi-cycle if x(j)i¯x(j), i{μ,,ν}, x(j)μ1<¯x(j) and x(j)ν+1<¯x(j), j{1,2,,p}.

    A 'string' of sequential terms {x(j)μ,,x(j)ν}, μ1, ν+ is said to be a negative semi-cycle if x(j)i<¯x(j), i{μ,,ν}, x(j)μ1¯x(j) and x(j)ν+1¯x(j), j{1,2,,p}.

    A 'string' of sequential terms {(x(1)μ,x(2)μ,,x(p)μ),,(x(1)ν,x(2)ν,,x(p)ν)}, μ1, ν+ is said to be a positive semi-cycle (resp. negative semi-cycle) if if {x(1)μ,,x(1)ν},,{x(p)μ,,x(p)ν} are positive semi-cycles (resp. negative semi-cycles).

    A 'string' of sequential terms {(x(1)μ,x(2)μ,,x(p)μ),,(x(1)ν,x(2)ν,,x(p)ν)}, μ1, ν+ is said to be a positive semi-cycle (resp. negative semi-cycle) with respect to x(q)n and negative semi-cycle (resp. positive semi-cycle) with respect to x(s)n if {x(q)μ,,x(q)ν} is a positive semi-cycle (resp. negative semi-cycle) and {x(s)μ,,x(s)ν} is a negative semi-cycle (resp. positive semi-cycle).

    Definition 2.2. (see, [14]) A function x(i)n oscillates about ¯x(i) if for every ξN there exist μ,νN, μξ, νξ such that

    (x(i)μ¯x(i))(x(i)μ¯x(i))0,i=1,2,,p.

    We say that a solution {x(1)n,x(2)n,,x(p)n}nm of system (3) oscillates about (¯x(1),¯x(2),,¯x(p)) if x(q)n oscillates about ¯x(q), q{1,2,,p}.

    Let f(1),f(2),,f(p) be p continuously differentiable functions:

    f(i):Ik+11×Ik+12××Ik+1pIk+1i,i=1,2,,p,

    where Ii,i=1,2,,p are some intervals of real numbers. Consider the system of difference equations

    {x(1)n+1=f(1)(x(1)n,x(1)n1,,x(1)nk,x(2)n,x(2)n1,,x(2)nk,,x(p)n,x(p)n1,,x(p)nk)x(2)n+1=f(2)(x(1)n,x(1)n1,,x(1)nk,x(2)n,x(2)n1,,x(2)nk,,x(p)n,x(p)n1,,x(p)nk)x(p)n+1=f(p)(x(1)n,x(1)n1,,x(1)nk,x(2)n,x(2)n1,,x(2)nk,,x(p)n,x(p)n1,,x(p)nk) (4)

    where n,kN0, (x(i)k,x(i)k+1,,x(i)0)Ik+1i,i=1,2,,p.

    Define the map

    F:I(k+1)1×I(k+1)2××I(k+1)pI(k+1)1×I(k+1)2××I(k+1)p

    by

    F(W)=(f(1)0(W),f(1)1(W),,f(1)k(W),f(2)0(W),f(2)1(W),,
    ,f(2)k(W),,f(p)0(W),f(p)1(W),,f(p)k(W)),

    where

    W=(u(1)0,u(1)1,,u(1)k,u(2)0,u(2)1,,u(2)k,,u(p)0,u(p)1,,u(p)k)T,
    f(i)0(W)=f(i)(W),f(i)1(W)=u(i)0,,f(i)k(W)=u(i)k1,i=1,2,,p.

    Let

    Wn=(x(1)n,x(1)n1,,x(1)nk,x(2)n,x(2)n1,,x(2)nk,,x(p)n,x(p)n1,,x(p)nk)T.

    Then, we can easily see that system (4) is equivalent to the following system written in vector form

    Wn+1=F(Wn),nN0. (5)

    Definition 2.3. (see, [13]) Let (¯x(1),¯x(2),,¯x(p)) be an equilibrium point of the map F where f(i), i=1,2,,p are continuously differentiable functions at (¯x(1),¯x(2),,¯x(p)). The linearized system of (3) about the equilibrium point (¯x(1),¯x(2),,¯x(p)) is

    Xn+1=F(Xn)=BXn

    where Xn=(x(1)n,x(1)n1,,x(1)nk,x(2)n,x(2)n1,,x(2)nk,,x(p)n,x(p)n1,,x(p)nk)T and B is a Jacobian matrix of the system (3) about the equilibrium point (¯x(1),¯x(2),,¯x(p)).

    Theorem 2.4. (see, [13])

    1. If all the eigenvalues of the Jacobian matrix B lie in the open unit disk |λ|<1, then the equilibrium point ¯X of system (3) is asymptotically stable.

    2. If at least one eigenvalue of the Jacobian matrix B has absolute value greater than one, then the equilibrium point ¯X of system (3) is unstable.

    In this section, we discuss the behavior of positive solutions of system (3) via semi-cycle analysis method. It is easy to see that system (3) has a unique positive equilibrium point (¯x(1),¯x(2),,¯x(p))=(A+1,A+1,,A+1).

    Lemma 3.1. Let {(x(1)n,x(2)n,,x(p)n)}nm be a solution to system (3). Then, either {(x(1)n,x(2)n,,x(p)n)}nm consists of a single semi-cycle or {(x(1)n,x(2)n,,x(p)n)}nm oscillates about the equilibrium (¯x(1),¯x(2),,¯x(p))=(A+1,A+1,,A+1) with semi-cycles having at most m terms.

    Proof. Suppose that {(x(1)n,x(2)n,,x(p)n)}nm has at least two semi-cycles. Then, there exists n0m such that either

    x(j)n0<A+1x(j)n0+1 or x(j)n0+1<A+1x(j)n0,j=1,2,,p.

    We suppose the first case, that is, x(j)n0<A+1x(j)n0+1. The other case is similar and will be omitted. Assume that the positive semi-cycle beginning with the term (x(1)n0+1,x(2)n0+1,,x(p)n0+1) have m terms. In this case we have

    x(j)n0<A+1x(j)n0+m,j=1,2,,p.

    So, we get from system (3)

    x(j)n0+m+1=A+x(j+1)mod(p)n0x(j+1)mod(p)n0+m<A+1,j=1,2,,p.

    The Lemma is proved.

    Lemma 3.2. Let {(x(1)n,x(2)n,,x(p)n)}nm be a solution to system (3) which has m1 sequential semi-cycles of length one. Then, every semi-cycle after this point is of length one.

    Proof. Assume that there exists n0m such that either

    x(j)n0,x(j)n0+2,,x(j)n0+m1<A+1x(j)n0+1,x(j)n0+3,,x(j)n0+m,j=1,2,,p, (6)

    or

    x(j)n0+1,x(j)n0+3,,x(j)n0+m<A+1x(j)n0,x(j)n0+2,,x(j)n0+m1,j=1,2,,p. (7)

    We will prove the case (6). The case (7) Is identical and will not be included. According to system (3) we obtain

    x(j)n0+m+1=A+x(j+1)mod(p)n0x(j+1)mod(p)n0+m<A+1,j=1,2,,p,

    and

    x(j)n0+m+2=A+x(j+1)mod(p)n0+1x(j+1)mod(p)n0+m+1>A+1,j=1,2,,p,

    The result proceeds by induction. Thus, the proof is completed.

    Lemma 3.3. System (3) has no nontrivial periodic solutions of (not necessarily prime) period m.

    Proof. Suppose that

    (α(1)1,α(2)1,,α(p)1),(α(1)2,α(2)2,,α(p)2),,(α(1)m,α(2)m,,α(p)m),(α(1)1,α(2)1,,α(p)1),

    is a m-periodic solution of system (3). It is obvious then that for this solution,

    (x(1)nm,x(2)nm,,x(p)nm)=(x(1)n,x(2)n,,x(p)n),n0.

    So, the equilibrium solution (¯x(1),¯x(2),,¯x(p))=(A+1,A+1,,A+1) must be this solution. Thus, the proof is completed.

    Lemma 3.4. All non-oscillatory solutions of system (3) converge to the equilibrium (¯x(1),¯x(2),,¯x(p))=(A+1,A+1,,A+1).

    Proof. We assume there exists non-oscillatory solutions of system (3). We will prove this lemma for the case of a single positive semi-cycle, the situation is identical for a single negative semi-cycle, so it will be omitted. Assume that (x(1)n,x(2)n,,x(p)n)(¯x(1),¯x(2),,¯x(p)) for all nm. From system (3) we have

    x(j)n+1=A+x(j+1)mod(p)nmx(j+1)mod(p)nA+1,j=1,2,,p,

    So, we get

    A+1x(j)nx(j)nm,n0,j=1,2,,p (8)

    From (8), there exists δ(j)i fori=0,1,,m1 such that

    limn+x(j)nm+i=δ(j)i.

    Hence,

    (δ(1)0,δ(2)0,,δ(p)0),(δ(1)1,δ(2)1,,δ(p)1),,(δ(1)m1,δ(2)m1,,δ(p)m1)

    is a periodic solution of (not necessarily prime period) period m. But, from Lemma (3.3), we saw system (3) has no nontrivial periodic solutions of (not necessarily prime period) period m. Thus, the solution must be the equilibrium solution. So, the proof is over.

    Theorem 4.1. Suppose 0<A<1 and {(x(1)n,x(2)n,,x(p)n)}nm be a positive solution to system (3). Then the following statements hold.

    ⅰ): If m is odd, and 0<x(j)2k1<1, x(j)2k>11A for k=1m2,3m2,,0, then

    limn+x(j)2n=+,limn+x(j)2n+1=A.

    ⅱ): If m is odd, and 0<x(j)2k<1, x(j)2k1>11A for k=1m2,3m2,,0, then

    limn+x(j)2n=A,limn+x(j)2n+1=+.

    Proof. (ⅰ): From (3), for i=1,2,,p, we get

    x(i)1=A+x(i+1)mod(p)mx(i+1)mod(p)0<A+1x(i+1)mod(p)0<A+(1A)=1,x(i)2=A+x(i+1)mod(p)1mx(i+1)mod(p)1>A+x(i+1)mod(p)1m>x(i+1)mod(p)1m>11A.

    By induction, for n =0,1,2, and i=1,2,,p, we obtain

    x(i)2n1<1,x(i)2n>11A. (9)

    So, from (3) and (9), we have

    x(i)2n=A+x(i+1)mod(p)2n1mx(i+1)mod(p)2n1>A+x(i+1)mod(p)2n1m>2A+x(i+1)mod(p)2n3m>3A+x(i+1)mod(p)2n5m>

    So

    x(i)2n>nA+x(i+1)mod(p)0. (10)

    By limiting the inequality (10), we get

    limnx(i)2n=. (11)

    On the other hand, from(3), (9) and (11), we get

    limnx(i)2n+1=limn(A+x(i+1)mod(p)2nmx(i+1)mod(p)2n)=A.

    (ⅱ): The proof is similar to the proof of (ⅰ).

    Open Problem. Investigate the asymptotic behavior of the system (3) when m is even.

    Lemma 4.2. Suppose A=1. Then every positive solution of the system (3) is bounded and persists.

    Proof. Let {(x(1)n,x(2)n,,x(p)n)}nm be a positive solution to system (3). Then, it is clear that for n1, x(j)n>A=1,j=1,2,,p. So, we get

    x(j)i[L,LL1],i=1,2,,m+1,j=1,2,,p,

    where

    L=min{α,ββ1}>1,α=min1jm+1{x(1)j,x(2)j,,x(p)j},
    β=max1jm+1{x(1)j,x(2)j,,x(p)ji}.

    So, we get

    L=1+LL/(L1)x(j)m+2=1+x(j+1)mod(p)1x(j+1)mod(p)m+1LL1,

    thus, the following is obtained

    Lx(j)mLL1.

    By induction, we get

    x(j)i[L,LL1],j=1,2,,p,i=1,2, (12)

    Theorem 4.3. Suppose A=1 and {(x(1)n,x(2)n,,x(p)n)}nm be a positive solution to system (3). Then

    lim infn+x(i)n=lim infn+x(j)n,i,j=1,2,,p,lim supn+x(i)n=lim supn+x(j)n,i,j=1,2,,p.

    Proof. From (12), we can set

    Li=limnsupx(i)n,mi=limninfx(i)n,i=1,2,,p. (13)

    We first prove the theorem for p=2. From system (3), we have

    L11+L2m2,L21+L1m1,m11+m2L2,m21+m2L2,

    which implies

    L1m2m2+L2m1L2m1+L1m2L1

    thus, the following equalities are obtained

    m2+L2=m1+L1,L1m2=m1L2.

    So, we get that m1=m2 and L1=L2. Now we suppose that

    Li=Lj,mi=mj,i,j=1,2,,p1,

    From system (3), we have

    Lp11+Lpmp,Lp1+Lp1mp1,mp11+mpLp,mp1+mpLp,

    hence, we get

    Lp1mpmp+Lpmp1Lpmp1+Lp1mpLp1,

    consequently, the following equalities are obtained

    mp+Lp=mp1+Lp1,Lp1mp=mp1Lp.

    So, we get that mp=mp1 and Lp=Lp1. Thus, the proof completes.

    Theorem 4.4. Assume that A>1. Then, the unique positive equilibrium (¯x(1),¯x(2),,¯x(p))=(A+1,A+1,,A+1) of system (3) is locally asymptotically stable.

    Proof. The linearized equation of system (3) about the equilibrium point (¯x(1),¯x(2),,¯x(p)) is

    Xn+1=BXn

    where Xn=(x(1)n,x(1)n1,,x(1)nm,x(2)n,x(2)n1,,x(2)nm,,x(p)n,x(p)n1,,,x(p)nm)t, and B=(bij), 1i,jpm+p is an (pm+p)×(pm+p) matrix such that

    B=(JAOOOOOJAOOOOOJAOOOOOOJAAOOOOJ)

    where A,J and O are (m+1)×(m+1) matrix defined as follows

    J=(000010000010),O=(000000000000), (14)
    A=(1A+1001A+100000000). (15)

    Let λ1,λ2,,λpm+p denote the eigenvalues of matrix B and let

    D=diag(d1,d2,,dpm+p)

    be a diagonal matrix where d1=dm+2=d2m+3==d(p1)m+p=1, dk=dm+1+k=1kε for k{1,2,,p2(m+1)}. Since A>1, we can take a positive number ε such that

    0<ε<A1(m+1)(A+1). (16)

    It is obvious that D is an invertible matrix. Computing matrix DBD1, we get

    DBD1=(J(1)A(1)OOOOOJ(2)A(2)OOOOOJ(3)A(3)OOOOOOJ(p1)A(p1)A(p)OOOOJ(p)),

    where

    J(j)=(0000d(j1)m+j+1d(j1)m+j00000d(j1)m+m+jd(j1)m+m+j10),j=0,1,,p,
    A(j)=(1A+1djdjm+j+1001A+1djdjm+j+100000000),j=0,1,,p1,

    and

    A(p)=(1A+1d(p1)m+pd1001A+1d(p1)m+pdm+100000000).

    From d1>d2>>dp2(m+1) and dp2(m+1)+1>dp2(m+1)+2>>dpm+p we can get that

    A(p)=(1A+1d(p1)m+pd1001A+1d(p1)m+pdm+100000000).

    Moreover, from A>1 and (16) we have

    1A+1+1(1(m+1)ε)(A+1)<1(1(m+1)ε)(A+1)+1(1(m+1)ε)(A+1)<2(1(m+1)ε)(A+1)<1.

    It is common knowledge that B has the same eigenvalues as DBD1, we have that

    1A+1+1(1(m+1)ε)(A+1)<1(1(m+1)ε)(A+1)+1(1(m+1)ε)(A+1)<2(1(m+1)ε)(A+1)<1.

    We have that all eigenvalues of B lie inside the unit disk. According to Theorem (2.4) we obtain that the unique positive equilibrium (¯x(1),¯x(2),,¯x(p))=(A+1,A+1,,A+1) is locally asymptotically stable. Thus, the proof is completed.

    To prove the global stability of the positive equilibrium, we need the following lemma.

    Lemma 4.5. Suppose A>1. Then every positive solution of the system (3) is bounded and persists.

    Proof. Let {(x(1)n,x(2)n,,x(p)n)}nm be a positive solution to system (3). Then, it is clear that for n1, x(j)n>A>1,j=1,2,,p. So, we get

    x(j)i[L,LLA],i=1,2,,m+1,j=1,2,,p,

    where

    L=min{α,ββ1}>1,α=min1jm+1{x(1)j,x(2)j,,x(p)j},
    β=max1jm+1{x(1)j,x(2)j,,x(p)ji}.

    So, we get

    L=A+LL/(LA)x(j)m+2=A+x(j+1)mod(p)1x(j+1)mod(p)m+1LL1,

    thus, the following is obtained

    Lx(j)mLL1.

    By induction, we get

    x(j)i[L,LL1],j=1,2,,p,i=1,2, (17)

    Theorem 4.6. Assume that A>1. Then the positive equilibrium of system (3) is globally asymptotically stable.

    Proof. Let {(x(1)n,x(2)n,,x(p)n)}nm be a solution of system (3). By Theorem (4.4) we need only to prove that the equilibrium point (A+1,A+1,,A+1) is global attractor, that is

    limn(x(1)n,x(2)n,,x(p)n)=(A+1,A+1,,A+1).

    To do this, we prove that for i=1,2,,p, we have

    limnx(i)n=A+1.

    From Lemma (4.5), we can set

    Li=limnsupx(i)n,mi=limninfx(i)n,i=1,2,,p. (18)

    So, from (3) and (13), we have

    LiA+L(i+1)mod(p)m(i+1)mod(p),miA+m(i+1)mod(p)L(i+1)mod(p). (19)

    We first prove the theorem for p=2. From (19), we get

    AL1+m1L1m2Am2+L2,AL2+m2L2m1Am1+L1.

    So,

    AL1+m1(Am1+L1)Am2+L2(AL2+m2),

    hence

    (A1)(L1m1+L2m2)0,

    since A>1, It follows that

    L1m1+L2m2=0,

    we know that L1m10 and L2m20, so we obtain L1=m1 and L2=m2. Now we assume that the theorem holds for p1, that is Li=mi,i=1,2,,p1 and prove the theorem for p. From (19), we have

    ALp+mpLpm1Am1+L1,AL1+m1L1mpAmp+Lp.

    So,

    ALp+mp(Amp+Lp)Am1+L1(AL1+m1),

    Thus, the following inequality is obtained

    (A1)(Lpmp+L1m1)0,

    since A>1, L1m10 and Lpmp0, we obtain Lp=mp, it signify that

    Li=mi,=1,2,,p.

    Therefore every positive solution {(x(1)n,x(2)n,,x(p)n)}n1 of system (3) tends to (A+1,A+1,,A+1) as n+.

    In this section, we estimate the rate of convergence of a solution that converges to the equilibrium point (¯x(1),¯x(2),,¯x(p))=(A+1,A+1,,A+1) of the system (3) in the region of parameters described by A>1. We give precise results about the rate of convergence of the solutions that converge to the equilibrium point by using Perron's theorems. The following result gives the rate of convergence of solutions of a system of difference equations

    Xn+1=(A+Bn)Xn (20)

    where Xn is a (pm+p)-dimensional vector, AC(pm+p)×(pm+p) is a constant matrix and B:Z+C(pm+p)×(pm+p) is a matrix function satisfying

    Bn0, when n (21)

    where . indicates any matrix norm which is associated with the vector norm ..

    Theorem 5.1. (Perron's first Theorem, see [16]) Suppose that condition (21) holds. If Xn is a solution of (20), then either Xn=0 for all largen or

    ρ=limn+Xn+1Xn

    exists and is equal to the modulus of one of the eigenvalues of matrix A.

    Theorem 5.2. (Perron's second Theorem, see [16]) Suppose that condition (21) holds. If Xn is a solution of (20), then either Xn=0 for all largen or

    ρ=limn+(Xn)1n

    exists and is equal to the modulus of one of the eigenvalues of matrix A.

    Theorem 5.3. Assume that a solution {(x(1)n,x(2)n,,x(p)n)}nm of system (3) converges to the equilibrium (¯x(1),¯x(2),,¯x(p)) which is globally asymptotically stable. Then, the error vector

    en=(e(1)ne(1)n1e(1)nme(p)ne(p)n1e(p)nm)=(x(1)n¯x(1)x(1)n1¯x(1)x(1)nm¯x(1)x(p)n¯x(p)x(p)n1¯x(p)x(p)nm¯x(p))

    of every solution of system (3) satisfies both of the following asymptotic relations:

    limn+en+1en=|λiJF((¯x(1),¯x(2),,¯x(p)))|,i=1,2,,m
    limn+(en)1n=|λiJF((¯x(1),¯x(2),,¯x(p)))|,i=1,2,,m

    where |λiJF((¯x(1),¯x(2),,¯x(p)))| is equal to the modulus of one the eigenvalues of the Jacobian matrix evaluated at the equilibrium point (¯x(1),¯x(2),,¯x(p)).

    Proof. First, we will find a system that satisfies the error terms. The error terms are given as

    x(j)n+1¯x(j)=mi=0(j)A(1)i(x(1)ni¯x(1))+mi=0(j)A(2)i(x(2)ni¯x(2))++mi=0(j)A(1)i(x(p)ni¯x(p)), (22)

    for i=1,2,,m,j=1,2,,p. Set

    e(j)n=x(j)n¯x(j),j=1,2,,p

    Then, system (22) can be written as

    e(j)n+1=mi=0(j)A(1)ie(1)ni+mi=0(j)A(2)ie(2)ni++mi=0(j)A(1)ie(p)ni

    where

    e(j)n+1=mi=0(j)A(1)ie(1)ni+mi=0(j)A(2)ie(2)ni++mi=0(j)A(1)ie(p)ni

    and the others parameters (k)A(j)i are equal zero.

    If we consider the limiting case, It is obvious then that

    e(j)n+1=mi=0(j)A(1)ie(1)ni+mi=0(j)A(2)ie(2)ni++mi=0(j)A(1)ie(p)ni

    That is

    e(j)n+1=mi=0(j)A(1)ie(1)ni+mi=0(j)A(2)ie(2)ni++mi=0(j)A(1)ie(p)ni

    where α(i)n,β(i)n0 when n. Now we have the following system of the form (20)

    en+1=(A+Bn)en

    where en=(e(1)n,e(1)n1,,e(1)nm,e(2)n,e(2)n1,,e(2)nm,,e(p)n,e(p)n1,,e(p)nm)t and

    A=JF((¯x(1),¯x(2),,¯x(p)))=(JA(1)nOOOOOJA(2)nOOOOOJA(3)nOOOOOOJA(p1)nA(p)nOOOOJ)
    Bn=(JAOOOOOJAOOOOOJAOOOOOOJAAOOOOJ)

    where

    A(j)n=(α(j)n00β(j)n00000000),j=1,2,,p.

    and A,J and O are the (m+1)×(m+1) matrix defined in (14) and (15).

    Bn0 when n. Therefore, the limiting system of error terms can be written as

    en+1=(JAOOOOOJAOOOOOJAOOOOOOJAAOOOOJ)(e(1)ne(1)n1e(1)nme(p)ne(p)n1e(p)nm)

    and Bn0 when n. This system is exactly the linearized system of (3) evaluated at the equilibrium point (¯x(1),¯x(2),,¯x(p)). From Theorems (5.1) and (5.2), the result follows.

    In this section we will consider several interesting numerical examples to verify our theoretical results. These examples shows different types of qualitative behavior of solutions of the system (3). All plots in this section are drawn with Matlab.

    Exemple 6.1. Let m=1 and p=10 in system (3), then we obtain the system

    x(1)n+1=1.2+x(2)n1x(2)n,x(2)n+1=A+x(3)n1x(3)n,,x(10)n+1=1.2+x(1)n1x(1)n,nN0 (23)

    with A=1.2>1 and the initial values x(1)1=3.3,x(1)0=2,x(2)1=1.1,x(2)0=0.3,x(3)1=2.3,x(3)0=1.5,x(4)1=0.5,x(4)0=2,x(5)1=1.9,x(5)0=0.8,x(6)1=4,x(6)0=1.3,x(7)1=1.2,x(7)0=1.3,x(8)1=2.1,x(8)0=2.3,x(9)1=3.6,x(9)0=0.2,x(10)1=2.3,x(10)0=1.1. Then the positive equilibrium point (¯x(1),¯x(2),,¯x(10))= (2.2,2.2,,2.2) of system (23)) is globally asymptotically stable (see Figure (1), Theorem (4.4)).

    Figure 1.  The plot of system (23) with A=1.2>1.

    Exemple 6.2. Consider the system (23) with A=1 and the initial values x(1)1=0.3,x(1)0=1.1,x(2)1=1.3,x(2)0=0.3,x(3)1=1.4,x(3)0=1.5,x(4)1=0.5,x(4)0=2,x(5)1=1.9,x(5)0=0.8,x(6)1=4,x(6)0=1.3,x(7)1=1.4,x(7)0=1.3,x(8)1=0.1,x(8)0=1.1,x(9)1=1.6,x(9)0=1.7,x(10)1=1.9,x(10)0=1.1. Then the solution oscillates about the positive equilibrium point (¯x(1),¯x(2),,¯x(10))=(2,2,,2) of system (23) with semi-cycles having at most five terms. Also, the equilibrium is not globally asymptotically stable (see Figure (2), Theorem 4.2).

    Figure 2.  The plot of system (23) with A=1.

    Exemple 6.3. Consider the system (23) with A=0.9 and the initial values x(1)1=1.2,x(1)0=0.7,x(2)1=1.2,x(2)0=2.3,x(3)1=0.4,x(3)0=1.1,x(4)1=0.8,x(4)0=8,x(5)1=1.3,x(5)0=1.8,x(6)1=2.6,x(6)0=0.9,x(7)1=1.4,x(7)0=1.1,x(8)1=0.1,x(8)0=1.4,x(9)1=0.9,x(9)0=1.3,x(10)1=1.2,x(10)0=2.1. Then the positive equilibrium point (¯x(1),¯x(2),¯x(3),¯x(4))=(1.9,1.9,,1.9) of system (23) is not globally asymptotically stable. Also, this solution is unbounded solution see Figure (3), Theorem 4.2).

    Figure 3.  The plot of system (23) with A=0.9<1.

    Exemple 6.4. Let m=5 and p=4 in system (3), then we obtain the system

    x(1)n+1=A+x(2)n5x(2)n,x(2)n+1=A+x(3)n5x(3)n,x(3)n+1=A+x(4)n5x(4)n,x(4)n+1=A+x(1)n5x(1)n,nN0 (24)

    with A=1.4>1 and the initial values x(1)5=1.2,x(1)4=0.8,x(1)3=1.9,x(1)2=2.2,x(1)1=0.3,x(1)0=1.7,x(2)5=1.3,x(2)4=2.4,x(2)3=1.2,x(2)2=0.5,x(2)1=1.6,x(2)0=2.3,x(3)5=0.4,x(3)4=1.1,x(3)3=1.4,x(3)2=2.1,x(3)1=0.3,x(3)0=1.1,x(4)5=0.8,x(4)4=1.2,x(4)3=1.8,x(4)2=3.1,x(4)1=0.7,x(4)0=1.8,. Then the positive equilibrium point (¯x(1),¯x(2),¯x(3),¯x(4))=(2.4,2.4,2.4,2.4) of system (24)) is globally asymptotically stable (see Figure (4), Theorem (4.4)).

    Figure 4.  The plot of system (24) with A=1.4>1.

    Exemple 6.5. Consider the system (24) with A=1 and the initial values x(1)5=0.4,x(1)4=1.3,x(1)3=2.9,x(1)2=1.2,x(1)1=0.8,x(1)0=1.2,x(2)5=0.3,x(2)4=1.4,x(2)3=1.3x(2)2=0.5,x(2)1=1.6,x(2)0=2.1,x(3)5=1.3,x(3)4=2.1,x(3)3=1.4,x(3)2=2.1,x(3)1=0.3,x(3)0=1.5,x(4)5=0.6,x(4)4=1.2,x(4)3=1.3,x(4)2=0.8,x(4)1=1.7,x(4)0=0.1,. Then the solution oscillates about the positive equilibrium point (¯x(1),¯x(2),¯x(3),¯x(4))=(2.4,2.4,2.4,2.4) of system (24) with semi-cycles having at most five terms. Also, the equilibrium is not globally asymptotically stable (see Figure (5), Theorem 4.2).

    Figure 5.  The plot of system (24) with A=1.

    Exemple 6.6. Consider the system (24) with A=0.7 and the initial values x(1)5=1.3,x(1)4=0.9,x(1)3=2.1,x(1)2=0.9,x(1)1=0.7,x(1)0=2.2,x(2)5=1.3,x(2)4=0.4,x(2)3=1.3x(2)2=1.5,x(2)1=1.2,x(2)0=1.1,x(3)5=1.7,x(3)4=1.6,x(3)3=1.5,x(3)2=2.3,x(3)1=0.9,x(3)0=1.5,x(4)5=0.6,x(4)4=1.4,x(4)3=2.3,x(4)2=3.1,x(4)1=2.7,x(4)0=1.9. Then the positive equilibrium point (¯x(1),¯x(2),¯x(3),¯x(4))=(1.7,1.7,1.7,1.7) of system (23) is not globally asymptotically stable. Also, this solution is unbounded solution see Figure (6), Theorem 4.2).

    Figure 6.  The plot of system (24) with A=0.7<1.

    In the paper, we studied the global behavior of solutions of system (3) composed by p rational difference equations. More exactly, we here study the global asymptotic stability of equilibrium, the rate of convergence of positive solutions. Also, we present some results about the general behavior of solutions of system (3) and some numerical examples are carried out to support the analysis results. Our system generalized the equations and systems studied in [2,8] and [20].

    The findings suggest that this approach could also be useful for extended to a system with arbitrary constant different parameters, or to a system with a nonautonomous parameter, or to a system with different parameters and arbitrary powers. So, we will give the following some important open problems for difference equations theory researchers.

    Open Problem 1. study the dynamical behaviors of the system of difference equations

    x(1)n+1=A1+x(2)nmx(2)n,x(2)n+1=A2+x(3)nmx(3)n,,x(p)n+1=Ap+x(1)nmx(1)n,n,m,pN0

    where Ai, i=1,2,,p are nonnegative constants and x(j)m,x(j)m+1,,x(j)1,x(j)0,j=1,2,,p are positive real numbers.

    Open Problem 2. study the dynamical behaviors of the system of difference equations

    x(1)n+1=αn+x(2)nmx(2)n,x(2)n+1=αn+x(3)nmx(3)n,,x(p)n+1=αn+x(1)nmx(1)n,n,m,pN0

    where αn is a sequence (this sequence can be chosen as convergent, periodic or bounded), and x(j)m,x(j)m+1,,x(j)1,x(j)0,j=1,2,,p are positive real numbers.

    Open Problem 3. study the dynamical behaviors of the system of difference equations

    x(1)n+1=A1+(x(2)nm)p1(x(2)n)q1,x(2)n+1=A2+(x(3)nm)p2(x(3)n)q2,,x(p)n+1=Ap+(x(1)nm)pp(x(1)n)qp,

    wheren,m,pN0, Ai, i=1,2,,p are nonnegative constants, the parameters pi,qi, i=1,2,,p are non-negative and x(j)m,x(j)m+1,,x(j)1,x(j)0,j=1,2,,p are positive real numbers.

    This work was supported by Directorate General for Scientific Research and Technological Development (DGRSDT), Algeria.



    [1] Jackson PG, Steenfelt JS, Foged NN, et al. (2004) Evaluation of Bryozoan limestone properties based on in-situ and laboratory element tests. Geotech Geophys Site Charact 1813–1820.
    [2] Foged NN (2008) Rock Mass Characterisation in Limestone. Lecture presented at Dansk Geoteknisk Forening Mode nr. 2 Generalforsamling. (Danish Geotechnical Society Meeting nr. 2 General assembly.)
    [3] Foged NN, Hansen SL, Stabell S (2010) Developments in Rock Mass Evaluation of Limestone in Denmark. In: Rock mechanics in the Nordic countries, Norway: Kongberg.
    [4] Galsgaard J. (2014) Flint in the Danian København Limestone Formation. (Flint in the Danian Copenhagen Limestone Formation.) Available from: https://www.geo.dk/media/1951/flint-in-the-danian-koebenhavn-limestone-formation_jgalsgaard_2014.pdf
    [5] Jakobsen L, Foged NN, Erichsen L, et al. (2015) Face logging in Copenhagen Limestone, Denmark. Proceedings of the XVI ECSMGE Geotechnical Engineering for Infrastructure and Development, 2939–2944.
    [6] Hansen SL, Galsgaard J, Foged NN (2015) Rock mass characterization for Copenhagen Metro using face logs. SEE TUNNEL-Promoting tunnelling in SE European region, Presented at: 41st General Assembly and Congress of International Tunneling and Underground Space.
    [7] Katić N, Christensen HF (2014). Upscaling elastic moduli in Copenhagen Limestone. In Rock Engineering and Rock Mechanics: Structures in and on Rock Masses: Proceedings of EUROCK 2014, ISRM European Regional Symposium, London: Taylor & Francis Group, 235–240.
    [8] Katić N, Christensen HF (2015) Composite Elasticity of Copenhagen Limestone. In Proceedings of the ISRM Regional Symposium EUROCK 2015 & 64th Geomechanics Colloquium-Future Development of Rock Mechanics, Salzburg: Austrian Society for Geomechanics, 451–456.
    [9] Vangkilde-Pedersen T, Mielby S, Jakobsen PR, et al. (2011) Kortlægning af kalkmagasiner. GEUS. Geo-vejledning 8. De nationale geologiske undersøgelser for Danmark og Grønland. Ministeriet for klima og energy. (Mapping of limestone reservoirs. GEUS. Geo-guidance 8. National geological investigations for Denmark and Greenland. Ministry of climate and energy.) Available from: gk.geus.info/xpdf/geovejledning_8_kalk_final_net.pdf.
    [10] Bjerager M, Surlyk F (2007) Danian Cool-Water Bryozoan Mounds at Stevns Klint, Denmark–A New Class of Non-Cemented Skeletal Mounds. J Sediment Res 77:634–660. doi: 10.2110/jsr.2007.064
    [11] Japsen P, Bidstrup T, Lidmar-Berström K (2002) Neogene uplift and erosion of southern Scandinavia induced by the rise of the South Swedish Dome. Geol Soc 196: 183–207. doi: 10.1144/GSL.SP.2002.196.01.12
    [12] Andersen TB, Møgaard MR (2018) Copenhagen Area Overview of the geological conditions in the Copenhagen area and surrounding areas. GeoAtlas Live Documentation. Report 1. Available from: http://wgn.geo.dk/geodata/modeldokumentation/Copenhagen%20_25m_2018-07-12.pdf
    [13] Olsen H, Nielsen UT (2002) Logstratigrafisk inddeling af kalken I Københavns-området. In Frederiksen JK, Eriksen FS, Hansen HK, et al., editors. Ingeniørgeologiske forhold i København. Dgf-Bulletin 19, Danish Geotechnical Society. (Logstratigraphical division of limestone in Copenhagen Area. In Frederiksen JK, Eriksen FS, Hansen HK, et al., editors. Engineering-geological conditions in Copenhagen. Dgf-Bulletin 19, Danish Geotechnical Society.)
    [14] Damholt T, Surlyk F (2012) Nomination of Stevns Klint for inclusion in the World Heritage List. Østsjællands Museum. Pedersen AS (2011) Rockfalls at Stevns Klint. Landslide hazard assessment based on photogrametrical supported geological analysis of the limestone cliff Stevns Klint in eastern Denmark. Danmarks og Grønlands Geologiske Undersøgelse Rapport 2011/93 (Danmark's and Greenland's Geological Investigaton Report 2011/93). Available from: https://whc.unesco.org/uploads/nominations/1416.pdf.
    [15] Mortensen N, Hansen HK, Hansen PB (1999) Malmö Citytunneln.Rock Mechanical Description. Limestone. Malmö (SE). 32p. Report 1, 22 March 1999, Revision 1. DGI job No. 155 16092. Geo archive.
    [16] Jørgensen NO (1975) Mg/Sr distribution and diagenesis of Maastrichtian white chalk and Danian bryozoan limestone from Jylland, Denmark. Bull Geol Soc Den 24: 299–325.
    [17] Rosenbom A, Jakobsen PR (2000) Kalk, Sprækker og Termografi. Geol Nyt fra GEUS 3: 1–8. (Chalk, Fractures and Thermography. Geol News From GEUS 3: 1–8.)
    [18] Surlyk F, Damholt T, Bjerager M (2006) Stevns Klint, Denmark: uppermost Maastrichtian chalk, Cretaceous-Tertiary boundary, and lower Danian bryozoan mound complex, Geological Society of Denmark, 54: 1–48.
    [19] Hoek E, Carter TG, Diedrichs MS (2013) Quantification of the Geological Strength Index Chart. 47th US Rock Mechanics/Geomechanics Symposium, 1757–1764.
    [20] Eberli GP, Beachle TG, Anselmetti FS, et al. (2003) Factors controlling elastic properties in carbonate sediments and rocks. Lead Edge 22: 654–660. doi: 10.1190/1.1599691
    [21] Brigaud B, Vincent B, Durlet C, et al. (2010) Acoustic properties of ancient shallow-marine carbonates: effects of depositional environments and diagenetic processes (Middle Jurassic, Paris basin, France). J Sediment Res 80:791–807. doi: 10.2110/jsr.2010.071
    [22] Bergdahl U, Steenfelt JS (1994) Digest report on strength and deformation properties of Copenhagen limestone, Swedish Geotechnical Institute/Danish Geotechnical Institute, 67.
  • Reader Comments
  • © 2019 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(7103) PDF downloads(1164) Cited by(2)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog