Processing math: 61%
Research article Special Issues

The mR scheme to the shallow water equation with horizontal density gradients in one and two dimensions

  • Received: 13 May 2023 Revised: 11 August 2023 Accepted: 21 August 2023 Published: 07 September 2023
  • MSC : 35L60, 35L67, 76M12, 86A05

  • In this work, we consider the model of shallow water equation with horizontal density gradients. We develop the modified Rusanov (mR) scheme to solve this model in one and two dimensions. Predictor and corrector are the two stages of the suggested scheme. The predictor stage is dependent on a local parameter (αni+12) that allows for diffusion control. The balance conservation equation is recovered in the corrector stage. The proposed approach is well-balanced, conservative, and straightforward. Several 1D and 2D test cases are produced after presenting the shallow water model and the numerical technique. In the 1D case, we compared the proposed scheme with the Rusanov scheme, mR with constant α and analytical solutions. The numerical simulation demonstrates the mR's great resolution and attests to its capacity to produce accurate simulations of the shallow water equation with horizontal density gradients. Our results demonstrate that the mR technique is a highly effective instrument for solving a variety of equations in applied science and developed physics.

    Citation: Kamel Mohamed, H. S. Alayachi, Mahmoud A. E. Abdelrahman. The mR scheme to the shallow water equation with horizontal density gradients in one and two dimensions[J]. AIMS Mathematics, 2023, 8(11): 25754-25771. doi: 10.3934/math.20231314

    Related Papers:

    [1] Ndolane Sene . Fractional input stability for electrical circuits described by the Riemann-Liouville and the Caputo fractional derivatives. AIMS Mathematics, 2019, 4(1): 147-165. doi: 10.3934/Math.2019.1.147
    [2] Thabet Abdeljawad, Sabri T. M. Thabet, Imed Kedim, Miguel Vivas-Cortez . On a new structure of multi-term Hilfer fractional impulsive neutral Levin-Nohel integrodifferential system with variable time delay. AIMS Mathematics, 2024, 9(3): 7372-7395. doi: 10.3934/math.2024357
    [3] Hadjer Belbali, Maamar Benbachir, Sina Etemad, Choonkil Park, Shahram Rezapour . Existence theory and generalized Mittag-Leffler stability for a nonlinear Caputo-Hadamard FIVP via the Lyapunov method. AIMS Mathematics, 2022, 7(8): 14419-14433. doi: 10.3934/math.2022794
    [4] Sabri T. M. Thabet, Reem M. Alraimy, Imed Kedim, Aiman Mukheimer, Thabet Abdeljawad . Exploring the solutions of a financial bubble model via a new fractional derivative. AIMS Mathematics, 2025, 10(4): 8587-8614. doi: 10.3934/math.2025394
    [5] Minghung Lin, Yiyou Hou, Maryam A. Al-Towailb, Hassan Saberi-Nik . The global attractive sets and synchronization of a fractional-order complex dynamical system. AIMS Mathematics, 2023, 8(2): 3523-3541. doi: 10.3934/math.2023179
    [6] Wei Liu, Qinghua Zuo, Chen Xu . Finite-time and global Mittag-Leffler stability of fractional-order neural networks with S-type distributed delays. AIMS Mathematics, 2024, 9(4): 8339-8352. doi: 10.3934/math.2024405
    [7] Veliappan Vijayaraj, Chokkalingam Ravichandran, Thongchai Botmart, Kottakkaran Sooppy Nisar, Kasthurisamy Jothimani . Existence and data dependence results for neutral fractional order integro-differential equations. AIMS Mathematics, 2023, 8(1): 1055-1071. doi: 10.3934/math.2023052
    [8] Anumanthappa Ganesh, Swaminathan Deepa, Dumitru Baleanu, Shyam Sundar Santra, Osama Moaaz, Vediyappan Govindan, Rifaqat Ali . Hyers-Ulam-Mittag-Leffler stability of fractional differential equations with two caputo derivative using fractional fourier transform. AIMS Mathematics, 2022, 7(2): 1791-1810. doi: 10.3934/math.2022103
    [9] Weerawat Sudsutad, Chatthai Thaiprayoon, Aphirak Aphithana, Jutarat Kongson, Weerapan Sae-dan . Qualitative results and numerical approximations of the (k,ψ)-Caputo proportional fractional differential equations and applications to blood alcohol levels model. AIMS Mathematics, 2024, 9(12): 34013-34041. doi: 10.3934/math.20241622
    [10] Rabah Khaldi, Assia Guezane-Lakoud . On a generalized Lyapunov inequality for a mixed fractional boundary value problem. AIMS Mathematics, 2019, 4(3): 506-515. doi: 10.3934/math.2019.3.506
  • In this work, we consider the model of shallow water equation with horizontal density gradients. We develop the modified Rusanov (mR) scheme to solve this model in one and two dimensions. Predictor and corrector are the two stages of the suggested scheme. The predictor stage is dependent on a local parameter (αni+12) that allows for diffusion control. The balance conservation equation is recovered in the corrector stage. The proposed approach is well-balanced, conservative, and straightforward. Several 1D and 2D test cases are produced after presenting the shallow water model and the numerical technique. In the 1D case, we compared the proposed scheme with the Rusanov scheme, mR with constant α and analytical solutions. The numerical simulation demonstrates the mR's great resolution and attests to its capacity to produce accurate simulations of the shallow water equation with horizontal density gradients. Our results demonstrate that the mR technique is a highly effective instrument for solving a variety of equations in applied science and developed physics.



    The colored noise was first introduced in [23,24] in order to obtain the information of velocity of randomly moving particles, which cannot be obtained from the white noise since the the Wiener process is nowhere differentiable. Moreover, for many physical systems, the stochastic fluctuations are correlated and should be modeled by the colored noise rather than the white noise, see [20].

    This paper is concerned the asymptotic behavior of the plate equation driven by nonlinear colored noise in unbounded domains:

    {utt+αut+Δ2u+0μ(s)Δ2(u(t)u(ts))ds+νu+f(x,u)                 =g(x,t)+h(t,x,u)ζδ(θtω), t>τ, xRn,u(x,τ)=u0(x),ut(x,τ)=u1,0(x), xRn,  tτ, (1.1)

    where τR, α,ν are positive constants, μ is the memory kernel, f and h are given nonlinearity, gL2loc(R,H1(Rn)), and ζδ is a colored noise with correlation time δ>0.

    It is clear that (1.1) becomes a deterministic plate equation as μ0 and h0. In this case, we can characterize the long-time behavior of solutions by virtue of the concept of global attractors under the framework of semigroup. Some authors have extensively studied the existence of global attractors for the autonomous plate equation. For instance, the attractors of deterministic plate equations have been investigated in [2,8,12,14,30,32,33,34,35,44] in bounded domains. In [2,30,34,35], the authors considered global attractor for the plate equation with thermal memory; Khanmamedov investigated a global attractor for the plate equation with displacement-dependent damping in [8]; Liu and Ma obtained the existence of time-dependent strong pullback attractors for non-autonomous plate equations in [12,14]; Yang and Zhong studied the uniform attractor and global attractor for non-autonomous plate equations with nonlinear damping in [32,33], respectively; In [44], the author obtained global existence and blow-up of solutions for a Kirchhoff type plate equation with damping. For the case of unbounded domains, see refereces [9,10,13,31,42].

    The existence and uniqueness of pathwise random attractors of stochastic plate equations have been studied in [15,16,21,22] in the case of bounded domains; and in [36,37,38,39,40,41] in the case of unbounded domains. In all these publications ([36,37,38,39,40,41]), only the additive white noise and linear multiplicative white noise were considered. Notice that the random equation (1.1) is driven by the colored noise rather than the white noise. In general, it is very hard to study the asymptotic dynamics of differential equations driven by nonlinear white noise, including the random attractors. Indeed, only when the white noise is linear, the stochastic equations can be transformed into a deterministic equations, then one can obtain the existence of random attractors of the plate equation (1.1). However, this transformation does not apply to stochastic equations driven by nonlinear white noise, and that is why we are currently unable to prove the existence of random attractors for systems with nonlinear white noise.

    For the colored noise, even it is nonlinear, we are able to show system (1.1) has a random attractor in H2(Rn)×L2(Rn)×Rμ,2 (the definition of Rμ,2 see Section 3), which is quite different from the nonlinear white noise. The reader is referred to [6,7,26,27] for more details on random attractors of differential equations driven by colored noise. However, for the random plate equations driven by colored noise (1.1), we find that there is no results available to the existence of random attractors. In the present paper, we will prove that (1.1) is pathwise well-posed and generate a continuous cocycle, and the cocycle possesses a unique tempered random attractor. This is different from the corresponding stochastic system driven by white noise

    utt+αut+Δ2u+0μ(s)Δ2(u(t)u(ts))ds+νu+f(x,u)=g(x,t)+h(t,x,u)dWdt,t>τ, xRn, (1.2)

    where the symbol indicates that the equation is understood in the sense of stratonovich integration. For (1.2), one can define a random dynamical system when h(,,u) is a linear function, see [41]. But for a general nonlinear function h, random dynamical system associated with (1.2) can not be defined due to the absence of appropriate transformation, hence asymptotic behavior of such stochastic equations has not been investigated until now by the random dynamical system approach. This paper indicates that the colored noise is much easier to handle than the white noise for studying pathwise dynamics of such stochastic equations.

    The main purpose of the paper is establish the existence and uniqueness of measurable tempered random attractors in H2(Rn)×L2(Rn)×Rμ,2 for the dynamical system associated with (1.1). The key for achieving our goal is to establish the tempered pullback asymptotic compactness of solutions of (1.1) in H2(Rn)×L2(Rn)×Rμ,2. Involving to our problem (1.1), there are two essential difficulties in verifying the compactness. On the one hand, notice that system (1.1) is defined in the unbounded domain Rn where the noncompactness of Sobolev embeddings on unbounded domains gives rise to difficulty in showing the pullback asymptotic compactness of solutions, to get through of it, we use the tail-estimates method (as in[25]) and the splitting technique (see [3]) to obtain the pullback asymptotic compactness. On the other hand, there is no applicable compact embedding property in the "history'' space. In this case, we solve it with the help of a useful result in [19]. For our purpose, we introduce a new variable and an extend Hilbert space.

    The rest of this article consists of four sections. In the next section, we define some functions sets and recall some useful results. In Section 3, we first establish the existence, uniqueness and continuity of solutions in initial data of (1.1) in H2(Rn)×L2(Rn)×Rμ,2, then define a non-autonomous random dynamical system based on the solution operator of problem (1.1). The last two section are devoted to derive necessary estimates of solutions of (1.1) and the existence of random attractors.

    Throughout the paper, the inner product and the norm of L2(Rn) will be denoted by (,) and ||||, respectively. The letters c and ci(i=1,2,) are generic positive constants which may depend on some parameters in the contexts.

    In this section, we define some functions sets and recall some useful results, see [4,17,18,28,29,43]. These results will be used to establish the asymptotic compactness of the solutions and attractor for the random plate equation defined on the entire space Rn.

    From now on, we assume (Ω,F,P) is the canonical probability space where Ω={ωC(R,R):ω(0)=0} with compact-open topology, F is the Borel σ-algebra of Ω, and P is the Wiener measure on (Ω,F). Recall the standard group of transformations {θt}tR on Ω:

    θtω()=ω(t+)ω(t),  tR and  ωΩ.

    Suppose Φ:R+×R×Ω×XX is a continuous cocycle on X over (Ω,F,P,{θt}tR). Let D be a collection of some families of nonempty subset of X:

    D={D={D(τ,ω)X:D(τ,ω),τR,ωΩ}}.

    Suppose Φ has a D-pullback absorbing set K={K(τ,ω):τR,ωΩ}D; that is, for every τR, ωΩ and DD there exists T=T(τ,ω,D)>0 such that for all tT,

    Φ(t,τt,θtω,D(τt,θtω))K(τ,ω). (2.1)

    Assume that

    Φ(t,τ,ω,x)=Φ1(t,τ,ω,x)+Φ2(t,τ,ω,x),  tR+, τR, ωΩ, xX, (2.2)

    where both Φ1 and Φ2 are mappings from R+×R×Ω×X to X.

    Given kN, denote by Ok={xRn:|x|<k} and ˜Ok={xRn:|x|>k}. Let X be a Banach space with norm X which consists of some functions defined on Rn. Given a function u:RnR, the restrictions of u to Ok and ˜Ok are written as u|Ok and u|˜Ok, respectively. Denote by

    XOk={u|Ok:uX}  and  X˜Ok={u|˜Ok:uX}.

    Suppose XOk and X˜Ok are Banach spaces with norm Ok and ˜Ok, respectively, and

    uXu|OkOk+u|˜Ok˜Ok,   uX. (2.3)

    We further assume that for every δ>0, τR, and ωΩ, there exists t0=t0(δ,τ,ω,K)>0 and k0=k0(δ,τ,ω)1 such that

    Φ(t0,τt0,θt0ω,x)|˜Ok0˜Ok0<δ,  xK(τt0,θt0ω), (2.4)

    and

    Φ1(t0,τt0,θt0ω,K(τt0,θt0ω))|Ok0has a finite cover of balls of radius δ in X|Ok0. (2.5)

    In addition, we assume that for every kN, tR+, τR, and ωΩ, the set

    Φ2(t,τt,θtω,K(τt,θtω)) is precompact in X|Ok. (2.6)

    Theorem 2.1 [29]. If (2.1)-(2.6) hold, then the cocycle Φ is D-pullback asymptotically compact in X; that is, the sequence {Φ(tn,τtn,θtnω,xn)}n=1 is precompact in X for any τR,ωΩ,DD,tn monotonically, and xnD(τtn,θtnω).

    Theorem 2.2 [29]. Let D be an inclusion closed collection of some families of nonempty subsets of X, and Φ be a continuous cocycle on X over (Ω,F,P,{θt}tR). Then Φ has a unique D-pullback random attractor A in D if Φ is D-pullback asymptotically compact in X and Φ has a closed measurable D-pullback absorbing set K in D.

    In this section, we first establish the existence of solution for problem (1.1), then define a non-autonomous cocycle of (1.1).

    Given δ>0, let ζδ(θtω) be the unique stationary solution of the stochastic equation:

    dζδ+1δζδdt=1δdW, (3.1)

    where W is a two-sided real-valued Wiener process on (Ω,F,P). The process ζδ(θtω) is called the one-dimensional colored noise. Recall that there exists a θt-invariant subset of full measure (see [1]), which is still denoted by Ω, such that for all ωΩ, ζδ(θtω) is continuous in tR and

    limt±ζδ(θtω)t=0.

    Let Δ denote the Laplace operator in Rn, A=Δ2 with the domain D(A)=H4(Rn). We can also define the powers Aν of A for νR. The space Vν=D(Aν4) is a Hilbert space with the following inner product and norm

    (u,v)ν=(Aν4u,Aν4v),ν=Aν4.

    Following Dafermos [5], we introduce a Hilbert "history" space Rμ,2=L2μ(R+,V2) with the inner product

    (η1,η2)μ,2=0μ(s)(Δη1(s),Δη2(s))ds,   η1,η2Rμ,2,

    and new variables

    η=ηt(x,s)=u(x,t)u(x,ts), (x,s)Rn×R+,  tτ.

    By differentiation we have

    ηtt(x,s)=ηts(x,s)+ut(x,t), (x,s)Rn×R+,  tτ.

    Then (1.1) can be rewritten as the equivalent system

    {utt+αut+Δ2u+0μ(s)Δ2ηt(s)ds+νu+f(x,u)                 =g(x,t)+h(t,x,u)ζδ(θtω), t>τ, xRn,ηtt+ηts=ut,u(x,τ)=u0(x),ut(x,τ)=u1,0(x), xRn,  tτ,ητ(x,s)=η0(x,s)=u(x,τ)u(x,τs),  xRn,sR+. (3.2)

    We introduce the following hypotheses to complete the uniform estimates.

    Assume that the memory kernel function μC1(R+)L1(R+), and satisfy the following conditions:

     sR+ and some ϱ>0.

    μ(s)0,μ(s)+ϱμ0, (3.3)

    note that (3.3) implies ϖdef=μL1(R+)=0μ(s)ds>0.

    Let f:Rn×RR be a continuous function and F(x,r)=r0f(x,s)ds for all xRn,rR and s,s1,s2R,

    lim inf|s|infxRn(f(x,s)s)>0, (3.4)
    f(x,0)=0, |f(x,s1)f(x,s2)|α1(φ(x)+|s1|p+|s2|p)|s1s2|, (3.5)
    F(x,s)+φ1(x)0, (3.6)

    where p>0 for 1n4 and 0<p4n4 for n5, α1 is a positive constant, φ1L1(Rn), and φL(Rn).

    Let h:R×Rn×R×R be continuous such that for all t,s,s1,s2R and xRn,

    |h(t,x,s)|α2|s|+φ2(t,x), (3.7)
    |h(t,x,s1)h(t,x,s2)|α3|s1s2|, (3.8)

    where α2 and α3 are positive constants, and φ2L2loc(R,L2(Rn)).

    By (3.3), the space Rμ,r=L2μ(R+,Vr)(rR) is a Hilbert space of Vr-valued functions on R+ with the inner product and norm

    (ηt1,ηt2)μ,r=0μ(s)(Ar4ηt1(s),Ar4ηt2(s))ds,ηt2μ,r=0μ(s)(Ar4ηt(s),Ar4ηt(s))ds,ηt,ηt1,ηt2Vr,

    and on Rμ,r, the linear operator s has domain

    D(s)={ηtH1μ(R+,Vr):η0=0}  where  H1μ(R+,Vr)={ηt:ηt(s),sηtL2μ(R+,Vr)}.

    Definition 3.1. Given τR,ωΩ, T>0,u0H2(Rn), u1,0L2(Rn), and η0Rμ,2, a function z(t)=(u,ut,ηt) is called a (weak) solution of (3.2) if the following conditions are fulfilled:

    (i) u(,τ,ω,u0,u1,0)L(τ,τ+T;H2(Rn))C([τ,τ+T],L2(Rn)) with u(τ,τ,ω,u0,u1,0)=u0,ut(,τ,ω,u0,u1,0)L(τ,τ+T;L2(Rn))C([τ,τ+T],L2(Rn)) with ut(τ,τ,ω,u0,u1,0)=u1,0 and ηt(,τ,ω,η0,s)L(τ,τ+T;Rμ,2)C([τ,τ+T],L2(Rn)) with ηt(τ,τ,ω,η0,s)=η0.

    (ii) u(t,τ,,u0,u1,0):ΩH2(Rn) is (F,B(H2(Rn))-measurable, ut(t,τ,,u0,u1,0):ΩL2(Rn) is (F,B(L2(Rn))-measurable, and ηt(t,τ,,η0,s):ΩRμ,2 is (F,B(Rμ,2)-measurable.

    (iii) For all ξC0((τ,τ+T)×Rn),

    τ+Tτ(ut,ξt)dt+ατ+Tτ(ut,ξ)dt+τ+Tτ(Δu,Δξ)dt             +0μ(s)(Δ2ηt(s),ξ)ds+ντ+Tτ(u,ξ)dt+τ+TτRnf(x,u(t,x))ξ(t,x)dxdt=τ+Tτ(g(t,x),ξ)dt+τ+TτRnh(t,x,u(t,x))ζδ(θtω)ξ(t,x)dxdt.

    In order to investigate the long-time dynamics, we are now ready to prove the existence and uniqueness of solutions of (3.2). We first recall the following well-known existence and uniqueness of solutions for the corresponding linear plate equations of (1.1)(see [34,35]).

    Lemma 3.1. Let u0H2(Rn),u1,0L2(Rn) and gL1(τ,τ+T;L2(Rn)) with τR and T>0. Then the linear plate equation

    utt+αut+Δ2u+0μ(s)Δ2(u(t)u(ts))ds+νu=g(t),  τ<tτ+T,

    with the initial conditions

    u(τ)=u0,   and    ut(τ)=u1,0,

    possesses a unique solution (u,ut,ηt) in the sense of Definition 3.1. In addition,

    uC([τ,τ+T],H2(Rn)),  utC([τ,τ+T],L2(Rn)) and   ηtC([τ,τ+T],Rμ,2)

    and there exists a positive number C depending only on ν (but independent of τ,T,u0,u1,0 and g) such that for all t[τ,τ+T],

    u(t)H2(Rn)+ut(t)+ηtμ,2C(u0H2(Rn)+u1,0+τ+Tτg(t)dt). (3.9)

    Furthermore, the solution (u,ut,ηt) satisfies the energy equation

    ddt(ut2+Δu2+νu2+ηt2μ,2)=2αut2+0μ(s)Δηt2ds+2(g(t),ut), (3.10)

    and

    ddt(u(t),ut(t))+α(u(t),ut(t))+Δu(t)2+(ηt(s),u(t))μ,2+νu(t)2=ut(t)2+(g(t),u(t)), (3.11)

    for almost all t[τ,τ+T].

    Theorem 3.1. Let τR,u0H2(Rn),u1,0L2(Rn) and η0Rμ,2. Suppose (3.3)-(3.8) hold, then:

    (a) Problem (3.2) possesses a solution z(t)=(u,ut,ηt) in the sense of Definition 3.1;

    (b) The solution z(t)=(u,ut,ηt) to problem (3.2) is unique, continuous in initial data in H2(Rn)×L2(Rn)×Rμ,2, and

    uC([τ,τ+T],H2(Rn)),  utC([τ,τ+T],L2(Rn))  and  ηtC([τ,τ+T],Rμ,2). (3.12)

    Moreover, the solution z(t)=(u,ut,ηt) to problem (3.2) satisfies the energy equation:

    ddt(ut2+νu2+Δu2+ηt2μ,2+2RnF(x,u(t,x))dx)+2αut2=0μ(s)Δηt2ds+2(g(t),ut)+2ζδ(θtω)Rnh(t,x,u(t,x))ut(t,x)dx (3.13)

    for almost all t[τ,τ+T].

    Proof. The proof will be divided into four steps. We first construct a sequence of approximate solutions, and then derive uniform estimates, in the last two steps we take the limit of those approximate solutions to prove the uniqueness of solutions.

    Step (i): Approximate solutions. Given kN, define a function ηk:RR by

    ηk(s)={s,     if  ksk,k,     if  s>k,k,   if  s<k. (3.14)

    Then for every fixed kN, the function ηk as defined by (3.14) is bounded and Lipschitz continuous; more precisely, for all s,s1,s2R

    ηk(0)=0,|ηk(s)||s|  and  |ηk(s1)ηk(s2)||s1s2|. (3.15)

    For all xRn and t,sR, denote

    fk(x,s)=f(x,ηk(s)),  Fk(x,s)=s0fk(x,r)dr  and  hk(t,x,s)=h(t,x,ηk(s)). (3.16)

    By (3.4) we know that there exists k0N such that for all |s|k0 and xRn,

    f(x,s)s>0, (3.17)

    thus, for all kk0 and xRn,

    fk(x,k)>0,      fk(x,k)<0. (3.18)

    By (3.5)-(3.6), (3.15)-(3.16) and (3.18) we know that for all s,s1,s2R and xRn,

    |fk(x,s1)fk(x,s2)|α1(φ(x)+|s1|p+|s2|p)|s1s2|,  k1, (3.19)

    and

    Fk(x,s)+φ1(x)0,  kk0. (3.20)

    By (3.19) we get that for all sN and xRn,

    |Fk(x,s)|α1(φ(x)|s|2+|s|p+2),   k1. (3.21)

    By (3.7)-(3.8) and (3.15)-(3.16) we obtain that for all k1,t,s,s1,s2R and xRn,

    |hk(t,x,s)|α2|s|+φ2(t,x), (3.22)
    |hk(t,x,s1)hk(t,x,s2)|α3|s1s2|. (3.23)

    By (3.3) and (3.15)-(3.16), we find that for all kN,s,s1,s2N and xRn,

    |fk(x,s)|α1k(φ(x)+kp), (3.24)
    |fk(x,s1)fk(x,s2)|α1(φ(x)+2kp)|s1s2|. (3.25)

    For every kN, consider the following approximate system for uk,ηtk:

    {2t2uk+αtuk+Δ2uk+0μ(s)Δ2ηtk(s)ds+νuk+fk(,uk)             =g(,t)+hk(t,,uk)ζδ(θtω), t>τ,uk(τ)=u0,tuk(τ)=u1,0,ητk(x,s)=η0(x,s). (3.26)

    From (3.23)-(3.24), φL(Rn) and the standard method (see, e.g., [11]), it follows that for each τR,ωΩ,u0H2(Rn),u1,0L2(Rn) and η0Rμ,2, problem (3.26) has a unique global solution (uk,tuk,ηtk) defined on [τ,τ+T] for every T>0 in the sense of Definition 3.1. In particular, uk(,τ,ω,u0)C([τ,τ+T],H2(Rn)) and uk(t,τ,ω,u0) is measurable with respect to ωΩ in H2(Rn) for every t[τ,τ+T]; tuk(,τ,ω,u0)C([τ,τ+T],L2(Rn)) and tuk(t,τ,ω,u0) is measurable with respect to ωΩ in L2(Rn) for every t[τ,τ+T]; ηtk(,τ,ω,η0,s)C([τ,τ+T],Rμ,2) and ηtk(t,τ,ω,η0,s) is measurable with respect to ωΩ in Rμ,2 for every t[τ,τ+T] Furthermore, the solution uk satisfies the energy equation:

    ddt(tuk2+νuk2+Δuk2+ηtk2μ,2+2RnFk(x,uk(t,x))dx)+2αtuk2=0μ(s)Δηtk2ds+2(g(t),tuk)+2ζδ(θtω)Rnhk(t,x,uk(t,x))tuk(t,x)dx (3.27)

    for almost all t[τ,τ+T]. Next, we use the energy equation (3.25) to derive uniform estimate on the sequence {uk,tuk,ηtk}k=1.

    Step (ii): Uniform estimates.

    For the last term on the right-hand side of (3.25), by (3.21) we have

    2ζδ(θtω)Rnhk(t,x,uk(t,x))tuk(t,x)dx2|ζδ(θtω)|(α2Rn|uk(t,x)||tuk(t,x)|dx+Rn|φ2(t,x)||tuk(t,x)|dx)|ζδ(θtω)|(α2uk(t)2+(1+α2)tuk(t)2+φ2(t)2). (3.28)

    By Young's inequality, we get

    2(g(t),tuk)tuk(t)2+g(t)2. (3.29)

    By (3.27)–(3.29) together with (3.3), it follows that for almost all t[τ,τ+T],

    ddt(tuk2+νuk2+Δuk2+ηtk2μ,2+2RnFk(x,uk(t,x))dx)+2αtuk2c1(1+|ζδ(θtω)|)(uk(t)2+tuk(t)2)+|ζδ(θtω)|φ2(t)2+g(t)2, (3.30)

    where c1>0 depends only on α2, but independent of k.

    By (3.20) and (3.30) we obtain

    ddt(tuk2+νuk2+Δuk2+ηtk2μ,2+2RnFk(x,uk(t,x))dx)c2(1+|ζδ(θtω)|)(tuk(t)2+νuk(t)2+Δuk2+ηtk2μ,2+2RnFk(x,uk(t,x))dx)+|ζδ(θtω)|φ2(t)2+2c1(1+|ζδ(θtω)|)φ1L1(Rn)+g(t)2, (3.31)

    where c2>0 depends only on ν and α2, but independent of k.

    Multiplying (3.31) with ec2t0(1+|ζδ(θrω)|)dr, and then integrating the inequality on (τ,t), we have

    tuk2+νuk2+Δuk2+ηtk2μ,2+2RnFk(x,uk(t,x))dxec2tτ(1+|ζδ(θrω)|)dr(u1,02+νu02+Δu02+η02μ,2+2RnFk(x,u0(x))dx)+tτec2ts(1+|ζδ(θrω)|)dr(|ζδ(θsω)|φ2(s)2+2c1(1+|ζδ(θsω)|)φ1L1(Rn)+g(s)2)ds. (3.32)

    By (3.21) we get, for all k1,

    2Rn|Fk(x,u0(x))|dx2α1(φL(Rn)u02+u0p+2Lp+2(Rn))2α1(φL(Rn)u02+u0p+2H2(Rn)). (3.33)

    By (3.32)-(3.33) imply that there exists a positive constant c3=c3(τ,T,φ,φ1,φ2,g,ω,δ,α1,ν) (but independent of k,u0,u1,0) such that for all t[τ,τ+T] and k1,

    tuk2+νuk2+Δuk2+ηtk2μ,2+2RnFk(x,uk(t,x))dxc3+c3(1+u1,02+u0p+2H2(Rn)+η02μ,2),

    which along with (3.20) show that for all t[τ,τ+T] and kk0,

    tuk2+νuk2+Δuk2+ηtk2μ,2+2RnFk(x,uk(t,x))dxc3+2φ1L1(Rn)+c3(1+u1,02+u0p+2H2(Rn)+η02μ,2), (3.34)

    thus,

    {uk}k=1  is bounded in   L(τ,τ+T;H2(Rn)), (3.35)
    {tuk}k=1  is bounded in   L(τ,τ+T;L2(Rn)). (3.36)
    {ηtk}k=1  is bounded in   L(τ,τ+T;Rμ,2), (3.37)

    By (3.19), there exists a positive constant c4=c4(p,n,α1) such that

    Rn|fk(x,uk(t,x))|2dxc4(Rn|φ(x)|2dx+Rn|uk(t,x)|2(p+1)dx),

    which along with the embedding H2(Rn)L2(p+1)(Rn) and the assumption φL(Rn) implies that there exists c5=c5(p,n,α1,φ)>0 (independent of k) such that

    Rn|fk(x,uk(t,x))|2dxc5(1+uk(t)2(p+1)H2(Rn)). (3.38)

    By (3.35) and (3.38) we see that

    {fk(,uk)}k=1  is bounded in   L2(τ,τ+T;L2(Rn)). (3.39)

    By (3.22) we get

    Rn|hk(t,x,uk(t,x))|2dx2α2uk2+2φ2(t)2,

    which together with (3.35) shows that

    {hk(,,uk)}k=1  is bounded in   L2(τ,τ+T;L2(Rn)). (3.40)

    By (3.35)–(3.37) and (3.39)-(3.40), it follows that there exists uL(τ,τ+T;H2(Rn)) with tuL(τ,τ+T;L2(Rn)),κ1L2(τ,τ+T;L2(Rn)),κ2L2(τ,τ+T;L2(Rn)),vτ+TH2(Rn) and vτ+T1L2(Rn) such that

    uku  weak-star in  L(τ,τ+T;H2(Rn)), (3.41)
    tuktu  weak-star in  L(τ,τ+T;L2(Rn)), (3.42)
    ηtkηt  weak-star in  L(τ,τ+T;Rμ,2), (3.43)
    fk(,uk)κ1  weakly in  L2(τ,τ+T;L2(Rn)), (3.44)
    hk(,,uk)κ2  weakly in  L2(τ,τ+T;L2(Rn)), (3.45)
    uk(τ+T)vτ+T  weakly in  H2(Rn), (3.46)
    tuk(τ+T)vτ+T1  weakly in  L2(Rn). (3.47)

    It follows from (3.41)-(3.42) that there exists a subsequence which is still denoted uk, such that

    uk(t,x)u(t,x)  for almost all  (t,x)[τ,τ+T]×Rn. (3.48)

    By (3.15) and (3.48) we get that for almost all (t,x)[τ,τ+T]×Rn,

    |ηk(uk(t,x))u(t,x)||ηk(uk(t,x))ηk(u(t,x))|+|ηk(u(t,x))u(t,x)||uk(t,x)u(t,x)|+|ηk(u(t,x))u(t,x)|0,  as  k. (3.49)

    By (3.49), we have

    fk(x,uk(t,x))f(x,u(t,x))  for almost all  (t,x)[τ,τ+T]×Rn, (3.50)
    hk(t,x,uk(t,x))h(t,x,u(t,x))  for almost all  (t,x)[τ,τ+T]×Rn. (3.51)

    It follows from (3.44)-(3.45), (3.50)-(3.51) that

    fk(,uk)f(,u)  weakly in  L2(τ,τ+T;L2(Rn)), (3.52)
    hk(,,uk)h(,,u)  weakly in  L2(τ,τ+T;L2(Rn)). (3.53)

    Step (iii): Existence of solutions.

    Choosing an arbitrary ξC0((τ,τ+T)×Rn). By (3.26) we get

    τ+Tτ(tuk,ξt)dt+ατ+Tτ(tuk,ξ)dt+τ+Tτ(Δuk,Δξ)dt+ντ+Tτ(uk,ξ)dt      +τ+Tτ0μ(s)(Δ2ηtk(s),ξ)dsdt+τ+TτRnfk(x,uk(t,x))ξ(t,x)dxdt=τ+Tτ(g(t),ξ)dt+τ+TτRnhk(t,x,uk(t,x))ζδ(θtω)ξ(t,x)dxdt. (3.54)

    Letting k in (3.54), it follows from (3.41)-(3.43) and (3.52)-(3.53) that for any ξC0((τ,τ+T)×Rn),

    τ+Tτ(ut,ξt)dt+ατ+Tτ(ut,ξ)dt+τ+Tτ(Δu,Δξ)dt+ντ+Tτ(u,ξ)dt      +τ+Tτ0μ(s)(Δ2ηt(s),ξ)dsdt+τ+TτRnf(x,u(t,x))ξ(t,x)dxdt=τ+Tτ(g(t),ξ)dt+τ+TτRnh(t,x,u(t,x))ζδ(θtω)ξ(t,x)dxdt. (3.55)

    Notice that

    uL(τ,τ+T;H2(Rn))  and   tuL(τ,τ+T;L2(Rn)). (3.56)

    By (3.56) we obtain

    h(,,u)L2(τ,τ+T;L2(Rn)). (3.57)

    We claim that

    f(,u)   belongs to   L(τ,τ+T;L2(Rn)). (3.58)

    In fact, by (3.5) we obtain that there exists some c6=c6(p,n,α1,φ)>0 such that

    f(,u(t))22α21(φ2L(Rn)u(t)2+u(t)2(p+1)L2(p+1)(Rn))c6(u(t)2+u(t)2(p+1)H2(Rn)),

    which along with (3.56) to obtain (3.58).

    By (3.54)–(3.58), we can get

    utt   belongs to   L2(τ,τ+T;H2(Rn)), (3.59)

    where H2(Rn) is the dual space of H2(Rn).

    Next, we prove (u,ut,ηt) satisfy the initial conditions (3.2)2.

    By (3.26), we get that for any vC0(Rn) and ψC2([τ,τ+T]),

    τ+Tτ(uk(t),v)ψ(t)dt+(tuk(τ+T),v)ψ(τ+T)(uk(τ+T),v)ψ(τ+T)+(u0,v)ψ(τ)(u1,0,v)ψ(τ)+ατ+Tτ(tuk(t),v)ψ(t)dt+τ+Tτ(Δuk(t),Δv)ψ(t)dt+τ+Tτ0μ(s)(Δ2ηtk(s),v)ψ(t)dsdt+ντ+Tτ(uk(t),v)ψ(t)dt+τ+TτRnfk(x,uk(t,x))v(x)ψ(t)dxdt=τ+Tτ(g(t),v)ψ(t)dt+τ+TτRnhk(t,x,uk(t,x))ζδ(θtω)v(x)ψ(t)dxdt. (3.60)

    Letting k in (3.60), by (3.41)-(3.43), (3.46)-(3.47) and (3.52)-(3.53) we obtain, for any vC0(Rn) and ψC2([τ,τ+T]),

    τ+Tτ(u(t),v)ψ(t)dt+(vτ+T1,v)ψ(τ+T)(vτ+T,v)ψ(τ+T)+(u0,v)ψ(τ)(u1,0,v)ψ(τ)+ατ+Tτ(tu(t),v)ψ(t)dt+τ+Tτ(Δu(t),Δv)ψ(t)dt+τ+Tτ0μ(s)(Δ2ηt(s),v)ψ(t)dsdt+ντ+Tτ(u(t),v)ψ(t)dt+τ+TτRnf(x,u(t,x))v(x)ψ(t)dxdt=τ+Tτ(g(t),v)ψ(t)dt+τ+TτRnh(t,x,u(t,x))ζδ(θtω)v(x)ψ(t)dxdt. (3.61)

    By (3.55) we get that for any vC0(Rn),

    ddt(ut,v)+α(ut,v)+(Δu,Δv)+0μ(s)(Δ2ηt(s),v)ds+ν(u,v)+Rnf(x,u(t,x))v(x)dx=(g(t),v)+Rnh(t,x,u(t,x))ζδ(θtω)v(x)dx. (3.62)

    By (3.62) we find that for any vC0(Rn) and ψC2([τ,τ+T]),

    τ+Tτ(u(t),v)ψ(t)dt+(tu(τ+T),v)ψ(τ+T)(u(τ+T),v)ψ(τ+T)+(u(τ),v)ψ(τ)(tu(τ),v)ψ(τ)+ατ+Tτ(tu(t),v)ψ(t)dt+τ+Tτ(Δu(t),Δv)ψ(t)dt+τ+Tτ0μ(s)(Δ2ηt(s),v)ψ(t)dsdt+ντ+Tτ(u(t),v)ψ(t)dt+τ+TτRnf(x,u(t,x))v(x)ψ(t)dxdt=τ+Tτ(g(t,),v)ψ(t)dt+τ+TτRnh(t,x,u(t,x))ζδ(θtω)v(x)ψ(t)dxdt, (3.63)

    together with (3.61) to obtain, for vC0(Rn) and ψC2([τ,τ+T]),

    (vτ+T1,v)ψ(τ+T)(vτ+T,v)ψ(τ+T)+(u0,v)ψ(τ)(u1,0,v)ψ(τ)=(tu(τ+T),v)ψ(τ+T)(u(τ+T),v)ψ(τ+T)+(u(τ),v)ψ(τ)(tu(τ),v)ψ(τ). (3.64)

    Let ψC2([τ,τ+T]) such that ψ(τ+T)=ψ(τ+T)=ψ(τ)=0 and ψ(τ)=1, by (3.64), we have

    (tu(τ),v)=(u1,0,v),    vC0(Rn). (3.65)

    Let ψC2([τ,τ+T]) such that ψ(τ+T)=ψ(τ+T)=ψ(τ)=0 and ψ(τ)=1, by (3.64), we have

    (u(τ),v)=(u0,v),    vC0(Rn), (3.66)

    which together with (3.65) that (u,ut,ηt) satisfies the initial conditions (3.2)2.

    Through choosing proper ψC2([τ,τ+T]), we can also obtain from (3.64) that

    u(τ+T)=vτ+T,   and   tu(τ+T)=vτ+T1,

    which along with (3.46)-(3.47) implies that

    uk(τ+T)u(τ+T)  weakly in  H2(Rn), (3.67)
    tuk(τ+T)tu(τ+T)  weakly in  L2(Rn), (3.68)

    thereby,

    ηtk(τ+T)ηt(τ+T)  weakly in  Rμ,2. (3.69)

    Similar to (3.67)-(3.69), one can verify that for any t[τ,τ+T],

    uk(t)u(t)  weakly in  H2(Rn), (3.70)
    tuk(t)tu(t)  weakly in  L2(Rn), (3.71)
    ηtkηt  weakly in  Rμ,2. (3.72)

    By (3.70)–(3.72), we get the that (u,ut,ηt) is a solution of (3.2) in the sense of Definition 3.1.

    Step (iv): Uniqueness of solutions.

    Let (u1,(u1)t,ηt1) and (u2,(u2)t,ηt2) be solutions to (3.2), denote v=u1u2,ˉηt=ηt1ηt2. Then we have

    {vtt+αvt+Δ2v+0μ(s)Δ2ˉηt(s)ds+νv         =f(,u2)f(,u1)+(h(t,,u1)h(t,,u2))ζδ(θtω),v(τ)=0,vt(τ)=0. (3.73)

    by (3.10), we get

    ddt(vt2+Δv2+ˉηt(s)2μ,2+νv2)=2αvt2+2(f(,u2)f(,u1),vt)+2(h(t,,u1)h(t,,u2),vt)ζδ(θtω). (3.74)

    Since H2(Rn)L2(p+1)(Rn) for 0<p4n4, by (3.5), we get

    f(,u2)f(,u1)α1φL(Rn)v+α1(u1pH2(Rn)+u2pH2(Rn))vH2(Rn)

    and hence

    2(f(,u2)f(,u1),vt)2f(,u2)f(,u1)vtα1(φL(Rn)+u1pH2(Rn)+u2pH2(Rn))(v2H2(Rn)+vt2). (3.75)

    By (3.8) we get

    2(h(t,,u1)h(t,,u2),vt)ζδ(θtω)h(t,,u1)h(t,,u2)vt|ζδ(θtω)|2α3vvt|ζδ(θtω)|α3(v2+vt2)|ζδ(θtω)|. (3.76)

    It follows from (3.74)–(3.76) that

    ddt(vt2+Δv2+ˉηt(s)2μ,2+νv2)c7(1+u1pH2(Rn)+u2pH2(Rn))(vt2+Δv2+ˉη(s)2μ,2+νv2), (3.77)

    where c7>0 depends on τ and T. Since u1,u2L(τ,τ+T;H2(Rn)), then applying the Gronwall's lemma on [τ,τ+T], we can obtain that the uniqueness of solution as well as the continuous dependence property of solution with initial data.

    We now define a mapping Φ:R+×R×Ω×H2(Rn)×L2(Rn)×Rμ,2H2(Rn)×L2(Rn)×Rμ,2 such that for all tR+,τR,ωΩ and (u0,u1,0,η0)H2(Rn)×L2(Rn)×Rμ,2,

    Φ(t,τ,ω,(u0,u1,0,η0))=(u(t+τ,τ,θτω,u0),ut(t+τ,τ,θτω,u1,0),ηt(t+τ,τ,θτω,η0,s)), (3.78)

    where (u,ut,ηt) is the solution of (3.2). Then Φ is a continuous cocycle on H2(Rn)×L2(Rn)×Rμ,2 over (Ω,F,P,{θt}tR).

    In this section, we derive necessary estimates of solutions of (3.2) under stronger conditions than (3.4)-(3.8) on the nonlinear functions f and h. These estimates are useful for proving the asymptotic compactness of the solutions and the existence of pullback random attractors.

    From now on, we assume f satisfies: for all xRn and sR,

    f(x,s)sγF(x,s)φ3(x), (4.1)
    F(x,s)+φ1(x)α4|s|p+2, (4.2)
    |sf(x,s)|ι|s|p+ς,   |xf(x,s)|φ4(x), (4.3)

    where p>0 for 1n4 and 0<p4n4 for n5, γ(0,1], α4,ς are positive constants, φ3L1(Rn), and φ4L2(Rn)L(Rn),ι>0 will be denoted later.

    By (3.5) and (4.1) we get that for all xRn and sR,

    γF(x,s)α1s2φ(x)+α1|s|p+2φ3(x). (4.4)

    Assume the nonlinearity h satisfies: for all xRn and t,sR,

    |h(t,x,s)|φ5(x)|s|+φ6(x), (4.5)
    |xh(t,x,s)|+|sh(t,x,s)|φ7(x), (4.6)

    where φ5L(Rn)L2+4p(Rn), φ6L2(Rn), and φ7L2(Rn)L(Rn).

    Let D be the set of all tempered families of nonempty bounded subsets of H2(Rn)×L2(Rn)×Rμ,2. D={D(τ,Ω):τR,ωΩ} is called tempered if for any c>0,

    limt+ectD(τt,θtω)H2(Rn)×L2(Rn)×Rμ,2=0,

    where DH2(Rn)×L2(Rn)×Rμ,2=supξDξH2(Rn)×L2(Rn)×Rμ,2.

    Under α>0,ν>0,ϱ>0,ϖ>0 and γ(0,1], we can choose a sufficiently small positive constant ε such that

    ε<min{1,ν,2α5,32ϱ,3ϱγ}, 12α2ε18εγ>0, ν12νγεα+18ε2γ>0,νεεα+12ε2>0,       1γ22ϖεϱ>0. (4.7)

    We also assume

    \begin{align*} &\int^\tau_{-\infty}e^{\frac{1}{4}\varepsilon\gamma s}\|g(s)\|^2_1ds < \infty,\ \ \forall\ \tau\in\mathbb{R}, \end{align*} (4.8)
    \begin{align*} &\lim\limits_{t\rightarrow +\infty}e^{-ct}\int^0_{-\infty}e^{\frac{1}{4}\varepsilon\gamma s}\|g(s-t)\|^2_1ds = 0, \ \ \text{for}\ \forall\ c > 0. \end{align*} (4.9)

    Lemma 4.1. Let (3.3)–(3.5), (3.8), (4.1)-(4.2) and (4.5)–(4.8) hold. Then for any \tau\in\mathbb{R}, \omega\in\Omega and D\in\mathcal{D} , there exists T = T(\tau, \omega, D) > 0 such that for all t\geq T , the solution of (3.2) satisfies

    \begin{align*} &\|u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0})\|^2+\|u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2_{H^{2}(\mathbb{R}^n)} +\|\eta^t(\tau,\tau-t,\theta_{-\tau}\omega,\eta^0,s)\|^2_{\mu,2}\\ +&\int^\tau_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)}(\|u_t(s,\tau-t,\theta_{-\tau}\omega,u_{1,0})\|^2+\|u(s,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2_{H^{2}(\mathbb{R}^n)} \\ +& \|\eta^t(s,\tau-t,\theta_{-\tau}\omega,\eta^0,s)\|^2_{\mu,2})ds\\ \leq&M_1+M_1\int^0_{-\infty}e^{\frac{1}{4}\varepsilon\gamma s}(1+\|g(s+\tau)\|^2+|\zeta_\delta(\theta_s\omega)|^{2+\frac{4}{p}})ds, \end{align*}

    where (u_0, u_{1, 0}, \eta^0) \in D(\tau-t, \theta_{-t}\omega) and M_1 is a positive constant independent of \tau, \omega and D .

    Proof. By (3.11), (3.13), (4.1) and (4.10) we obtain, for almost all t\in[\tau, \tau+T] ,

    \begin{align*} &\frac{d}{dt}\bigg(\|u_t\|^2+\nu \|u\|^2+\|\Delta u\|^2+\|\eta^t\|^2_{\mu,2}+2\int_{\mathbb{R}^n}F(x,u(t,x))dx+\varepsilon(u,u_t)\bigg)\\ &+(2\alpha-\varepsilon)\|u_t\|^2+\varepsilon\alpha(u,u_t)+\varepsilon\|\Delta u\|^2+\varepsilon(\eta^t(s),u(t))_{\mu,2}\\ &-\int^\infty_0\mu'(s)\|\Delta\eta^t\|^2ds+\varepsilon\nu \|u\|^2+\varepsilon\gamma\int_{\mathbb{R}}F(x,u(t,x))dx\\ \leq&\varepsilon\|\varphi_3\|_{L^1(\mathbb{R}^n)}+(g(t)+h(t,\cdot,u(t))\zeta_\delta(\theta_t\omega),\varepsilon u+2u_t). \end{align*} (4.10)

    By (3.3), (4.2) and (4.5) we have

    \begin{align*} &\varepsilon(\eta^t(s),u(t))_{\mu,2} \geq -\frac{\varrho}{4}\|\eta^t\|^2_{\mu,2}-\frac{\varpi\varepsilon^2}{\varrho}\|\Delta u\|^2, \end{align*} (4.11)
    \begin{align*} &-\int^\infty_0\mu'(s)\|\Delta\eta^t\|^2ds \geq \varrho\|\eta^t\|^2_{\mu,2}, \end{align*} (4.12)
    (4.13)

    where c_4 > 0 depends on \alpha, \nu, \gamma, \varepsilon .

    It follows from (4.10)-(4.13) and rewrite the result obtained, we have

    (4.14)

    where c_5 > 0 depends on \alpha, \nu, \gamma, \varepsilon .

    For the second term on the right-hand side of (4.14) we get

    \begin{align*} &-\varepsilon(\alpha-\frac{1}{4}\varepsilon\gamma)(u,u_t))\\ \leq&\varepsilon(\alpha-\frac{1}{4}\varepsilon\gamma)\|u\|\|u_t\|\\ \leq&\frac{1}{2}\varepsilon^2(\alpha-\frac{1}{4}\varepsilon\gamma)\|u\|^2+\frac{1}{2}(\alpha-\frac{1}{4}\varepsilon\gamma)\|u_t\|^2. \end{align*} (4.15)

    By (4.14)-(4.15) we get

    \begin{align*} &\frac{d}{dt}(\|u_t\|^2+\nu \|u\|^2+\|\Delta u\|^2+\|\eta^t\|^2_{\mu,2}+2\int_{\mathbb{R}^n}F(x,u(t,x))dx+\varepsilon(u,u_t))\\ &+\frac{1}{4}\varepsilon\gamma(\|u_t\|^2+\nu \|u\|^2+\|\Delta u\|^2+2\int_{\mathbb{R}^n}F(x,u(t,x))dx+\varepsilon(u,u_t))+(\frac{1}{2}\alpha-\varepsilon-\frac{1}{8}\varepsilon\gamma)\|u_t\|^2\\ &+\varepsilon(1-\frac{1}{4}\gamma-\frac{\varpi\varepsilon}{\varrho})\|\Delta u\|^2+\frac{1}{4}(3\varrho-\varepsilon\gamma)\|\eta^t\|^2_{\mu,2}+\frac{1}{2}\varepsilon(\nu-\frac{1}{2}\nu\gamma-\varepsilon\alpha+\frac{1}{4}\varepsilon^2\gamma)\|u\|^2\\ \leq& c_5(1+\|g(t)\|^2+|\zeta_\delta(\theta_t\omega)|^{2+\frac{4}{p}}). \end{align*} (4.16)

    Multiplying (4.14) by e^{\frac{1}{4}\varepsilon\gamma t} , and then integrating the inequality [\tau-t, \tau] , after replacing \omega by \theta_{-\tau}\omega , we get

    \begin{align*} &\|u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0})\|^2+\nu \|u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2+\|\Delta u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2\\ &+\|\eta^t(\tau,\tau-t,\theta_{-\tau}\omega,\eta^0,s)\|^2_{\mu,2}+2\int_{\mathbb{R}^n}F(x,u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0}))dx\\ &+\varepsilon(u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0}),u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0}))\\ &+(\frac{1}{2}\alpha-\varepsilon-\frac{1}{8}\varepsilon\gamma)\int^\tau_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)}\|u_t(s,\tau-t,\theta_{-\tau}\omega,u_{1,0})\|^2ds\\ &+\varepsilon(1-\frac{1}{4}\gamma-\frac{\varpi\varepsilon}{\varrho})\int^\tau_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)}\|\Delta u(s,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2ds\\ &+\frac{1}{4}(3\varrho-\varepsilon\gamma)\int^\tau_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)}\|\eta^t(\tau,\tau-t,\theta_{-\tau}\omega,\eta^0,s)\|^2_{\mu,2}ds\\ &+\frac{1}{2}\varepsilon(\nu-\frac{1}{2}\nu\gamma-\varepsilon\alpha+\frac{1}{4}\varepsilon^2\gamma)\int^\tau_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)}\|u(s,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2ds\\ \leq& e^{-\frac{1}{4}\varepsilon\gamma t}\bigg(\|u_{1,0}\|^2+\nu \|u_0\|^2+\|\Delta u_{0}\|^2+\|\eta^0\|^2_{\mu,2}+2\int_{\mathbb{R}^n}F(x,u_{0})dx+\varepsilon(u_{0},u_{1,0})\bigg)\\ &+c_5\int^\tau_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)}\bigg(1+\|g(s)\|^2+|\zeta_\delta(\theta_{s-\tau}\omega)|^{2+\frac{4}{p}}\bigg)ds. \end{align*} (4.17)

    For the first term on the right-hand side of (4.17), by (4.4) we get

    \begin{align*} &e^{-\frac{1}{4}\varepsilon\gamma t}\bigg(\|u_{1,0}\|^2+\nu \|u_0\|^2+\|\Delta u_{0}\|^2+\|\eta^0\|^2_{\mu,2}+2\int_{\mathbb{R}^n}F(x,u_{0})dx+\varepsilon(u_{0},u_{1,0})\bigg)\\ \leq&c_6e^{-\frac{1}{4}\varepsilon\gamma t}\bigg(1+\|u_{1,0}\|^2+\|u_0\|^2_{H^2(\mathbb{R}^n}+\|u_0\|^{p+2}_{H^2(\mathbb{R}^n)}+\|\eta^0\|^2_{\mu,2}\bigg)\\ \leq&c_7e^{-\frac{1}{4}\varepsilon\gamma t} (1+\|D(\tau-t,\theta_{-t}\omega)\|^{p+2})\rightarrow0, \ \ \ \text{as} \ \ t\rightarrow \infty. \end{align*} (4.18)

    By (4.7) we get

    \begin{align*} &|\varepsilon(u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0}),u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0}))|\\ \leq&\frac{1}{2}\varepsilon\|u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2+ \frac{1}{2}\varepsilon\|u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0})\|^2\\ \leq&\frac{1}{2}\nu\|u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2+ \frac{1}{2}\|u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0})\|^2, \end{align*}

    which along with (4.2) and (4.18) that for all t\geq T ,

    \begin{align*} &\frac{1}{2}\|u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0})\|^2+\frac{1}{2}\nu \|u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2+\|\Delta u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2\\ &+\|\eta^t(\tau,\tau-t,\theta_{-\tau}\omega,\eta^0,s)\|^2_{\mu,2} +(\frac{1}{2}\alpha-\varepsilon-\frac{1}{8}\varepsilon\gamma)\int^\tau_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)}\|u_t(s,\tau-t,\theta_{-\tau}\omega,u_{1,0})\|^2ds\\ &+\varepsilon(1-\frac{1}{4}\gamma-\frac{\varpi\varepsilon}{\varrho})\int^\tau_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)}\|\Delta u(s,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2ds\\ &+\frac{1}{4}(3\varrho-\varepsilon\gamma)\int^\tau_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)}\|\eta^t(s,\tau-t,\theta_{-\tau}\omega,\eta^0,s)\|^2_{\mu,2}ds\\ &+\frac{1}{2}\varepsilon(\nu-\frac{1}{2}\nu\gamma-\varepsilon\alpha+\frac{1}{4}\varepsilon^2\gamma)\int^\tau_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)}\|u(s,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2ds\\ \leq& 1+2\|\varphi_1\|_{L^1(\mathbb{R}^n)}+c_5\int^0_{-\infty}e^{\frac{1}{4}\varepsilon\gamma s}\bigg(1+\|g(s+\tau)\|^2+|\zeta_\delta(\theta_{s}\omega)|^{2+\frac{4}{p}}\bigg)ds. \end{align*}

    Then the proof is completed.

    Based on Lemma 4.1, we can easily obtain the following Lemma that implies the existence of tempered random absorbing sets of \Phi .

    Lemma 4.2. If (3.3)-(3.5), (3.8), (4.1)-(4.2) and (4.5)-(4.9) hold, then the cocycle \Phi possesses a closed measurable \mathcal{D} -pullback absorbing set B = \{B(\tau, \omega):\tau\in\mathbb{R}, \omega\in\Omega\}\in\mathcal{D} , which is given by

    \begin{align} B(\tau,\omega) = \{(u_0,u_{1,0},\eta^0)\in H^2(\mathbb{R}^n)\times L^2(\mathbb{R}^n)\times \\ \mathfrak{R}_{\mu,2}:\|u_0\|^2_{H^2(\mathbb{R}^n)}+\|u_{1,0}\|^2+\|\eta^0\|^2_{\mu,2}\leq L(\tau,\omega)\}, \end{align} (4.19)

    where

    L(\tau,\omega) = M_1+M_1\int^0_{-\infty}e^{\frac{1}{4}\varepsilon\gamma s}\bigg(1+\|g(s+\tau)\|^2+|\zeta_\delta(\theta_{s}\omega)|^{2+\frac{4}{p}}\bigg)ds.

    In order to derive the uniform tail-estimates of the solutions of (3.2) for large space variables when times is large enough, we need to derive the regularity of the solutions in a space higher than H^2(\mathbb{R}^n) .

    Lemma 4.3. Let (3.3)–(3.5), (3.8), (4.1)-(4.2) and (4.5)–(4.8) hold. Then for any \tau\in\mathbb{R}, \omega\in\Omega and D\in\mathcal{D} , there exists T = T(\tau, \omega, D) > 0 such that for all t\geq T , the solution of (3.2) satisfies

    \begin{align*} &\|A^{\frac{1}{4}}u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0})\|^2+\|A^{\frac{3}{4}}u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2 +\|A^{\frac{1}{4}}\eta^t(\tau,\tau-t,\theta_{-\tau}\omega,\eta^0,s)\|^2_{\mu,2}\\ +&\int^\tau_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)}(\|A^{\frac{1}{4}}u_t(s,\tau-t,\theta_{-\tau}\omega,u_{1,0})\|^2+\|A^{\frac{3}{4}}u(s,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2)ds\\ &+\int^\tau_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)}(\|A^{\frac{1}{4}}\eta^t(s,\tau-t,\theta_{-\tau}\omega,\eta^0,s)\|^2_{\mu,2}\\ \leq&M_2+M_2\int^0_{-\infty}e^{\frac{1}{4}\varepsilon\gamma s}(1+\|g(s+\tau)\|^2_1+|\zeta_\delta(\theta_s\omega)|^{2})ds, \end{align*}

    where (u_0, u_{1, 0}, \eta^0) \in D(\tau-t, \theta_{-\tau}\omega) and M_2 is a positive number independent of \tau, \omega and D .

    Proof. Taking the inner product of (3.2)_1 with A^{\frac{1}{2}} u in L^2(\mathbb{R}^n) , we have

    \begin{align*} &\frac{d}{dt}(A^{\frac{1}{4}}u_t,A^{\frac{1}{4}}u)+\alpha(A^{\frac{1}{4}}u_t,A^{\frac{1}{4}}u) +\|A^{\frac{3}{4}}u\|^2+(\int_0^\infty\mu(s)\Delta^2\eta(s)ds,A^{\frac{1}{2}}u)+\nu\|A^{\frac{1}{4}}u\|^2\\+&(f(x,u),A^{\frac{1}{2}}u) = \|A^{\frac{1}{4}}u_t\|^2+(g(t)+h(t,\cdot,u)\zeta_\delta(\theta_t\omega),A^{\frac{1}{2}} u) \end{align*} (4.20)

    Taking the inner product of (1.1)_1 with A^{\frac{1}{2}} u_t in L^2(\mathbb{R}^n) , we find that

    \begin{align*} &\frac{d}{dt}(\|A^{\frac{1}{4}}u_t\|^2+\nu \|A^{\frac{1}{4}}u\|^2+\|A^{\frac{3}{4}} u\|^2+\|A^{\frac{1}{4}}\eta^t\|^2_{\mu,2})\\ = & \int^\infty_0\mu'(s)\|A^{\frac{3}{4}}\eta^t\|^2ds-2\alpha\|A^{\frac{1}{4}}u_t\|^2-2(f(x,u),A^{\frac{1}{2}} u_t)+2(g(t)+h(t,\cdot,u)\zeta_\delta(\theta_t\omega),A^{\frac{1}{2}} u_t) \end{align*} (4.21)

    By (4.20) and (4.21), we get

    \begin{align*} &\frac{d}{dt}\bigg(\|A^{\frac{1}{4}}u_t\|^2+\nu \|A^{\frac{1}{4}}u\|^2+\|A^{\frac{3}{4}} u\|^2+\|A^{\frac{1}{4}}\eta^t\|^2_{\mu,2}+\varepsilon(A^{\frac{1}{4}}u_t,A^{\frac{1}{4}}u)\bigg)+(2\alpha-\varepsilon)\|A^{\frac{1}{4}}u_t\|^2 \\ &+\varepsilon\alpha(A^{\frac{1}{4}}u_t,A^{\frac{1}{4}}u)+\varepsilon\|A^{\frac{3}{4}}u\|^2+\varepsilon(\int_0^\infty\mu(s)\Delta^2\eta(s)ds,A^{\frac{1}{2}}u) -\int^\infty_0\mu'(s)\|A^{\frac{3}{4}}\eta^t\|^2ds\\ &+\varepsilon\nu\|A^{\frac{1}{4}}u\|^2+\varepsilon(f(x,u),A^{\frac{1}{2}} u)+2(f(x,u),A^{\frac{1}{2}} u_t)\\ = &(g(t)+h(t,\cdot,u)\zeta_\delta(\theta_t\omega),\varepsilon A^{\frac{1}{2}} u+2A^{\frac{1}{2}} u_t). \end{align*} (4.22)

    By (3.3), (4.5), (4.6) and Lemma 4.1, we have

    \begin{align*} &\varepsilon(\int_0^\infty\mu(s)\Delta^2\eta(s)ds,A^{\frac{1}{2}}u)\geq -\frac{\varrho}{4}\|A^{\frac{1}{4}}\eta^t\|^2_{\mu,2}-\frac{\varpi\varepsilon^2}{\varrho}\|A^{\frac{3}{4}} u\|^2, \end{align*} (4.23)
    \begin{align*} &-\int^\infty_0\mu'(s)\|A^{\frac{3}{4}}\eta^t\|^2ds\geq\varrho\|A^{\frac{1}{4}}\eta^t\|^2_{\mu,2}, \end{align*} (4.24)
    \begin{align*} &(g(t)+h(t,\cdot,u(t))\zeta_\delta(\theta_t\omega),\varepsilon A^{\frac{1}{2}}u+2A^{\frac{1}{2}}u_t)\\ \leq&(\|g(t)\|_1+\|h(t,\cdot,u(t))\zeta_\delta(\theta_t\omega)\|_1)(\varepsilon\| A^{\frac{1}{4}} u\|+2\|A^{\frac{1}{2}}u_t\|)\\ \leq&\frac{1}{2}\varepsilon\nu\|A^{\frac{1}{4}}u\|^2+\alpha\|A^{\frac{1}{2}}u_t\|^2+(\alpha^{-1}+\frac{1}{2}\varepsilon\nu^{-1}) (\|g(t)\|_1+\|h(t,\cdot,u(t))\zeta_\delta(\theta_t\omega)\|_1)^2\\ \leq&\frac{1}{2}\varepsilon\nu\|A^{\frac{1}{4}}u\|^2+\alpha\|A^{\frac{1}{4}}u_t\|^2+(2\alpha^{-1} +\varepsilon\nu^{-1})\|g(t)\|^2_1+(2\alpha^{-1}+\varepsilon\nu^{-1})\|h(t,\cdot,u(t))\zeta_\delta(\theta_t\omega)\|^2_1\\ \leq&\frac{1}{2}\varepsilon\nu\|A^{\frac{1}{4}}u\|^2+\alpha\|A^{\frac{1}{4}}u_t\|^2+(2\alpha^{-1} +\varepsilon\nu^{-1})\|g(t)\|^2_1+c_8|\zeta_\delta(\theta_t\omega)|^2. \end{align*} (4.25)

    From (4.3) and Lemma 4.1 yields

    \begin{align*} &|\varepsilon(f(x,u),A^{\frac{1}{2}} u)+2(f(x,u),A^{\frac{1}{2}} u_t)|\\ \leq&2\int_{\mathbb{R}^n}|\frac{\partial f}{\partial u}(x,u)\cdot A^{\frac{1}{4}} u\cdot A^{\frac{1}{4}} u_t+\frac{\partial f}{\partial x}(x,u)\cdot A^{\frac{1}{4}} u_t|dx\\ &+\varepsilon\int_{\mathbb{R}^n}|\frac{\partial f}{\partial u}(x,u)\cdot A^{\frac{1}{4}} u\cdot A^{\frac{1}{4}} u+\frac{\partial f}{\partial x}(x,u)\cdot A^{\frac{1}{4}} u|dx\\ \leq&2\iota\int_{\mathbb{R}^n}|u|^p\cdot |A^{\frac{1}{4}} u|\cdot |A^{\frac{1}{4}} u_t|dx+2\varsigma\int_{\mathbb{R}^n}|A^{\frac{1}{4}} u|\cdot |A^{\frac{1}{4}} u_t|dx+2\int_{\mathbb{R}^n}|\varphi_4|\cdot|A^{\frac{1}{4}} u_t|dx\\ &+\varepsilon\iota\int_{\mathbb{R}^n}|u|^p\cdot |A^{\frac{1}{4}} u|\cdot |A^{\frac{1}{4}} u|dx+\varepsilon\varsigma\int_{\mathbb{R}^n}|A^{\frac{1}{4}} u|\cdot |A^{\frac{1}{4}} u|dx+\varepsilon\int_{\mathbb{R}^n}|\varphi_4|\cdot|A^{\frac{1}{4}} u|dx\\ \leq&2\iota\|u\|^p_{L^{\frac{10p}{4}}}\cdot\|A^{\frac{1}{4}} u\|_{L^{10}}\cdot\|A^{\frac{1}{4}} u_t\| +2\varsigma\|A^{\frac{1}{4}} u\|\cdot\|A^{\frac{1}{4}} u_t\|+\frac{\varepsilon}{4}\|A^{\frac{1}{4}} u_t\|^2+ \frac{4}{\varepsilon}\|\varphi_4\|^2\\ &+\varepsilon\iota\|u\|^p\cdot\|A^{\frac{1}{4}} u\|^2 +\varepsilon\varsigma\|A^{\frac{1}{4}} u\|^2+\frac{\varepsilon}{2}\|A^{\frac{1}{4}} u\|^2+ \frac{\varepsilon}{2}\|\varphi_4\|^2\\ \leq&\varepsilon\|A^{\frac{1}{4}} u_t\|^2+\frac{2C^{p+1}\iota^2}{\varepsilon}L^p\|A^{\frac{3}{4}} u\|^2+c_9, \end{align*}

    where the definition of L see Lemma 4.2, and C is the positive constant satisfying

    C\|\Delta u\|^2\geq\bigg(\int_{\mathbb{R}^n}|u|^{10}dx\bigg)^{\frac{1}{5}},\ \ \ C\|u\|^2_2\geq\bigg(\int_{\mathbb{R}^n}|u|^{\frac{10p}{4}}dx\bigg)^{\frac{2}{10p}}.

    Choosing

    0 < \iota^2\leq\frac{\varepsilon^2}{4L^pC^{p+1}},

    thus, we get

    \begin{align} |\varepsilon(f(x,u),A^{\frac{1}{2}} u)+2(f(x,u),A^{\frac{1}{2}} u_t)|\leq\varepsilon\|A^{\frac{1}{4}} u_t\|^2+\frac{\varepsilon}{2}\|A^{\frac{3}{4}} u\|^2+c_9. \end{align} (4.26)

    By (4.22)–(4.26), we get

    \begin{align*} &\frac{d}{dt}\bigg(\|A^{\frac{1}{4}}u_t\|^2+\nu \|A^{\frac{1}{4}}u\|^2+\|A^{\frac{3}{4}} u\|^2+\|A^{\frac{1}{4}}\eta^t\|^2_{\mu,2}+\varepsilon(A^{\frac{1}{4}}u_t,A^{\frac{1}{4}}u)\bigg)+(\alpha-2\varepsilon)\|A^{\frac{1}{4}}u_t\|^2 \\ &+\varepsilon\alpha(A^{\frac{1}{4}}u_t,A^{\frac{1}{4}}u)+ \varepsilon(\frac{1}{2}-\frac{\varpi\varepsilon}{\varrho})\|A^{\frac{3}{4}}u\|^2+\frac{3}{4}\varrho\|A^{\frac{1}{4}}\eta^t\|^2_{\mu,2}+\frac{\varepsilon}{2}\nu\|A^{\frac{1}{4}}u\|^2\\ \leq&c_{10}(1+\|g(t)\|^2_1+|\zeta_\delta(\theta_t\omega)|^2), \end{align*}

    which can be rewritten as

    \begin{align*} &\frac{d}{dt}\bigg(\|A^{\frac{1}{4}}u_t\|^2+\nu \|A^{\frac{1}{4}}u\|^2+\|A^{\frac{3}{4}} u\|^2+\|A^{\frac{1}{4}}\eta^t\|^2_{\mu,2}+\varepsilon(A^{\frac{1}{4}}u_t,A^{\frac{1}{4}}u)\bigg)\\ &+\frac{1}{4}\varepsilon\gamma\bigg(\|A^{\frac{1}{4}}u_t\|^2+\nu \|A^{\frac{1}{4}}u\|^2+\|A^{\frac{3}{4}} u\|^2+\|A^{\frac{1}{4}}\eta^t\|^2_{\mu,2}+\varepsilon(A^{\frac{1}{4}}u_t,A^{\frac{1}{4}}u)\bigg)\\ &+(\alpha-2\varepsilon-\frac{1}{4}\varepsilon\gamma)\|A^{\frac{1}{4}}u_t\|^2 +\frac{\varepsilon}{2}(1-\frac{2\varpi\varepsilon}{\varrho}-\frac{\gamma}{2})\|A^{\frac{3}{4}}u\|^2 \\ +&\frac{3}{4}(\varrho-\frac{1}{3}\varepsilon\gamma)\|A^{\frac{1}{4}}\eta^t\|^2_{\mu,2}+\frac{\varepsilon}{2}\nu(1-\frac{\gamma}{2})\|A^{\frac{1}{4}}u\|^2\\ \leq&c_{10}(1+\|g(t)\|^2_1+|\zeta_\delta(\theta_t\omega)|^2) -\varepsilon(\alpha-\frac{1}{4}\varepsilon\gamma)(A^{\frac{1}{4}}u_t,A^{\frac{1}{4}}u). \end{align*} (4.27)

    For the last term on the right-hand side of (4.27) we have

    \begin{align*} &-\varepsilon(\alpha-\frac{1}{4}\varepsilon\gamma)(A^{\frac{1}{4}}u_t,A^{\frac{1}{4}}u)\\ \leq&\varepsilon(\alpha-\frac{1}{4}\varepsilon\gamma)\|A^{\frac{1}{4}}u\|\|A^{\frac{1}{4}}u_t\|\\ \leq&\frac{1}{2}\varepsilon^2(\alpha-\frac{1}{4}\varepsilon\gamma)\|A^{\frac{1}{4}}u\|^2+ \frac{1}{2}(\alpha-\frac{1}{4}\varepsilon\gamma)\|A^{\frac{1}{4}}u_t\|^2, \end{align*}

    which together with (4.27), we get

    \begin{align*} &\frac{d}{dt}\bigg(\|A^{\frac{1}{4}}u_t\|^2+\nu \|A^{\frac{1}{4}}u\|^2+\|A^{\frac{3}{4}} u\|^2+\|A^{\frac{1}{4}}\eta^t\|^2_{\mu,2}+\varepsilon(A^{\frac{1}{4}}u_t,A^{\frac{1}{4}}u)\bigg)\\ &+\frac{1}{4}\varepsilon\gamma\bigg(\|A^{\frac{1}{4}}u_t\|^2+\nu \|A^{\frac{1}{4}}u\|^2+\|A^{\frac{3}{4}} u\|^2+\|A^{\frac{1}{4}}\eta^t\|^2_{\mu,2}+\varepsilon(A^{\frac{1}{4}}u_t,A^{\frac{1}{4}}u)\bigg)\\ &+(\frac{\alpha}{2}-2\varepsilon-\frac{1}{8}\varepsilon\gamma)\|A^{\frac{1}{4}}u_t\|^2 +\frac{\varepsilon}{2}(1-\frac{2\varpi\varepsilon}{\varrho}-\frac{\gamma}{2})\|A^{\frac{3}{4}}u\|^2 +\frac{3}{4}(\varrho-\frac{1}{3}\varepsilon\gamma)\|A^{\frac{1}{4}}\eta^t\|^2_{\mu,2}\\ &+\frac{\varepsilon}{2}(\nu-\frac{\nu}{2}\gamma-\frac{\varepsilon}{2}\alpha+\frac{1}{8}\varepsilon^2\gamma)\|A^{\frac{1}{4}}u\|^2\\ \leq&c_{10}(1+\|g(t)\|^2_1+|\zeta_\delta(\theta_t\omega)|^2). \end{align*}

    Similar to the remainder of Lemma 4.1, we can obtain the desired result.

    Lemma 4.4. Let (3.3)–(3.5), (3.8), (4.1)-(4.2) and (4.5)–(4.8) hold. Then for every \eta > 0, \tau\in\mathbb{R}, \omega\in\Omega and D\in\mathcal{D} , there exists T_0 = T_0(\eta, \tau, \omega, D) > 0 and m_0 = m_0(\eta, \tau, \omega)\geq1 such that for all t\geq T_0 , m\geq m_0 and (u_0, u_{1, 0}, \eta^0) \in D(\tau-t, \theta_{-\tau}\omega) , the solution of (3.2) satisfies

    \begin{align*} &\int_{|x|\geq m}(|u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0})|^2+|u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})|^2\\ & + |\Delta u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})|^2 +|\eta^t(\tau,\tau-t,\theta_{-\tau}\omega,\eta^{0},s)|^2_{\mu,2})dx < \eta. \end{align*}

    Proof. Let \rho:\mathbb{R}^n\rightarrow \mathbb{R} be a smooth function such that 0\leq\rho(x)\leq1 for all x\in\mathbb{R}^n , and

    \rho(x) = 0 \ \ \text{for}\ \ \ |x|\leq\frac{1}{2};\ \ \ \text{and}\ \ \ \rho(x) = 1 \ \ \text{for}\ \ \ |x|\geq1.

    For every m\in\mathbb{N} , let

    \rho_m(x) = \rho(x/m),\ \ x\in\mathbb{R}^n.

    Then there exist positive constants c_{11} and c_{12} independent of m such that |\nabla\rho_m(x)|\leq\frac{1}{m}c_{11} , |\Delta\rho_m(x)|\leq\frac{1}{m}c_{12} for all x\in\mathbb{R}^n and m\in\mathbb{N} .

    Similar to the energy equation (3.11), we have

    \begin{align*} &\frac{d}{dt}\int_{\mathbb{R}^n}\rho_m(x)\big(|u_t(t,x)|^2+\nu |u(t,x)|^2+|\Delta u(t,x)|^2+|\eta^t(s)|^2_{\mu,2}+2F(x,u(t,x))\big)dx\\ &+2\alpha\int_{\mathbb{R}^n}\rho_m(x)|u_t(t,x)|^2dx-\int_{\mathbb{R}^n}\rho_m(x)\int^\infty_0\mu'(s)|\Delta\eta^t(s)|^2dsdx\\ = &-4\int_{\mathbb{R}^n}\nabla\rho_m(x)\cdot\Delta u(t,x)\cdot\nabla u_t(t,x)dx-2\int_{\mathbb{R}^n}\Delta\rho_m(x)\cdot\Delta u(t,x)\cdot u_t(t,x)dx\\ &-4\int_{\mathbb{R}^n}\nabla\rho_m(x)\int^\infty_0\mu(s)\Delta\eta^t(s)\nabla u_t(t,x)dsdx- 2\int_{\mathbb{R}^n}\Delta\rho_m(x)\int^\infty_0\mu(s)\Delta\eta^t(s) u_t(t,x)dsdx\\ &+2\int_{\mathbb{R}^n}\rho_m(x) g(t,x) u_t(t,x)dx +2\zeta_\delta(\theta_t\omega)\int_{\mathbb{R}^n}\rho_m(x)h(t,x,u(t,x))u_t(t,x)dx. \end{align*} (4.28)

    Taking the inner product of (3.2)_1 with \rho_m(x)u in L^2(\mathbb{R}^n) , we have

    (4.29)

    By (4.28)-(4.29) and (4.1), we get

    (4.30)

    Similar to the arguments of (4.11)-(4.13), we have the following estimates:

    \begin{align*} &\varepsilon\int_{\mathbb{R}^n}\rho_m(x)\int^\infty_0\mu(s)\Delta\eta^t(s) \Delta u(t,x)dsdx \geq-\frac{\varrho}{4}\int_{\mathbb{R}^n}\rho_m(x) |\eta^t |^2_{\mu,2}dx-\frac{\varpi\varepsilon^2}{\varrho}\int_{\mathbb{R}^n}\rho_m(x) |\Delta u |^2dx, \end{align*} (4.31)
    \begin{align*} &-\int_{\mathbb{R}^n}\rho_m(x)\int^\infty_0\mu'(s)|\Delta\eta^t(s)|^2dsdx \geq \varrho\int_{\mathbb{R}^n}\rho_m(x)|\eta^t |^2_{\mu,2}dx, \end{align*} (4.32)
    \begin{align*} &|\int_{\mathbb{R}^n}\rho_m(x)(g(t,x)+h(t,x,u(t,x))\zeta_\delta(\theta_t\omega))(\varepsilon u(t,x)+2u_t(t,x))dx|\\ \leq&\frac{1}{2}\varepsilon\nu\int_{\mathbb{R}^n}\rho_m(x)|u(t,x)|^2dx +\alpha\int_{\mathbb{R}^n}\rho_m(x)|u_t(t,x)|^2dx+\frac{1}{2}\varepsilon\gamma\int_{\mathbb{R}^n}\rho_m(x)F(x,u(t,x))dx\\ &+c_{13}\int_{\mathbb{R}^n}\rho_m(x)\bigg(|g(t,x)|^2+|\varphi_1(x)|+|\zeta_\delta(\theta_t\omega)\varphi_6(x)|^2 +|\zeta_\delta(\theta_t\omega)\varphi_5(x)|^{2+\frac{4}{p}}\bigg)dx, \end{align*} (4.33)

    where c_{13} depends only on \alpha, \nu, \gamma and \varepsilon .

    By (4.30)–(4.33) we get

    (4.34)

    where c_{14} > 0 depends only on \alpha, \nu, \gamma and \varepsilon , but not on m .

    By (4.34) we get

    (4.35)

    By Young's inequality we get

    \begin{align*} &\bigg|\varepsilon(\alpha-\frac{1}{4}\gamma)\int_{\mathbb{R}^n}\rho_m(x)u(t,x)u_t(t,x)dx\bigg|\\ \leq&\frac{1}{2}\varepsilon^2(\alpha-\frac{1}{4}\varepsilon\gamma)\int_{\mathbb{R}^n}\rho_m(x)|u(t,x)|^2dx+ \frac{1}{2}(\alpha-\frac{1}{4}\varepsilon\gamma)\int_{\mathbb{R}^n}\rho_m(x)|u_t(t,x)|^2dx. \end{align*} (4.36)

    By (4.35)-(4.36) we get

    (4.37)

    By (4.7) and (4.37) we have

    (4.38)

    Multiplying (4.38) by e^{\frac{1}{4}\varepsilon\gamma t} , and then integrating the inequality [\tau-t, \tau] , after replacing \omega by \theta_{-\tau}\omega , we get

    \begin{align*} &\int_{\mathbb{R}^n}\rho_m(x)\bigg(|u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0})|^2+\nu |u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})|^2+|\Delta u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})|^2\\ &+|\eta^t(\tau,\tau-t,\theta_{-\tau}\omega,\eta^{0},s)|^2_{\mu,2}+2F(x,u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0}))+\varepsilon u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0}) \bigg)dx\\ \leq&e^{-\frac{1}{4}\varepsilon\gamma t}\int_{\mathbb{R}^n}\rho_m(x)(|u_{1,0}|^2+\nu|u_0|^2+|\Delta u_0|^2+|\eta^0|^2_{\mu,2}+2F(x,u_0(x))+\varepsilon u_0(x)u_{1,0}(x))dx\\ &+c_{14}\int^{\tau}_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)} \int_{\mathbb{R}^n}\rho_m(x) (|g(s,x)|^2+|\varphi_1(x)|+|\varphi_3(x)|)dxds\\ &+c_{14}\int^{\tau}_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)} \int_{\mathbb{R}^n}\rho_m(x)(|\zeta_\delta(\theta_{s-\tau}\omega)\varphi_6(x)|^2 +|\zeta_\delta(\theta_{s-\tau}\omega)\varphi_5(x)|^{2+\frac{4}{p}})dxds\\ &+\frac{2c_{14}}{m}\int^{\tau}_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)}(\|u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2_{H^2(\mathbb{R}^n)} +\|u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0})\|^2_{H^1(\mathbb{R}^n)}\\ &+\|\eta^t(\tau,\tau-t,\theta_{-\tau}\omega,\eta^{0},s)\|^2_{\mu,2})ds. \end{align*} (4.39)

    Next, we estimate the right-hand side of (4.39). By (4.18), we know that there exists T_1(\eta, \tau, \omega, D) > 0 such that for all t\geq T_1 ,

    \begin{align} e^{-\frac{1}{4}\varepsilon\gamma t}\int_{\mathbb{R}^n}\rho_m(x)(|u_{1,0}|^2+\nu|u_0|^2+|\Delta u_0|^2+|\eta^0|^2_{\mu,2}+2F(x,u_0(x))+\varepsilon u_0(x)u_{1,0}(x))dx < \eta. \end{align} (4.40)

    For the second and the third terms on the right-hand side of (4.39) we get

    \begin{align*} &c_{14}\int^{\tau}_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)} \int_{\mathbb{R}^n}\rho_m(x)(|g(s,x)|^2+|\varphi_1(x)|+|\varphi_3(x)|)dxds\\ &+c_{14}\int^{\tau}_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)} \int_{\mathbb{R}^n}(\rho_m(x)|\zeta_\delta(\theta_{s-\tau}\omega)\varphi_6(x)|^2 +|\zeta_\delta(\theta_{s-\tau}\omega)\varphi_5(x)|^{2+\frac{4}{p}} )dxds\\ \leq&c_{14}\int^{\tau}_{-\infty}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)} \int_{|x|\geq\frac{1}{2}m}(|g(s,x)|^2+|\varphi_1(x)|+|\varphi_3(x)|)dxds\\ &+c_{14}\int^{\tau}_{-\infty}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)} \int_{|x|\geq\frac{1}{2}m}(|\zeta_\delta(\theta_{s-\tau}\omega)\varphi_6(x)|^2 +|\zeta_\delta(\theta_{s-\tau}\omega)\varphi_5(x)|^{2+\frac{4}{p}})dxds\\ \leq&c_{14}\int^{\tau}_{-\infty}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)} \int_{|x|\geq\frac{1}{2}m}(|g(s,x)|^2+|\varphi_1(x)|+|\varphi_3(x)|)dxds\\ &+c_{14}\int^{0}_{-\infty}e^{\frac{1}{4}\varepsilon\gamma s }|\zeta_\delta(\theta_{s}\omega)|^2ds\int_{|x|\geq\frac{1}{2}m}|\varphi_6(x)|^2dx\\ &+c_{14}\int^{0}_{-\infty}e^{\frac{1}{4}\varepsilon\gamma s }|\zeta_\delta(\theta_{s}\omega)|^{2+\frac{4}{p}}ds\int_{|x|\geq\frac{1}{2}m}|\varphi_5(x)|^{2+\frac{4}{p}}dx. \end{align*} (4.41)

    By (4.8) and the conditions of \varphi_i(x)(i = 1, 3, 5, 6) satisfy, we know that there exists m_1 = m_1(\eta, \tau, \omega)\geq1 such that for all m\geq m_1 , the right-hand of side of (4.39) is bounded by \eta , i.e.,

    \begin{align*} &c_{14}\int^{\tau}_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)} \int_{\mathbb{R}^n}\rho_m(x)(|g(s,x)|^2+|\varphi_1(x)|+|\varphi_3(x)|)dxds\\ &+c_{14}\int^{\tau}_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)} \int_{\mathbb{R}^n}(\rho_m(x)|\zeta_\delta(\theta_{s-\tau}\omega)\varphi_6(x)|^2 +|\zeta_\delta(\theta_{s-\tau}\omega)\varphi_5(x)|^{2+\frac{4}{p}} )dxds\\ < &\eta. \end{align*} (4.42)

    For the last term in (4.39), by Lemma 4.1 and Lemma 4.3, we know that there exists T_2(\eta, \tau, \omega, D)\geq T_1 such that for all t\geq T_2 ,

    \begin{align*} &\frac{2c_{14}}{m}\int^{\tau}_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)}(\|u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2_{H^2(\mathbb{R}^n)} +\|u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0})\|^2_{H^1(\mathbb{R}^n)}\\ &+\|\eta^t(\tau,\tau-t,\theta_{-\tau}\omega,\eta^{0},s)\|^2_{\mu,2})ds\\ \leq&\frac{c_{15}}{m}, \end{align*}

    where c_{15} > 0 depends only on \alpha, \nu, \gamma, \varepsilon, \tau and \omega , but not on m . Thus, there exists m_2 = m_2(\eta, \tau, \omega)\geq m_1 such that for all m\geq m_2 and t\geq T_2 ,

    \begin{align*} &\frac{2c_{14}}{m}\int^{\tau}_{\tau-t}e^{\frac{1}{4}\varepsilon\gamma (s-\tau)}(\|u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2_{H^2(\mathbb{R}^n)} +\|u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0})\|^2_{H^1(\mathbb{R}^n)}\\ &+\|\eta^t(\tau,\tau-t,\theta_{-\tau}\omega,\eta^{0},s)\|^2_{\mu,2})ds\\ \leq&\eta, \end{align*} (4.43)

    By (4.39), (4.40), (4.42) and (4.43) we see that for all m\geq m_2 and t\geq T_2 ,

    \begin{align*} &\int_{\mathbb{R}^n}\rho_m(x)\bigg(|u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0})|^2+\nu |u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})|^2+|\Delta u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})|^2\\ &+ |\eta^t(\tau,\tau-t,\theta_{-\tau}\omega,\eta^{0},s) |^2_{\mu,2}+2F(x,u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0}))+\varepsilon u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0}) \bigg)dx\\ < &3\eta. \end{align*} (4.44)

    By (4.7) we have

    \begin{align*} &\varepsilon\int_{\mathbb{R}^n}\rho_m(x)u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0})dx\\ \leq&\frac{1}{2}\nu\int_{\mathbb{R}^n}\rho_m(x)|u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})|^2dx+ \frac{1}{2}\int_{\mathbb{R}^n}\rho_m(x)|u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0})|^2dx, \end{align*}

    which together with (4.2) and (4.44) yields that for all m\geq m_2 and t\geq T_2 ,

    \begin{align*} &\int_{\mathbb{R}^n}\rho_m(x)\bigg(\frac{1}{2}|u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0})|^2+\frac{1}{2}\nu |u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})|^2+|\Delta u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})|^2 \\ &+ |\eta^t(\tau,\tau-t,\theta_{-\tau}\omega,\eta^{0},s) |^2_{\mu,2})dx\\ \leq&3\eta+2\int_{\mathbb{R}^n}\rho_m(x)\varphi_1(x)dx. \end{align*} (4.45)

    Since \varphi_1\in L^1(\mathbb{R}^n) , there exists m_3 = m_3(\eta, \tau, \omega)\geq m_2 such that for all m\geq m_3 ,

    \begin{align} 2\int_{\mathbb{R}^n}\rho_m(x)\varphi_1(x)dx = 2\int_{|x|\geq\frac{1}{2}m}\rho_m(x)\varphi_1(x)dx\leq2\int_{|x|\geq\frac{1}{2}m}|\varphi_1(x)|dx < \eta. \end{align} (4.46)

    From (4.45)-(4.46) we obtain, for all m\geq m_3 and t\geq T_2 ,

    \begin{align*} &\int_{|x|\geq m}\rho_m(x)\bigg(\frac{1}{2}|u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0})|^2+\frac{1}{2}\nu |u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})|^2+|\Delta u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})|^2\\ &+|\eta^t(\tau,\tau-t,\theta_{-\tau}\omega,\eta^{0},s)\|^2_{\mu,2}|)dx\\ \leq&\int_{\mathbb{R}^n}\rho_m(x)\bigg(\frac{1}{2}|u_t(\tau,\tau-t,\theta_{-\tau}\omega,u_{1,0})|^2+\frac{1}{2}\nu |u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})|^2+|\Delta u(\tau,\tau-t,\theta_{-\tau}\omega,u_{0})|^2\\ &+|\eta^t(\tau,\tau-t,\theta_{-\tau}\omega,\eta^{0},s)\|^2_{\mu,2}|)dx\\ < &4\eta. \end{align*}

    In this section, we present the existence and uniqueness of \mathcal{D} -pullback random attractors of (3.2).

    Let z = (u, u_t, \eta^t) be the solution of (3.2). Denote u = \tilde{v}+v, \eta^t = \tilde{\eta}^t+\eta where (\tilde{v}, \tilde{\eta}^t) and (v, \eta^t) are the solutions of the following equations, respectively,

    \begin{align} \left\{\begin{array}{ll} \tilde{v}_{tt}+\alpha \tilde{v}_t+\Delta^{2}\tilde{v}+\int_0^\infty\mu(s)\Delta^2\tilde{\eta}^t(s)ds+\nu \tilde{v} = g(t), \ t > \tau, \\[1ex] \tilde{v}(\tau) = u_0,\; \; \tilde{v}_t(\tau) = u_{1,0},\; \; \tilde{\eta}^t(\tau) = \eta^0 \end{array}\right. \end{align} (5.1)

    and

    \begin{align} \left\{\begin{array}{ll} v_{tt}+\alpha v_t+\Delta^{2}v+\int_0^\infty\mu(s)\Delta^2\eta^t(s)ds+\nu v = -f(x,u)+h(t,x,u)\zeta_\delta(\theta_t\omega),\ t > \tau, \\[1ex] v(\tau) = 0,\; \; v_t(\tau) = 0,\; \; \eta^t(\tau) = 0. \end{array}\right. \end{align} (5.2)

    Lemma 5.1. Suppose (3.3), (4.7)-(4.8) hold. Then for every \tau\in\mathbb{R}, \omega\in\Omega and D\in\mathcal{D} , there exists T = T(\tau, \omega, D) > 0 such that for all t\geq T and r\in[-t, 0] , the solution \tilde{v} of (5.1) satisfies

    \begin{align*} &\|\tilde{v}(\tau+r,\tau-t,\theta_{-\tau}\omega,u_0)\|^2_{H^2(\mathbb{R}^n)}+ \|\tilde{v}_r(\tau+r,\tau-t,\theta_{-\tau}\omega,u_{1,0})\|^2 +\|\tilde{\eta}^t(\tau+r,\tau-t,\theta_{-\tau}\omega,\eta^0,s)\|^2_{\mu,2}\\ \leq&e^{-\frac{1}{2}\varepsilon r}M_2\bigg(1+\int^0_\infty e^{\frac{1}{2}\varepsilon s}\|g(s+\tau)\|^2ds\bigg), \end{align*}

    where (u_0, u_{1, 0})\in D(\tau-t, \theta_{-t}\omega) and M_2 is a positive number independent of \tau, \omega and D .

    Proof. From (3.10)-(3.11) and (5.1) we see that

    \begin{align*} &\frac{d}{dt}(\|\tilde{v}_t\|^2+\|\Delta \tilde{v}\|^2+\|\tilde{\eta}^t\|^2_{\mu,2}+\nu \|\tilde{v}\|^2+\varepsilon (\tilde{v}(t),\tilde{v}_t(t)))+(2\alpha-\varepsilon)\|\tilde{v}_t\|^2 \\ &+\varepsilon\|\Delta \tilde{v}\|^2+ \varepsilon\nu \|\tilde{v}\|^2+\varepsilon\alpha(\tilde{v}(t),\tilde{v}_t(t)) +\varepsilon(\tilde{\eta}^t(s),\tilde{v}(t))_{\mu,2} -\int^\infty_0\mu'(s)\|\Delta\tilde{\eta}^t\|^2ds\\ = &(g(t),\varepsilon\tilde{v}(t)+2\tilde{v}_t(t))\\ \leq&\varepsilon\|g(t)\|\|\tilde{v}(t)\|+2\|g(t)\|\|\tilde{v}_t(t)\|\\ \leq&\frac{1}{2}\varepsilon^2\|\tilde{v}(t)\|^2+\alpha\|\tilde{v}_t(t)\|^2+(\frac{1}{2}+\alpha^{-1})\|g(t)\|^2. \end{align*} (5.3)

    In addition, we get

    \begin{align} |(\alpha-\frac{1}{2}\varepsilon)\varepsilon(\tilde{v}(t),\tilde{v}_t(t))| \leq\frac{1}{2}(\alpha-\frac{1}{2}\varepsilon)(\varepsilon^2\|\tilde{v}(t)\|^2+\|\tilde{v}_t(t)\|^2). \end{align} (5.4)

    By (4.11)-(4.12) and (5.3)-(5.4) we have

    \begin{align*} &\frac{d}{dt}(\|\tilde{v}_t\|^2+\|\Delta \tilde{v}\|^2+\|\tilde{\eta}^t\|^2_{\mu,2}+\nu \|\tilde{v}\|^2+\varepsilon (\tilde{v}(t),\tilde{v}_t(t)))+(\frac{1}{2}\alpha-\frac{3}{4}\varepsilon)\|\tilde{v}_t\|^2 \\ &+\varepsilon(1-\frac{\varpi\varepsilon}{\varrho})\|\Delta \tilde{v}\|^2+\frac{3\varrho}{4}\|\tilde{\eta}^t\|^2_{\mu,2}+ \varepsilon(\nu-\frac{1}{2}\varepsilon-\frac{1}{2}\varepsilon\alpha+\frac{1}{4} \varepsilon^2) \|\tilde{v}\|^2+\frac{1}{2}\varepsilon^2(\tilde{v}(t),\tilde{v}_t(t))\\ \leq&(\frac{1}{2}+\alpha^{-1})\|g(t)\|^2, \end{align*}

    which can be rewritten as

    \begin{align*} &\frac{d}{dt}(\|\tilde{v}_t\|^2+\|\Delta \tilde{v}\|^2+\|\tilde{\eta}^t\|^2_{\mu,2}+\nu \|\tilde{v}\|^2+\varepsilon (\tilde{v}(t),\tilde{v}_t(t)))\\ &+\frac{1}{2}\varepsilon(\|\tilde{v}_t\|^2+\|\Delta \tilde{v}\|^2+\|\tilde{\eta}^t\|^2_{\mu,2}+\nu \|\tilde{v}\|^2+\varepsilon (\tilde{v}(t),\tilde{v}_t(t)))\\ &+(\frac{1}{2}\alpha-\frac{5}{4}\varepsilon)\|\tilde{v}_t\|^2+\frac{1}{2}\varepsilon(1-\frac{2\varpi\varepsilon}{\varrho})\|\Delta \tilde{v}\|^2+\frac{3}{4}(\varrho-\frac{2}{3}\varepsilon)\|\tilde{\eta}^t\|^2_{\mu,2}+\frac{1}{2}\varepsilon(\nu- \varepsilon- \varepsilon\alpha+\frac{1}{2} \varepsilon^2) \|\tilde{v}\|^2\\ \leq&(\frac{1}{2}+\alpha^{-1})\|g(t)\|^2. \end{align*} (5.5)

    It follows from (4.7) and (5.5) that

    \begin{align*} &\frac{d}{dt}(\|\tilde{v}_t\|^2+\|\Delta \tilde{v}\|^2+\|\tilde{\eta}^t\|^2_{\mu,2}+\nu \|\tilde{v}\|^2+\varepsilon (\tilde{v}(t),\tilde{v}_t(t)))\\ &+\frac{1}{2}\varepsilon(\|\tilde{v}_t\|^2+\|\Delta \tilde{v}\|^2+\|\tilde{\eta}^t\|^2_{\mu,2}+\nu \|\tilde{v}\|^2+\varepsilon (\tilde{v}(t),\tilde{v}_t(t)))\\ \leq&(\frac{1}{2}+\alpha^{-1})\|g(t)\|^2. \end{align*} (5.6)

    Applying Gronwall's lemma to (5.6), we get for all \tau\in\mathbb{R}, t\geq0, r\in[-t, 0] and \omega\in\Omega ,

    \begin{align*} &\|\tilde{v}_r(\tau+r,\tau-t,\theta_{-\tau}\omega,u_{1,0})\|^2+\|\Delta \tilde{v}(\tau+r,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2+\|\tilde{\eta}^t(\tau+r,\tau-t,\theta_{-\tau}\omega,\eta^0,s)\|^2_{\mu,2}\\ &+\nu \|\tilde{v}(\tau+r,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2+\varepsilon (\tilde{v}(\tau+r,\tau-t,\theta_{-\tau}\omega,u_{0}),\tilde{v}_r(\tau+r,\tau-t,\theta_{-\tau}\omega,u_{1,0}))\\ \leq&e^{-\frac{1}{2}\varepsilon r}e^{-\frac{1}{2}\varepsilon t}\big(\|u_{1,0}\|^2+\nu \|u_0\|^2+\|\Delta u_{0}\|^2+ \varepsilon(u_{0},u_{1,0})\big)\\ &+(\frac{1}{2}+\alpha^{-1})e^{-\frac{1}{2}\varepsilon r}\int^{\tau+r}_{\tau-t}e^{\frac{1}{2}\varepsilon (s-\tau)}\|g(s)\|^2ds. \end{align*} (5.7)

    By (4.7) we have

    \begin{align*} &\varepsilon (\tilde{v}(\tau+r,\tau-t,\theta_{-\tau}\omega,u_{0}),\tilde{v}_r(\tau+r,\tau-t,\theta_{-\tau}\omega,u_{1,0}))\\ \leq&\frac{1}{2}\varepsilon\|\tilde{v}(\tau+r,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2+ \frac{1}{2}\varepsilon\|\tilde{v}_r(\tau+r,\tau-t,\theta_{-\tau}\omega,u_{1,0})\|^2\\ \leq&\frac{1}{2}\nu\|\tilde{v}(\tau+r,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2+ \frac{1}{2}\|\tilde{v}_r(\tau+r,\tau-t,\theta_{-\tau}\omega,u_{1,0})\|^2. \end{align*} (5.8)

    By (5.7)-(5.8) we see that for all \tau\in\mathbb{R}, t\geq0, r\in[-t, 0] and \omega\in\Omega ,

    \begin{align*} &\frac{1}{2}\|\tilde{v}_r(\tau+r,\tau-t,\theta_{-\tau}\omega,u_{1,0})\|^2+\|\Delta \tilde{v}(\tau+r,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2+\|\tilde{\eta}^t(\tau+r,\tau-t,\theta_{-\tau}\omega,\eta^0,s)\|^2_{\mu,2}\\ &+\frac{1}{2}\nu \|\tilde{v}(\tau+r,\tau-t,\theta_{-\tau}\omega,u_{0})\|^2\\ \leq&e^{-\frac{1}{2}\varepsilon r}e^{-\frac{1}{2}\varepsilon t}\big(\|u_{1,0}\|^2+\nu \|u_0\|^2+\|\Delta u_{0}\|^2+\|\eta^0\|^2_{\mu,2}+ \varepsilon(u_{0},u_{1,0})\big)\\ &+(\frac{1}{2}+\alpha^{-1})e^{-\frac{1}{2}\varepsilon r}\int^{\tau+r}_{\tau-t}e^{\frac{1}{2}\varepsilon (s-\tau)}\|g(s)\|^2ds. \end{align*} (5.9)

    Similar to (4.16), one can verify that

    e^{-\frac{1}{2}\varepsilon t}\big(\|u_{1,0}\|^2+\nu \|u_0\|^2+\|\Delta u_{0}\|^2+\|\eta^0\|^2_{\mu,2}+ \varepsilon(u_{0},u_{1,0})\big)\rightarrow0,\ \ \text{as}\ \ t\rightarrow \infty,

    which along with (5.9) yields the desire result.

    Based on Lemma 5.1, we infer that system (5.1) has a tempered pullback random absorbing set.

    Lemma 5.2. Suppose (3.3), (4.8)-(4.9) hold, then (5.1) possesses a closed measurable \mathcal{D} -pullback absorbing set B_1 = \{B_1(\tau, \omega):\tau\in\mathbb{R}, \omega\in\Omega\}\in\mathcal{D} , which is given by

    \begin{align} B_1(\tau,\omega) = \{(u_0,u_{1,0},\eta^0)\in H^2(\mathbb{R}^n)\times L^2(\mathbb{R}^n)\times\mathfrak{R}_{\mu,2}:\|u_0\|^2_{H^2(\mathbb{R}^n)}+\|u_{1,0}\|^2+\|\eta^0\|^2_{\mu,2}\leq L_1(\tau,\omega)\}, \end{align} (5.10)

    where

    L_1(\tau,\omega) = M_2+M_2\int^0_{-\infty}e^{\frac{1}{2}\varepsilon s} \|g(s+\tau)\|^2ds.

    Lemma 5.3. Suppose (4.8)-(4.9) hold, then the sequence of the solutions to (5.1)

    \{\tilde{v}(\tau,\tau-t_n,\theta_{-\tau}\omega,u^{(n)}_0),\tilde{v}_t(\tau,\tau-t_n,\theta_{-\tau}\omega,u^{(n)}_{1,0}), \tilde{\eta}^t(\tau,\tau-t_n,\theta_{-\tau}\omega,\eta^{(0n)})\}^\infty_{n = 1}

    converges in H^2(\mathbb{R}^n)\times L^2(\mathbb{R}^n)\times\mathfrak{R}_{\mu, 2} for any \tau\in\mathbb{R}, \omega\in\Omega, D\in\mathcal{D}, t_n\rightarrow \infty monotonically, and (u^{(n)}_0, u^{(n)}_{1, 0}, \eta^{(0n)})\in D(\tau-t_n, \theta_{-t_n}\omega) .

    Proof. Let m > n and

    \begin{align*} &v_{n,m}(t,\tau-t_n,\theta_{-\tau}\omega)\\ = &\tilde{v}(t,\tau-t_n,\theta_{-\tau}\omega,u^{(n)}_0)-\tilde{v}(t,\tau-t_m,\theta_{-\tau}\omega,u^{(m)}_0)\\ = &\tilde{v}(t,\tau-t_n,\theta_{-\tau}\omega,u^{(n)}_0)-\tilde{v}(t,\tau-t_n,\theta_{-\tau}\omega,\tilde{v}(\tau-t_n,\tau-t_m,\theta_{-\tau}\omega,u^{(m)}_0)\\ &\eta^t_{n,m}(t,\tau-t_n,\theta_{-\tau}\omega,s)\\ = &\tilde{\eta}^t(t,\tau-t_n,\theta_{-\tau}\omega,\eta^{(0n)},s)-\tilde{\eta}^t(t,\tau-t_m,\theta_{-\tau}\omega,\eta^{(0m)},s)\\ = &\tilde{\eta}^t(t,\tau-t_n,\theta_{-\tau}\omega,\eta^{(0n)},s)-\tilde{\eta}^t(t,\tau-t_n,\theta_{-\tau}\omega,s,\tilde{\eta}^t(\tau-t_n,\tau-t_m,\theta_{-\tau}\omega,\eta^{(0m)},s). \end{align*} (5.11)

    for t\geq\tau-t_n .

    by (5.1) we get

    \begin{align} \left\{\begin{array}{ll} \partial^2_{tt}v_{n,m}(t)+\alpha\partial_{t}v_{n,m}(t)+\Delta^{2}v_{n,m}(t)+\int^\infty_0\mu(s)\Delta^2\eta^t_{n,m}ds+\nu v_{n,m}(t) = 0, \ t > \tau-t_n, \\[1ex] v_{n,m}(\tau-t_n) = u^{(n)}_0-\tilde{v}(\tau-t_n,\tau-t_m,\theta_{-\tau}\omega,u^{(m)}_0),\; \; \partial_{t}v_{n,m}(\tau-t_n) = u^{(n)}_{1,0}-\tilde{v}_t, \\[1ex] \eta^\tau_{n,m}(\tau-t_n,s) = \eta^{(0n)}-\tilde{\eta}^t(\tau-t_n,\tau-t_m,\theta_{-\tau}\omega,\eta^{(0m)},s). \end{array}\right. \end{align} (5.12)

    Similar to (5.9) with r = 0, t = t_n and g = 0 , we obtain

    \begin{align*} &\frac{1}{2}\|\partial_{t}v_{n,m}(\tau,\tau-t_n,\theta_{-\tau}\omega)\|^2+\|\Delta v_{n,m}(\tau,\tau-t_n,\theta_{-\tau}\omega)\|^2+\|\eta^t_{n,m}(\tau,\tau-t_n,\theta_{-\tau}\omega,s)\|^2_{\mu,2}\\ &+\frac{1}{2}\nu v_{n,m}(\tau,\tau-t_n,\theta_{-\tau}\omega)\|^2\\ \leq&e^{-\frac{1}{2}\varepsilon t_n}(\|\partial_{t}v_{n,m}(\tau-t_n)\|^2+\|v_{n,m}(\tau-t_n)\|^2+\|\Delta v_{n,m}(\tau-t_n)\|^2+\|\eta^\tau_{n,m}(\tau-t_n,s)\|^2_{\mu,2}), \end{align*} (5.13)

    which together with (5.12)_2 , we get

    \begin{align*} &\|\partial_{t}v_{n,m}(\tau,\tau-t_n,\theta_{-\tau}\omega)\|^2+2\|\Delta v_{n,m}(\tau,\tau-t_n,\theta_{-\tau}\omega)\|^2+\|\eta^t_{n,m}(\tau,\tau-t_n,\theta_{-\tau}\omega,s)\|^2_{\mu,2}\\ &+ \nu v_{n,m}(\tau,\tau-t_n,\theta_{-\tau}\omega)\|^2\\ \leq&2e^{-\frac{1}{2}\varepsilon t_n}(\|\tilde{v}_t(\tau-t_n,\tau-t_m,\theta_{-\tau}\omega,u^{(m)}_{1,0}\|^2+ \|\tilde{v}(\tau-t_n,\tau-t_m,\theta_{-\tau}\omega,u^{(m)}_{0}\|^2_{H^2})\\ &+\|\tilde{\eta}^t(\tau-t_n,\tau-t_m,\theta_{-\tau}\omega,\eta^{(0m)},s)\|^2_{\mu,2})\\ &+2e^{-\frac{1}{2}\varepsilon t_n}(\|u^{(n)}_{1,0}\|^2+\|u^{(n)}_{0}\|^2+\|\Delta u^{(n)}_{0}\|^2+\|\eta^{(0n)} \|^2_{\mu,2}). \end{align*} (5.14)

    By (5.9) with r = -t_n , and t = t_m , we obtain

    \begin{align*} &\|\tilde{v}_t(\tau-t_n,\tau-t_m,\theta_{-\tau}\omega,u^{(m)}_{1,0})\|^2+2\|\Delta \tilde{v}(\tau-t_n,\tau-t_m,\theta_{-\tau}\omega,u^{(m)}_{0})\|^2 \\ &+\|\tilde{\eta}^t(\tau-t_n,\tau-t_m,\theta_{-\tau}\omega,\eta^{(0m)})\|^2_{\mu,2}+\nu \|\tilde{v}(\tau-t_n,\tau-t_m,\theta_{-\tau}\omega,u^{(m)}_{0})\|^2\\ \leq&2e^{\frac{1}{2}\varepsilon t_n}e^{-\frac{1}{2}\varepsilon t_m}\big(\|u^{(n)}_{1,0}\|^2+\nu \|u^{(n)}_0\|^2+\|\Delta u^{(n)}_{0}\|^2+\|\eta^{(0n)} \|^2_{\mu,2}+ \varepsilon(u^{(n)}_{0},u^{(n)}_{1,0})\big)\\ &+(1+2\alpha^{-1})e^{\frac{1}{2}\varepsilon t_n}\int^{\tau-t_n}_{\tau-t_m}e^{\frac{1}{2}\varepsilon (s-\tau)}\|g(s)\|^2ds. \end{align*} (5.15)

    It follows from (5.14)-(5.15) that for m > n\rightarrow \infty ,

    \|\partial_{t}v_{n,m}(\tau,\tau-t_n,\theta_{-\tau}\omega)\|^2+\| v_{n,m}(\tau,\tau-t_n,\theta_{-\tau}\omega)\|^2_{H^2(\mathbb{R}^n)}+\|\eta^t_{n,m}(\tau,\tau-t_n,\theta_{-\tau}\omega,s)\|^2_{\mu,2}\rightarrow0,

    together with (5.11) implies \{\tilde{v}(\tau, \tau-t_n, \theta_{-\tau}\omega, u^{(n)}_0), \tilde{v}_t(\tau, \tau-t_n, \theta_{-\tau}\omega, u^{(n)}_{1, 0}), \tilde{\eta}^t(\tau, \tau-t_n, \theta_{-\tau}\omega, \eta^{(0n)})\}^\infty_{n = 1} is a Cauchy sequence in H^2(\mathbb{R}^n)\times L^2(\mathbb{R}^n)\times\mathfrak{R}_{\mu, 2} . This complete the proof.

    Lemma 5.4. Suppose (3.3), (4.8)-(4.9) hold, then (5.1) has a unique \mathcal{D} -pullback random attractor \mathcal{A}_1 = \{\mathcal{A}_1(\tau, \omega):\tau\in\mathbb{R}, \omega\in\Omega\}\in\mathcal{D} in H^2(\mathbb{R}^n)\times L^2(\mathbb{R}^n)\times\mathfrak{R}_{\mu, 2} , which is actually a singleton; that is, \mathcal{A}_1(\tau, \omega) consisting of a single point for all \tau\in\mathbb{R}, \omega\in\Omega .

    Proof. From Lemmas 5.2 and 5.3 by applying the abstract results in [29], we can get the existence and uniqueness of the \mathcal{D} -pullback random attractor \mathcal{A}_1\in\mathcal{D} of (5.1) in H^2(\mathbb{R}^n)\times L^2(\mathbb{R}^n)\times\mathfrak{R}_{\mu, 2} immediately.

    Next, we prove \mathcal{A}_1 is a singleton. Suppose \{t_n\}^\infty_{ n = 1} 1 be a sequence of numbers such that t_n\rightarrow \infty as n\rightarrow \infty . Given \tau\in\mathbb{R}, \omega\in\Omega , let (z^{(n)}_0, z^{(n)}_{1, 0}, \eta^{(0n)}), (y^{(n)}_0, y^{(n)}_{1, 0}, y^{(0n)})\in\mathcal{A}_1(\tau-t_n, \theta_{-t_n}\omega) .

    Similar to (5.13) we have

    \begin{align*} &\|\tilde{v}_t (\tau,\tau-t_n,\theta_{-\tau}\omega,z^{(n)}_{1,0})-\tilde{v}_t (\tau,\tau-t_n,\theta_{-\tau}\omega,y^{(n)}_{1,0})\|^2\\ &+2\|\Delta\tilde{v}(\tau,\tau-t_n,\theta_{-\tau}\omega,z^{(n)}_0)- \Delta\tilde{v}(\tau,\tau-t_n,\theta_{-\tau}\omega,y^{(n)}_0)\|^2\\ &+\|\tilde{\eta}^t (\tau,\tau-t_n,\theta_{-\tau}\omega,\eta^{(0n)})-\tilde{\eta}^t (\tau,\tau-t_n,\theta_{-\tau}\omega,y^{(0n)})\|^2_{\mu,2}\\ &+ \nu \|\tilde{v}(\tau,\tau-t_n,\theta_{-\tau}\omega,z^{(n)}_0)- \tilde{v}(\tau,\tau-t_n,\theta_{-\tau}\omega,y^{(n)}_0)\|^2\\ \leq&e^{-\frac{1}{2}\varepsilon t_n}(\|z^{(n)}_{1,0}-y^{(n)}_{1,0}\|^2+\|z^{(n)}_{0}-y^{(n)}_{0}\|^2+\|\Delta z^{(n)}_{0}-\Delta y^{(n)}_{0}\|^2+\|\eta^{(0n)}-y^{(0n)}\|^2_{\mu,2})\\ \leq&2e^{-\frac{1}{2}\varepsilon t_n}(\|z^{(n)}_{1,0}\|^2+\|z^{(n)}_{0}\|^2_{H^2(\mathbb{R}^n)}+\|y^{(n)}_{1,0}\|^2 +\|y^{(n)}_{1,0}\|^2_{H^2(\mathbb{R}^n)}+\|\eta^{(0n)}\|^2_{\mu,2}+\|y^{(0n)}\|^2_{\mu,2})\\ \leq&4e^{-\frac{1}{2}\varepsilon t_n}\|\mathcal{A}_1(\tau-t_n,\theta_{-t_n}\omega)\|^2_{H^2(\mathbb{R}^n)\times L^2(\mathbb{R}^n)\times\mathfrak{R}_{\mu,2}}. \end{align*} (5.16)

    Due to \mathcal{A}_1\in\mathcal{D} , we see that the right-hand side of (5.16) tends to zero as n\rightarrow \infty , and thus we get

    \begin{align*} &\lim\limits_{n\rightarrow \infty}(\tilde{v}_t (\tau,\tau-t_n,\theta_{-\tau}\omega,z^{(n)}_{1,0})-\tilde{v}_t (\tau,\tau-t_n,\theta_{-\tau}\omega,y^{(n)}_{1,0})) = 0 \ \ \ \text{in} \ \ L^2(\mathbb{R}^n),\\ &\lim\limits_{n\rightarrow \infty}(\tilde{v} (\tau,\tau-t_n,\theta_{-\tau}\omega,z^{(n)}_{0})-\tilde{v} (\tau,\tau-t_n,\theta_{-\tau}\omega,y^{(n)}_{0})) = 0 \ \ \ \text{in} \ \ H^2(\mathbb{R}^n),\\ &\lim\limits_{n\rightarrow \infty}( \tilde{\eta}^t (\tau,\tau-t_n,\theta_{-\tau}\omega,\eta^{(0n)})-\tilde{\eta}^t (\tau,\tau-t_n,\theta_{-\tau}\omega,y^{(0n)})) = 0 \ \ \ \text{in} \ \ \mathfrak{R}_{\mu,2}. \end{align*}

    which together with the invariance of \mathcal{A}_1 , we know that the \mathcal{D} -pullback random attractor \mathcal{A}_1 is a singleton. This complete the proof.

    To obtain the asymptotic compactness of the solutions of (5.2), we need the following Lemma.

    Lemma 5.5. Let u_0\in H^2(\mathbb{R}^n) , u_{1, 0}\in L^2(\mathbb{R}^n), \eta^0\in\mathfrak{R}_{\mu, 2}, \tau\in\mathbb{R}, \omega\in\Omega and T > 0 . If (3.3)-(3.5), (3.8), (4.1)-(4.2) and (4.5)-(4.8) hold, then the solution of (5.2) satisfies, for all t\in[\tau, \tau+T] ,

    \|A^{\frac{3}{4}}v(t,\tau,\omega)\|+\|A^{\frac{1}{4}}v_t(t,\tau,\omega)\|+\|A^{\frac{1}{4}}\eta^t(t,\tau,\omega,s)\|_{\mu,2}\leq C,

    where C is a positive number depending on \tau, \omega, T and R when \|(u_0, u_{1, 0}, \eta^0)\|_{H^2(\mathbb{R}^n)\times L^2(\mathbb{R}^n)\times\mathfrak{R}_{\mu, 2}}\leq R .

    Proof. This is an immediate consequence of Lemma 4.3.

    Lemma 5.6. Let (3.3)–(3.5), (3.6), (4.1)–(4.3) and (4.5)–(4.9) hold. Then the cocycle \Phi is \mathcal{D} -pullback asymptotically compact in H^2(\mathbb{R}^n)\times L^2(\mathbb{R}^n)\times\mathfrak{R}_{\mu, 2} ; that is, the sequence \{\Phi(t_n, \tau-t_n, \theta_{-t_n}\omega, (u^{(n)}_0, u^{(n)}_{1, 0}), \eta^{(0n)}\}^\infty_{n = 1} has a convergent subsequence in H^2(\mathbb{R}^n)\times L^2(\mathbb{R}^n)\times\mathfrak{R}_{\mu, 2} for any \tau\in\mathbb{R}, \omega\in\Omega, D\in\mathcal{D}, t_n\rightarrow \infty and (u^{(n)}_0, u^{(n)}_{1, 0}, \eta^{(0n)})\in D(\tau-t_n, \theta_{-t_n}\omega) .

    Proof. Given t\in\mathbb{R}^+, \tau\in\mathbb{R}, \omega\in\Omega and (u_0, u_{1, 0}, \eta^0)\in H^2(\mathbb{R}^n)\times L^2(\mathbb{R}^n)\times\mathfrak{R}_{\mu, 2} , define

    \begin{align*} &\Phi_1(t,\tau,\omega,(u_0,u_{1,0},\eta^0)) = (\tilde{v}(t+\tau,\tau,\theta_{-\tau}\omega,u_0),\tilde{v}_t(t+\tau,\tau,\theta_{-\tau}\omega,u_{1,0}),\tilde{\eta}^t(t+\tau,\tau,\theta_{-\tau}\omega,\eta^{0},s)),\\ &\Phi_2(t,\tau,\omega,(u_0,u_{1,0},\eta^0)) = (v(t+\tau,\tau,\theta_{-\tau}\omega,u_0),v_t(t+\tau,\tau,\theta_{-\tau}\omega,u_{1,0}),\eta^t(t+\tau,\tau,\theta_{-\tau}\omega,\eta^{0},s)), \end{align*}

    where (\tilde{v}, \tilde{\eta}^t) and (v, \eta^t) are the solutions of (5.1) and (5.2), respectively.

    By(3.78) we have

    \begin{align} \Phi(t,\tau,\omega,(u_0,u_{1,0},\eta^0)) = \Phi_1(t,\tau,\omega,(u_0,u_{1,0},\eta^0))+\Phi_2(t,\tau,\omega,(u_0,u_{1,0},\eta^0)). \end{align} (5.17)

    Let B\in\mathcal{D} be the \in\mathcal{D} -pullback absorbing set of \Phi given by (4.19). From Lemmas 4.2, 4.4 and 5.4 we see that for every \delta > 0 there exists t_0 = t_0(\delta, \tau, \omega, B) > 0 and k_0 = k_0(\delta, \tau, \omega)\geq1 such that for all (u_0, u_{1, 0}, \eta^0)\in B(\tau-t_0, \theta_{-t_0}\omega) ,

    \begin{align} \|\Phi(t_0,\tau-t_0,\theta_{-t_0}\omega,(u_0,u_{1,0},\eta^0))| _{\tilde{\mathcal{O}}_{k_0}}\|_{H^2(\tilde{\mathcal{O}}_{k_0})\times L^2(\tilde{\mathcal{O}}_{k_0})\times\mathfrak{R}_{\mu,2}} < \delta, \end{align} (5.18)

    with \tilde{\mathcal{O}}_{k_0} = \{x\in\mathbb{R}^n:|x| > k_0\} , and

    \begin{align} \Phi_1(t_0,\tau-t_0,\theta_{-t_0}\omega,B(\tau-t_0,\theta_{-t_0}\omega))\ \ \text{ is covered by a ball of radius}\ \ \ \delta \end{align} (5.19)

    in H^2(\mathbb{R}^n)\times L^2(\mathbb{R}^n)\times\mathfrak{R}_{\mu, 2} .

    In addition, by Lemma 5.5 we know that for every t\in\mathbb{R}^+, \tau\in\mathbb{R}, \omega\in\Omega and k\in\mathbb{N} ,

    \Phi_2(t,\tau-t,\theta_{-t}\omega,B(\tau-t,\theta_{-t}\omega))\ \ \text{ is bounded in}\ \ \ H^{3}(\mathbb{R}^n)\times H^{1}(\mathbb{R}^n)\times\mathfrak{R}_{\mu,3},

    and thus for each k\in\mathbb{N} ,

    \begin{align} \Phi_2(t,\tau-t,\theta_{-t}\omega,B(\tau-t,\theta_{-t}\omega))|_{\mathcal{O}_{k}} \ \ \ \text{is precompact} \ \ \ H^2(\mathcal{O}_{k})\times L^2(\mathcal{O}_{k})\times\mathfrak{R}_{\mu,2}, \end{align} (5.20)

    with \mathcal{O}_{k} = \{x\in\mathbb{R}^n:|x| < k\} .

    It follows from (5.17)–(5.20) we get that all conditions of Theorem 2.1 are satisfied, so \Phi is \mathcal{D} -pullback asymptotically compact in H^{2}(\mathbb{R}^n)\times L^{2}(\mathbb{R}^n)\times\mathfrak{R}_{\mu, 2} .

    Since Lemma 4.2 implies a closed measurable \mathcal{D} -pullback absorbing set for \Phi , and \Phi is \mathcal{D} -pullback asymptotically compact in H^{2}(\mathbb{R}^n)\times L^{2}(\mathbb{R}^n)\times\mathfrak{R}_{\mu, 2} from Lemma 5.6, we immediately get the following existence theorem by Theorem 2.2.

    Theorem 5.1. Let (3.3)–(3.5), (3.6), (4.1)–(4.3) and (4.5)–(4.9) hold. Then the cocycle \Phi has a unique \mathcal{D} -pullback random attractor in H^2(\mathbb{R}^n)\times L^2(\mathbb{R}^n)\times\mathfrak{R}_{\mu, 2} .

    In this paper, we use the uniform estimates on the tails of solutions and the splitting technique to obtained the existence and uniqueness of \mathcal{D} -pullback attractor for the problem (1.1). The method used in this paper is proposed by P. W. Bates et al [3], they applied the method to deal with the asymptotic behavior of the non-automatous random system on unbounded domains. More precisely, one first need to show that the tails of the solutions of (1.1) are uniformly small outside a bounded domain for large time, and then derive the asymptotic compactness of solutions in bounded domains by splitting the solutions as two parts: one part has trivial dynamics in the sense that it possesses a unique tempered attracting random solution; and the other part has regularity higher than H^2(\mathbb{R}^n)\times L^2(\mathbb{R}^n)\times\mathfrak{R}_{\mu, 2} based on the estimates of solutions (see Lemma 4.3).

    Using the uniform estimates on the tails of solutions and the splitting technique, we obtained the existence and uniqueness of \mathcal{D} -pullback attractor for the problem (1.1). It is well-known that the pullback random attractors are employed to describe long-time behavior for an non-autonomous dynamical system with random term, while the \mathcal{D} -pullback attractor that we obtained can characterize the asymptotic behavior of the equation like (1.1), which is featured with both stochastic term and non-autonomous term.

    The author X. Yao was supported by the Natural Science Foundation of China (No. 12161071, 11961059).

    The authors declare that there is no conflict of interests regarding the publication of this article.



    [1] G. Hernandez-Duenas, A hybrid method to solve shallow water flows with horizontal density gradients, J. Sci. Comput., 73 (2017), 753–782. https://doi.org/10.1007/s10915-017-0553-1 doi: 10.1007/s10915-017-0553-1
    [2] V. A. Dorodnitsyn, E. I. Kaptsov, Discrete shallow water equations preserving symmetries and conservation laws, J. Math. Phys., 62 (2021), 083508. https://doi.org/10.1063/5.0031936 doi: 10.1063/5.0031936
    [3] V. A. Dorodnitsyn, E. I. Kaptsov, Shallow water equations in Lagrangian coordinates: symmetries, conservation laws and its preservation in difference models, Commun. Nonlinear Sci. Numer. Simul., 89 (2020), 105343. https://doi.org/10.1016/j.cnsns.2020.105343 doi: 10.1016/j.cnsns.2020.105343
    [4] E. Godlewski, P. A. Raviart, Numerical approximation of hyperbolic systems of conservation laws, Springer, New York, 1996. https://doi.org/10.1007/978-1-4612-0713-9
    [5] L. C. Evans, Partial differential equations, American Mathematical Society, 1998.
    [6] R. J. LeVeque, Finite volume methods for hyperbolic problems, Cambridge University Press, 2002. https://doi.org/10.1017/CBO9780511791253
    [7] M. A. E. Abdelrahman, On the shallow water equations, Z. Naturforschung A, 72 (2017), 873–879. https://doi.org/10.1515/zna-2017-0146 doi: 10.1515/zna-2017-0146
    [8] K. Mohamed, M. A. E. Abdelrahman, The modified Rusanov scheme for solving the ultra-relativistic Euler equations, Eur. J. Mech.-B/Fluids, 90 (2021), 89–98. https://doi.org/10.1016/j.euromechflu.2021.07.014 doi: 10.1016/j.euromechflu.2021.07.014
    [9] M. A. E. Abdelrahman, On the shallow water equations, Z. Naturforschung A, 72 (2017), 873–879. https://doi.org/10.1515/zna-2017-0146 doi: 10.1515/zna-2017-0146
    [10] E. F. Toro, Riemann solvers and numerical methods for fluid dynamics, Springer Berlin, Heidelberg, 1999. https://doi.org/10.1007/b79761
    [11] Z. Fu, Z. Tang, Q. Xi, Q. Liu, Y. Gu, F. Wang, Localized collocation schemes and their applications, Acta Mech. Sin., 38 (2022), 422167. https://doi.org/10.1007/s10409-022-22167-x doi: 10.1007/s10409-022-22167-x
    [12] Z. J. Fu, Z. Y. Xie, S. Y. Ji, C. C. Tsai, A. L. Li, Meshless generalized finite difference method for water wave interactions with multiple-bottom-seated-cylinder-array structures, Ocean Eng., 195 (2020), 106736. https://doi.org/10.1016/j.oceaneng.2019.106736 doi: 10.1016/j.oceaneng.2019.106736
    [13] A. R. Alharbi, M. B. Almatrafi, New exact and numerical solutions with their stability for Ito integro-differential equation via Riccati–Bernoulli sub-ODE method, J. Taibah Univ. Sci., 14 (2020), 1447–1456. https://doi.org/10.1080/16583655.2020.1827853 doi: 10.1080/16583655.2020.1827853
    [14] M. A. E. Abdelrahman, M. B. Almatrafi, A. Alharbi, Fundamental solutions for the coupled KdV system and its stability, Symmetry, 12 (2020), 429. https://doi.org/10.3390/sym12030429 doi: 10.3390/sym12030429
    [15] M. A. E. Abdelrahman, A. Alharbi, Analytical and numerical investigations of the modified Camassa-Holm equation, Pramana-J. Phys., 95 (2021), 117. https://doi.org/10.1007/s12043-021-02153-6 doi: 10.1007/s12043-021-02153-6
    [16] K. Mohamed, Simulation numérique en volume finis, de problémes d'écoulements multidimensionnels raides, par un schéma de flux á deux pas, Doctoral dissertation, Université Paris-Nord-Paris XIII, 2005.
    [17] K. Mohamed, M. Seaid, M. Zahri, A finite volume method for scalar conservation laws with stochastic time-space dependent flux function, J. Comput. Appl. Math., 237 (2013), 614–632. https://doi.org/10.1016/j.cam.2012.07.014 doi: 10.1016/j.cam.2012.07.014
    [18] F. Benkhaldoun, K. Mohamed, M. Seaid, A generalized Rusanov method for Saint-Venant equations with variable horizontal density, In: J. Foõt, J. Fürst, J. Halama, R. Herbin, F. Hubert, Finite volumes for complex applications VI problems & perspectives, Springer Proceedings in Mathematics, Springer, Berlin, Heidelberg, 4 (2011), 89–96. https://doi.org/10.1007/978-3-642-20671-9_10
    [19] K. Mohamed, F. Benkhaldoun, A modified Rusanov scheme for shallow water equations with topography and two phase flows, Eur. Phys. J. Plus, 131 (2016), 207. https://doi.org/10.1140/epjp/i2016-16207-3 doi: 10.1140/epjp/i2016-16207-3
    [20] K. Mohamed, H. A. Alkhidhr, M. A. E. Abdelrahman, The NHRS scheme for the Chaplygin gas model in one and two dimensions, AIMS Math., 7 (2022), 17785–17801. https://doi.org/10.3934/math.2022979 doi: 10.3934/math.2022979
    [21] K. Mohamed, M. A. E. Abdelrahman, The NHRS scheme for the two models of traffic flow, Comp. Appl. Math., 42 (2023), 53. https://doi.org/10.1007/s40314-022-02172-y doi: 10.1007/s40314-022-02172-y
    [22] K. Mohamed, S. Sahmim, M. A. E. Abdelrahman, A Predictor-corrector scheme for simulation of two-phase granular flows over a moved bed with a variable topography, Eur. J. Mech.-B/Fluids, 96 (2022), 39–50. https://doi.org/10.1016/j.euromechflu.2022.07.001 doi: 10.1016/j.euromechflu.2022.07.001
    [23] M. Dumbser, D. S. Balsara, A new efficient formulation of the HLLM Riemann solver for general conservative and non-conservative hyperbolic systems, J. Comput. Phys., 304 (2016), 275–319. https://doi.org/10.1016/j.jcp.2015.10.014 doi: 10.1016/j.jcp.2015.10.014
    [24] R. J. LeVeque, Balancing source terms and flux gradients in high-resolution godynov methods: the quasi-steady wave propagation algorithm, J. Comput. Phys., 146 (1998), 346–365. https://doi.org/10.1006/jcph.1998.6058 doi: 10.1006/jcph.1998.6058
    [25] L. Gosse, A well-balanced scheme using non-conservative products designed for hyperbolic systems of conservation laws with source terms, Math. Models Methods Appl. Sci., 11 (2001), 339–365. https://doi.org/10.1142/S021820250100088X doi: 10.1142/S021820250100088X
    [26] A. Bermudez, M. E. Vazquez, Upwind methods for hyperbolic conservation laws with source term, Comput. Fluids, 23 (1994), 1049–1071. https://doi.org/10.1016/0045-7930(94)90004-3 doi: 10.1016/0045-7930(94)90004-3
  • This article has been cited by:

    1. C. L. Frota, M. A. Jorge Silva, S. B. Pinheiro, A time-fractional superdiffusion wave-like equation with subdiffusion possibly damping term: well-posedness and Mittag-Leffler stability, 2024, 27, 1311-0454, 1236, 10.1007/s13540-024-00249-5
    2. Jamilu Hashim Hassan, Nasser-eddine Tatar, Banan Al-Homidan, Mittag-Leffler stability and Lyapunov stability for a problem arising in porous media, 2024, 27, 1311-0454, 2397, 10.1007/s13540-024-00299-9
    3. Mohammed D. Kassim, Mittag-Le­ffler stability for a one-dimensional fractional elastic-porous system: nonstandard frictional damping and nonstandard Kelvin-Voigt damping, 2025, 43, 0037-8712, 10.5269/bspm.75198
    4. Adel M. Al‐Mahdi, Mohammad M. Al‐Gharabli, Mohammed D. Kassim, Nasser‐eddine Tatar, Mittag–Leffler stability for a fractional swelling soil problem, 2025, 1561-8625, 10.1002/asjc.3710
  • Reader Comments
  • © 2023 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(2046) PDF downloads(185) Cited by(3)

Figures and Tables

Figures(20)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog