Return to Article Details Laurent operator-based representation of discrete solutions in the Newmark scheme with non-homogeneous terms

Laurent Operator-Based Representation
of Discrete Solutions in the Newmark Scheme
with Non-Homogeneous Terms

Eliass Zafati
(Date: May 10, 2025; accepted: September 15, 2025; published online: September 19, 2025.)
Abstract.

This paper investigates representation results for second-order evolution equations arising in structural dynamics, discretized using the Newmark time integration scheme. More precisely, the discrete solution is expressed in terms of bi-infinite Toeplitz or Laurent operators. A spectral analysis of the associated discrete operators is discussed, and a convergence analysis is performed under relaxed regularity assumptions on the source term. Furthermore, we examine the errors introduced by some truncation strategies, including one that is commonly used in engineering practice.

Key words and phrases:
Newmark time scheme, Laurent operator, spectral analysis, convergence and error estimates
2005 Mathematics Subject Classification:
47B35, 47A10, 65L06
EDF R&D ERMES, 7 boulevard Gaspard Monge, 91120, Palaiseau, France, e-mail: eliass.zafati@edf.fr, orcid.org/0000-0002-5927-6525.

1. Introduction

It is well-known that the time integration schemes play a central role in the numerical simulation of several problems in solid mechanics. The accurate time evolution of mechanical systems subject to transient loads, vibrations, or dynamic interactions is essential in a wide range of engineering applications, including aerospace, civil infrastructure, and mechanical design. The challenge lies in developing numerical methods that are not only robust and computationally efficient but also capable of accurately capturing the dynamic response of complex structures over long time intervals.

In this paper, we focus on a fundamental problem in structural dynamics. Specifically, we consider the second-order system of differential equations given by:

(1.4) {M𝒰¨+C𝒰˙+K𝒰=Fesslimt𝒰(t)=0esslimt𝒰˙(t)=0

where the vector-valued functions t𝒰¨(t), t𝒰˙(t), and t𝒰(t) represent the n-dimensional acceleration, velocity, and displacement vectors, respectively, with the dot symbol denoting the time derivative. The function tF(t) represents the external force. The matrices M, K, and C are symmetric and positive definite. In this setting, let ω12,,ωn2>0 be the real, positive eigenvalues (possibly repeated) of M1K, arranged in non-increasing order. It is known that the eigenvectors of M1K are orthogonal with respect to the Hermitian product induced by M, i.e., ,M. Concerning the matrix C, we assume that the positive eigenvalues M1C are written as 2ξ1ω1,,2ξnωn, where ξ1,ξ2,,ξn>0.

Furthermore, the following assumptions are implicitly considered in the subsequent sections:

(H1):

  1. i)

    The function tF(t) is Lebesgue-measurable on and satisfies

    esslimtF(t)=0.
  2. ii)

    For every integer 1in, the eigenspaces associated with the eigenvalues ωi2 and 2ξiωi coincide. In other words, there exist orthogonal projections 𝒫i, 1in, with respect to the product ,M such that:

    (1.5) M=i=1nM𝒫i,K=i=1nωi2M𝒫i,andC=i=1n2ξiωiM𝒫i.

Over the decades, numerous time integration methods have been proposed to solve numerically (1.4), each developped to specific modeling goals, such as energy conservation, high-frequency damping, unconditional stability, or second-order accuracy. Classical schemes such as the Newmark family [15], the Wilson-θ method [1], the Hilber–Hughes–Taylor (HHT-α) method [13] and the generalized-α method [7] have been widely adopted in industrial codes due to their simplicity and effectivenessw. Furthermore, these time integration schemes have also served as building blocks for multi-time-step methods, which allow different parts of a structure or different physical subdomains to be integrated using different time resolutions [8, 12, 16, 17, 18, 4, 5].

Although it is one of the earliest time integration schemes developed for structural analysis, the Newmark family of methods remains among the most widely used techniques for solving second-order differential systems in structural dynamics, such as the system described in (1.4). Introduced by Newmark in the 1950s [15], this class of methods encompasses both explicit and implicit variants, with two parameters that offer control over numerical dissipation and stability. Most accuracy analyses in the literature have been conducted under the assumption of smooth (at leat two differentiable) or vanishing nonhomogeneous terms [6, 10, 2]. The method’s adaptability, stability properties, and reliable performance continue to justify its widespread adoption in modern commercial solvers.

This paper aims to provide new representation results for the discrete solution in terms of Laurent operators (or bi-infinite Toeplitz operators). These representations allow us to derive some spectral properties of the associated operators, along with convergence results under relaxed smoothness assumptions on the source term F in (1.4). Furthermore, we analyze the errors introduced by two truncation procedures, one of which is commonly employed in engineering applications.

The rest of the paper is organized as follows. Section 2 reviews the Newmark scheme in the form of a block matrix formulation. Section 3 presents the representation of the discrete solution using Laurent operators and discusses related spectral properties, convergence results, and some truncation errors.

2. Review on the matrix formulation of the Discretized Equation

In this section, we present the matrix formulation of the discretized equation associated with (1.4), together with the main assumptions on the Newmark parameters and classical results that play a key role in the analysis developed in the subsequent sections.

To begin, we choose a time step h, such that the approximate solution of (1.4) is described at discrete time instances tl=lh, where l is an integer, i.e., l. Furthermore, let 𝒰¨l, 𝒰˙l, 𝒰l, and Fl denote the acceleration, velocity, displacement, and external force, respectively, at time tl=lh.

In this paper, Fl is considered an approximation of F(lh) and does not necessarily coincide with its exact value. For a fixed l, the discretized equation at the time tl writes:

(2.1) M𝒰¨l+C𝒰˙l+K𝒰l=Fl

The approximated quantities 𝒰l and 𝒰˙l, computed using the Newmark scheme with parameters γ and β, are given by:

(2.2) {𝒰l=𝒰l1+h𝒰˙l1+h2(12β)𝒰¨l1+h2β𝒰¨l,𝒰˙l=𝒰˙l1+h(1γ)𝒰¨l1+hγ𝒰¨l.

Furthermore, the discrete sequences (𝒰l)l and (𝒰˙l)l should satisfy the decay condition:

(2.3) liml𝒰l=0,liml𝒰˙l=0.

It is more convenient to rewrite the previous time discretized equations in a block matrix representation between two times tk and tj (with <k<j) as:

(2.4) [𝕄𝕄....𝕄][𝕌k𝕌k+1..𝕌j]=[k𝕌k1k+1..j]

where we have:

(2.5) 𝕄=[MCKγhInIn0βh2In0In],=[000(1γ)hInIn0(12β)h2InhInIn]l=[Fl00],𝕌l=[𝒰¨l𝒰˙l𝒰l]

For every klj. Here, the matrix In stands for the n×n-identity matrix.

We consider the following assumption (𝐇𝟐): The Newmark parameters (γ,β,h) satisfy:

  1. i)

    γ12.

  2. ii)

    h>0.

  3. iii)

    M~=M+h2(βγ2)K is positive definite.

  4. iv)

    The inequality

    (2.6) (γ+12)24β<min1in[4(1ξi2)ωi2h2+2ξiωih(2γ1)]

    is commonly used in practice for physical purposes (see, for instance, Section 7.2.7 in [10]). In addition, we assume 0<ξi<1.

Throughout the remainder of this paper, assumptions (𝐇𝟏) and (𝐇𝟐) are considered to be satisfied, even if not explicitly mentioned and the time step belongs to the set for which the above assumption holds. The following results are easy to establish by arguments similar to those in [19] and [20].

Lemma 2.1.

Let 𝒟={z|z|<1}. The spectrum of 𝕄1 is a subset of 𝒟. More precisely, the spectrum is given by:

(2.7) {0,z1,z¯1,,zn,z¯n}

For every 1in, the real and imaginary parts of zi are given by:

(2.8) {(zi)=12((γi+12)Ωi21+βiΩi22),(zi)=124Ωi21+βiΩi2(Ωi21+βiΩi2)2(γi+12)2.

where (z) and (z) denote the real and imaginary parts of a complex number z, and Ωi=hωi.

Additionally, the modified parameters γi and βi are defined as:

(2.9) γi=γ+2ξiΩi,andβi=β+2γξiΩi.

In this case, the magnitude of zi is given by:

(2.10) |zi|=1(γi12)Ωi21+βiΩi2.

Remark 2.2.

If we define the resolvent of 𝕄1 as

(2.11) (z)=(zI3n𝕄1)1=𝕄(z𝕄)1

where z and I3n is the 3n×3n-identity matrix, it can be observed that (z) is well-defined on 𝒟 under the hypothesis of Lemma 2.1.

Lemma 2.3.

If (z𝕄)1 is written as 3×3 block matrix where each entry is a n×n-matrix. Let [X11(z)X21(z)X31(z)]𝖳 be the first column of the previous matrix, then:

(2.15) {X11(z)=(1+z)2zQ1(z)X21(z)=h(1+z)(γ(1+z)1)zQ1(z)X31(z)=h2β(1+z)2(1+z)(γ+12)+1zQ1(z)

where:

(2.16) Q(z)=(1+z)2M+h2(β(1+z)2(γ+12)(1+z)+1)K+h(γ(1+z)2(1+z))C

Remark 2.4.

Using the decomposition (1.5), one can verify that:

(2.17) Q(z)=i=1nΛi(Ωi)(zzi)(zz¯i)M𝒫i,

where we define

(2.18) Λi(Ωi):=1+βiΩi2.

3. Laurent Operators and Representation Results for the Newmark Scheme

This section focuses on the representation of various quantities in (1.4) in terms of Laurent operators, as well as the behavior of the error when dealing with less regular nonhomogeneous terms compared to those studied in the literature. To begin, we introduce the following classical definitions:

Definition 3.1.

Let p1 and k be a positive integer, let U be an open set, and let 𝕂 be either or . We define the following spaces along with their associated norms:

  • C0(U,𝕂k): The space of continuous functions from U to 𝕂k, equipped with the supremum norm:

    fC0=suptUf(t).
  • Lp(U,𝕂k): The space of p-integrable functions from U to 𝕂k, i.e.,

    Lp(U,𝕂k)={{f:U𝕂k:Uf(t)p𝑑t<},1p<,{f:U𝕂k:esssuptUf(t)<},p=.

    The associated norm is:

    fLp={(Uf(t)p𝑑t)1p,1p<,esssuptUf(t),p=.
  • For sequence spaces, we define:

    lp(𝕂k)={{(Xl)l𝕂k:lXlp<},1p<,{(Xl)l𝕂k:suplXl<},p=.

    The corresponding norm for X=(Xl)l is:

    Xlp={(lXlp)1p,1p<,suplXl,p=.

    We also define the space c0(𝕂k), consisting of all sequences in l(𝕂k) that converge to zero at :

    c0(𝕂k)={(Xl)ll(𝕂k):limlXl=0},

Remark 3.2.

In the preceding Definition 3.1, the norm notations are written without explicit reference to the index k or the domain U for the sake of simplicity; their precise meaning should be inferred from the context.

Definition 3.3.

Let aL((πh,πh),) and 0<p. The Laurent operator (or bi-infinite Toeplitz operator ) T(a) on lp(n) is defined as follows: for every sequence X~=(,X1,X0,X1,)lp(n),

(3.1) (T(a)X~)m=l=cml(a)Xl,for all m,

where (cl(a))l are the Fourier coefficients of the function a, defined by:

(3.2) cl(a)=h2ππhπha(t)eiclht𝑑t,for all l.

where ic is the imaginary unit. ∎

When 1p2, it follows that the operator T(a) is bounded as a consequence of the Riesz-Thorin interpolation theorem (see, for instance, Theorem 1.3.4 in [11]).

Definition 3.4.

Let k>0 be an integer and X~=(X) be a sequence of elements in k. We define the following operators:

  1. (i)

    Discrete Fourier Transform: The operator 𝔉h on l2(k) is given by

    (3.3) 𝔉hX~(θ)==Xeichθ,θ[πh,πh].
  2. (ii)

    Piecewise Constant Interpolation: The interpolation operator h is defined by

    (3.4) hX~(t)==Xχ[h,(+1)h)(t),

    where χ[h,(+1)h)(t) is the characteristic function of the interval [h,(+1)h).

Remark 3.5.

Let 𝕂= or , and r>1. It is straightforward to show that the operator h is continuous from lr(𝕂n) into Lr(,𝕂n). Moreover, its adjoint operator h is given by:

hX=(lh(l+1)hX(s)𝑑s)l,for XLr(,𝕂n),

and we have:

(3.5) h(lr(𝕂n),Lr(,𝕂n))=h(Lr(,𝕂n),lr(𝕂n))=h1r=hr1r

where 1r+1r=1. ∎

We are now in a position to state the main result concerning the representation of the discrete solution in terms of Laurent operators. This will be followed by a series of corollaries presenting some convergence results and analyzing the errors introduced by some truncation procedures.

Theorem 3.6.

Assume that (F)c0(n). Let w𝒟 with w0. Define the functions:

gwu(θ) =βh2+=1h2[(1)w1(β(1+w)2(1+w)(γ+12)+1)]weichθ,
(3.6) gwv(θ) =γh+=1h[(1)w1(1+w)(γ(1+w)1)]weichθ,
gwa(θ) =1+=1[(1)w1(1+w)2]weichθ.

Each of these series defines an uniformly convergent function. Moreover, we have:

(3.7) {𝒰~=i=1n1Λi(Ωi)T(gziu)𝒫iM1F~,𝒰˙~=i=1n1Λi(Ωi)T(gziv)𝒫iM1F~,𝒰¨~=i=1n1Λi(Ωi)T(gzia)𝒫iM1F~,

where Λi(Ωi) is defined in (2.18), and the notations are as follows:

𝒰~=(𝒰),𝒰˙~=(𝒰˙),𝒰¨~=(𝒰¨),M1F~=(M1F),

and, for any 1in and any bi-infinite sequence X~=(X),

(3.8) 𝒫iX~:=(𝒫iX).

In the proof of Theorem 3.6, we need the following lemma:

Lemma 3.7.

Under the assumptions of Theorem 3.6, the discrete block solution (𝕌m)m, defined in (2.5), is given for all m by:

(3.9) 𝕌m=l=m(1)ml𝕄1(𝕄1)mll.

Proof.

First, observe that the right-hand side of (3.9) is well defined. Indeed, by Eq. 2.8, the eigenvalues of the matrix 𝕄1 lie strictly inside the unit disk, and the sequence (F) is bounded.

It is straightforward to verify that the constructed solution satisfies the recurrence relation

𝕄𝕌m+𝕌m1=m,for all m,

as well as the decay condition (2.3). By the uniqueness of the discrete solution, the result follows. ∎

Proof of Theorem 3.6.

Let ϵ>0. We introduce a small perturbation by replacing the sequence (F) with the exponentially damped sequence (Fϵ), defined by

Fϵ=eϵ2F,.

We denote by ϵ and 𝕌ϵ the perturbed block vectors corresponding to the discrete data and the discrete solution, respectively, as defined in (2.5):

(3.10) ϵ =[Fϵ00],𝕌ϵ=[𝒰¨ϵ𝒰˙ϵ𝒰ϵ].

and from (3.9), we have for every m:

(3.11) 𝕌mϵ=l=m(1)ml𝕄1(𝕄1)mllϵ.

Since the eigenvalues of the matrix 𝕄1 lie strictly inside the unit disk, we conclude that

limϵ0𝕌mϵ=𝕌m,m.

Let ~ϵ=(lϵ)l. Using the Dunford–Taylor integral representation [14] and the definition of the resolvent in Remark 2.2, we can express 𝕌mϵ for every integer m as:

(3.12) 𝕌mϵ =l=m(1)ml𝕄1(𝕄1)mllϵ
=h2ππhπheicmhθl=m(1)ml𝕄1(𝕄1)mleic(ml)hθ𝔉h~ϵ(θ)dθ
=h(2π)2icπhπheicmhθ[𝒞(l=0(1)leiclhθzl)(z𝕄)1𝑑z]𝔉h~ϵ(θ)𝑑θ

where 𝒞 is a positively oriented circle of radius strictly less than one, whose interior contains all the roots zi described in (2.8). Hence, by applying Lemma 2.3 and using the definition of the resolvent in Remark 2.2, we obtain:

(3.13) {𝒰mϵ=h(2π)2icπhπheicmhθ[𝒞X13(z)1+eichθz𝑑z]𝔉hF~ϵ(θ)𝑑θ,𝒰˙mϵ=h(2π)2icπhπheicmhθ[𝒞X12(z)1+eichθz𝑑z]𝔉hF~ϵ(θ)𝑑θ,𝒰¨mϵ=h(2π)2icπhπheicmhθ[𝒞X11(z)1+eichθz𝑑z]𝔉hF~ϵ(θ)𝑑θ

A direct application of the residue theorem, combined with the identity (2.17), yields the desired result for the sequence (Fϵ). Taking the limit as ϵ0, we obtain the corresponding result for (F), since the series c(gzir) converges absolutely. Here, c(gzir) denotes the Fourier coefficients of the uniformly convergent functions gzir, with r{u,v,a}.

By extending the definition of the operator 𝒫i to the space l2(n) as given in (3.8), the following result follows from Theorem 3.6:

Corollary 3.8.

We have the following:

  1. (i)

    For every r{u,v,a}, consider the operator

    𝒯r:=i=1n1Λi(Ωi)T(gzir)𝒫i

    acting on the Hilbert space l2(n), equipped with the Hermitian inner product

    X~,Y~h:=X,MYn,for X~=(X),Y~=(Y)l2(n).

    Then, the spectrum of 𝒯r is given by

    (3.14) σ(𝒯r)=i=1n1Λi(Ωi)gzir([πh,πh]).
  2. (ii)

    The operator 𝒯r defines a bijection from l2(n) onto the following spaces:

    (3.15) {l2(n),if r=u,{(Xm)ml2(n):Xm=llm(1)mlmlYl,(Yl)ll2(n)},if r=v,{(Xm)ml2(n):Xm=π26Ym+llm(1)ml(ml)2Yl,(Yl)ll2(n)},if r=a.

    This holds under the condition γ>12. Moreover, if γ=12 and β<14, the operator defines a bijection from l2(n) onto:

    (3.16) {l2(n),if r=u,{(Xm)ml2(n):Xm=llm(1)ml(ml)3Yl,(Yl)ll2(n)},if r=v,{(Xm)ml2(n):Xm=π26Ym+llm(1)ml(ml)2Yl,(Yl)ll2(n)},if r=a.

Proof of Corollary 3.8.

For a fixed r{u,v,a}, observe that for each 1in, the operator 𝒯r is stable on the subspace

Ran(1Λi(Ωi)T(gzir)𝒫i),

since the 𝒫i’s are orthogonal projections in the sense of (3.8), with respect to the Hermitian inner product defined in the present lemma. It is clear that the restriction of 𝒯r to this subspace coincides with 1Λi(Ωi)T(gzir)𝒫i.

Therefore, by applying Lemma 1 (I.128) from Bourbaki [3], we deduce:

σ(𝒯r)=i=1nσ(1Λi(Ωi)T(gzir)𝒫i).

Moreover, the operator 1Λi(Ωi)T(gzir)𝒫i, when restricted to its range, is unitarily equivalent to the multiplication operator

Mgzir/Λi(Ωi):f1Λi(Ωi)gzirf,

acting on the Hilbert space

L2((πh,πh);Ran(𝒫i)).

Following the arguments in [9], and using the fact that gzir is continuous on the interval [πh,πh], we conclude that the spectrum of Mgzir/Λi(Ωi) is given by

σ(Mgzir/Λi(Ωi))={1Λi(Ωi)gzir(θ)|θ[πh,πh]}.

This yields the desired spectral characterization and concludes the proof of the first assertion.

The second statement is proved as follows: We focus only on (3.15), since (3.16) can be established by analogy. Replacing (𝒰¨l)l, (𝒰˙l)l, (𝒰l)l, and (Fl)l by X~=(Xl)l, Y~=(Yl)l, Z~=(Zl)l, and W~=(Wl)l, respectively, where all these sequences belong to l2(n), in (2.1) and (2.2), we obtain, by applying the discrete Fourier transform 𝔉h:

(3.17) {M𝔉hX~(θ)+C𝔉hY~(θ)+K𝔉hZ~(θ)=𝔉hW~(θ),(1eichθ)𝔉hZ~(θ)=heichθ𝔉hY~(θ)+h2(β+(12β)eichθ)𝔉hX~(θ),(1eichθ)𝔉hY~(θ)=h((1γ)eichθ+γ)𝔉hX~(θ).

Given that 𝔉h is an isomorphism between l2(n) and L2((πh,πh),n), it follows from (3.17) that the operator 𝒯r is injective for r{u,v,a}. Moreover, we can easily verify that 𝔉hZ~, 𝔉hY~, and 𝔉hX~ belong to the function spaces

L2((πh,πh),n),
{θffL2((πh,πh),n)},

and

{θ2ffL2((πh,πh),n)},

respectively. One can notice by computing the Fourier coefficients that the premiage of the previous spaces by 𝔉h are given by (3.15). The surjectivity is a consequence of the assumption γ>12, (3.17) and the fact that 𝔉h is an isomorphism.

In the case of (3.16), one can verify that 𝔉hZ~, 𝔉hY~, and 𝔉hX~ belong to the following function spaces:

L2((πh,πh),n),
{(π2h2θ2)θf|fL2((πh,πh),n)},

and

{θ2f|fL2((πh,πh),n)}.

This concludes the proof. ∎

Remark 3.9.

In Corollary 3.8, the spectrum σ(𝒯r) provides, from a physical point of view, essential information about the system’s behavior in the frequency domain for each mode. Specifically, it describes how the system amplifies or attenuates various frequency components (gain) and introduces corresponding phase shifts, all within the discrete framework. Moreover, analyzing the Fourier coefficients in (3.6) offers insight into which frequencies contribute most significantly to the spectrum.

It follows from Corollary 3.8 that if γ>12 or γ=12 with β<14, then 𝒯u is an isomorphism, and we have 0𝒯u. Moreover, the spaces in (3.15) and (3.16) associated with the operators 𝒯v and 𝒯a are not closed in l2(n).

In [6], a discretization error was established for twice-differentiable functions F. The following result extends this analysis for positive coefficients ξi to the cases of bounded continuous functions and integrable functions.

Corollary 3.10.

With the same notations as in Theorem 3.6, we claim the following:

  1. i.

    If FC0(,n) is bounded and FlF([lh,(l+1)h]), then there exists h0>0 such that for every 0<hh0 and for every x,y with y>x, we have:

    (3.18) h𝒰~(y)i=1n(Gi𝒫iM1F)(y)+h𝒰˙~(y)i=1nddt(Gi𝒫iM1F)(y)
    +h𝒰¨~(y)i=1nd2dt2(Gi𝒫iM1F)(y)
    [max1ineξiωi(yx)supsx+hF(s)+hFL+ψF,[xh,y+h](h)].

    where:

    • is independent of h, F, x, and y.

    • The function hψF,[x,y](h) denotes the modulus of continuity of F over [x,y].

    • The convolution product Gi𝒫iM1F is defined as:

      Gi𝒫iM1F(t)=1ωditexp(ξiωi(ts))sin(ωdi(ts))𝒫iM1F(s)𝑑s

      where the kernel Gi is given by:

      Gi(t)=1ωdiexp(ξiωit)sin(ωdit)χ+(t),

      and ωdi=ωi1ξi2 is the damped natural frequency.

  2. ii.

    If FLp(,n), with 1<p2, and

    Fl=1hlh(l+1)hF(s)𝑑s,l,

    then, as h0, we have the following convergences:

    (3.19) h𝒰~ i=1nGi𝒫iM1F in Lp(,n)
    h𝒰˙~ i=1nddt(Gi𝒫iM1F) in Lp(,n)+Lp(,n)
    h𝒰¨~ i=1nd2dt2(Gi𝒫iM1F) in Lp(,n)+Lp(,n)

    with 1=1p+1p.

Proof.

i- We restrict ourselves to the case h𝒰~, as the remaining cases can be treated analogously. Let 0<ϵ<1 and >0 an arbitrary constant independent of h, F, x, and y but may depends on ϵ. Moreover, we choose h0 sufficently small such that:

(3.20) |1Λi(Ωi)1|ϵ,for all 1in and 0<h<h0

It suffices to prove that the inequality (3.18) holds on the subspace Ran(𝒫i) for each 1in, assuming that h satisfies (3.20). More precisely, our goal is to establish the following estimate:

(3.21) 1Λi(Ωi)h(T(gziu)𝒫iM1F~)(y)(Gi𝒫iM1F)(y)
[eξiωi(yx)supsx+hF(s)+hFL+ψF,[xh,y+h](h)]

To simplify the presentation, we assume without loss of generality that 𝒫iM1F=F. Furthermore, we use the notation f(h)=𝒪(hr), with r0, to indicate that |f(h)||hr| for all hh0, where h0 is sufficiently small. We also define the sequence 𝐜=(cl)l by:

(3.22) cl=1Λi(Ωi)h2ππhπhgziu(t)eiclht𝑑t,for all l.

Let m be a positive integer such that mhy<mh+h. First, we have:

(3.23) {1+zi=𝒪(h),h(zi)=1ωdi+𝒪(h)1Λi(Ωi)=1+𝒪(h)

Thus,

(3.24) 1Λi(Ωi)h(zi)[β(1+zi)2(1+zi)(γ+12)+1]1ωdi=𝒪(h).

Moreover, taking into account (2.8) and (2.10), we have for every l:

(3.25) ((zi)l)exp(ξiωilh)sin(ωdilh)
=[exp(l2ln(1(γi12)Ωi2Λi(Ωi)))exp(ξiωilh)](exp(iclarg(zi)))
+exp(ξiωilh)[(exp(iclarg(zi)))sin(ωdilh)].

By the mean value theorem, there exists t[0,1] such that

(3.26) |exp(l2ln(1(γi12)Ωi2Λi(Ωi)))exp(ξiωilh)|
exp(αtl)|l2ln(1(γi12)Ωi2Λi(Ωi))ξiωilh|,

where

(3.27) αt=t(12ln(1(γi12)Ωi2Λi(Ωi)))+(1t)ξiωih.

Since γ12 and taking into account (3.20), we have:

(3.28) {αt(1ϵ)ξiωih,exp(αtl)exp((1ϵ)ξiωilh)

Using the expression (2.8) and the Taylor expansion, we obtain:

(3.29) {|l2ln(1(γi12)Ωi2Λi(Ωi))ξiωilh|=l𝒪(h2),|(exp(iclarg(zi)))sin(ωdilh)|=l𝒪(h2).

The constants implicit in the 𝒪() notation in (3.29) are, of course, independent of l. Thus, using (3.25), (3.28) and (3.29):

(3.30) |((zi)l)exp(ξiωilh)sin(ωdilh)| exp((1ϵ)ξiωilh)lh2.

Since

l=m1h|(zi)ml|=𝒪(1),

combining (3.24) and (3.30), we obtain:

(3.31) l=mcmlFlhωdil=mexp(ξiωi(ml)h)sin(ωdi(ml)h)Fl
hFL

Moreover, it is not difficult to show, taking into account that |ys(ml)h|h for lhs<(l+1)h, and using the mean value theorem, that:

(3.32) hωdil=mexp(ξiωi(ml)h)sin(ωdi(ml)h)Fl
1ωdiyexp(ξiωi(ys))sin(ωdi(ys))hF~(s)dshFL.

and

(3.33) yexp(ξiωi(ys))sin(ωdi(ys))[hF~(s)F(s)]𝑑s
(ψF,[xh,y+h](h)+exp(ξiωi(yx))supsx+hF(s)).

Here, F~=(F). Thus, we obtain the desired result for the first claim.

ii- Let p denote the conjugate exponent of p, i.e., such that 1p+1p=1. We focus on the first case related to h𝒰~, and we only need to prove that

h(T(gziu)𝒫iM1F~)Gi𝒫iM1F

in Lp(,n), for a fixed 1in, since Λi(Ωi)1 as h0. For this purpose and without loss of generality, we assume 𝒫iM1F=F for simplicity.

First, observe that hF~F in Lp(,n), where F~=(F). Indeed, one can check that hF~ is uniformly bounded with respect to h in Lp(,n), with

hF~LpFLp.

More precisely, using (3.5), we have

(3.34) hF~Lp =1hhhFLp
1hh(lp(n),Lp(,n))h(Lp(,n),lp(n))FLp
FLp.

Moreover, the convergence holds for functions in C0(,n) with compact support. By density of this space in Lp(,n) and by the contractivity property in (3.34), we deduce the desired result.

Let Gih be the piecewise constant kernel defined by

Gih(t)=Gi(lh)for lht<(l+1)h,l,

Define also the function hiu by

(3.35) hiu(θ)=l=1hGih(lh)eiclhθ,

Taking into account the fact that Gi(0)=0, we write:

(3.36) hT(gziu)F~GihF~= hT(gziu)F~GihhF~+GihhF~GihF~
= h(T(gziu)T(hiu))1hhF+
(GihGi)(h1hh)F

Moreover, the operators h(T(gziu)T(hiu))1hhand(GihGi)(h1hh) are well defined on L1(,n) and L2(,n). Furthermore, we have the following estimates:

For every XL1(,n), we have:

h(T(gziu)T(hiu))1hhXL supl|1hclGih(lh)|XL1,
(GihGi)(h1hh)XL GihGiLXL1.

For every XL2(,n), we have:

h(T(gziu)T(hiu))1hhXL2 gziuhiuLXL2,
(GihGi)(h1hh)XL2 𝔉Gih𝔉GiLXL2,

where 𝔉 denotes the Fourier transform.

As a consequence, using the Riesz–Thorin interpolation theorem, we obtain the following estimate:

hT(gziu)F~GihF~Lp (supl|1hclGih(lh)|2p1gziuhiuL2(11p)
(3.37) +GihGiL2p1𝔉Gih𝔉GiL2(11p))FLp

It is not difficult to show, using the asymptotic expansion as h0 and following similar arguments as in the previous case, that the right-hand side of (3) tends to zero. Moreover, applying once again the Riesz–Thorin interpolation theorem on XGiX, we deduce that

GihF~GiFinLp(,n),

taking into account the convergence hF~F in Lp(,n) established above. Thus, we have hT(gziu)F~GiF in Lp(,n)

In the case of h𝒰˙~, we prove, as in the previous case, that:

h(T(gziv)F~)ddt(GiF)

in Lp(,n)+Lp(,n).

Taking as before the following notations:

G˙ih(t)=ddtGi(mh)for mht<(m+1)h,m,

and

(3.38) hiv(θ)=l=1hG˙ih(lh)eiclhθ,

It is sufficient to observe that (ddtGi)F=ddt(GiF) almost everywhere. In particular, at every t, we have:

(3.39) hT(gziv)F~(t)(ddtGi)hF~(t) =h(T(gziv)T(hiv))1hhF(t)
+(G˙ihddtGi)(h1hh)F(t)
(tthh)G˙ih(0)h1hhF(t)

where th denotes the integer part of th. As in the previous case, the first two terms on the right-hand side of (3.39) tend to zero in Lp(,n).

Denoting the last term on the right-hand side of (3.39) by the map Eh(t), we obtain:

(3.40) (ddtGi)hF~Eh(ddtGi)F

In Lp(,n)+Lp(,n), since Eh0 in Lp(,n) and (ddtGi)hF~(ddtGi)F in Lp(,n). Thus, we conclude the desired convergence result.

The final case, concerning h𝒰¨~, can be handled analogously, with only minor modifications. It suffices to observe that, at every Lebesgue point t of the map F, the identity

(d2dt2Gi)F(t)+ddtGi(0)F(t)=d2dt2(GiF)(t)

holds.

In many structural dynamics applications, a cut-off frequency is employed for modal truncation, allowing the solution to be computed in the subspace generated by the projection operators {𝒫1,,𝒫q}, where 1qn.

The cut-off frequency is characterized by the existence of an integer q such that, for all iq, the approximation

ωi2Gi(𝒫iM1F)𝒫iM1F

holds in the asymptotic regime where ωi is sufficiently large.

This means that the contribution of higher modes becomes negligible, and the dynamics can be captured by the first q modes. Moreover, using the notation of Corollary 3.10 and assuming additionally that the weak derivative F˙L(,n), one can show that

𝒫iM1Fωi2Gi𝒫iM1FL1ωiξi1ξi2𝒫iM1F˙L.

The discretized version of the above inequality is given by the following:

Corollary 3.11.

Assume that FC0(,n), F˙L(,n) and FlF([lh,(l+1)h]). For a fixed 1in, we have the following estimate:

(3.41) 𝒫iM1F~ωi2Λi(Ωi)T(gziu)𝒫iM1F~lωiξig(Ωi)𝒫iM1F˙L

where:

(3.42) g(Ωi)=Λi(Ωi)Λi(Ωi)14Ωi2(γi+12)2

and depends only on γ and β. Recall that γi is given by (2.9).

Moreover, we have the asymptotic behavior:

(3.43) limΩi0g(Ωi)=11ξi2.

Proof.

Let be an arbitrary constant that depends only on γ and β and m, we put:

(3.44) cl=h2ππhπhgziu(t)eiclht𝑑t,for all l.

and for arbitrary integer q, <qm:

(3.45) Aq=ωi2l=qcml

Using Abel’s summation by parts, we obtain:

(3.46) ωi2l=mcml𝒫iM1Fl=Am𝒫iM1Fml=m1Al𝒫iM1(Fl+1Fl)

Using the expression (2.8) on can establish:

(3.47) Am=Λi(Ωi)

Moreover, taking into account that |zi|<1, we have for q<m:

(3.48) |Aq| =Ωi2|[(zi)mq1+zi(β(1+zi)2(1+zi)(γ+12)+1)](zi)|
Ωi2|(zi)||zi|mq|1+zi|
=(Λi(Ωi))32Λi(Ωi)14Ωi2(γi+12)2|zi|mq

Combining this with the fact that F˙L(,n) and using again that |zi|<1 with (2.10), we have for every l<m:

(3.49) {𝒫iM1Fl+1𝒫iM1Fl2h𝒫iM1F˙L=2Ωiωi𝒫iM1F˙LΩiq=m1|zi|mq=Ωi|zi|1|zi|(Λi(Ωi))12ξi

Combining equations (3.46), (3.47), (3.48), and (3.49), we obtain the desired result. This completes the proof.

The following corollary provides an explicit convergence rate for the truncated operator representation introduced in Theorem 3.6. It can be interpreted as the error introduced by considering only the N recent time steps.

Corollary 3.12.

With the notations of Theorem 3.6, assume that F~=(F)l2(n). Let N, and define the following truncated functions:

(3.50) {gw,Nu(θ)=βh2+l=1Nh2[(1)lwl1(β(1+w)2(1+w)(γ+12)+1)]weiclhθ,gw,Nv(θ)=γh+l=1Nh[(1)lwl1(1+w)(γ(1+w)1)]weiclhθgw,Na(θ)=1+l=1N[(1)lwl1(1+w)2]weiclhθ

Next, define the associated truncated sequences:

(3.51) {𝒰~N=i=1n1Λi(Ωi)T(gzi,Nu)𝒫iM1F~,𝒰˙~N=i=1n1Λi(Ωi)T(gzi,Nv)𝒫iM1F~,𝒰¨~N=i=1n1Λi(Ωi)T(gzi,Na)𝒫iM1F~.

Then, for every integer r>0, there exists a constant h0>0 such that for every 0<h<h0, the following estimate holds:

(3.52) 𝒰~N𝒰~l2+𝒰˙~N𝒰˙~l2+𝒰¨~N𝒰¨~l2LN+1(hN)rF~l2,

where LN denotes the Lebesgue constant (see Chapter II, Section 12 of [21] for its definition), and is a constant independent of h, N and F~ but depends on r. ∎

Proof.

Throughout this proof, let >0 be an arbitrary constant, independent of h, N and F~, but possibly depending on r. Since the projectors 𝒫i are orthogonal with respect to the inner product ,h introduced in Corollary 3.8, and since M is positive definite, we deduce, taking into account that 1Λi(Ωi)1, that:

(3.53) 𝒰~N𝒰~l2i=1ngziugzi,NuLF~l2.

Moreover, for each 1in, using inequality (13.25) from [21] and the fact that gziu is h-periodic, we obtain:

(3.54) gziugzi,NuLLN+1(hN)rdrdθrgziuL.

Furthermore, using the fact that γ12 and |zi|<1, we have:

drdθrgziuL h|(zi)|l=1(lh)rexp(ξiωi(l1)hΛi(Ωi))
(3.55) h|(zi)|exp(2ξiΩiΛi(Ωi))0srexp(ξiωisΛi(Ωi))𝑑s
(3.56) =h|(zi)|exp(2ξiΩiΛi(Ωi))[Λi(Ωi)ξiωi]rΓ(r)
(3.57) h|(zi)|exp(2ξiΩi)[Λi(Ωi)ξiωi]r

where rΓ(r) denotes the Gamma function.

In the other cases, i.e., when considering gziv or gzia, we use the following identity from (2.8):

|1+zi|=hωiΛi(Ωi).

and we obtain the following estimates:

(3.58) drdθrgzivL hωi|(zi)|exp(2ξiΩi)[Λi(Ωi)ξiωi]r,
(3.59) drdθrgziaL hωi2|(zi)|exp(2ξiΩi)[Λi(Ωi)ξiωi]r.

Thus we obtain:

(3.60) 𝒰~N𝒰~l2+𝒰˙~N𝒰˙~l2+𝒰¨~N𝒰¨~l2
(LN+1)(hN)r(i=1nh(1+ωi)2exp(2ξiΩi)|(zi)|[Λi(Ωi)ξiωi]r)F~l2,

Using the Taylor approximations in (3.23), we obtain the desired result for 0<h<h0, for some h0>0 satisfying the assumption (𝐇𝟐). ∎

4. Conclusions

In conclusion, this paper investigates some representation results for the discrete solutions of second-order evolution equations, discretized using the Newmark scheme, with the solutions expressed through bi-infinite Toeplitz or Laurent operators. This approach provides some insights into the spectral properties of the associated operators. Additionally, we establish convergence results under relaxed regularity assumptions, requiring only either continuous or integrable source terms. These results, although derived in the context of the Newmark scheme, can be adapted to other time discretization methods that preserve similar structural properties such the convolution-type recurrence relations.

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