Review Special Issues

Inaccurate polyester textile environmental product declarations

  • Received: 30 December 2021 Revised: 20 February 2022 Accepted: 01 March 2022 Published: 09 March 2022
  • Development of Environmental Product Declarations (EPD)s used for green marketing, specification, procurement, certification and green building rating systems are important for documenting and understanding product environmental performance. Considering such applications any misleading of stakeholders has serious legal ramifications. Various studies have highlighted EPD veracity depends mainly on the data quality of underpinning life cycle assessment (LCA). This paper compares data quality across polyester product case studies, literature surveys and EPDs. Life Cycle Inventory (LCI) and Life Cycle Impact Assessment (LCIA) results are presented and interpreted. Surveys show recycled polyester fibre results are most sensitive to melt spinning energy data which varies over a wide range. The case studies compare results from median, lower and upper energy use in melt spinning. The work highlights that, accurate, clear definitions and vocabulary is as vital for specific foreground process data as it is for generic background supply chain data. This is to avoid misconceptions and mismatched assumptions in respect of EPD data quality and incorrect acceptance of inadequate charting of all essential processes. If product-specific accurate data is inaccessible, EPD options include presenting impact assessment results from LCI of best and worst-case scenarios. This is preferable to legal risks of using junk data that misleads stakeholders in marketing. General recommendations are presented for LCA practitioners to improve EPD data quality and accuracy. These include using multiple data sources to avoid reliance on any single database. Data also needs to be verified by a third-party with industry expertise independent of the specific manufacturer. It recommends using suitable, comprehensive and specific product-related scenarios for data development in any EPD.

    Citation: Shadia Moazzem, Delwyn Jones, Mathilde Vlieg, Direshni Naiker. Inaccurate polyester textile environmental product declarations[J]. Clean Technologies and Recycling, 2022, 2(1): 47-63. doi: 10.3934/ctr.2022003

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  • Development of Environmental Product Declarations (EPD)s used for green marketing, specification, procurement, certification and green building rating systems are important for documenting and understanding product environmental performance. Considering such applications any misleading of stakeholders has serious legal ramifications. Various studies have highlighted EPD veracity depends mainly on the data quality of underpinning life cycle assessment (LCA). This paper compares data quality across polyester product case studies, literature surveys and EPDs. Life Cycle Inventory (LCI) and Life Cycle Impact Assessment (LCIA) results are presented and interpreted. Surveys show recycled polyester fibre results are most sensitive to melt spinning energy data which varies over a wide range. The case studies compare results from median, lower and upper energy use in melt spinning. The work highlights that, accurate, clear definitions and vocabulary is as vital for specific foreground process data as it is for generic background supply chain data. This is to avoid misconceptions and mismatched assumptions in respect of EPD data quality and incorrect acceptance of inadequate charting of all essential processes. If product-specific accurate data is inaccessible, EPD options include presenting impact assessment results from LCI of best and worst-case scenarios. This is preferable to legal risks of using junk data that misleads stakeholders in marketing. General recommendations are presented for LCA practitioners to improve EPD data quality and accuracy. These include using multiple data sources to avoid reliance on any single database. Data also needs to be verified by a third-party with industry expertise independent of the specific manufacturer. It recommends using suitable, comprehensive and specific product-related scenarios for data development in any EPD.



    The Sasa-Satsuma equation

    ut+uxxx+6|u|2ux+3u(|u|2)x=0, (1.1)

    so-called high-order nonlinear Schrödinger equation [1], is relevant to several physical phenomena, for example, in optical fibers [2,3], in deep water waves [4] and generally in dispersive nonlinear media [5]. Because this equation describes these important nonlinear phenomena, it has received considerable attention and extensive research. The Sasa-Satsuma equation has been discussed by means of various approaches such as the inverse scattering transform [1], the Riemann-Hilbert method [6], the Hirota bilinear method [7], the Darboux transformation [8], and others [9,10,11]. The initial-boundary value problem for the Sasa-Satsuma equation on a finite interval was studied by the Fokas method [12], which is also effective for the initial-boundary value problems on the half-line [35,36,37]. In Ref. [13], finite genus solutions of the coupled Sasa-Satsuma hierarchy are obtained in the basis of the theory of trigonal curves, the Baker-Akhiezer function and the meromorphic functions [14,15,16]. In Ref. [17], the super Sasa-Satsuma hierarchy associated with the 3×3 matrix spectral problem was proposed, and its bi-Hamiltonian structures were derived with the aid of the super trace identity.

    The nonlinear steepest descent method [18], also called Deift-Zhou method, for oscillatory Riemann-Hilbert problems is a powerful tool to study the long-time asymptotic behavior of the solution for the soliton equation, by which the long-time asymptotic behaviors for a number of integrable nonlinear evolution equations associated with 2×2 matrix spectral problems have been obtained, for example, the mKdV equation, the KdV equation, the sine-Gordon equation, the modified nonlinear Schrödinger equation, the Camassa-Holm equation, the derivative nonlinear Schrödinger equation and so on [19,20,21,22,23,24,25,26,27,28,29,30]. However, there is little literature on the long-time asymptotic behavior of solutions for integrable nonlinear evolution equations associated with 3×3 matrix spectral problems [31,32,33]. Usually, it is difficult and complicated for the 3×3 case. Recently, the nonlinear steepest descent method was successfully generalized to derive the long-time asymptotics of the initial value problems for the coupled nonlinear Schrödinger equation and the Sasa-Satsuma equation with the complex potentials [33,34]. The main differences between the 2×2 and 3×3 cases is that the former corresponds to a scalar Riemann-Hilbert problem, while the latter corresponds to a matrix Riemann-Hilbert problem. In general, the solution of the matrix Riemann-Hilbert problem can not be given in explicit form, but the scalar Riemann-Hilbert problem can be solved by the Plemelj formula.

    The main aim of this paper is to study the long-time asymptotics of the Cauchy problem for the generalized Sasa-Satsuma equation [38] via nonlinear steepest decent method,

    {ut+uxxx6a|u|2ux6bu2ux3au(|u|2)x3bu(|u|2)x=0,u(x,0)=u0(x), (1.2)

    where a is a real constant, b is a complex constant that satisfies a2|b|2, the asterisk "" denotes the complex conjugate. It is easy to see that the generalized Sasa-Satsuma equation (1.2) can be reduced to the Sasa-Satsuma equation (1.1) when a=1 and b=0. Suppose that the initial value u0(x) lies in Schwartz space S(R)={f(x)C(R):supxR|xαβf(x)|<,α,βN}. The vector function γ(k) is determined by the initial data in (2.15) and (2.19), and γ(k) satisfies the conditions (P1) and (P2), where

    (P1):{γ(k)B1γ(k)+|b|24(γ(k)σ3γ(k))2<1,γ(k)B1γ(k)+aγ(k)σ3γ(k)<2,2γ(k)B1γ(k)+|γ(k)|2+|B1γ(k)|2<4,

    with

    σ3=(1001),B1=(abba); (1.3)

    (P2): When detB1>0 and a>0, (2a|B1γ(k)|2) and (2adetB1|γ(k)|2)/(1γ(k)B1γ(k)) are positive and bounded; otherwise, (|B1γ(k)|22a) and (detB1|γ(k)|22a)/(1γ(k)B1γ(k)) are positive and bounded.

    The main result of this paper is as following:

    Theorem 1.1. Let u(x,t) be the solution of the Cauchy problem for the generalized Sasa-Satsuma equation (1.2) with the initial value u0S(R). Suppose that the vector function γ(k) is defined in (2.19), the hypotheses (P1) and (P2) hold. Then, for x<0 and xt<C,

    u(x,t)=ua(x,t)+O(c(k0)t1logt). (1.4)

    where C is a fixed constant, and

    ua(x,t)=ν12tk0γ(k0)B1γ(k0)(|γ1(k0)|ei(ϕ+argγ1(k0))+|γ2(k0)|ei(ϕ+argγ2(k0))),k0=x12t,ν=12πlog(1γ(k0)B1γ(k0)),ϕ=νlog(196tk30)16tk30+argΓ(iν)+1πk0k0log|ξ+k0|d(1γ(ξ)B1γ(ξ))π4,

    c() is rapidly decreasing, Γ() is the Gamma function, γ1 and γ2 are the first and the second row of γ(k), respectively.

    Remark 1.1. The two conditions (P1) and (P2) satisfied by γ(k) are necessary. The condition (P1) guarantees the existence and the uniqueness of the solutions of the basic Riemann-Hilbert problem (2.16) and the Riemann-Hilbert problem (3.1). The boundedness of the function δ(k) defined in subsection 3.1 relies on the condition (P2).

    Remark 1.2. In the case of a=1 and b=0, the generalized Sasa-Satsuma equation (1.2) can be reduced to the Sasa-Satsuma equation. Then it is obvious that the condition (P1) is true, and the condition (P2) is reduced to the case that |γ(k)| is bounded. Therefore, the conditions (P1) and (P2) in this case are equivalent to the condition related to the reflection coefficient in [34], that is, |γ(k)| is bounded for the Sasa-Satsuma equation.

    The outline of this paper is as follows. In section 2, we derive a Riemann-Hilbert problem from the scattering relation. The solution of the generalized Sasa-Satsuma equation is changed into the solution of the Riemann-Hilbert problem. In section 3, we deal with the Riemann-Hilbert problem via nonlinear steepest decent method, from which the long-time asymptotics in Theorem 1.1 is obtained at the end.

    We begin with the 3×3 Lax pair of the generalized Sasa-Satsuma equation

    ψx=(ikσ+U)ψ, (2.1a)
    ψt=(4ik3σ+V)ψ, (2.1b)

    where ψ is a matrix function and k is the spectral parameter, σ=diag(1,1,1),

    U=(00u00uau+buau+bu0) (2.2)
    V=4k2U+2ik(U2+Ux)σ+[Ux,U]Uxx+2U3. (2.3)

    We introduce a new eigenfunction μ through μ=ψeikσx4ik3σt, where eσ=diag(e,e,e1). Then (2.1a) and (2.1b) become

    μx=ik[σ,μ]+Uμ, (2.4a)
    μt=4ik3[σ,μ]+Vμ, (2.4b)

    where [,] is the commutator, [σ,μ]=σμμσ. From (2.4a), the matrix Jost solution μ± satisfy the Volterra integral equations

    μ±(k;x,t)=I+x±eikσ(xξ)U(ξ,t)μ±(k;ξ,t)eikσ(xξ)dξ. (2.5)

    Set μ±L represent the first two columns of μ±, and μ±R denote the third column, i.e., μ±=(μ±L,μ±R). Furthermore, we can infer that μ+R and μL are analytic in the lower complex k-plane C, μ+L and μR are analytic in the the upper complex k-plane C+. Then we can introduce sectionally analytic function P1(k) and P2(k) by

    P1(k)=(μL(k),μ+R(k)),kC,P2(k)=(μ+L(k),μR(k)),kC+.

    One can find that U is traceless from (2.2), so detμ± are independent of x. Besides, detμ±=1 according to the evolution of detμ± at x=±. Because all the μ±eikσx+4ik3σt satisfy the differential equations (2.1a) and (2.1b), they are linear related. So there exists a scattering matrix s(k) that satisfies

    μ=μ+eikσx+4ik3σts(k)eikσx4ik3σt,dets(k)=1. (2.6)

    In this paper, we denote a 3×3 matrix A by the block form

    A=(A11A12A21A22),

    where A11 is a 2×2 matrix and A22 is scalar. Let q=(u,u)T and we can rewrite U of (2.2) as

    U=(02×2qqB10),

    where "" is the Hermitian conjugate. In addition, there are two symmetry properties for U,

    B1U(k)B=U(k),τU(k)τ=U(k), (2.7)
    B=(B1001),τ=(σ1001),σ1=(0110), (2.8)

    where B and τ are represented as block forms. Hence, the Jost solutions μ± and the scattering matrix s(k) also have the corresponding symmetry properties

    B1μ±(k)B=μ1±(k),τμ±(k)τ=μ±(k); (2.9)
    B1s(k)B=s1(k),τs(k)τ=s(k). (2.10)

    We write s(k) as block form (sij)2×2 and from the symmetry properties (2.10) we have

    s22(k)=det[s11(k)],B11s21(k)=adj[s11(k)]s12(k), (2.11)

    where adjX denote the adjoint of matrix X. Then we can write s(k) as

    s(k)=(s11(k)s12(k)s12(k)adj[s11(k)]B1det[s11(k)]), (2.12)

    where

    σ1s11(k)σ1=s11(k),σ1s12(k)=s12(k). (2.13)

    From the evaluation of (2.6) at t=0, one infers

    s(k)=limx+eikxσμ(k;x,0)eikxσ, (2.14)

    which implies that

    {s11(k)=I++q(ξ,0)μ21(k;ξ,0)dξ,s12(k)=+e2ikξq(ξ,0)μ22(k;ξ,0)dξ. (2.15)

    Theorem 2.1. Let M(k;x,t) be analytic for kCR and satisfy the Riemann-Hilbert problem

    {M+(k;x,t)=M(k;x,t)J(k;x,t),kR,M(k;x,t)I,k, (2.16)

    where

    M±(k;x,t)=limϵ0+M(kiϵ;x,t), (2.17)
    J(k;x,t)=(Iγ(k)γ(k)B1e2itθγ(k)e2itθγ(k)B11) (2.18)
    θ(k;x,t)=xtk4k3,γ(k)=s111(k)s12(k), (2.19)

    γ(k) lies in Schwartz space and satisfies

    σ1γ(k)=γ(k). (2.20)

    Then the solution of this Riemann-Hilbert problem exists and is unique, the function

    q(x,t)=(u(x,t),u(x,t))T=2ilimk(k(M(k;x,t))12) (2.21)

    and u(x,t) is the solution of the generalized Sasa-Satsuma equation.

    Proof. The matrix (J(k;x,t)+J(k;x,t))/2 is positive definite because of the condition (P1) that γ(k) satisfies, then the solution of the Riemann-Hilbert problem (2.16) is existent and unique according to the Vanishing Lemma [39]. We define M(k;x,t) by

    M(k;x,t)={(μL(k),μ+R(k)det[a(k)]),kC,(μ+L(k)a(k),μR(k)),kC+. (2.22)

    Considering the scattering relation (2.6) and the construction of M(k;x,t), we can obtain the jump condition and the corresponding Riemann-Hilbert problem (2.16) after tedious but straightforward algebraic manipulations. Substituting the large k asymptotic expansion of M(k;x,t) into (2.4a) and compare the coefficients of O(1k), we can get (2.21).

    In this section, we compute the Riemann-Hilbert problem (2.16) by the nonlinear steepest decent method and study the long-time asymptotic behavior of the solution. We make the following basic notations. (i) For any matrix M define |M|=(trMM)12 and for any matrix function A() define A()p=|A()|p. (ii) For two quantities A and B define AB if there exists a constant C>0 such that |A|CB. If C depends on the parameter α we shall say that AαB. (iii) For any oriented contour Σ, we say that the left side is + and the right side is .

    First of all, it is noteworthy that there are two stationary points ±k0, where ±k0=±x12t satisfied dθdk|k=±k0=0. The jump matrix J(k;x,t) have a lower-upper triangular factorization and a upper-lower triangular factorization. We can introduce an appropriate Rieman-Hilbert problem to unify these two forms of factorizations. In this process, we have to reorient the contour of the Riemann-Hilbert problem.

    The two factorizations of the jump matrix J are

    J={(Ie2itθγ(k)01)(I0e2itθγ(k)B11),(I0e2itθγ(k)B11γ(k)B1γ(k)1)(Iγ(k)γ(k)B100(1γ(k)B1γ(k))1)(Ie2itθγ(k)1γ(k)B1γ(k)01).

    We introduce a 2×2 matrix function δ(k) to make the two factorization unified, and δ(k) satisfies the following Riemann-Hilbert problem

    {δ+(k)=δ(k)(Iγ(k)γ(k)B1),k(k0,k0),=δ(k),k(,k0)(k0,+),δ(k)I,k, (3.1)

    which implies a scalar Riemann-Hilbert problem

    {detδ+(k)=detδ(k)(1γ(k)B1γ(k)),k(k0,k0),=detδ(k),k(,k0)(k0,+),detδ(k)1,k. (3.2)

    The jump matrix Iγ(k)γ(k)B1 of Riemann-Hilbert problem (3.1) is positive definite, so the solution δ(k) exists and is unique. The scalar Riemann-Hilbert problem (3.2) can be solved by the Plemelj formula,

    detδ(k)=(kk0k+k0)iνeχ(k), (3.3)

    where

    ν=12πlog(1γ(k0)B1γ(k0)),χ(k)=12πik0k0log(1γ(ξ)B1γ(ξ)1γ(k0)B1γ(k0))dξξk.

    Then we have by uniqueness that

    δ(k)=B11(δ(k))1B1,δ(k)=σ1δ(k)σ1. (3.4)

    Substituting (3.4) to (3.1), we have

    δ+(k)B1δ+(k)=B1B1γ(k)γ(k)B1, (3.5)

    which means that

    tr[δ+(k)B1δ+(k)]=2a|B1γ(k)|2. (3.6)

    Actually, the condition (P2) satisfied by γ(k) guarantee the boundedness of δ±(k) and we give a brief proof below. When detB1>0, we find that the Hermitian matrix B1 can be decomposition. In other words, there exists a triangular matrix S that satisfies B1=aSS. So tr[δ+B1δ+]=a|Sδ+|2. When detB1<0 and |a|>0, the matrix B1 has a decomposition B1=SDS, where S is a triangular matrix and D is a diagonal matrix and the diagonal elements have opposite signs. In the case of a>0, B1 can be decomposed as below,

    B1=(ab01)1(adetB100a)(a0b1)1. (3.7)

    We denote Sδ+(k) by (Gij)3×3 and c1=2a|B1γ(k)|2 is negative, then

    adetB1(|G11|2+|G21|2)+a(|G12|2+|G22|2)=c1. (3.8)

    Noticing that detB1<0, we find a negative constant c2 that satisfies c2adetB1(c31)/(1detB1c3), where c3 is a constant and 0<c3<1, which impies

    |Sδ+(k)|2c1c21. (3.9)

    The case that a<0 is similar. In particular, when a=0, then |b|>0, it is easy to see that B1 is not definite. For |Reb|>0, we have the decomposition

    B1=(b|b|2+(b)2b|b|2+(b)2b|b|2+(b)2b|b|2+(b)2)1(1b+b001b+b)(b|b|2+b2b|b|2+b2b|b|2+b2b|b|2+b2)1. (3.10)

    For |Reb|=0, we have

    B1=(i21i2i21+i2)1(ib/200ib/2)(i2i21+i21i2)1. (3.11)

    So we get the boundedness of |δ+(k)|. The others have the same analysis,

    δ(k)B1δ(k)=(B1γ(k)γ(k))1,ask(k0,k0), (3.12)
    |δ+(k)|2=|δ(k)|2=2,ask(,k0)(k0,+), (3.13)
    |detδ+(k)|={1γ(k)B1γ(k),k(k0,k0),1,k(,k0)(k0,+), (3.14)
    |detδ(k)|={11γ(k)B1γ(k),k(k0,k0),1,k(,k0)(k0,+). (3.15)

    Hence, by the maximum principle, we have

    |δ(k)|const<,|detδ(k)|const<, (3.16)

    for all kC. We define the functions

    ρ(k)={γ(k),k(,k0)(k0,+),γ(k)1γ(k)B1γ(k),k(k0,k0), (3.17)
    Δ(k)=(δ(k)00(detδ(k))1). (3.18)

    We reverse the orientation for k(,k0)(k0,+) as in Figure 1, and MΔ(k;x,t)=M(k;x,t)Δ1(k) satisfies the Riemann-Hilbert problem on the reoriented contour

    {MΔ+(k;x,t)=MΔ(k;x,t)JΔ(k;x,t),kR,MΔ(k;x,t)I,k, (3.19)
    Figure 1.  The reoriented contour on R.

    where the jump matrix JΔ(k;x,t) has a decomposition

    JΔ(k;x,t)=(b)1b+=(I0e2itθ(k)ρ(k)B1δ1(k)detδ(k)1)(Ie2itθδ+(k)ρ(k)[detδ+(k)]01). (3.20)

    For the convenience of discussion, we define

    L={k0+αk0e3πi4:<α2}{k0+αk0eπi4:<α2},Lϵ={k0+αk0e3πi4:ϵ<α2}{k0+αk0eπi4:ϵ<α2}.

    Theorem 3.1. The vector function ρ(k) has a decomposition

    ρ(k)=h1(k)+h2(k)+R(k),kR,

    where R(k) is a piecewise-rational function and h2(k) has a analytic continuation to L. Besides, they admit the following estimates

    |e2itθ(k)h1(k)|1(1+|k|2)tl,kR, (3.21)
    |e2itθ(k)h2(k)|1(1+|k|2)tl,kL, (3.22)
    |e2itθ(k)R(k)|e16ϵ2k30t,kLϵ, (3.23)

    for an arbitrary positive integer l. Considering the Schwartz conjugate

    ρ(k)=R(k)+h1(k)+h2(k),

    we can obtain the same estimate for e2itθ(k)h1(k), e2itθ(k)h2(k) and e2itθ(k)R(k) on RL.

    Proof. It follows from Proposition 4.2 in [18].

    A direct calculation shows that b± of (3.20) can be decomposed further

    b+=bo+ba+=(I3×3+ωo+)(I3×3+ωa+)=(I2×2e2itθ[detδ+(k)]δ+(k)h1(k)01)(I2×2e2itθ[detδ+(k)]δ+(k)[h2(k)+R(k)]01),b=boba=(I3×3ωo)(I3×3ωa)=(I2×20e2itθh1(k)B1δ1(k)detδ(k)1)(I2×20e2itθ[h2(k)+R(k)]B1δ1(k)detδ(k)1).

    Define the oriented contour Σ by Σ=LL as in Figure 2. Let

    M(k;x,t)={MΔ(k;x,t),kΩ1Ω2,MΔ(k;x,t)(ba+)1,kΩ3Ω4Ω5,MΔ(k;x,t)(ba)1,kΩ6Ω7Ω8. (3.24)
    Figure 2.  The contour Σ.

    Lemma 3.1. M(k;x,t) is the solution of the Riemann-Hilbert problem

    {M+(k;x,t)=M(k;x,t)J(k;x,t),kΣ,M(k;x,t)I,k, (3.25)

    where the jump matrix J(k;x,t) satisfies

    J(k;x,t)=(b)1b+={I1ba+,kL,(ba)1I,kL,(bo)1bo+,kR. (3.26)

    Proof. We can construct the Riemann-Hilbert problem (3.25) based on the Riemann-Hilbert problem (3.19) and the decomposition of b±. In the meantime, the asymptotics of M(k;x,t) is derived from the convergence of b± as k. For fixed x and t, we pay attention to the domain Ω3. Noticing the boundedness of δ(k) and detδ(k) in (3.16), we arrive at

    |e2itθ[detδ(k)][h2(k)+R(k)]δ(k)||e2itθh2(k)|+|e2itθR(k)|.

    Consider the definition of R(k) in this domain,

    |e2itθh2(k)|1|k+i|2,|e2itθR(k)||mi=0μi(kk0)i||(k+i)m+5|1|k+i|5,

    where m is a positive integer and μi is the coefficient of the Taylor series around k0. Combining with the boundedness of h2(k) in Theorem 3.1, we obtain that M(k;x,t)I when kΩ3 and k. The others are similar to this domain.

    The above Riemann-Hilbert problem (3.25) can be solved as follows. Set

    ω±=±(b±I),ω=ω++ω.

    Let

    (C±f)(k)=Σf(ξ)ξk±dξ2πi,fL2(Σ) (3.27)

    denote the Cauchy operator, where C+f (Cf) denotes the left (right) boundary value for the oriented contour Σ in Figure 2. Define the operator Cω:L2(Σ)+L(Σ)L2(Σ) by

    Cωf=C+(fω)+C(fω+) (3.28)

    for the 3×3 matrix function f.

    Lemma 3.2 (Beals-Coifman). If μ(k;x,t)L2(Σ)+L(Σ) is the solution of the singular integral equation

    μ=I+Cωμ.

    Then

    M(k;x,t)=I+Σμ(ξ;x,t)ω(ξ;x,t)ξkdξ2πi

    is the solution of the Riemann-Hilbert problem (3.25).

    Proof. See [18], P. 322 and [40].

    Theorem 3.2. The expression of the solution q(x,t) can be written as

    q(x,t)=(u(x,t),u(x,t))T=1π(Σ((1Cω)1I)(ξ)ω(ξ)dξ)12. (3.29)

    Proof. From (2.21), (3.24) and Lemma 2, the solution q(x,t) of the generalized Sasa-Satsuma equation is expressed by

    q(x,t)=limk2i[k(M(k;x,t))12]=1π(Σμ(ξ;x,t)ω(ξ)dξ)12=1π(Σ((1Cω)1I)(ξ)ω(ξ)dξ)12.

    Set Σ=Σ(RLϵLϵ) oriented as in Figure 3. We will convert the Riemann-Hilbert problem on the contour Σ to a Riemann-Hilbert problem on the contour Σ and estimate the errors between the two Riemann-Hilbert problems. Let ω=ωe+ω=ωa+ωb+ωc+ω, where ωa=ω|R is supported on R and is composed of terms of type h1(k) and h1(k); ωb is supported on LL and is composed of contribution to ω from terms of type h2(k) and h2(k); ωc is supported on LϵLϵ and is composed of contribution to ω from terms of type R(k) and R(k).

    Figure 3.  The contour Σ.

    Lemma 3.3. For arbitrary positive integer l, as t,

    ωaL1(R)L2(R)L(R)tl, (3.30)
    ωbL1(LL)L2(LL)L(LL)tl, (3.31)
    ωcL1(LϵLϵ)L2(LϵLϵ)L(LϵLϵ)e16ϵ2k30t, (3.32)
    ωL2(Σ)(tk30)14,ωL1(Σ)(tk30)12 (3.33)

    Proof. The proof of estimates (3.30), (3.31), (3.32) follows from Theorem 3.1. Afterwards, we consider the definition of R(k) on the contour {k=k0+αk0e3πi4|<α<ϵ},

    |R(k)|(1+|k|5)1.

    Resorting to Re(iθ)8α2k30 and the boundedness of δ(k) and detδ(k) in (3.16), we can obtain

    |e2itθ[detδ(k)]R(k)δ(k)|e16tk30α2(1+|k|5)1.

    Then we obtain (3.33) by simple computations.

    Lemma 3.4. As t, (1Cω)1:L2(Σ)L2(Σ) exists and is uniformly bounded:

    (1Cω)1L2(Σ)1.

    Furthermore, (1Cω)1L2(Σ)1.

    Proof. It follows from Proposition 2.23 and Corollary 2.25 in [18].

    Lemma 3.5. As t,

    Σ((1Cω)1I)(ξ)ω(ξ)dξ=Σ((1Cω)1I)(ξ)ω(ξ)dξ+O((tk30)l). (3.34)

    Proof. A simple computation shows that

    ((1Cω)1I)ω=((1Cω)1I)ω+ωe+((1Cω)1(CωeI))ω+((1Cω)1(CωI))ωe+((1Cω)1Cωe(1Cω))(CωI)ω. (3.35)

    After a series of tedious computations and utilizing the consequence of Lemma 4, we arrive at

    ωeL1(Σ)ωaL1(R)+ωbL1(LL)+ωcL1(LϵLϵ)(tk30)l,((1Cω)1(CωeI))ωL1(Σ)(1Cω)1L2(Σ)CωeIL2(Σ)ωL2(Σ)ωeL2(Σ)ωL2(Σ)(tk30)l14,((1Cω)1(CωI))ωeL1(Σ)(1C1ω)L2(Σ)CωIL2(Σ)ωeL2(Σ)ωL2(Σ)ωeL2(Σ)(tk30)l14,((1Cω)1Cωe(1Cω))(CωI)ωL1(Σ)(1Cω)1L2(Σ)(1Cω)1L2(Σ)CωeL2(Σ)CωIL2(Σ)ωL2(Σ)ωeL(Σ)ω2L2(Σ)(tk30)l12.

    Then the proof is accomplished as long as we substitute the estimates above into (3.35).

    Notice that ω(k)=0 when kΣΣ, let Cω|L2(Σ) denote the restriction of Cω to L2(Σ). For simplicity, we write Cω|L2(Σ) as Cω. Then

    Σ((1Cω)1I)(ξ)ω(ξ)dξ=Σ((1Cω)1I)(ξ)ω(ξ)dξ.

    Lemma 3.6. As t,

    q(x,t)=(u(x,t),u(x,t))T=1π(Σ((1Cω)1I)(ξ)ω(ξ)dξ)12+O((tk30)l). (3.36)

    Proof. From (3.29) and (3.34), we can obtain the result directly.

    Let L=LLϵ and μ=(1Cω)1I. Then

    M(k;x,t)=I+Σμ(k;x,t)ω(k;x,t)ξkdξ2πi

    solves the Riemann-Hilbert problem

    {M+(k;x,t)=M(k;x,t)J(k;x,t),kΣ,M(k;x,t)I,k,

    where

    J=(b)1b+=(Iω)1(I+ω+),ω=ω++ω,b+=(Ie2itθ[detδ(k)]δ(k)R(k)01),b=I,on L,b+=I,b=(I0e2itθR(k)B1δ1(k)detδ(k)1),on (L).

    Let the contour Σ=ΣAΣB and ω±=ωA±+ωB±, where

    ωA±(k)={ω±(k),kΣA,0,kΣB,ωB±(k)={0,kΣA,ω±(k),kΣB. (3.37)

    Define the operators CωA and CωB: L2(Σ)+L(Σ)L2(Σ) as in definition (3.28).

    Lemma 3.7.

    ||CωBCωA||L2(Σ)=||CωACωB||L2(Σ)k0(tk30)12,
    ||CωBCωA||L(Σ)L2(Σ),||CωACωB||L(Σ)L2(Σ)k0(tk30)34.

    Proof. See Lemma 3.5 in [18].

    Lemma 3.8. As t,

    Σ((1Cω)1I)(ξ)ω(ξ)dξ=ΣA((1CωA)1I)(ξ)ωA(ξ)dξ+ΣB((1CωB)1I)(ξ)ωB(ξ)dξ+O(c(k0)t). (3.38)

    Proof. From identity

    (1CωACωB)(1+CωA(1CωA)1+CωB(1CωB)1)=1CωBCωA(1CωA)1CωACωB(1CωB)1,

    we have

    (1Cω)1=1+CωA(1CωA)1+CωB(1CωB)1+[1+CωA(1CωA)1+CωB(1CωB)1][1CωBCωA(1CωA)1CωACωB(1CωB)1]1[CωBCωA(1CωA)1+CωACωB(1CωB)1].

    Based on Lemma (3.7) and Lemma (3.4), we arrive at (3.38).

    For the sake of convenience, we write the restriction CωAL2(ΣA) as CωA, similar for CωB. From the consequences of Lemma 3.6 and Lemma 3.8, as t, we have

    q(x,t)=(ΣA((1CωA)1I)(ξ)ωA(ξ)dξπ)12(ΣB((1CωB)1I)(ξ)ωB(ξ)dξπ)12+O(c(k0)t). (3.39)

    Extend the contours ΣA and ΣB to the contours

    ˆΣA={k=k0+k0αe±πi4:αR}, (3.40)
    ˆΣB={k=k0+k0αe±3πi4:αR}, (3.41)

    respectively. We introduce ˆωA and ˆωB on ˆΣA and ˆΣB, respectively, by

    ˆωA±={ωA±(k),kΣA,0,kˆΣAΣA,ˆωB±={ωB±(k),kΣB,0,kˆΣBΣB. (3.42)

    Let ΣA and ΣB denote the contours {k=k0αe±πi4:αR} oriented inward as in ΣA, ˆΣA, and outward as in ΣB, ˆΣB, respectively. Define the scaling operators

    NA: L2(ˆΣA)L2(ΣA),f(k)(NAf)(k)=f(k48tk0k0), (3.43)
    NB: L2(ˆΣB)L2(ΣB),f(k)(NBf)(k)=f(k48tk0+k0), (3.44)

    and set

    ωA=NAˆωA,ωB=NBˆωB.

    A simple change-of-variable arguments shows that

    CˆωA=N1ACωANA,CˆωB=N1BCωBNB,

    where the operator CωA (CωB) is a bounded map from L2(ΣA) (L2(ΣB)) into L2(ΣA) (L2(ΣB)). On the part

    LA={k=αk048tk0e3πi4:ϵ<α<+}

    of ΣA, we have

    ωA=ωA+=(0(NAs1)(k)00),

    on LA we have

    ωA=ωA=(00(NAs2)(k)0),

    where

    s1(k)=e2itθ(k)[detδ(k)]δ(k)R(k),s2(k)=e2itθR(k)B1δ1(k)detδ(k).

    Lemma 3.9. As t, and kLA, then

    |(NA˜δ)(k)|tl, (3.45)

    where ˜δ(k)=e2itθ(k)[δ(k)R(k)(detδ(k))R(k)].

    Proof. It follows from (3.1) and (3.2) that ˜δ satisfies the following Riemann-Hilbert problem:

    {˜δ+(k)=˜δ(k)(1γ(k)B1γ(k))+e2itθf(k),k(k0,k0),˜δ(k)0,k. (3.46)

    where f(k)=δ(k)[γ(k)B1γ(k)Iγ(k)γ(k)B1]R(k). The solution for the above Riemann-Hilbert problem can be expressed by

    ˜δ(k)=X(k)k0k0e2itθ(ξ)f(ξ)X+(ξ)(ξk)dξ2πi,X(k)=exp{12πik0k0log(1|γ(ξ)|2)ξkdξ}.

    Observing that

    (γ(k)B1γ(k)Iγ(k)γ(k)B1)R(k)=(γ(k)B1γ(k)Iγ(k)γ(k)B1)(R(k)ρ(k))=adj[B1]adj[γ(k)γ(k)](h1(k)+h2(k)),

    we obtain f(k)=O((k2k20)l). Similar to the Lemma 3.1, f(k) can be decomposed into two parts: f(k)=f1(k)+f2(k), and

    |e2itθ(k)f1(k)|1(1+|k|2)tl,kR, (3.47)
    |e2itθ(k)f2(k)|1(1+|k|2)tl,kLt, (3.48)

    where f2(k) has an analytic continuation to Lt, l is a positive integer and l2,

    Lt={k=k0+k0αe3πi4:0α2(112t)}{k=k0tk0+k0αeπi4:0α2(112t)},

    (see Figure 5).

    Figure 4.  The contour ΣA(ΣB).
    Figure 5.  The contour Lt.

    As kLA, we obtain

    (NA˜δ)(k)=X(k48tk0k0)k0k0tk0e2itθ(ξ)f(ξ)X+(ξ)(ξ+k0k48tk0)dξ2πi+X(k48tk0k0)k0tk0k0e2itθ(ξ)f1(ξ)X+(ξ)(ξ+k0k48tk0)dξ2πi+X(k48tk0k0)k0tk0k0e2itθ(ξ)f2(ξ)X+(ξ)(ξ+k0k48tk0)dξ2πi=I1+I2+I3.
    |I1|k0tk0k0|f(ξ)||ξ+k0k48tk0|dξtl1,
    |I2|k0k0tk0|e2itθ(ξ)f1(ξ)||ξ+k0k48tk0|dξtl2tk0(2k0k0t)tl+1.

    As a consequence of Cauchy's Theorem, we can evaluate I3 along the contour Lt instead of the interval (k0tk0,k0) and obtain |I3|tl+1. Therefore, (3.45) holds.

    Corollary 3.1. As t, and kLA, then

    |(NAˆδ)(k)|tl,t,kLA, (3.49)

    where ˆδ(k)=e2itθ(k)R(k)B1[δ1(k)(detδ(k))1I].

    Let JA0=(IωA0)1(I+ωA0+), where

    ωA0=ωA0+={(0(δ0A)2(k)2iνeik22γ(k0)1γ(k0)B1γ(k0)00),kΣ1A,(0(δ0A)2(k)2iνeik22γ(k0)00),kΣ3A, (3.50)
    δ0A=(196tk30)iν2e8itk30eχ(k0) (3.51)
    ωA0=ωA0={(00(δ0A)2(k)2iνeik22γ(k0)B11γ(k0)B1γ(k0)0),kΣ2A,(00(δ0A)2(k)2iνeik22γ(k0)B10),kΣ4A. (3.52)

    It follows from (3.78) in [18] that

    ωAωA0L1(ΣA)L2(ΣA)L(ΣA)k0logttk30. (3.53)

    There are similar consequences for kΣB. Let JB0=(IωB0)1(I+ωB0+), where

    ωB0=ωB0+={(0(δ0B)2k2iνeik22γ(k0)00),kΣ2B,(0(δ0B)2k2iνeik22γ(k0)1γ(k0)B1γ(k0)00),kΣ4B, (3.54)
    δ0B=(196tk30)iν2e8itk30eχ(k0) (3.55)
    ωB0=ωB0={(00(δ0B)2k2iνeik22γ(k0)B10),kΣ1B,(00(δ0B)2k2iνeik22γ(k0)B11γ(k0)B1γ(k0)0),kΣ3B. (3.56)

    Theorem 3.3. As t,

    q(x,t)=(u(x,t),u(x,t))T=1π48tk0(ΣA((1CωA0)1I)(ξ)ωA0(ξ)dξ)12+1π48tk0(ΣB((1CωB0)1I)(ξ)ωB0(ξ)dξ)12+O(c(k0)logtt). (3.57)

    Proof. Notice that

    ((1CωA)1I)ωA=((1CωA0)1I)ωA0+((1CωA)1I)(ωAωA0)+(1CωA)1(CωACωA0)(1CωA0)IωA0.

    Utilizing the triangle inequality and the boundedness in (3.53), we have

    ΣA((1CωA)1I)(ξ)ωA(ξ)dξ=ΣA((1CωA0)1I)(ξ)ωA0(ξ)dξ+O(logtt).

    According to (3.5) and a simple change-of-variable argument, we have

    1π(Σ((1CωA)1I)(ξ)ωA(ξ)dξ)12=1π(ˆΣA(N1A(1CωA)1I)(ξ)ωA(ξ)dξ)12=1π(ˆΣA((1CωA)1I)((ξ+k0)48tk0)(NAωA)((ξ+k0)48tk0)dξ)12=1π48tk0(ΣA((1CωA)1I)(ξ)ωA(ξ)dξ)12=1π48tk0(ΣA((1CωA0)1I)(ξ)ωA0(ξ)dξ)12+O(c(k0)logtt).

    There are similar computations for the other case. Together with (3.39), one can obtain (3.57).

    For kCΣA, set

    MA0(k;x,t)=I+ΣA((1CωA0)1I)(ξ)ωA0(ξ)ξkdξ2πi. (3.58)

    Then MA0(k;x,t) is the solution of the Riemann-Hilbert problem

    {MA0+(k;x,t)=MA0(k;x,t)JA0(k;x,t),kΣA,MA0(k;x,t)I,k. (3.59)

    In particular

    MA0(k)=I+MA01k+O(k2),k, (3.60)

    then

    MA01=ΣA((1CωA0)1I)(ξ)ωA0(ξ)dξ2πi. (3.61)

    There is a analogous Riemann-Hilbert problem on ΣB,

    {MB0+(k;x,t)=MB0(k;x,t)JB0(k;x,t),kΣB,MB0(k;x,t)I,k, (3.62)

    where JB0(k;x,t) is defined in (3.54) and (3.56). In the meantime, we have

    MB0(k)=I+MB01k+O(k2),k. (3.63)

    Next, we consider the relation between MA01 and MB01. From the expression (3.50), (3.52), (3.54) and (3.56), we have the symmetry relation

    JA0(k)=τ(JB0(k))τ.

    By the uniqueness of the Riemann-Hilbert problem,

    MA0(k)=τ(MB0(k))τ.

    Combining with the expansion (3.60) and (3.63), one can verify that

    MA01=τ(MB01)τ,(MA01)12=σ1(MB01)12.

    Therefore, from (3.57) and (3.61), we have

    q(x,t)=(u(x,t),u(x,t))T=2i48tk0(MA01+MB01)12+O(c(k0)logtt)=i12tk0((MA01)12σ1(MA01)12)+O(c(k0)logtt). (3.64)

    In this subsection, we compute (MA01)12 explicitly. It is important to set

    Ψ(k)=H(k)(k)iνσe14ik2σ,H(k)=(δ0A)σMA0(k)(δ0A)σ. (3.65)

    Then it follows from (3.59) that

    Ψ+(k)=Ψ(k)v(k0),v=e14ik2σ(k)iνσ(δ0A)σJA0(k)(δ0A)σ(k)iνσe14ik2σ. (3.66)

    The jump matrix is the constant one on the four rays Σ1A, Σ2A, Σ3A, Σ4A, so

    dΨ+(k)dk=dΨ(k)dkv(k0). (3.67)

    Then it follows that (dΨ/dk+ikσΨ)Ψ1 has no jump discontinuity along any of the four rays. Besides, from the relation between Ψ(k) and H(k), we have

    dΨ(k)dkΨ1(k)=dH(k)dkH1(k)ik2H(k)σH1(k)+iνkH(k)σH1(k)=O(k1)ikσ2+i2(δ0A)σ[σ,MA01](δ0A)σ.

    It follows by the Liouville's Theorem that

    dΨ(k)dk+ik2σΨ(k)=βΨ(k), (3.68)

    where

    β=i2(δ0A)σ[σ,MA01](δ0A)σ=(0β12β210).

    Moreover,

    (MA01)12=i(δ0A)2β12. (3.69)

    Set

    Ψ(k)=(Ψ11(k)Ψ12(k)Ψ21(k)Ψ22(k)).

    From (3.68) and its differential, we obtain

    d2β21Ψ11(k)dk2+(i2+k24β21β12)β21Ψ11(k)=0,Ψ21(k)=1β21β12(dβ21Ψ11(k)dk+ik2β21Ψ11(k)),d2Ψ22(k)dk2+(i2+k24β21β12)Ψ22(k)=0,β21Ψ12(k)=(dΨ22(k)dkik2Ψ22(k)).

    As is well known, the Weber's equation

    d2g(ζ)dζ2+(ϱ+12ζ24)g(ζ)=0

    has the solution

    g(ζ)=c1Dϱ(ζ)+c2Dϱ(ζ),

    where Dϱ() denotes the standard parabolic-cylinder function, and c1, c2 are constants. The parabolic-cylinder function satisfies [41]

    dDϱ(ζ)dζ+ζ2Dϱ(ζ)ϱDϱ1(ζ)=0, (3.70)
    Dϱ(±ζ)=Γ(ϱ+1)eiπϱ22πDϱ1(±iζ)+Γ(ϱ+1)eiπϱ22πDϱ1(iζ). (3.71)

    As ζ, from [42], we have

    Dϱ(ζ)={ζϱeζ24(1+O(ζ2)),|argζ|<3π4,ζϱeζ24(1+O(ζ2))2πΓ(ϱ)eϱπi+ζ24ζϱ1(1+O(ζ2)),π4<argζ<5π4,ζϱeζ24(1+O(ζ2))2πΓ(ϱ)eϱπi+ζ24ζϱ1(1+O(ζ2)),5π4<argζ<π4, (3.72)

    where Γ() is the Gamma function. Set ϱ=iβ21β12,

    β21Ψ11(k)=c1Dϱ(eπi4k)+c2Dϱ(e3πi4k), (3.73)
    Ψ22(k)=c3Dϱ(eπi4k)+c4Dϱ(e3πi4k), (3.74)

    where a1,a2,a3,a4 are constants. As argk(π,3π4)(3π4,π) and k, we arrive at

    Ψ11(k)(k)iνeik24I,Ψ22(k)(k)iνeik241,

    then

    β21Ψ11(k)=β21eπν4Dϱ(e3πi4k),ν=β21β12,Ψ22(k)=eπν4Dϱ(e3πi4k).

    Consequently,

    Ψ21(k)=β21eπν4eπi4Dϱ1(e3πi4k),β21Ψ12(k)=ϱeπν4eπi4Dϱ1(e3πi4k).

    For argk(3π4,π4) and k, we have

    Ψ11(k)(k)iνeik24I,Ψ22(k)(k)iνeik241,

    then

    β21Ψ11(k)=β21e3πν4Dϱ(eπi4k),Ψ22(k)=eπν4Dϱ(e3πi4k).

    Consequently,

    Ψ21(k)=β21e3πν4e3πi4Dϱ1(eπi4k),β21Ψ12(k)=ϱeπν4eπi4Dϱ1(e3πi4k).

    Along the ray argk=3π4,

    Ψ+(k)=Ψ(k)(I0γ(k0)B11). (3.75)

    Notice the (2,1) entry of the Riemann-Hilbert problem,

    β21eπ(νi)4Dϱ1(e3πi4k)=β21eπ(3i3ν)4Dϱ1(eπi4k)eπν4Dϱ(e3πi4k)γ(k0)B1.

    It follows from (3.71) that

    Dϱ(e3πi4k)=Γ(ϱ+1)eπν22πDϱ1(e3πi4k)+Γ(ϱ+1)eπν22πDϱ1(eπi4k).

    Then we separate the coefficients of the two independent functions and obtain

    β21=e3πi4eπν2Γ(ϱ+1)2πγ(k0)B1. (3.76)

    Noting that B1(JA0(k))B=(JA0(k))1, we have β12=B11β21, which means that

    β12=B11B1γ(k0)e3πi4eπν2Γ(ϱ+1)2π=eπi4eπν2νΓ(iν)2πγ(k0). (3.77)

    Finally, we can obtain (1.4) from (3.64), (3.69) and (3.77).

    This work is supported by the National Natural Science Foundation of China (Grant Nos. 11871440 and 11931017).

    The authors declare no conflict of interest.



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