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HAL Id: hal-02884947 https://hal.archives-ouvertes.fr/hal-02884947 Submitted on 30 Jun 2020 HAL is a multi-disciplinary open access archive for the deposit and dissemination of sci- entific research documents, whether they are pub- lished or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Shifted-Chebyshev-polynomial-based numerical algorithm for fractional order polymer visco-elastic rotating beam Lei Wang, Yi-Ming Chen To cite this version: Lei Wang, Yi-Ming Chen. Shifted-Chebyshev-polynomial-based numerical algorithm for fractional or- der polymer visco-elastic rotating beam. Chaos, Solitons and Fractals, Elsevier, 2020, 132, pp.109585. 10.1016/j.chaos.2019.109585. hal-02884947

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Page 1: Shifted-Chebyshev-polynomial-based numerical algorithm for

HAL Id: hal-02884947https://hal.archives-ouvertes.fr/hal-02884947

Submitted on 30 Jun 2020

HAL is a multi-disciplinary open accessarchive for the deposit and dissemination of sci-entific research documents, whether they are pub-lished or not. The documents may come fromteaching and research institutions in France orabroad, or from public or private research centers.

L’archive ouverte pluridisciplinaire HAL, estdestinée au dépôt et à la diffusion de documentsscientifiques de niveau recherche, publiés ou non,émanant des établissements d’enseignement et derecherche français ou étrangers, des laboratoirespublics ou privés.

Shifted-Chebyshev-polynomial-based numericalalgorithm for fractional order polymer visco-elastic

rotating beamLei Wang, Yi-Ming Chen

To cite this version:Lei Wang, Yi-Ming Chen. Shifted-Chebyshev-polynomial-based numerical algorithm for fractional or-der polymer visco-elastic rotating beam. Chaos, Solitons and Fractals, Elsevier, 2020, 132, pp.109585.10.1016/j.chaos.2019.109585. hal-02884947

Page 2: Shifted-Chebyshev-polynomial-based numerical algorithm for

Shifted-Chebyshev-polynomial-based numericalalgorithm for fractional order polymer visco-elastic

rotating beam

Lei Wanga, Yi-Ming Chena,b,c,∗

aSchool of Sciences, Yanshan University, Qinhuangdao, Hebei, P.R.China, 066004.bLE STUDIUM RESEARCH PROFESSOR, Loire Valley Institute for Advanced Studies,

Orleans, FrancecINSA - Institut National des sciences appliquees - 88, Boulevard Lahitolle, Blois Cedex,

France

Abstract

In this paper, an effective numerical algorithm is proposed for the first timeto solve the fractional visco-elastic rotating beam in the time domain. On thebasis of fractional derivative Kelvin-Voigt and fractional derivative element con-stitutive models, the two governing equations of fractional visco-elastic rotatingbeams are established. According to the approximation technique of shiftedChebyshev polynomials, the integer and fractional differential operator matri-ces of polynomials are derived. By means of the collocation method and matrixtechnique, the operator matrices of governing equations can be transformed intothe algebraic equations. In addition, the convergence analysis is performed. Inparticular, unlike the existing results, we can get the displacement and thestress numerical solution of the governing equation directly in the time domain.Finally, the sensitivity of the algorithm is verified by numerical examples.

Keywords: Fractional visco-elastic rotating beam, Fractional governingequation, Shifted Chebyshev polynomials, Approximation technique, Operatormatrix, Numerical solution

1. Introduction

Fractional calculus and fractional differential equations have been widelyused in physics, engineering, economics and other research fields [1–5], sincefractional derivative has better memory [6] than integer order one, especially inthe application of visco-elastic polymer materials. The fractional order consti-tutive model [7–12] can describe material properties more accurately with fewerparameters, so it is considered to be a good mathematical model to describe the

∗Corresponding author.Email addresses: [email protected] (Lei Wang), [email protected] (Yi-Ming Chen)

Preprint submitted to Elsevier December 25, 2019

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dynamic mechanical behavior of visco-elastic materials. There are also manyresearches on fractional order visco-elastic beams [13–18].

The complexity of the fractional derivative determines that the numericalsolution of the beam governing equation became more difficult to deal with.Scholars have used Laplace or Fourier transform to transform the time domainproblem into a frequency domain problem to study the fractional order govern-ing equation in the frequency domain. For example, Lewandowski et al. [14, 19]used fractional four-parameter model and fractional Zener model to describevisco-elastic materials. The virtual work principle and Laplace transform havebeen used to derive the motion equations of the considered system in the fre-quency domain, and then the dynamic characteristics of the visco-elastic beamhave been studied. Kiasat et al. [20] used the Fourier transform to calculatethe unknown coefficient of the dynamic response function to research the freevibration of isotropic visco-elastic beams and plates on visco-elastic media. Theprocess of solving the fractional visco-elastic governing equations in the variabledomain was complicated. This has led scholars to solve the analysis in the timedomain.

Methods for solving fractional visco-elastic beams in the time domain includethe finite element method [21, 22], multi-scale method [23], Galerkin method[24] and the variational iteration method [25] which have been found in theliterature. But so far, the numerical solutions of the displacement and thestress of fractional visco-elastic rotating beams in time domain has not beenstudied.

As an important tool for the in-depth research and development of math-ematics, function approximation theory has been successfully applied in thefields of control science and engineering, mechanical engineering, system sci-ence and so on [26–30]. It is well known that the study of numerical solutionsof fractional visco-elastic beams can be attributed to the problem of solvingfractional differential equations. The solutions of fractional differential equa-tions mainly include analytical methods, polynomial approximation methodsand other methods. Due to the complex form of fractional derivative, the so-lution of the fractional order differential equation is intractable to obtain. Theanalytical method has tedious numerical calculation and limited to solving somesimple problems. Compared with the former, the polynomial approximationmethod of fractional differential equations is particularly significant becauseof its fast speed, high efficiency and high precision. Polynomial approxima-tion methods include Legendre polynomial method [31, 32], Chebyshev waveletmethod [33, 34], Bernoulli wavelet method [35], Bernstein polynomial method[36, 37] and shifted Chebyshev polynomials (SCPs) method [38]. The SCPsmethod can be used to approximate the unknown function on the extended in-terval, which makes it easier to solve the fractional differential equations withdifferent physical mechanisms governing and historical background [39–42].

Rotating beams has been widely used in helicopter rotors, wind turbineblades, propellers and various rotating mechanical structures. The study of thevibration characteristics of the rotating beams [43–46] has been an importantbasis for the design of the rotating beam machinery. Based on this, in this paper,

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we use the fractional derivative element (FDE) and the fractional derivativeKelvin-Voigt (FDKV) constitutive models. Polymers Poly(ether ether ketone)(PEEK) rotating beam and High-density polyethylene (HDPE) [47] rotatingbeam are studied by SCPs method. The SCPs algorithm is solved directlyin the time domain, the process is simple, and the numerical solutions of thedisplacement and the stress of the fractional visco-elastic rotating beam can beobtained.

This paper is structured as follows, in Section 2, some preliminaries includingthe basic definition of fractional differential operators, the fractional visco-elasticconstitutive models and the properties of SCPs are described. In Section 3, theSCPs solving algorithm is described. In Section 4, FDE model and FDKV modelare used to establish two governing equations of visco-elastic rotating beam.The convergence analysis is performed in Section 5. In Section 6, the numericalresults of the displacement and the stress of the visco-elastic rotating beams areobtained and discussed to show the advantages of the proposed approach. Theresearch work in this paper is concluded in Section 7.

2. Preliminaries and notations

Some basic definitions and properties of the fractional order calculus areprovided in this section.

2.1. The basic definition of fractional differential operator

Definition 1. [48] The Caputo definition of fractional differential operator

(cDαf) of order α is given by

(cDαf)(t) =

1Γ(m−α)

∫ t

0f(m)(τ)

(t−τ)α−m+1 dτ, α > 0,m− 1 ≤ α < m,

dmf(t)dtm , α = m.

(1)

for the Caputo derivative, we have

cDαtχ =

0, for χ ∈ N0 and χ < α,

Γ(χ+1)Γ(χ+1−α)

tχ−α, for χ ∈ N0 and χ ≥ α or χ /∈ N0 and χ > α.(2)

It has following two basic properities for m− 1 ≤ α < m and f ∈ L1[a, b]:

(cDαcIαf)(t) = f(t) (3)

and

(cIαcDαf)(t) = f(t)−∑m−1

k=0f (k)(0+)

(t− a)k

k!, t > 0 (4)

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2.2. Properties of the SCPsSCPs are considered as useful tools to solve the fractional equation in the

physical problems. The well-known Chebyshev polynomials satisfy the followingterm recurrence relation:

Ti+1(t) = 2tTi(t)− Ti−1(t), i = 1, 2, ... (5)

where T0(t) = 1, T1(t) = t. t is defined on the interval [−1, 1] and i = 1, 2, · · ·.On the interval [0, L], where L is a non-negative real number, the SCPs are

defined by the change of variable t = 2xL − 1. Let the SCPs Ti(

2xL − 1) denote

by Gi(x), which can be obtained as follows:

Gi+1(x) = 2(2x

L− 1)Gi(x)−Gi−1(x), i = 1, 2, ... (6)

where G0(x) = 1, G1(x) = 2xL − 1. The analytic form of Gi(x) of i-degree is

given by:

Gi(x) = i

i∑k=0

(−1)i−k (i+ k − 1)!22k

(i− k)!(2k)!Lkxk, i = 1, 2, ... (7)

where Gi(0) = (−1)i and Gi(L) = 1. The orthogonally condition is∫ L

0

Gj(x)Gk(x)ωL(x)dx = hk, (8)

where ωL(x) =1√

Lx−x2and hk =

bk2 π, k = j,0, k = j,

b0 = 2, bk = 1, k ≥ 1.

The operational matrix is defined by:

Φn(x) = [G0(x), G1(x), · · · , Gn(x)]T (9)

The following equation can be obtained:

Φn(x) = AnZn(x) (10)

where Zn(x) =[1, x, x2, · · · , xn

]T, and An is the SCPs coefficient matrix given

as follows:

An =

P0,0 0 · · · 0P1,0 P1,1 · · · 0

...... . . . ...

Pn,0 Pn,1 · · · Pn,n

, (11)

where P0,0 = 1,Pi,j = 2( 2

LPi−1,j−1 − Pi−1,j)− Pi−2,j ,Pi,j = 0, for i < j or i < 0 or j < 0.

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Obviously, An is full rank and reversible.

2.3. Visco-elastic constitutive and fractional derivative modelsThe general form of a one-dimensional generalized fractional constitutive

equation describing the stress-strain relationship of a visco-elastic material is:n∑

κ=0

µκdpκσ(t)

dtpκ=

n∑κ=0

ηκdqκε(t)

dtqκ(12)

where dκ/dtκ uses the Caputo type fractional differential definition, σ is thestress, ε is the strain, µκ, ηκ are the material constants. κ is a positive inte-ger. And pκ, qκ are real numbers corresponding to fractional order of the timederivative.

When pκ, qκ = 0, the constitutive equation becomes ideal elastic behaviourlaw or Hooke’s law. When pκ = 0, qκ = 1, the constitutive equation becomesideal viscous behaviour law or Newton’s law. When 0 < qκ < 1, the constitutiveequation could be used to describe the physical behaviour of a visco-elasticmaterial. In the current visco-elastic constitutive fractional derivative models,the first order derivatives d/dt are replaced by the fractional derivatives dqκ/dtqκwith 0 < qκ < 1.

(a) (b)

Fig. 1. Schematic representation of visco-elastic model: (a) the FDE model; (b) the FDKVmodel.

The simplest fractional model of visco-elastic media is the FDE model [47]as shown in Fig. 1(a), which has the following form of stress-strain relationship

σ(t) = ηdαε(t)

dtα(13)

By replacing the elastic and viscous elements of the classical linear viscoelas-tic model with fractional elements, two fractional elements arranged in parallelcan obtained as shown in Fig. 1(b), which is the FDKV model [47]. And itsconstitutive equation as follows:

σ(t) = η1dβε(t)

dtβ+ η2

dγε(t)

dtγ(14)

where η1, η2 are the material dependent constants, and 0 < β, γ < 1.

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3. Numerical algorithm

3.1. Approximation of functionFor arbitrary continuous function ω(x, t) ∈ L2([0, L] × [0, T ]), it can be

expanded as the following formula:

ω(x, t) =

∞∑i=0

∞∑j=0

ωijGi(x)Gj(t) (15)

where ωij =1

hihj

∫ L

0

∫ T

0ω(x, t)Gi(x)Gj(t)ωL(x)ωT (t)dtdx, i, j = 0, 1, 2, · · ·.

If we consider truncated series in Eq. (15), then it can rewritten as:

ω(x, t) ≈n∑

i=0

n∑j=0

ωijGi(x)Gj(t) = ΦTn (x)UΦn(t) (16)

where Φn(x) = [G0(x), G1(x), · · · , Gn(x)]T , Φn(t) = [G0(t), G1(t), · · · , Gn(t)]

T ,U = uijn,ni,j=0.

3.2. SCPs differential operator matrix3.2.1. First order differential operator matrix of SCPs

Definition 2. If there is matrix P(1)x , satisfying d

dxΦn(x) = P(1)x Φn(x), then

P(1)x is called the first order differential operator matrix of SCPs.

By calculating the first order derivative of Φn(x), ddxΦn(x) can expressed as:

d

dxΦn(x) = (AXZn(x))

′= AXZ ′

n(x)

= AX

1′

x′

...(xn)

= AX

01...

nxn−1

= AXV(n+1)×nZ∗n(x)

(17)

and

V(n+1)×n =

0 0 · · · 01 0 · · · 00 2 · · · 0...

... . . . 00 0 · · · n

, Z∗n(x) =

1x...

xn−2

xn−1

(18)

By using Eq. (10), Z∗n(x) is obtained as:

Z∗n(x) = B∗

XΦn(x) (19)

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where B∗X =

[A−1

X, [1], A−1X, [2], · · · , A−1

X, [n]

]T.

According to Eq. (16), Eq. (19) can rewritten as:

d

dxΦn(x) = AXV(n+1)×nB

∗XΦn(x) (20)

where P(1)x = AXV(n+1)×nB

∗X is a first order differential operator matrix of the

SCPs. Substituting Eq. (11), Eq. (17) and matrix B∗X into P

(1)x :

P (1)x = [λ0, λ1, · · · , λi, · · · , λn]

T , i = 0, 1, · · · , n (21)

where λi =i∑

j=1

jPijA−1x, [j].

Now, using Eq. (16) and Eq. (20), we get:

∂ω(x, t)

∂x≈ ∂(ΦT

n (x)UΦn(t))

∂x

= ΦTn (x)(P

(1)x )TUΦn(t)

= ΦTn (x)(AXV(n+1)×nB

∗X)TUΦn(t)

(22)

Furthermore, the higher-order differential operator matrices derived fromSCPs by mathematical induction have the following form:

dn

dxnΦn(x) =

(P (1)x

)nΦn(x) (23)

3.2.2. Fractional order differential operator matrix of the SCPs

Definition 3. If there is matrix P βt (t), satisfying cDβ

t Φn(t) = P βt (t)Φn(t), then

P βt (t) is called fractional order differential operator matrix of SCPs.

By taking the fractional derivative of Φn(t), we obtain:

cDβt ω(x, t) ≈

cDβt

(ΦT

n (x)UΦn(t))

= ΦTn (x)UcDβ

t Φn(t)

= ΦTn (x)U

[0, · · · ,

Γ (β + 1)

Γ (β + 1− β)tβ−β , · · · ,

Γ (i+ 1)

Γ (i+ 1− β)ti−β , · · ·

]T= ΦT

n (x)UATV β(n+1)×(n+1)

A−1T Φn(t)

(24)

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where i = β, β + 1, · · · , n, P βt (t) = ATV

β(n+1)×(n+1)A

−1T , and

V β(n+1)×(n+1) =

0 · · · 0 · · · 0 · · · 0...

. . ....

......

......

0 · · · Γ(β+1)t−β

Γ(β+1−β)· · · 0 · · · 0

......

.... . .

......

...0 · · · 0 · · · Γ(i+1)t−β

Γ(i+1−β)· · · 0

......

......

.... . .

...0 · · · 0 · · · 0 · · · Γ(m+1)t−β

Γ(m+1−β)

(25)

The fractional order differential operator matrix P βt (t) is

P βt (t) =

0 · · · 0 · · · 0 · · · 0...

......

......

......

0 · · · 0 · · · 0 · · · 0Sβ (β, 0) · · · Sβ (β, β) · · · 0 · · · 0

......

.... . .

......

...Sβ (i, 0) · · · Sβ (i, β) · · · Sβ (i, i) · · · 0

......

......

.... . .

...Sβ (n, 0) · · · Sβ (n, β) · · · Sβ (n, i) · · · Sβ (n, n)

(26)

4. Establishment and solution of government equations for visco-elastic rotating beam

4.1. Beam governing equation under the FDKV modelA visco-elastic rotating beam is considered in this study. A distributed load

is applied on the vertical direction of the beam. The beam is made of a visco-elastic material. The bending deformation occurs on the beam in the verticaldirection, as shown in Fig. 2, in which ω(x, t) is the beam deflection, f(x, t) isthe distributed load, Ω is the speed and l is the length of the beam.

For visco-elastic beams, the stress and strain satisfy the two-dimensionalFDKV model can be expressed as:

σ(x, t) = η1cDβ

t ε(x, t) + η2cDγ

t ε(x, t) (27)

where ε(x, t) is the transverse strain, η1, η2, β, γ are parameters of visco-elasticmaterial, cDβ

t ,cDγ

t use the Caputo type fractional differential definition.The relation between the strain and the displacement can be expressed as:

ε(x, t) = z∂2ω(x, t)

∂x2(28)

where x and z represent the axial and transverse coordinates.

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Fig. 2. The bending deformation of the visco-elastic rotating beam under distributed load.

The bending moment M(x, t) of the beam is written as:

M(x, t) =

∫A

zσ(x, t)dz (29)

where σ(x, t) is the normal stress on the cross-section.Using Eq. (27), the beam bending moment M(x, t) is equal to:

M(x, t) = η1IcDβ

t

∂2ω(x, t)

∂x2+ η2I

cDγt

∂2ω(x, t)

∂x2(30)

where I is the moment of inertia of the section given by∫Az2dA.

The potential energy of the rotating beam is

U =1

2

∫ L

0

M(x, t)∂2ω(x, t)

∂x2dx+

1

2

∫ L

0

Tx∂2ω(x, t)

∂x2dx (31)

Rotating centrifugal force Tx can be expressed as:

Tx = ρAΩ2x (32)

Kinetic energy is

T =1

2

∫ L

0

ρA∂2ω(x, t)

∂t2dx (33)

The beam is subjected to a load of f(x, t), according to the Hamiltonianprinciple, we obtain that

δ

∫ t2

t1

(T − U)dt+

∫ t2

t1

δWdt = 0 (34)

where the work done by the external load W = 12∫ l

0f(x, t)ω(x, t)dx.

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The governing equation of the visco-elastic rotating beam under the FDKVconstitutive model is obtained:

ρA∂2ω(x, t)

∂t2+η1I

CDβt

∂4ω(x, t)

∂x4+η2I

CDγt

∂4ω(x, t)

∂x4−ρAΩ2x

∂2ω(x, t)

∂x2= f(x, t) (35)

4.2. Beam governing equation under the FDE modelThe stress and strain satisfy the FDE constitutive model is proposed:

σ(x, t) = ηcDαt ε(x, t) (36)

According to Eq. (36), the beam bending moment M(x, t) can be rewrittenas:

M(x, t) = ηIcDαt

∂2ω(x, t)

∂x2(37)

where I is the moment of inertia of the section given by∫Az2dA.

The governing equation of the visco-elastic rotating beam under the FDKVconstitutive model is obtained as follows:

ρA∂2ω(x, t)

∂t2+ ηIcDα

t

∂4ω(x, t)

∂x4− ρAΩ2x

∂2ω(x, t)

∂x2= f(x, t) (38)

4.3. The solution of governing equation based on SCPsBased on integer order differential operator matrix of SCPs in the Section

3.2.1, the following equations can be obtained:

∂2ω(x, t)

∂x2≈ ∂2(ΦT

n (x)UΦn(t))

∂x2

= ΦTn (x)((P

(1)x )T )2UΦn(t)

= ΦTn (x)((AXV(n+1)×nB

∗X)T )2UΦn(t)

(39)

∂4ω(x, t)

∂x4≈ ∂4(ΦT

n (x)UΦn(t))

∂x4

= ΦTn (x)((P

(1)x )T )4UΦn(t)

= ΦTn (x)((AXV(n+1)×nB

∗X)T )4UΦn(t)

(40)

∂2ω(x, t)

∂t2≈ ∂2(ΦT

n (x)UΦn(t))

∂t2

= ΦTn (x)U(P

(1)t )2Φn(t)

= ΦTn (x)U(ATV(n+1)×nB

∗T )

2Φn(t)

(41)

By the fractional order differential operator matrix of SCPs in the Section

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3.2.2, the following equations can be obtained:

cDβt

∂4ω(x, t)

∂x4≈ cDβ

t ΦTn (x)

((AXV(n+1)×nB

∗X)

T)4

UΦn(t)

= ΦTn (x)

((AXV(n+1)×nB

∗X)

T)4

U cDβt Φn(t)

= ΦTn (x)

((AXV(n+1)×nB

∗X)

T)4

UATPβt (t)A

−1T Φn(t)

(42)

Similarly,

cDγt

∂4ω(x, t)

∂x4≈ cDγ

t ΦTn (x)

((AXV(n+1)×nB

∗X)

T)4

UΦn(t)

= ΦTn (x)

((AXV(n+1)×nB

∗X)

T)4

U cDγt Φn(t)

= ΦTn (x)

((AXV(n+1)×nB

∗X)

T)4

UATPγt (t)A

−1T Φn(t)

(43)

where P γt (t) is obtained by replacing β with γ in Eq. (26).

The gverning equation Eq. (35) can be rewritten into the operator matrixform as follows:

ρAΦTn (x)U

(P

(1)t

)2Φn(t) + η1IΦ

Tn (x)

((P

(1)x )

T)4

UPβt (t)Φn(t)

+η2IΦTn (x)

((P

(1)x )

T)4

UP γt (t)Φn(t)− ρAΩ2xΦT

n (x)

((P

(1)x )

T)2

UΦn(t) = f(x, t)

(44)

Specifically, Eq. (44) can be written as:

ρAΦTn (x)U

(ATV(n+1)×nB

∗T

)2Φn(t) + η1IΦ

Tn (x)

((AXV(n+1)×nB

∗X)T

)4UAT×

V β(n+1)×(n+1)

A−1T Φn(t) + η2IΦ

Tn (x)

((AXV(n+1)×nB

∗X)T

)4UAT×

V γ(n+1)×(n+1)

A−1T Φn(t)− ρAΩ2x

((AXV(n+1)×nB

∗X)T

)2UΦn(t) = f(x, t)

(45)

Similarly, the governing equation Eq. (38) can be rewritten into the operatormatrix form as follows:

ρAΦTn (x)U

(P

(1)t

)2Φn(t) + ηIΦT

n (x)

((P

(1)t )

T)4

UPαt (t)Φn(t)

−ρAΩ2xΦTn (x)

((P

(1)x )

T)2

UΦn(t) = f(x, t)

(46)

The Eq. (46) can be written as:

ρAΦTn (x)U

(ATV(n+1)×nB

∗T

)2Φn(t) + ηIΦT

n (x)((AXV(n+1)×nB

∗X)T

)4UAT×

V α(n+1)×(n+1)A

−1T Φn(t) − ρAΩ2x

((AXV(n+1)×nB

∗X)T

)2UΦn(t) = f(x, t)

(47)

11

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where Pαt (t) is obtained by replacing β with α in Eq. (26).

Based on the collocation method, the reasonable match points xi =2i−1

2(n+1)L,

i = 0, 1, 2, · · · , n, ti =2j−1

2(n+1)T, j = 0, 1, 2, · · · , n have been used to dis-cretize the variable (x, t) to (xi, tj). Eq. (35) and Eq. (38) are transformed intoa set of algebraic equations. The coefficient ωi,j (i = 1, 2, · · · , n; j = 1, 2, · · · , n)is determinate by using Matlab platform and least square method. The numer-ical solution of the fractional derivative equations can be obtained.

5. Convergence analysis

In this section, for any function, the norm is defined as

∥ω (x, t)∥ = sup(x,t)∈Λ

|ω (x, t)| (48)

Theorem 1. Suppose ω (x, t) ∈ C3 (Λ), ω (x, t) is the exact solution of the

fractional governing equation, ωn (x, t) is the numerical solution. Then the

error bound is

∥en (x, t)∥ = ∥ω (x, t)− ωn (x, t)∥ ≤ Nh3 = O(h3)

(49)

Proof 1. Let

en,ij (x, t) =

ω (x, t)− ωn (x, t)

0

(x, t) ∈ Λn

(x, t) ∈ Λ− Λn

(50)

where Λn = (x, t)| ih ≤ x < (i+ 2)h, jh ≤ t < (j + 2)h, i, j = 0, 2, · · · , n− 2.

ωn(x, t) is the quadratic polynomial interpolation function on ω(x, t) on Λn.

Then,

en,ij (x, t) =1

6

∂3ω (ξ1,i, t)

∂x3

i+2∏i′=i

(x− xi′) +1

6

∂3ω (x, ζ1,j)

∂t3

j+2∏j′=j

(t− tj′)

− 1

36

∂6ω (ξ2,i, ζ2,j)

∂x3∂t3

i+2∏i′=i

(x− xi′)

j+2∏j′=j

(t− tj′)

(51)

where x, ξ1,i, ξ2,i ∈ [xi, xi+2), and t, ζ1,j , ζ2,j ∈ [tj , tj+2), i, j = 0, 2, · · · , n− 2.

12

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So,

∥en,ij (x, t)∥ =1

6

∥∥∥∥∂3ω (ξ1,i, t)

∂x3

∥∥∥∥∥∥∥∥∥i+2∏i′=i

(x− xi′)

∥∥∥∥∥+

1

6

∥∥∥∥∂3ω (x, ζ1,j)

∂t3

∥∥∥∥∥∥∥∥∥∥j+2∏j′=j

(t− tj′)

∥∥∥∥∥∥+

1

36

∥∥∥∥∂6ω (ξ2,i, ζ2,j)

∂x3∂t3

∥∥∥∥∥∥∥∥∥i+2∏i′=i

(x− xi′)

∥∥∥∥∥∥∥∥∥∥∥j+2∏j′=j

(t− tj′)

∥∥∥∥∥∥

(52)

where∥∥∥∥i+2∏i′=i

(x− xi′)

∥∥∥∥ = supx∈[xi,xi+2)

∣∣∣∣i+2∏i′=i

(x− xi′)

∣∣∣∣.According to |

i+2∏i′=i

(x− xi′)| is the maximum value of x = (i+ 1−√33 )h, we

can get:

∥∥∥∥∥i+2∏i′=i

(x− xi′)

∥∥∥∥∥ ≤ 2√3h3

9,∀x ∈ [xi, xi+2) (53)

∥∥∥∥∥∥j+2∏j′=j

(t− tj′)

∥∥∥∥∥∥ ≤ 2√3h3

9,∀t ∈ [tj , tj+2) (54)

Substituting Eq. (53) and Eq. (54) into Eq. (52), we can get:

∥en (x, t)∥ ≤√3h3

27

(∥∥∥∥∂3ω (x, t)

∂x3

∥∥∥∥+ ∥∥∥∥∂3ω (x, t)

∂t3

∥∥∥∥+ √3h3

27

∥∥∥∥∂6ω (x, t)

∂x3∂t3

∥∥∥∥)

= Nh3 = O(h3) (55)

In summary, the theorem is proved.

6. Numerical analysis

Based on HDPE, PEEK and rock creep experimental data, Xu et al. [47]used the interior point method to solve the corresponding nonlinear optimizationconstraint problem. The best simulation parameters of FDE model, fractionalMaxwell model, FDKV model and fractional Poynting-Thomson model were

13

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obtained. This paper uses HDPE and PEEK to have the best simulation pa-rameters [47] of the FDE model and the parameters of HDPE in the FDKVmodel as Tab. 1 and Tab. 2.

Table 1 The best simulation parameters of HDPE and PEEK under FDE constitutive model.

Material β γ η1 η2

HDPE 0.3320 0.1088 2.874 × 105Pa 1.558 × 105Pa

Table 2 The best simulation parameters of HDPE under FDKV constitutive model.

Material α η

HDPE 0.1603 3.341 × 105PaPEEK 0.2341 5.50 × 106Pa

Let the beam length l = 2.5m and the cross-section area A = 0.04m2.Moment of inertia I = (0.2)4

12 . Based on SCPs method, the numerical solutionsof the displacement of the visco-elastic rotating beams under the FDE modeland the FDKV model are solved. Assuming that the visco-elastic beam is acantilever beam, the boundary conditions and initial conditions are

ω(0, t) = ∂ω(0,t)∂x = 0

∂2ω(l,t)∂x2 = ∂3ω(l,t)

∂x3 = 0

ω(x, 0) = 0, ∂ω(x,0)∂t = 0

(56)

6.1. Numerical solutions of HDPE beam under FDKV modelIn this section, the displacements of HDPE rotating beam under different

loads under FDKV model are discussed. When Ω = 0, there is no rotationalforce. Fig. 3 shows the displacements of the non-rotating beam under differentuniform loads, simple harmonic loads and linear loads when t = 0.5s. Fig. 4shows the displacements of HDPE rotating beam under different uniform loads,simple harmonic loads and linear loads when rotating speed Ω = π/2.

0 0.5 1 1.5 2 2.5x/m

0

0.05

0.1

0.15

0.2

0.25

Def

lect

ion ω

(x)/

m

f(x,t)=10Heaviside(t)f(x,t)=20Heaviside(t)f(x,t)=30Heaviside(t)

(a)

0 0.5 1 1.5 2 2.5x/m

-0.05

0

0.05

0.1

0.15

Def

lect

ion ω

(x)/

m

f(x,t)=10πsin(t/2)f(x,t)=10πsin(t)f(x,t)=10πsin(3t/2)

(b)

0 0.5 1 1.5 2 2.5x/m

0

0.05

0.1

0.15

Def

lect

ion ω

(x)/

m

f(x,t)=x+10f(x,t)=3x+10f(x,t)=5x+10

(c)

Fig. 3. Displacements of HDPE non-rotating beams under different external loads: (a)Uniform loads; (b) Simple harmonic loads; (c) Linear loads.

14

Page 16: Shifted-Chebyshev-polynomial-based numerical algorithm for

0 0.5 1 1.5 2 2.5x/m

0

0.1

0.2D

efle

ctio

n ω

(x)/

mf(x,t)=10Heaviside(t)f(x,t)=20Heaviside(t)f(x,t)=30Heaviside(t)

(a)

0 0.5 1 1.5 2 2.5x/m

-0.05

0

0.05

0.1

0.15

Def

lect

ion ω

(x)/

m

f(x,t)=10πsin(t/2)f(x,t)=10πsin(t)f(x,t)=10πsin(3t/2)

(b)

0 0.5 1 1.5 2 2.5x/m

-0.05

0

0.05

0.1

0.15

Def

lect

ion ω

(x)/

m

f(x,t)=x+10f(x,t)=3x+10f(x,t)=5x+10

(c)

Fig. 4. Displacements of HDPE rotating beam at Ω = π2

under different external loads: (a)Uniform loads; (b) Simple harmonic loads; (c) Linear loads.

From Fig. 3, we can get that the displacements of the HDPE non-rotatingbeam gradually increases with time under the loads. At the same position, as theload increases, the displacement gradually increases. And the same conclusionscan also be obtained by means of Fig. 4. In [49], a Fourier series is constructedand supplemented by a boundary smoothing term to express the displacementof the rotating beam. The governing equation of Ref.[49] can be considered asthe governing Eq. (38) when α is fraction. Fig. 3 and Fig. 4 are similar tothe results of Ref.[49]. Compared with Ref.[49], the numerical result is verifiedto be correct. In addition, we can clearly see that the displacements of HDPEbeam changes with the rotation speed.

-0.051

0

0.05

2.5

ω(x

,t)

0.1

2

Ω=π/2

t

0.15

0.5 1.5

x

0.2

10.5

0 0

(a)

-0.051

0

2.5

0.05

ω(x

,t)

2

Ω=π

0.1

t

0.5 1.5

x

0.15

10.5

0 0

(b)

Fig. 5. Displacements of HDPE rotating beam under external load f(x, t) = 10Heaviside(t)at different rotational speeds: (a) Ω = π

2; (b) Ω = π.

Fig. 5 shows the numerical solutions of the displacement of the HDPErotating beam at rotating speeds of Ω = π

2 , Ω = π under the external loadf(x, t) = 10Heaviside(t). It can be seen from the image that the proposedalgorithm has a good simulation effect to solve such problems, and the feasibilityof the algorithm is verified.

However, in the case of slight deformation, the transverse strain of the neu-

15

Page 17: Shifted-Chebyshev-polynomial-based numerical algorithm for

tral surface can be expressed as:

ε =∂2ω(x, t)

∂x2(57)

According to Eq. (27), the stress can be obtained:

σ(x, t) = η1cDβ

t

∂2ω(x, t)

∂x2+ η2

cDγt

∂2ω(x, t)

∂x2(58)

-51

0

Stre

ss(P

a)

×104

5

2.5

t(s)

0.5 2

x(m)

10

1.510.50 0

(a)

-51

0

Stre

ss(P

a)×104

5

2.5

t(s)

0.5 2

x(m)

10

1.510.50 0

(b)

-51

0

×104

Stre

ss(P

a) 5

2.5

t(s)

0.5 2

x(m)

10

1.510.50 0

(c)

Fig. 6. The stress of HDPE rotating beam at Ω = π2

under different external loads: (a)Uniform load f(x, t) = 10Heaviside(t); (b) Simple harmonic load f(x, t) = 10πsin(t); (c)Linear load f(x, t) = 10 + 2x.

Fig. 6 shows the stress of the HDPE rotating beam at the different externalloads when the rotational speed Ω = π

2 . Through the images, we can clearly seethat the closer to the fixed end of the beam, the greater the stress. Therefore,the stronger the resistance to external force deformation near x = 0, the smallerthe displacement. This is consistent with the change in the displacement mapabove. The accuracy and feasibility of the algorithm are further verified.

6.2. Comparison HDPE beams and PEEK beamsThe displacement solutions of HDPE beam and PEEK beam under different

loads of the FDE constitutive model are discussed and compared in this section.

0 0.5 1 1.5 2 2.5x/m

-0.05

0

0.05

0.1

0.15

0.2

Def

lect

ion ω

(x)/

m

t=0.4 HDPEt=0.4 PEEKt=0.7 HDPEt=0.7 PEEKt=0.9 HDPEt=0.9 PEEK

(a)

0 0.5 1 1.5 2 2.5x/m

-0.05

0

0.05

0.1

0.15

Def

lect

ion ω

(x)/

m

t=0.4 HDPEt=0.4 PEEKt=0.7 HDPEt=0.7 PEEKt=0.9 HDPEt=0.9 PEEK

(b)

0 0.5 1 1.5 2 2.5x/m

-0.05

0

0.05

0.1

0.15

0.2

0.25

Def

lect

ion ω

(x)/

m

t=0.4 HDPEt=0.4 PEEKt=0.7 HDPEt=0.7 PEEKt=0.9 HDPEt=0.9 PEEK

(c)

Fig. 7. Comparison of displacements between HDPE non-rotating beam and PEEK non-rotating beam under different external loads: (a) Uniform load f(x, t) = 10Heaviside(t); (b)Simple harmonic load f(x, t) = 10πsin(t); (c) Linear load f(x, t) = 10 + 2x.

16

Page 18: Shifted-Chebyshev-polynomial-based numerical algorithm for

0 0.5 1 1.5 2 2.5x/m

-0.05

0

0.05

0.1

0.15

0.2D

efle

ctio

n ω

(x)/

mt=0.4 HDPEt=0.4 PEEKt=0.7 HDPEt=0.7 PEEKt=0.9 HDPEt=0.9 PEEK

(a)

0 0.5 1 1.5 2 2.5x/m

-0.05

0

0.05

0.1

0.15

Def

lect

ion ω

(x)/

m

t=0.4 HDPEt=0.4 PEEKt=0.7 HDPEt=0.7 PEEKt=0.9 HDPEt=0.9 PEEK

(b)

0 0.5 1 1.5 2 2.5x/m

-0.05

0

0.05

0.1

0.15

0.2

0.25

Def

lect

ion ω

(x)/

m

t=0.4 HDPEt=0.4 PEEKt=0.7 HDPEt=0.7 PEEKt=0.9 HDPEt=0.9 PEEK

(c)

Fig. 8. Comparison of displacements between HDPE rotating beam and PEEK rotatingbeam at Ω = π

2under different external loads: (a) Uniform load f(x, t) = 10Heaviside(t);

(b) Simple harmonic load f(x, t) = 10πsin(t); (c) Linear load f(x, t) = 10 + 2x.

Obviously, as can be seen from Fig. 7 and Fig. 8, the displacement of thePEEK beam is less than the displacement of the HDPE beam when the rota-tional speed and the external load are constant. The smaller the displacement,the greater the damping of the corresponding visco-elastic material and thebetter the bending resistance. Therefore, the PEEK beam have better bendingresistance than the HDPE beam. The results obtained are consistent with theactual material properties. The proposed algorithm calculates the displacementsolution well and has high precision. Thus, this method can provide a theoreti-cal basis for the research, development and performance prediction of dampingmaterials.

7. Conclusion

In this paper, an effective numerical algorithm for solving fractional visco-elastic rotating beam based on SCPs is proposed for the first time in the time do-main. The displacements of visco-elastic beam can reflect the positional changesof beam at different times. The fractional derivative model is used to analyzethe inherent laws of the dynamic performance of visco-elastic damping mate-rials, which can provide a theoretical basis for the research, development andperformance prediction of damping materials.

1. Two governing equations of fractional visco-elastic rotating beam are es-tablished by FDE and FDKV constitutive models, the dynamic equationof beam and strain-displacement relationship.

2. According to the properties of SCPs, the integer and fractional differentialoperator matrices of polynomials are derived. Using the polynomial to ap-proximate the unknown function, the fractional order governing equationis rewritten into the form of matrix product. The variables are discretizedbased on the collocation method, and the original problem is transformedinto an algebraic equation system. The numerical solutions of the govern-ing equations can be obtained directly in the time domain.

3. Numerical examples show the displacement and stress changes of HDPErotating beam under uniform load, harmonic load and linear load un-der FDKV constitutive model, and further verify the effectiveness and

17

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feasibility of the algorithm. By comparing the displacement of differentviscoelastic beams, HDPE rotating beam and PEEK rotating beam, theproperties of materials are analyzed theoretically.

Acknowledgments

This work is supported by the Natural Science Foundation of Hebei Province(A2017203100) in China and the LE STUDIUM RESEARCH PROFESSOR-SHIP award of Centre-Val de Loire region in France.

References

[1] Sweilam NH, Almekhlafi SM. Numerical study for multi-strain tuberculosis(TB) model of variable-order fractional derivatives[J]. Journal of AdvancedResearch. 2016, 7(2): 271–283.

[2] Ramirez, Coimbra. A variable order constitutive relation for viscoelastic-ity[J]. Annalen Der Physik. 2010, 16(7-8): 543–552.

[3] Lorenzo CF, Hartley TT. Initialization, conceptualization, and applicationin the generalized (fractional) calculus[J]. Critical Reviews in Biomedical En-gineering. 2007, 35(6): 447–553.

[4] Meerschaert MM, Scalas E. Coupled continuous time random walks in fi-nance[J]. Physica A Statistical Mechanics And Its Applications. 2006, 370(1):114–118.

[5] Chen W. Nonlinear dynamics and chaos in a fractional-order financial sys-tem[J]. Chaos Solitons and Fractals. 2008, 36(5): 1305–1314.

[6] Du M, Wang Z, Hu H. Measuring memory with the order of fractional deriva-tive[J]. Scientific Reports. 2013, 3(7478):3431.

[7] Gemant A. On fractional differences[J]. Phil Mag. 1938, 25(1):92–96.

[8] Bagley RL, Torvik PJ. On the fractional calculus model of viscoelasticitybehavior[J]. Journal of Rheology. 1986, 30(1):133–155.

[9] Leung AYT, Yang HX, Zhu P, Guo ZJ. Steady state response of fraction-ally damped nonlinear viscoelastic arches by residue harmonic homotopy[J].Computers and Structures. 2013, 121(5):10–21.

[10] Lewandowski R, Pawlak Z. Dynamic analysis of frames with viscoelasticdampers modelled by rheological models with fractional derivatives[J]. Jour-nal of Sound and Vibration. 2011, 330(5):923–936.

[11] Kang JH, Zhou FB, Liu C, Liu YK. A fractional nonlinear creep model forcoal considering damage effect and experimental validation[J]. InternationalJournal of Non-Linear Mechanics. 2015, 76:20–28.

18

Page 20: Shifted-Chebyshev-polynomial-based numerical algorithm for

[12] Gioacchino A, Mario DP, Giuseppe F. On the dynamics of non-local frac-tional viscoelastic beams under stochastic agencies[J]. Composites Part B:Engineering. 2018, 131:102–110.

[13] Lewandowski R, Wielentejczyk P. Nonlinear vibration of viscoelastic beamsdescribed using fractional order derivatives[J]. Journal of Sound and Vibra-tion. 2017, 339(2):228–243.

[14] Lewandowski R, Baum M. Dynamic characteristics of multilayered beamswith viscoelastic layers described by the fractional Zener model[J]. Archive ofApplied Mechanics. 2015, 85(12):1793–1814.

[15] Cortes F, Elejabarrieta MJ. Finite element formulations for transient dy-namic analysis in structural systems with viscoelastic treatments containingfractional derivative models[J]. International Journal for Numerical Methodsin Engineering. 2007, 69(10):2173–2195.

[16] Bahraini SMS, Farid M, Ghavanloo E. Large deflection of viscoelasticbeams using fractional derivative model[J]. Journal of Engineering Mathe-matics. 2013, 27(4):1063–1070.

[17] Paola MD, Heuer R, Pirrotta A. Fractional visco-elastic Euler–Bernoullibeam[J]. International Journal of Solids and Structures. 2013, 50(22-23):3505–3510.

[18] He XQ, Rafiee M, Mareishi S, Liew KM. Large amplitude vibration offractionally damped viscoelastic CNTs/fiber/polymer multiscale compositebeams[J]. Composite Structures. 2015, 131:1111–1123.

[19] Magdalena LP, Lewandowski R. Sensitivity Analysis of Dynamic Charac-teristics of Composite Beams with Viscoelastic Layers[J]. Procedia Engineer-ing. 2017, 199:366–371.

[20] Kiasat MS, Zamani HA, Aghdam MM. On the transient response of vis-coelastic beams and plates on viscoelastic medium[J]. International Journalof Mechanical Sciences. 2014, 83(7-8):133–145.

[21] Chang JR, Lin WJ, Huang CJ, Choi ST. Vibration and stability of anaxially moving Rayleigh beam[J]. Applied Mathematical Modelling. 2010,34(6):1482–1497.

[22] Friswell MI, Adhikari S, Lei Y. Vibration analysis of beams with non-local foundations using the finite element method[J]. International Journalfor Numerical Methods in Engineering. 2007, 71(11):1365–1386.

[23] Demir DD, Bildik N, Sınır BG. Linear dynamical analysis of fraction-ally damped beams and rods[J]. Journal of Engineering Mathematics. 2014,85(1):131–147.

19

Page 21: Shifted-Chebyshev-polynomial-based numerical algorithm for

[24] Permoon MR, Rashidinia J, Parsa A, Haddadpour H, Salehi R. Applicationof radial basis functions and sinc method for solving the forced vibration offractional viscoelastic beam[J]. Journal of Mechanical Science and Technology.2016, 30(7):3001–3008.

[25] Martin O. A modified variational iteration method for the analysis of vis-coelastic beams[J]. Applied Mathematical Modelling. 2016, 40(17):7988–7995.

[26] Akritas P, Antoniou I, Ivanov VV. Identification and prediction of discretechaotic maps applying a Chebyshev neural network[J]. Chaos, Solitons andFractals. 2000, 11(1-3):337–344.

[27] Sun KK, Mou SS, Qiu JB, Wang T, Gao HJ. Adaptive Fuzzy Control forNon-Triangular Structural Stochastic Switched Nonlinear Systems with FullState Constraints[J]. IEEE Transactions on Fuzzy Systems. 2019, 27(8):1587–1601.

[28] Qiu JB, Sun KK, Wang T, Gao HJ. Observer-Based Fuzzy Adaptive Event-Triggered Control for Pure-Feedback Nonlinear Systems with Prescribed Per-formance[J]. IEEE Transactions on Fuzzy Systems. 2019, 27(11):2152–2161.

[29] Qiu JB, Sun KK, Rudas IJ, Gao HJ. Command Filter-Based AdaptiveNN Control for MIMO Nonlinear Systems With Full-State Constraints andActuator Hysteresis[J]. IEEE Transactions on Fuzzy Systems. 2019, 1–11.

[30] Tadjeran C, Mark M. Meerschaert and Hans-Peter Scheffler. A second-orderaccurate numerical approximation for the fractional diffusion equation[J].Journal of Computational Physics. 2006, 213(1):205-213.

[31] Meng ZJ, Yi MX, Huang J, Lei S. Numerical solutions of nonlinear frac-tional differential equations by alternative Legendre polynomials[J]. AppliedMathematics and Computation. 2018, 336:454–464.

[32] Chen YM, Sun YN, Liu LQ. Numerical solution of fractional partial dif-ferential equations with variable coefficients using generalized fractional-order Legendre functions[J]. Applied Mathematics and Computation. 2014,244(2):847–858.

[33] Xie JQ, Yao ZB, Gui HL, Zhao FQ, Li DY. A two-dimensional Chebyshevwavelets approach for solving the Fokker-Planck equations of time and spacefractional derivatives type with variable coefficients[J]. Applied Mathematicsand Computation. 2018, 332:197–208.

[34] Chen YM, Sun L, Li X, Fu XH. Numerical solution of nonlinear fractionalintegral differential equations by using the second kind Chebyshev wavelets[J].Computer Modeling in Engineering and Sciences. 2013, 90(5):359–378.

[35] Wang J, Xu TZ, Wei YQ, Xie JQ. Numerical solutions for systems of frac-tional order differential equations with Bernoulli wavelets[J]. InternationalJournal of Computer Mathematics. 2018, 96(2):317–336.

20

Page 22: Shifted-Chebyshev-polynomial-based numerical algorithm for

[36] Chen YM, Liu LQ, Liu DY, Boutat D. Numerical study of a class of vari-able order nonlinear fractional differential equation in terms of Bernsteinpolynomials[J]. Ain Shams Engineering Journal. 2016,1235–1241.

[37] Chen YM, Liu LQ, Li BF, Sun YN. Numerical solution for the variable or-der linear cable equation with Bernstein polynomials[J]. Applied Mathematicsand Computation. 2014, 238(7):329–341.

[38] Fernanda SP, Miguel P, Higinio R. Extrapolating for attaining high pre-cision solutions for fractional partial differential equations[J]. Fractional Cal-culus and Applied Analysis. 2018, 21(6):1506–-1523.

[39] Suman S, Kumar A, Singh GK. A new method for higher-order linear phaseFIR digital filter using shifted Chebyshev polynomials[J]. Signal Image andVideo Processing. 2016, 10(6):1041–1048.

[40] Zaicenco AG. Sensitivity analysis of a seismic risk scenario using sparseChebyshev polynomial expansion[J]. Geophysical Journal International. 2015,200(3):1466–1482.

[41] Xing S, Guo HW. Temporal phase unwrapping for fringe projection pro-filometry aided by recursion of Chebyshev polynomials[J]. Applied Optics.2017, 56(6):1591–1602.

[42] Protasov V, Jungers R. Analysing the Stability of Linear Systems via Expo-nential Chebyshev Polynomials[J]. IEEE Transactions on Automatic Control.2016, 61(3):795–798.

[43] Srivatsa BK, Ganguli R. Non-rotating beams isospectral to rotatingRayleigh beams[J]. International Journal of Mechanical Sciences. 2018, 142-143:440–455.

[44] Tian JJ, Su JP, Kai Z, Hua HX. A modified variational method for nonlin-ear vibration analysis of rotating beams including Coriolis effects[J]. Journalof Sound and Vibration. 2018, 426:258–277.

[45] Bazoune A. Effect of tapering on natural frequencies of rotating beams[J].Shock and Vibration. 2014, 14(14):169–179.

[46] Banerjee JR, Su H, Jackson DR. Free vibration of rotating tapered beamsusing the dynamic stiffness method[J]. Journal of Sound and Vibration. 2006,298(4):1034–1054.

[47] Xu HY, Jiang XY. Creep constitutive models for viscoelastic materialsbased on fractional derivatives[J]. Computers and Mathematics with Appli-cations. 2017, 73(6):1377–1384.

[48] Lin YM, Xu CJ. Finite difference/spectral approximations for the time-fractional diffusion equation[J]. Journal of Computational Physics. 2007,255(2):1533–1552.

21

Page 23: Shifted-Chebyshev-polynomial-based numerical algorithm for

[49] Chen Q, Du JT. A Fourier series solution for the transverse vibration ofrotating beams with elastic boundary supports[J]. Applied Acoustics. 2019,155:1–15.

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