Free vibration analysis of a functionally graded material beam: evaluation of the Haar wavelet method.
Accuracy and complexity are two key factors characterizing any numerical method. The Haar wavelet method (HWM) considered in the current study was introduced by Chen and Hsiao in [1,2] almost 20 years ago and up to now it has been applied for solving a wide class of differential and integral equations covering engineering, economic, etc. problems [3-7]. An overview of the applications of the HWM is given in . The wavelet techniques based on the use of an operational matrix of integration are developed for solving ordinal and partial differential equations in [1-10] and for integral equations in [11-13]. All these studies implement the strong formulation based approach of the HWM. The weak formulation based approach of the HWM was introduced in .
Most of the authors characterize the HWM as a simple and effective method [3-9]. These estimates cover mainly implementation of the HWM, less its accuracy and convergence results, which are still under development. It is shown in  that in the case of function approximation with direct expansion into the Haar wavelet the convergence is of order one. However, according to the HWM approach considered, the highest order derivative included in the differential equation is expanded into a series of Haar functions. Thus, the estimate given in  holds good for estimating the accuracy of the highest order derivative, but not the solution of the differential equation. Recently, the convergence theorem of the HWM was proved in  for the nth order ordinal differential equations (ODEs) (n [greater than or equal to] 2). It was stated that the order of convergence of the HWM is equal to two. In  the accuracy estimates for the extrapolated results in the case of the fourth order ODE are derived, and it is shown that the order of convergence of the extrapolated results is equal to four (Richardson extrapolation is applied).
The application area of new simple methods often includes problems with advanced material models, constitutive laws, etc., which are not yet (well) covered by commercial software.
A new trend in the development of wavelet methods can be outlined as solution of fractional differential and integral equations [15, 18-24], which is an area not yet well covered by commercial software (finite element method (FEM), etc.). It is observed in  that in the case of fractional ODE the order of convergence of the HWM is equal to two if higher order derivative [alpha] in the fractional differential equation exceeds one ([alpha] > 1). However, in the case of 0 < [alpha] < 1 the order of convergence of the HWM tends to the value 1 + [alpha].
In [25,26] the HWM was adapted for the analysis of structures of functionally graded material (FGM). In the current study the vibration analysis of the FGM beams is performed and the results obtained by the HWM are compared with the corresponding results obtained by using the finite difference method (FDM) and the differential quadrature method (DQM). Selection of FDM and DQM for comparison of results was motivated by the fact that these methods are widely used numerical methods in engineering and are based on strong formulation (the complexity of implementation is similar). The methods considered are implemented by the authors in the MATLAB code.
In order to verify the obtained results and prepare solution procedures for structures with complex geometry and loading cases, the solid element 3D finite element model was developed.
2. BASICS OF HAAR WAVELETS
The Haar function is defined in [8,9] as
[mathematical expression not reproducible] (1)
In (1) i = m + k + 1, m = [2.sup.j] is the maximum number of square waves that can be sequentially deployed in interval [A, B] and the parameter k indicates the location of the particular square wave,
[mathematical expression not reproducible] (2)
The Haar functions are orthogonal to one another and form a good transform basis
[mathematical expression not reproducible] (3)
Any function f (x) that is square integrable and finite in the interval ([A, B] can be expanded into Haar wavelets as
[mathematical expression not reproducible] (4)
The integrals of the Haar functions (1) of order n can be calculated analytically as 
[mathematical expression not reproducible] (5)
The integrals of the Haar functions determined by (5) are continuous functions in the interval [A,B].
3. FREE VIBRATION ANALYSIS OF THE FGM BEAM
In the following the free vibration analysis of the FGM beam is considered [27-29]. It is assumed that the material properties of the beam of length L vary axially. The governing differential equation of the beam can be written as
[mathematical expression not reproducible] (6)
The varying properties of the bending stiffness EI(x) and the distributed mass per unit length [rho]A(x) are described by exponential functions as
[mathematical expression not reproducible] (7)
The reference values of the bending stiffness and distributed mass per unit length at x = 0 are denoted by EI(0) and [rho]A(0), respectively. Relation (7) is used in a number of papers [27-29]. The volume fractions of the material corresponding to relation (7) can be derived as
[mathematical expression not reproducible] (8)
The wavelet method approach considered can be applied for a wide range of functions describing properties of FGM. In the following a more general power law relation for describing FG materials is considered:
[mathematical expression not reproducible] (9)
[mathematical expression not reproducible] (10)
Here k is the non-negative power-law exponent describing the material variation profile along the length of the beam and the indexes L and R stand for the values of the material properties on the left and right support of the beam, respectively. Relations (9)-(10) seem to be the most widely used relations for describing FGM properties found in the literature .
In the following the solution of the partial differential equation (6) is assumed in the form
w(x,t) = W (x)sin([omega]t). (11)
Considering Eqs (7) and (11), the governing differential equation (6) can be rewritten in a non-dimensional form as
[mathematical expression not reproducible] (12)
[mathematical expression not reproducible] (13)
As a result, the vibration analysis problem of the FGM beam considered above is converted to solving the ordinal differential equation (12). The particular boundary conditions are introduced in Section 7.
4. THE HAAR WAVELET DISCRETIZATION METHOD
Herein the most commonly used approach of the HWM is employed. According to this method, the highest order derivative existing in a differential equation is expanded into Haar wavelets. Thus, Eq. (12) implies that the fourth order derivative should be expanded into Haar wavelets as
[mathematical expression not reproducible] (14)
where N = 2M is the resolution used.
The solution of the differential governing equation (12) W(X) can be obtained by integrating the expansion (14) four times with respect to X as
[mathematical expression not reproducible] (15)
In (15) the operational matrix of integration [P.sup.4] is defined by formulas (5) and [[alpha].sup.T] is a vector of coefficients. The integration constants [c.sub.0],...,[c.sub.3] can be determined for each particular boundary condition separately. Corresponding expressions of the integration constants are omitted for conciseness sake.
Inserting the solution of (15) in the differential equation (12) and assuming uniform grid points in the form
[mathematical expression not reproducible] (16)
one obtains a linear system of algebraic equations, which can be solved with respect to coefficient vector [a.sup.T]. Finally, substituting the values of [a.sup.T] in (15) gives the solution of the posed problem in an analytical form.
5. CONVERGENCE AND ACCURACY ESTIMATES
The convergence theorem for the HWM is given in  for the nth order ODE (n[greater than or equal to]2) as
THEOREM: Let us assume that [mathematical expression not reproducible] is a continuous function on [0,1] and its first derivative is bounded
[mathematical expression not reproducible] (17)
Then the HWM, based on the approach in [1,2], will be convergent, i.e. [E.sub.M] will vanish as the number of collocation points approaches N infinity. The convergence is of the order two
[mathematical expression not reproducible] (18)
The proof of the theorem is given in . Furthermore, the quadrate of the [L.sup.2] -norm of the error function can be estimated as
[mathematical expression not reproducible] (19)
In the case of the considered problem the highest order derivative in differential equation equals four (n = 4) and formula (19) reduces to
[mathematical expression not reproducible] (20)
Furthermore, it is proved in  that in the case of the general fourth-order ODE the accuracy of the results of the HWM can be improved from two to four by applying Richardson's extrapolation method. The theoretical estimates pointed out above are validated numerically in the following section.
6. FEM SIMULATION MODEL
Commercial analysis software Mechanical APDL 16.0 was used to develop a 3D finite element simulation model for free vibration analysis of an axially functionally graded beam. The FGM beam was partitioned through its length into a number of strips with constant material properties inside the strip (see Fig. 1).
Figure 1 shows the mesh of the zoomed right-hand side of the beam corresponding to the third row of Table 1 (5 elements in the thickness and width directions and 500 elements in the length direction). The elements considered were cubical 3D 8-Node Homogeneous Structural Elements SOLID185. The detailed mesh values used are given in column 1 of Table 1.
The geometrical parameters of the beam considered are width (b), height (h), and length (L). The material properties of the steel and aluminium used in the FEM analysis are given in Table 2. The boundary conditions considered correspond to a cantilever beam. The results obtained from FEM analysis were originally in the dimensional form, i.e. computed for a particular beam with the given geometry, rigidity, and mass per unit length values. In order to compare these results with the results of the FDM, DQM, and HWM, the frequency parameter was converted into the non-dimensional form using the following formula:
[mathematical expression not reproducible] (21)
where f stands for natural/dimensional frequency parameter value (in Hz). The FEM results are discussed in detail in the following section.
7. NUMERICAL RESULTS
In the following five different boundary conditions of the FGM beam are considered (see Fig. 2) and the results obtained by applying HWM, FDM, and DQM are compared (two symmetric and three non-symmetric conditions).
The first two values of the fundamental frequency parameter [OMEGA] are presented in Tables 3 and 4 for a pinned-pinned beam, in Tables 5 and 6 for a clamped--clamped beam, in Tables 7 and 8 for a clamped-pinned beam, in Tables 9 and 10 for a pinned-clamped beam, and in Tables 11 and 12 for a clamped-free beam).
Note that in the FE model all supports with pinned boundary conditions (a, c, and d) have the ability to move in the horizontal direction ([u.sub.y] = [u.sub.z] = 0,[u.sub.x] [not equal to] 0).
In Tables 1-10 the properties of the beam are considered to vary according to formula (7), i.e. by exponential functions.
In Tables 3-10 the value of the parameter [beta] is taken equal to 2. The exact solutions computed based on transcendental algebraic equations derived in  are given in the headings of Tables 3-10. Obviously, the convergence of the HWM (also of the FDM and DQM) to the exact solution can be observed in all these tables.
The numerical rates of the convergence, computed for the solutions presented in Table 3, are presented in Table 13.
In Table 13 the values of N start from 16 because each rate of convergence was computed on the basis of three consecutive values of the solution . The rate of the convergence of the HWM and FDM obviously tends to two, but the DQM has an ultrafast rate for N [less than or equal to] 32 and a negative rate for N > 32 (loss of accuracy).
In Table 14, the convergence rates of the extrapolated results of the HWM are given for four different boundary conditions considered above. The Richardson extrapolation method was applied, and it can be seen from Table 14 that the order of the convergence of extrapolated results tends to four in the case of all boundary conditions considered.
Based on results given in Tables 3-12, it can be concluded that in the case of the posed problem the highest accuracy was achieved by applying the DQM, also in most cases the accuracy of the results obtained by the HWM is higher than that obtained by the FDM (there fundamental frequencies in Tables 3 and 7 are exceptions). Detailed analysis of DQM results shows that the maximum accuracy was achieved extremely quickly with N = 16 or N = 32; thereafter the accuracy of the solution decreased with increasing resolution. These results are in agreement with the theoretical concept of the DQM (it is based on the use of high order polynomials whose denominator vanishes for large N) and results found in the literature.
It can be seen from Fig. 3 that in the case of the parameter value k = 1.5 the functions of the elasticity modulus corresponding to the exponential and power law functions (7) and (9) are close (here a steel/aluminium cantilever beam with [beta]= -0.549306 is considered).
In Tables 11 and 12 the FG material properties corresponding to steel/aluminium are considered with steel in the left and aluminium in the right support. The particular values of the material used are presented in Table 2.
The exponential model (7) does not include directly material properties at the right end of the beam. The required values of the material are obtained by determining the value of the parameter [beta]([beta]= -0.549306).
The first four mode shapes for the above-considered FG steel/aluminium cantilever beam are depicted in Fig. 4. The corresponding mode shapes obtained by a FEM are shown in Figs 5-8.
The results given in Table 15 were obtained by applying the HWM with the general power law function (9)-(10).
The steel/aluminium FGM with properties given in Table 2 is considered and the value of the exponent is taken equal to 1.5 (k = 1.5). The boundary conditions for a clamped-clamped beam are applied.
The FEM results computed for all boundary conditions considered above are given in the last row of each table. The number of elements used is 10 x 10 x 1000. Obviously, the values of the frequency parameters computed using 3D FEM analysis are in excellent agreement with those given in Tables 3-12, obtained by applying the HWM, DQM, and FDM.
An example of the results of more detailed FEM analysis is given in Table 15. In this table the first free frequencies for a pinned-pinned beam are presented. The convergence of the solution with increasing mesh can be observed. The results are in agreement with corresponding results obtained by applying the HWM, FDM, and DQM given in Tables 3 and 4.
Three strong formulation based numerical methods (HWM, FDM, and DQM) were applied for the analysis of the FGM beam and the obtained results were compared. The algorithms for all methods were coded by the authors in MATLAB. Good performance was observed in the case of all three methods used.
It can be concluded that in the case of the considered problem the accuracy of the solutions obtained by applying the HWM and FDM was in the same range. However, in most cases the accuracy of the results of the HWM outperformed that of the FDM. The accuracy of the DQM appears to be higher than that of the HWM and FDM. The convergence results presented in Table 13 confirm the accuracy of the HWM, FDM, and DQM. Similar accuracy was observed also for cylindrical shells in .
The obtained numerical results were validated with the solid element 3D finite element model developed for analysing more complex FGM structures. The results obtained with applying the 3D FEM and HWM were found to be in good (rather excellent) agreement.
Our future studies will focus on the application of the HWM for the analysis of nanostructures and solving fractional differential equations, which are not yet well covered by commercial software solutions. An interesting subtopic, whose research is underway, is adaption of global optimization methods and techniques, developed by the workgroup of design composite structures [31-36] to design nano- and graphene structures.
The research was supported by the Estonian Research Council (grant PUT1300); Estonian Centre of Excellence in Zero Energy and Resource Efficient Smart Buildings and Districts, ZEBE, TK146 funded by the European Regional Development Fund (grant 2014-2020.4.01.15-0016); Innovative Manufacturing Engineering Systems
Competence Centre IMECC (supported by Enterprise Estonia and co-financed by the European Union Regional Development Fund, project EU48685). The publication costs of this article were covered by Tallinn University of Technology and the Estonian Academy of Sciences.
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Funktsionaalgradientmaterjalist tala vabavonkumised: Haari lainikute meetodi evalveerimine
Maarjus Kirs, Kristo Karjust, Imran Aziz, Erko Ounapuu ja Ernst Tungel
Uurimistoos on keskendutud Haari lainikute meetodi evalveerimisele. Haari lainikute meetodi abil saadud tulemusi on vorreldud insenerirakendustes laialdaselt kasutatavate tugeval formulatsioonil pohinevate meetodite, nagu loplike vahede meetodi ja diferentsiaalkvadratuuride meetodi tulemustega. Vaadeldava ulesande korral on Haari lainikute meetod loplike vahede meetodist tapsem. Diferentsiaalkvadratuuride meetod osutus vaiksema kollokatsioonipunktide arvu korral Haari lainikute meetodist tapsemaks, kuid selle rakendamine suurema kollokatsioonipunktide arvu korral on komplitseeritud. Samuti on loodud 3D loplike elementide meetodil pohinev mudel ja selle rakendamisel saadud tulemused on eeltoodud meetodite tulemustega kooskolas. Haari lainikute meetodi abil saadud lahendi ja ekstrapoleeritud tulemuste koonduvuskiirus on kooskolas vastavate koonduvusteoreemidega toestatud teoreetiliste tulemustega.
Maarjus Kirs (a*), Kristo Karjust (a), Imran Aziz (b), Erko Ounapuu (a), and Ernst Tungel (a)
(a) Department of Mechanical and Industrial Engineering, School of Engineering, Tallinn University of Technology, Ehitajate tee 5, 19086 Tallinn, Estonia
(b) Department of Mathematics, University of Peshawar, Peshawar, Pakistan
(*) Corresponding author, Maarjus.Kirs@ttu.ee
Received 1 December 2016, revised 14 March 2017, accepted 10 May 2017, available online 17 August 2017
Table 1. FEM model. First three values of frequency parameter, pinned-pinned beam N [[ohm].sub.1] [[ohm].sub.2] [[ohm].sub.3] 2700 8.4522 41.2579 91.5302 (3 x 3 x 300) 6400 8.4366 41.1807 91.3549 (4 x 4 x 400) 12500 8.4276 41.1363 91.2543 (5 x 5 x 500) 100000 8.4136 41.0672 91.0984 (10 x 10 x 1000) Table 2. Material properties of FG steel/aluminium material Property Unit Steel Aluminium E GPa 210 70 [rho] Kg/[m.sup.3] 7800 2600 Table 3. Fundamental frequency parameter [[OMEGA].sub.1] ([beta]= 2, exact solution 8.41047573) N HWM FDM DQM 4 7.235577 8.157141 8 8.118951 8.332735 8.40822662 16 8.337942 8.390010 8.41047574 32 8.392365 8.405292 8.41047574 64 8.405950 8.409176 8.41047568 128 8.409344 8.410150 8.41047711 256 8.410193 8.410394 8.41047514 FEM results (10 x 10 x 1000 el.) 8.4136 Table 4. Second natural frequency parameter [[OMEGA].sub.2] ([beta]= 2, exact solution 41.07055822) N HWM FDM DQM 4 36.595239 34.453858 8 39.999094 39.252370 41.07596761 16 40.805039 40.603112 41.07055821 32 41.004320 40.952833 41.07055821 64 41.054008 41.041072 41.07055830 128 41.066421 41.063183 41.07055855 256 41.069524 41.068714 41.07056029 FEM results (10 x 10 x 1000 el.) 41.0672 Table 5. Fundamental frequency parameter [[OMEGA].sub.1] ([beta]= 2, exact solution 24.78955023) N HWM FDM DQM 4 21.242723 21.212781 8 24.016796 23.517337 24.24277247 16 24.602325 24.432036 24.78954915 32 24.743104 24.697286 24.78955023 64 24.777961 24.766296 24.78955023 128 24.786654 24.783725 24.78955013 256 24.788826 24.788093 24.78955092 FEM results (10 x 10 x 1000 el.) 24.8074 Table 6. Second natural frequency parameter [[OMEGA].sub.2] ([beta]= 2, exact solution 64.70943426) N HWM FDM DQM 4 57.202697 8 62.966887 57.405312 65.21032574 16 64.287324 62.612504 64.70946202 32 64.604874 64.163748 64.70943427 64 64.683357 64.571582 64.70943427 128 64.702919 64.674880 64.70943434 256 64.707806 64.700790 64.70943804 FEM results (10 x 10 x 1000 el.) 64.7032 Table 7. Fundamental frequency parameter [[OMEGA].sub.1] ([beta]= 2, exact solution 11.18278324) N HWM FDM DQM 4 8.764599 9.455451 8 10.647800 10.572089 11.17258124 16 11.052596 11.012971 11.18278324 32 11.150448 11.139111 11.18278324 64 11.174712 11.171786 11.18278327 128 11.180766 11.180029 11.18278302 256 11.182279 11.182094 11.18278285 FEM results (10 x 10 x 1000 el.) 11.1901 Table 8. Second natural frequency parameter [[OMEGA].sub.2] ([beta]= 2, exact solution 48.26066843) N HWM FDM DQM 4 41.945882 35.930268 8 46.799191 43.888087 48.31401606 16 47.903565 47.016589 48.26066840 32 48.171942 47.938093 48.26066844 64 48.238522 48.179262 48.26066848 128 48.255134 48.240268 48.26066852 256 48.259285 48.255565 48.26066842 FEM results (10 x 10 x 1000 el.) 48.2589 Table 9. Fundamental frequency parameter [[OMEGA].sub.1] ([beta]= 2, exact solution 20.777978) N HWM FDM DQM 4 18.799637 19.770973 8 20.309972 20.506995 20.77852832 16 20.662461 20.708729 20.77797932 32 20.749190 20.760567 20.77797932 64 20.770788 20.773620 20.77797931 128 20.776182 20.776889 20.77797921 256 20.777530 20.777707 20.77797837 FEM results (10 x 10 x 1000 el.) 20.7897 Table 10. Second natural frequency parameter [[OMEGA].sub.2] ([beta]= 2, exact solution 56.294438) N HWM FDM DQM 8 54.965168 52.599124 16 55.969009 55.338806 56.09705480 32 56.213501 56.053355 56.29443879 64 56.274230 56.234028 56.29443858 128 56.289388 56.279327 56.29443857 256 56.293176 56.290660 56.29443848 FEM results (10 x 10 x 1000 el.) 56.2907 Table 11. Fundamental frequency parameter [[OMEGA].sub.1] ([beta]= -0.549306) N HWM FDM DQM 8 4.884627 4.842031 4.87118515 16 4.874540 4.863858 4.87119849 32 4.872033 4.869360 4.87119848 64 4.871407 4.870739 4.87119797 128 4.871251 4.871084 4.87120621 256 4.871212 4.871170 4.87220829 FEM results (10 x 10 x 1000 el.) 4.8758 Table 12. Second natural frequency parameter [[OMEGA].sub.2] ([beta]= - 0.549306) N HWM FDM DQM 8 24.798280 23.143597 24.41704668 16 24.517676 24.092313 24.42645172 32 24.449153 24.342014 24.42645172 64 24.432120 24.405285 24.42645167 128 24.427868 24.421156 24.42645138 256 24.426806 24.425128 24.42665633 FEM results (10 x 10 x 1000 el.) 24.4397 Table 13. Rates of convergence corresponding to results given in Table 3 N HWM FDM QDM 16 2.0122 1.6163 - 32 2.0086 1.9060 23.8789 64 2.0023 1.9766 - 8.6258 128 2.0006 1.9942 - 4.6331 256 2.0001 1.9985 - 0.4590 Table 14. Fundamental frequency parameter [[ohm].sub.1], convergence rates of extrapolated results N Pinned-pinned Clamped-clamped Clamped-pinned Pinned-clamped 32 2.514821 4.2685 4.3015 4.1711 64 3.916921 4.0516 4.0774 4.0425 128 3.984539 4.0120 4.0191 4.0105 256 3.996411 4.0029 4.0047 4.0026 Table 15. First three values of fundamental frequency parameter (k = 1.5, power law) N [[OMEGA].sub.1] [[OMEGA].sub.2] [[OMEGA].sub.3] 8 22.573818 62.648322 124.802042 16 22.559805 62.097576 122.045771 32 22.552926 61.958469 121.384345 64 22.548905 61.920592 121.216644 128 22.546296 61.908898 121.172322 256 22.544517 61.904408 121.159519
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|Title Annotation:||INDUSTRIAL ENGINEERING|
|Author:||Kirs, Maarjus; Karjust, Kristo; Aziz, Imran; Ounapuu, Erko; Tungel, Ernst|
|Publication:||Proceedings of the Estonian Academy of Sciences|
|Date:||Mar 1, 2018|
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