Comparison of normalized buckling loads(
1. Introduction
In most of the real world engineering applications, stability analysis of compressed members is very crucial. There have been many researches dedicated tothe buckling behavior of axially compressed members. On the other hand, obtaining analytical solutions for the buckling behavior of columns with variable cross-section subjected to complicated load configurations are almost impossible in most of the cases. Some of the works related to obtaining analytical or analytical approximate solutions for the column buckling problem are provided below.
The problems of buckling of columns under variable distributed axial loads were solved in detail by Vaziri and Xie [1] and others. Some analytical closed-form solutions are given by Dinnik [2], Karman and Biot [3], Morley[4], Timoshenko and Gere [5] and others. One of the detailed references related to the structural stability topic is written by Simitses and Hodges [6] with detailed discussions. Iyengar [7] made some analysis on buckling of uniform with several elastic supports. Wang et al. [8] have given exact mathematical solutions for buckling of structural members for various cases of columns, beams, arches, rings, plates and shells. Ermopoulos [9] found the solution for buckling of tapered bars axially compressed by concentrated loads applied at various locations along their axes. Li [10] gave the exact solution for buckling of non-uniform columns under axially concentrated and distributed loading. Lee and Kuo [11] established an analytical procedure to investigate the elastic stability of a column with elastic supports at the ends under uniformly distributed follower forces. Furthermore, Gere and Carter [12] investigated and established the exact analytical solutions for buckling of several special types of tapered columns with simple boundary conditions. Solution of the problem of buckling of elastic columns with step varying thickness is established by Arbabei and Li [13]. Stability problems of a uniform bar with several elastic supports using the moment-distribution method were analyzed by Kerekes [14]. The research of Siginer [15] was about the stability of a column whose flexural stiffness has a continuous linear variation along the column. Moreover, the analytical solutions of a multi-step bar with varying cross section were obtained by Li et al. [16-18]. The energy method was used by Sampaio et al. [19] to find the solution for the problem of buckling behavior of inclined beam-column. Some of the important researchers who studied the mechanical behavior of beam-columns are Keller [20], Tadjbakhsh and Keller [21] and Taylor [22]. Later on, analytical approximate techniques were used for the stability analysis of elastic columns. Coşkun and Atay [23] and Atay and Coşkun [24] studied column buckling problems for the columns with variable flexural stiffness and for the columns with continuous elastic restraints by using the variational iteration method which produces analytical approximations. Coşkun [25, 26] used the homotopy perturbation method for buckling of Euler columns on elastic foundations and tilt-buckling of variable stiffness columns. Pınarbaşı [27] also analyzed the stability of nonuniform rectangular beams using homotopy perturbation method. These techniques were also used successfully in the vibration analysis of Euler-Bernoulli beams and in the vibration of beams on elastic foundations. [28-29]
Recently, by the emergence of new and innovative semi analytical approximation methods, research on this subject has gained momentum. Analytical approximate solution techniques are used widely to solve nonlinear ordinary or partial differential equations, integrodifferential equations, delay equations, etc. The main advantage of employing such techniques is that the problems are considered in a more realistic manner, and the solution obtained is a continuous function which is not the case for the solutions obtained by discretized solution techniques.
The methods that will be used throughout this study are, Adomian Decomposition Method (ADM), Variational Iteration Method (VIM) and Homotopy Perturbation Method (HPM). Each technique will be explained first, and then all will be applied to a selected case study related to the topic of the article.
2. Problem formulation
Derivation of governing equations related to stability analysis is given in detail in Timoshenko and Gere [5], Simitses and Hodges [6], and Wang et al. [8]. The reader can also refer to any textbook related to the subject. In this section, only the governing equation will be given for the related cases.
Consider the elastic columns given in Fig.1. The governing equation for the buckling of such columns is

Figure 1.
Elastic columns with various end conditions
In the case of constant flexural rigidity (
where
The governing equations (1) and (2) are both solved with respect to the problem’s end conditions. The end conditions for the columns shown in Fig.1 are given below:
Pin support:
Clamped support:
Free end:
Sliding restraint:
The governing equation given in Eq.(2) is a fourth order differential equation with constant coefficients which makes it possible to obtain analytical solutions easily. However, Eq.(1) includes variable coefficients due to variable flexural rigidity. For this type of differential equations, analytical solutions are limited for the special cases of
In some problems, obtaining analytical solutions is very difficult even for a constant coefficient governing equation. Consider the buckling of a column on an elastic foundation shown in Fig.2.

Figure 2.
Column with continuous elastic restraints.
The governing equation for the column in Fig.2 is
which, for the constant
In Eqs.(7) and (8),
Although Eq.(8) is a linear equation with constant coefficients, obtaining a solution from Eq.(9) is not that easy. It is very interesting that, even with a software, one can not easily produce the buckling loads in a sequential order from Eq.(9). In view of this experience, an analytical solution for Eq.(7) is almost impossible to obtain except very limited
Hence, analytical approximate techniques are efficient alternatives for solving these problems. By the use of these techniques, a solution which is continuous in the problem domain is possible for any variation in flexural rigidity. These techniques produce the buckling loads in a sequential order, and it is also very easy to obtain the buckling mode shapes from the solution provided by the method used. These are great advantages in the solution of such problems.
3. The methods used in the elastic stability analysis of Eulercolumns
3.1. Adomian Decomposition Method (ADM)
In the ADM a differential equation of the following form is considered
where,
Applying the inverse operator
After integrating source term and combining it with the terms arising from given conditions of the problem, a function
The nonlinear operator
The polynomials
The reader can refer to [30, 31] for the algorithms used in formulating Adomian polynomials. The solution
where, the components of the series are determined recursively as follows:
3.2. Variational Iteration Method (VIM)
According to VIM, the following differential equation may be considered:
where
where
3.3. Homotopy Perturbation Method (HPM)
HPM provides an analytical approximate solution for problems at hand as the other previously explained techniques. Brief theoretical steps for the equation of following type can be given as
with boundary conditions
whichsatisfies the following inequalities:
where
As
Theapproximate solution of
The convergence of the series in Eq.(31) has been proved in[33]. The method is described in detail in references [33-36].
4. Case studies
4.1. Buckling of a clamped-pinned column
The governing equation for this case was previously given in Eq.(1). ADM, VIM and HPM will be applied to this equation in order to compute the buckling loads for the clamped-pinned column with constant flexural stiffness,

Figure 3.
4.2. Formulation of the algorithms for uniform column
4.2.1. ADM
The linear operator and its inverse operator for Eq.(2) is
To keep the formulation a general one for all configurations to be considered, the boundary conditions are chosen as
Finally, the solution is defined by
4.2.2. VIM
Based on the formulation given previously, Lagrange multiplier,
An iterative algorithm can be constructed inserting Lagrange multiplier and governing equation into the formulation given in Eq.(31) as
where
4.2.3. HPM
Based on the formulation, Eq.(2) can be divided into two parts as
The solution can be expressed as a power series in
Inserting Eq.(50) into Eq.(35) provides a solution algorithm as
Hence, an approximate solution would be obtained as
Initial guess is very important for the convergence of solution in HPM. A cubic polynomial with four unknown coefficients can be chosen as an initial guess which was shown previously to be an effective one in problems related to Euler beams and columns [23-29].
4.3. Computation of buckling loads
By the use of described techniques, an iterative procedure is constructed and a polynomial including the unknown coefficients resulting from the initial guess is produced as the solution to the governing equation. Besides two unknowns from the initial guess, an additional unknown
where
4.4. Determination of bucklingmode shapes
Buckling mode shapes for the column can also be obtained from the polynomial approximations by the methods considered in this study. Introducing, the buckling loads into the solution, normalized polynomial eigen functions for the mode shapes are obtained from
The same approach can also be employed to predict mode shapes for the cases including variable flexural stiffness.
4.5. Analysis of a uniform column
After applying the procedures explained in the text, the following results are obtained for the buckling loads. Comparison with the exact solutions is also provided in order that one can observe an excellent agreement between the exact results and the computed results.
Twenty iterations are conducted for each method, and the computed values are compared with the corresponding exact values for the first four modes of buckling in the following table.
20.19072856 | 20.19072856 | 20.19072856 | 20.19072856 | |
59.67951594 | 59.67951594 | 59.67951594 | 59.67951594 | |
118.89986916 | 118.89986857 | 118.89986857 | 118.89986868 | |
197.85781119 | 197.88525697 | 197.88522951 | 197.88520511 |
Table 1.
From the table it can be seen that the computed values are highly accurate which show that the techniques used in the analysis are very effective. Only a few iterations are enough to obtain the critical buckling load which is Mode 1. Additional modes require additional iterations. The table also shows that additional two or three iterations will produce an excellent agreement for Mode 4. Even with twenty iterations, the error is less than 0.014% for all the methods used in the analyses.
The buckling mode shapes of uniform column for the first four modes are depicted in Fig.4. To prevent a possible confusion to the reader, the exact mode shapes and the computed ones are not shown separately in the figure since the obtained mode shapes coincide with the exact ones.

Figure 4.
Buckling modes of
4.6. Buckling of a rod with variable cross-section
A circular rod having a radius changing exponentially is considered in this case. Such a rod is shown below in Fig.5. The function representing the radius would be as
where

Figure 5.
Circular rod with a variable cross-section
Employing Eq.(49), cross-sectional area and moment of inertia for a section at an arbitrary point
where
Governing equation for the rod was previously given in Eq.(1) as
4.6.1. Formulation of the algorithms
4.6.1.1. ADM
Application of ADM leads to the following
where
and, where
ADM gives the following formulation with the previously defined fourth order linear operator.
4.6.1.2. VIM
Lagrange multiplier is the same as used in the uniform column case due to the fourth order derivative in Eq.(38). Hence, an algorithm by using VIM can be constructed as
4.6.1.3. HPM
Application of HPM produces the following set of recursive equations as the solution algorithm.
4.6.2. Results of the analyses
The proposed formulations are applied for two different variations,
16.47361380 | 16.47361380 | 16.47361380 | |
48.69674135 | 48.69674135 | 48.69674135 | |
97.02096924 | 97.02096916 | 97.02096921 | |
161.45155447 | 161.45151518 | 161.45150000 |
Table 2.
Comparison of normalized buckling loads(
13.35006457 | 13.35006457 | 13.35006457 | |
39.47004813 | 39.47004813 | 39.47004813 | |
78.64155457 | 78.64155458 | 78.64155466 | |
130.86858532 | 130.86856343 | 130.86853842 |
Table 3.
Comparison of normalized buckling loads(
The buckling mode shapes of the rod for the first four modes are depicted in between Figs.5-9. To demonstrate the effect of variable cross-section in the results, a comparison is made with normalized mode shapes for a uniform rod which are given in Fig.4. Constant flexural rigidity is defined as

Figure 6.
Comparison of buckling modes for

Figure 7.
Comparison of buckling modes for

Figure 8.
Comparison of buckling modes for
5. Conclusion
In this article, some analytical approximation techniques were employed in the elastic stability analysis of Euler columns. In a variety of such methods, ADM, VIM and HPM are widely used, and hence chosen for use in the computations. Firstly, a brief theoretical knowledge was given in the text, and then all of the methods were applied to the selected cases. Since the exact values for the buckling of a uniform rod were available, the analyses were initially conducted for that case. Results showed an excellent agreement with the exact ones that all three methods were highly effective in the computation of buckling loads and corresponding mode shapes. Finally, ADM, VIM and HPM were applied to the buckling of a rod having variable cross section. To this aim, a rod with exponentially varying radius was chosen and buckling loads with their corresponding mode shapes were obtained easily.
This study has shown that ADM, VIM and HPM can be used effectively in the analysis of elastic stability problems. It is possible to construct easy-to-use algorithms with these methods which are highly accurate and computationally efficient.
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