Advances in Mathematical Physics

Advances in Mathematical Physics / 2014 / Article
Special Issue

Nonlinear Fluid Flow and Heat Transfer

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Research Article | Open Access

Volume 2014 |Article ID 417643 |

Vasile Marinca, Remus-Daniel Ene, "Dual Approximate Solutions of the Unsteady Viscous Flow over a Shrinking Cylinder with Optimal Homotopy Asymptotic Method", Advances in Mathematical Physics, vol. 2014, Article ID 417643, 11 pages, 2014.

Dual Approximate Solutions of the Unsteady Viscous Flow over a Shrinking Cylinder with Optimal Homotopy Asymptotic Method

Academic Editor: Waqar Ahmed Khan
Received09 Jan 2014
Revised10 Feb 2014
Accepted17 Feb 2014
Published25 Mar 2014


The unsteady viscous flow over a continuously shrinking surface with mass suction is investigated using the optimal homotopy asymptotic method (OHAM). The nonlinear differential equation is obtained by means of the similarity transformation. The dual solutions exist for a certain range of mass suction and unsteadiness parameters. A very good agreement was found between our approximate results and numerical solutions, which prove that OHAM is very efficient in practice, ensuring a very rapid convergence after only one iteration.

1. Introduction

The flow of the Newtonian and non-Newtonian fluids is important for engineers and applied mathematicians because of its several applications in engineering or industrial processes. In the last few decades, these fluids have attracted considerable attention from researchers in many branches of nonlinear dynamical systems in science and technology. The flow over a stretching/shrinking cylinder is an important problem in many engineering processes with applications in industries such as in plastic and metallurgy industries, glass-fiber production, and wire drawing. The pioneering works in the area of the flow inside a tube with time dependent diameter were [1, 2], where Uchida and Aoki and Skalak and Wang studied the internal flow velocity and pressure due to tube expansion or contraction. Miklavčič and Wang [3] investigated the flow over a shrinking sheet, obtaining an exact solution of the Navier-Stokes equations. Ishak et al. [4] reported that injection reduces the skin friction as well as the heat transfer rate at the surface while suction acts in the opposite manner. Fang et al. [5] obtained the exact solution of the unsteady state Navier-Stokes equations. Fang et al. [6] studied the viscous flow over a shrinking sheet by a newly proposed second order slip flow model. The exact solution of the full governing Navier-Stokes equation has two branches in a certain range of the parameters. The problem of unsteady viscous flow over a permeable shrinking cylinder was solved by Zaimi et al. [7] numerically using the shooting method. The effects of suction and unsteadiness parameters on the flow velocity and the skin friction coefficient have been analyzed and presented graphically and the same authors in [8] studied the effects of the unsteadiness parameter and the Brownian motion parameter on the flow field and heat transfer characteristics. Dual solutions are found to exist in certain conditions.

Analytical solutions to nonlinear differential equations play an important role in the study of the unsteady viscous flow over a shrinking cylinder, but it is difficult to find these solutions in the presence of strong nonlinearity. Many new approaches have been proposed to find approximate solutions of nonlinear differential equations. Perturbation methods have been applied to determine approximate solutions to weakly nonlinear problems [9]. But the use of perturbation theory in many problems is invalid for parameters beyond a certain specified range.

Homotopy perturbation method is employed to investigate steady-state heat conduction with temperature dependent thermal conductivity and heat generation in a hollow sphere by Khan et al. [10]. The same method is applied in the study of the effects of temperature distribution and heat transfer from solids of arbitrary shapes in [11]. Another procedure, the Adomian decomposition method, is used to compute the Sumudu transform of some typical functions in [12, 13]. Other methods have been proposed such as the various modified Lindstedt-Poincare method [14], some linearization methods [15], and the optimal homotopy perturbation method [16].

In this paper we consider the unsteady viscous flow over a shrinking cylinder. A version of the optimal homotopy asymptotic method is applied in this study to derive highly accurate analytical expressions of solutions. Our procedure does not depend upon any small or large parameters, contradistinguishing from other known methods. The main advantage of this approach is the control of the convergence of approximate solutions in a very rigorous way. A very good agreement was found between our approximate solutions and numerical solutions, which proves that our procedure is very efficient and accurate.

2. The Governing Equation

In what follows, we assume an unsteady laminar boundary layer flow of a nanofluid over an infinite cylinder or a tube with a time dependent diameter in shrinking motion as shown in Figure 1.

Also we consider the three-dimensional unsteady Navier-Stokes equations for incompressible fluids without body force such that based on the axisymmetric flow assumption and the fact that there is no azimuthal velocity component we have where is the velocity vector, is the fluid density, is the pressure, and is the kinematic viscosity. The diameter of the cylinder is assumed as a function of time with unsteady radius . For a positive value of , the cylinder radius becomes smaller with time, that is, contracting, while, for a negative value of , the diameter becomes larger with time, that is, expanding. In cylindrical polar coordinates and are measured in the radial and axial directions, respectively; (1) and (2) can be written as [58]

If we consider the constant mass transfer velocity () and a positive constant, then the boundary conditions are of the following form:

By means of the similarity variables [8] it is clear that , and, on the other hand, (3) is satisfied automatically. Based on the defined velocity components, it is straightforward to derive from (4) that the pressure gradient is a function of and and is independent on , such that, from (4), we obtain or using (7) the pressure may be written as where is the constant of the integration on and is the unsteadiness parameter for the expanding () or contraction () cylinder showing the strength of expansion or contraction. Substituting (7) into (5) and rearranging terms, this becomes with the boundary conditions transformed into the following: where prime denotes differentiation with respect to and is the dimensionless suction parameter.

3. Basic Ideas of the OHAM

Equation (10) can be written in a more general form where is a linear operator and is a nonlinear operator and the boundary conditions (11) in the form

Let be an initial approximation of such as

We point out that the linear operator from (12) and (14) is not unique.

Let us consider the function in the form where denotes an embedding parameter. It follows that the first-order approximate solution can be written as where are arbitrary parameters, which will be determined later. The boundary conditions are

We construct a family of equations [1721]: with the properties where is an arbitrary auxiliary convergence-control function.

From (15) and (16) we get

Now, equating only the coefficients of and into (18), we obtain the governing equation of given by (14) and the governing equation on ; that is,

In general, the nonlinear operator from (23) may be written as where the functions and are known and depend on the functions and also on the nonlinear operator, being a known integer number. It is known that the general solution of the nonhomogeneous linear equation (23) is equal to the sum of general solution of the corresponding homogeneous equation and some particular solutions of the nonhomogeneous equation. In what follows, we do not solve (23), but from the theory of differential equations it is more convenient to consider the unknown function in the form or where within expression of from (25) appear linear combinations of some functions , some of the terms which are given by corresponding homogeneous equation and a number of unknown parameters , , being an arbitrary integer number. The same considerations can be made for (26) where and are interchangeable.

4. The Convergence of the Approximate Solution (16)

The convergence of the approximate solution given by (16) depends upon the auxiliary functions , , which appear in (25). There are many possibilities to choose these functions . We try to choose such function so that within (25) the terms are of the same shape as the terms given by (24) [1418]. The first-order approximate solution also depends on the parameters , . The values of these parameters can be optimally evaluated via various methods: the least-square method, minimization of the square residual error, the Galerkin method, collocation method or the Ritz method, and so on. In this way, it is clear that the first-order approximate solutions given by (16) are well determined. Because the auxiliary functions are not unique, we have freedom to determine multiple solutions for nonlinear differential equations (10) and (11). It should be emphasized that our procedure contains the auxiliary functions , , , which provides us with a simple way to adjust and control the convergence of the approximate solutions.

5. Multiple Approximate Solutions of the Unsteady Viscous Flow by OHAM

The linear operator can be chosen in the following forms: where is an unknown positive parameter and will be determined later.

The initial approximation can be obtained from (14), with boundary conditions

Equation (14) with the linear operators (28) or (29) has the solutions while (14) with the linear operators (30) or (31) has the solutions

The nonlinear operator corresponding to nonlinear differential equation (10) is defined as for linear operator defined by (28).

The same nonlinear operators for the linear operator defined by (29), (30), and (31) are, respectively,

Substituting (33) into (35) it holds that

Now, comparing (24) and (39), one gets

The first approximation can be written in the form where are arbitrary functions. Of course, we have freedom to choose such functions with conditions, obtained from (41):

For example are given by

Taking into consideration only the expression given by (43), from (33), (41), and (16) we obtain the first-order approximate solution of (10) and (11) in the form where are unknown parameters.

Many other approximate solutions can be obtained by means of combinations between initial approximations given by (33) and (34) and the nonlinear operators (36), (37), or (38).

6. Numerical Examples

In order to show the validity and accuracy of the OHAM, we compare previously obtained approximate solutions (46) with numerical integration results obtained by means of a fourth-order Runge-Kutta method in combination with shooting method and the Wolfram Mathematica 6.0 software. Using the least-square method for determination of the parameters and , we present the following four cases, for the different values of the coefficients and .

6.1. Case  1: and

We find dual solutions.(a) We have The first expression of the first-order approximate solution given by (46) can be written in the form (b) We have The second expression of the first-order approximate solution (48) is

6.2. Case  2: and

We obtain two dual solutions, respectively.(a) We have (b) We have

6.3. Case  3: and

We obtain the corresponding dual solutions, respectively.(a) We have (b) We have

6.4. Case  4: and

It holds that(a) (b)

In Table 1 we present a comparison between the skin friction coefficient obtained by means of OHAM and numerical results. The comparisons are found to be in very good agreement for the first and the second solutions.

The first expression of the first-order
approximate solution

1 −1 1.00000075440.9999999999
1 −2 2.60122066472.6012206637
2 −1 2.56320483692.5632048269
2 −2 3.71509113813.7150910381

In Tables 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, and 13 we present a comparison between all approximate solutions and and numerical results obtained by the Runge-Kutta method in combination with shooting method for different values of variable and different values of coefficients and .

(48) Error

1 1. 1. 0.
9/5 0.4493290026 0.4493289954
13/5 0.2018965295 0.2018965301
21/5 0.0407622028 0.0407622034
29/5 0.0082297496 0.0082297482
37/5 0.0016615551 0.0016615578
41/5 0.0007465838 0.0007465853
9 0.0003354620 0.0003354620

(48) Error

1 −1. −1. 0.
9/5 −0.4493289667 −0.4493289878
13/5 −0.2018965563 −0.2018965347
21/5 −0.0407621959 −0.0407621759
29/5 −0.0082297502 −0.0082297476
37/5 −0.0016615582 −0.0016615571
41/5 −0.0007465846 −0.0007465884
9 −0.0003354605 −0.0003354620
0 0 0

(50) Error

1 1. 1. 0.
9/5 0.3025681133 0.3025729017
13/5 −0.1319503386 −0.1319549886
21/5 −0.4960887571 −0.4961000384
29/5 −0.5909291088 −0.5909208156
37/5 −0.6138226907 −0.6138228346
41/5 −0.6174089320 −0.6174180498
9 −0.6191261345 −0.6191351201
−0.6206780156 −0.6206780156

(50) Error

1 −1. −1. 0.
9/5 −0.7034979138 −0.7036237128
13/5 −0.4016692734 −0.4016032225
21/5 −0.1094954512 −0.1095146046
29/5 −0.0270353065 −0.0270213000
37/5 −0.0063314620 −0.0063462255
41/5 −0.0030330955 −0.0030391496
9 −0.0014527986 −0.0014468075
0 0 0

(51) Error

1 1. 1. 0.
9/5 0.6540357246 0.6540356881
13/5 0.6019106890 0.6019108087
21/5 0.5917231482 0.5917232409
29/5 0.5914012763 0.5914011910
37/5 0.5913902415 0.5913901904
41/5 0.5913898860 0.5913898617
9 0.5913898108 0.5913897995
0.5913897892 0.5913897892

(51) Error

1 −1. −1. 0.
9/5 −0.1423061993 −0.1423072726
13/5 −0.0231135261 −0.0231135957
21/5 −0.0007095855 −0.0007094951
29/5 −0.0000238338 −0.0000238925
0 0 0

(52) Error

1 1. 1.′ 0.
9/5 −0.4931638904 −0.4931976737
13/5 −1.5746868741 −1.5746416452