Research Article  Open Access
Vasile Marinca, RemusDaniel Ene, Bogdan Marinca, "Analytic Approximate Solution for FalknerSkan Equation", The Scientific World Journal, vol. 2014, Article ID 617453, 22 pages, 2014. https://doi.org/10.1155/2014/617453
Analytic Approximate Solution for FalknerSkan Equation
Abstract
This paper deals with the FalknerSkan nonlinear differential equation. An analytic approximate technique, namely, optimal homotopy asymptotic method (OHAM), is employed to propose a procedure to solve a boundarylayer problem. Our method does not depend upon small parameters and provides us with a convenient way to optimally control the convergence of the approximate solutions. The obtained results reveal that this procedure is very effective, simple, and accurate. 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
It is known that the word “viscoelastic” means the simultaneous existence of viscous and simultaneous elastic responses of a material. Some materials having a viscoelastic behavior are relevant in many fields of study for industrial and technological applications such as polymers, plastic processing, cosmetics, geology composites, paint flow, adhesives, towers generators, accelerators, electrostatic filters, droplet filters, and the design of heat exchanges [1].
Motivated by significant applications of viscoelastic materials, a substantial amount of research works has been invested in the study of nonlinear systems. In 1931, Falkner and Skan [2] have used some approximate procedures to solve boundarylayer equations. Hartree [3] found the numerical solution using a shooting method with (see (7)) as free parameter. The boundary conditions (8) arise in the study of viscous flow past a wedge of angle ; corresponds to flow toward the wedge and corresponds to flow away from the wedge. The special case is called the Blasius equation where the wedge reduced to a flat plate. In [4, 5], it is proved that if then the FalknerSkan equation (7) with initial conditions (8) admits a unique smooth solution. For there exist two solutions, that is, one withand the other one with . Botta et al. [6] showed that the solution of FalknerSkan equation is unique for under the restriction . Forced convection boundarylayer flow over a wedge with uniform suction or injection is analyzed by Yih [7]. Asaithambi [8] studied the FalknerSkan equation using finite difference scheme. In [9], Zaturska and Banks presented a new solution branch in function of parameter . This solution branch is found to end singularity at ; its structure is analytically investigated and the principal characteristics are described. Also the spatial stability of such solutions is commented on. The differential transformation is adopted to investigate the velocity and shearstress fields associated with FalknerSkan boundarylayer problem in [10]. A group of transformations is used to reduce the boundary value problem into a pair of initial value problems, which are then solved by means of the differential transformation method. The nonlinear ordinary differential equation is solved using Adomian decomposition method (ADM) by Elgazery [11] such that the condition at infinity was applied to a related Padé approximation and Laplace transformation to the obtained solution. Also ADM is used in [12] by Alizadeh et al. to find an analytical solution in the form of infinite power series. Magnetohydrodynamic effects on the FalknerSkan wedge flow are studied by Abbasbandy and Hayat in [13]. The same authors used HankelPadé and homotopy analysis method for the derivation of the solutions [14]. From a fluid mechanical point of view, the pathophysiological situation in myocardical bridges involves fluid flow in a time dependent flow geometry caused by contracting cardiac muscles overlying an intramural segment of the coronary artery. A boundarylayer model for the calculation of the pressure drop and flow separation is presented in [15] under the assumption that the idealized flow through a constriction is given by near equilibrium velocity profiles of the FalknerSkanCooke family, the evolution of the boundarylayer is obtained by the simultaneous solution of the FalknerSkan equation and the transient nonKármán integral momentum equation.
Pirkhedri et al. [16] developed a numerical technique transforming the governing partial differential equation into a nonlinear thirdorder boundary value problem by similarity variables and then solved it by the rational Legendre collocation method. It used transformed HermiteGauss nodes as interpolation points. The steady FalknerSkan solution for gravitydriven film flow of micropolar fluid is investigated in [17]. The ordinary differential equations are solved numerically using an implicit finite difference scheme known as the Kellerbox method. In [18], Lakestani truncated the semiinfinite physical domain of the problem to a finite domain expanding the required approximate solution as the elements of Chebyshev cardinal functions. Yun proposed in [19] an iterative method for solving the FalknerSkan equation in the form of polynomial series without requiring any differentiations or integrations of the previous iterate solutions. The author suggests a correction method which is compared with the successive differences of the iterations. In [20], Hendi and Hussain considered FalknerSkan flow over a porous surface taking into account the case of uniform suction/blowing. Stream function formulation and suitable transformations reduce the arising problem to ordinary differential equation which has been solved by homotopy analysis method.
In science and engineering there exist a lot of nonlinear differential equations and even strongly nonlinear problems which are still very difficult to solve analytically by using traditional methods. Many methods exist for approximating the solutions of nonlinear problems, for example, the Adomian decomposition method [21], the modified LindstedtPoincare method [22], the parameterexpansion method [23], optimal variational method [24], optimal homotopy perturbation method [25], and so on [26].
The aim of the present paper is to propose an accurate approach to FalknerSkan equation using an analytical technique, namely, optimal homotopy asymptotic method [26–28].
The validity of our procedure, which does not imply the presence of a small parameter in the equation, is based on the construction and determination of the auxiliary functions combined with a convenient way to optimally control the convergence of the solution. The efficiency of the proposed procedure is proved while an accurate solution is explicitly analytically obtained in an iterative way after only one iteration.
2. The Governing Equation
The twodimensional laminar boundarylayer equations of an incompressible fluid subject to a pressure gradient are [2, 3, 9, 12] where is the pressure gradient, , is the streamwise velocity in the direction of the fluid flow, is the velocity in the direction normal to , is the constant kinematic viscosity, and is the velocity at the edge of the boundarylayer which obeys the powerlaw relation , (), where is the mean stream velocity and is a constant. The relevant boundary conditions for fixed plate are
A stream function is introduced such that
Equation (2) of continuity is satisfied identically. The momentum equation (1) becomes
Integrating (5) and using similarity variable yield
Substituting (6) into (5) gives the equation of FalknerSkan in the form with the initial and boundary conditions where is a measure of the pressure gradient and prime denotes derivative with respect to.
3. Fundamentals of the OHAM
In what follows, we consider nonlinear differential equation with boundary/initial condition
In (9),is a linear operator andis a nonlinear operator. In (10),is a boundary operator.
According to the basic ideas of OHAM [26–28], one constructs a family of equations
The boundary condition is where, is an unknown function, is an embedding parameter, and is an auxiliary function such that and for . When increases from 0 to 1, the solution , changes from initial approximation to the solution . For and it holds that, respectively,
Expanding in series with respect to the parameter, one has
The series (14) contains the auxiliary functionwhich determines their convergence region. For the auxiliary functionwe propose that where and are functions of variable and of a number of unknown parameters . In this paper we consider the thorder approximation in the form
Inserting (14) into (11) we obtain where is the coefficient of in the expansion of about the embedding parameter .
Substituting (14) and (15) into (11) and equating the coefficients of like powers of , we obtain the following linear equations:
At this moment, themthorder approximate solution (16) depends on the functions , . The parameters which appear in the expression of , can be identified optimally via various methodologies such as the least square method, the Galerkin method, and the collocation method. The parameters can be determined, for example, if we substitute (16) into (9), such that the residual becomes
If and are two values from the domain of the problem and , , then the residual (21) must vanish with q—the number of parameters which appear in the expression of the functions ,.
We remark that our procedure contains the auxiliary functions which provides us with a simple but rigorous way to adjust and control convergence of the solution. It must be underlined that it is very important to properly choose the functions which appear in the thorder approximation (16). With these parameters known, the approximate solution is well determined. The parameters are, namely, convergencecontrol parameters.
4. Application of OHAM to FalknerSkan Equation
To use the basic ideas of the proposed method, we choose the linear operator whereis the unknown parameter at this moment.
The nonlinear operator is
The boundary conditions are
Equation (18) can be written in the form and has the solution
From (17), (23), and (24) one obtain the expression
Substituting (27) into (28), we obtain
If we consider the firstorder approximate solution , (16) becomes where is obtained from (20):
Substituting (27) and (29) into (31) we obtain the equation
There are many possibilities to choose the function which appears into (32). The convergence of the solution and consequently the convergence of the approximate solution given by (30) depend on the auxiliary function . Basically, the shape of should follow the term appearing in (29) which is the product of polynomial and exponential functions. In general, we try to choose the function so that the product from (31) and would be of the same form. In our paper, for example, we can consider only the possibilities and so on, where are unknown parameters. In the following we have four cases.
4.1. Case 1
If the auxiliary convergencecontrol function has the form then (32) can be written as
Finally, using (27) and solving (35), we determine the firstorder approximate solution given by (30) in the form
4.2. Case 2
The auxiliary function has the form In this case, (32) becomes
The firstorder approximate solution (30) in this case is obtained from (38) and (27) and can be written as
4.3. Case 3
If the auxiliary function has the form then the firstorder approximate solution equation (30) has the form where is given by (36).
4.4. Case 4
In the last case, we consider such that the firstorder approximate solution equation (30) becomes where is given by (39).
5. Numerical Examples
In order to prove the accuracy of the obtained results, we will determine the convergencecontrol parameters which appear in (36), (39), (41), and (43) by means of Galerkin method. Let be the residual within the approximate solution (or ) given by (36), (39), (41), and (43) which satisfies (7):
Since contains the parameters , . The parameters can be determined from the conditions where are linear independent functions, taken as weighting functions. Equations (36) and (39) contain nine unknown parameters: and , , and therefore we consider the following nine weighting functions :
For (41) and (43) which contain the unknown parameters: , , and , , we consider weighting functions ()
In this way, the convergencecontrol parameters , are optimally determined and the firstorder approximate solutions are known for different values of the known parameter .
In what follows, we illustrate the accuracy of the OHAM comparing previously obtained approximate solutions with the numerical integration results computed by means of the shooting method combined with fourthorder RungeKutta method using Wolfram Mathematica 6.0 software. Also we will show that the error of the solutions decreases when the number of terms in the auxiliary convergencecontrol function increases. For some values of the parameter , we will determine the approximate solutions given by (36), (39), (41), and (43) and with the unknown parameters , , and obtained from the system given by (45).
Example 1. In the first case we consider that .
(a) For (36) and from the system (45), following the procedure described above the convergencecontrol parameters are obtained
and consequently the firstorder approximate solution (36) can be written in the form
In Tables 1 and 2 we present a comparison between the firstorder approximate solution given by (49) and velocity obtained from (49), respectively, with numerical results for some values of variable and the corresponding relative errors.


(b) From (39), obtained by means of the auxiliary convergencecontrol function given by (37), we obtain the following results for the parameters:
The firstorder approximate solution (39) becomes
In Tables 3 and 4 we present some values of stream function (51) and velocity obtained from (51), respectively, for different values of and the corresponding relative errors.


(c) For (41), which depends on the auxiliary convergencecontrol function given by (40), we obtain
Therefore, the firstorder approximate solution for stream function is
In Tables 5 and 6 we present some values of stream function (53) and velocity obtained from (53), respectively, for different values of variable and the corresponding relative errors.
