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Article

A New Scheme Using Cubic B-Spline to Solve Non-Linear Differential Equations Arising in Visco-Elastic Flows and Hydrodynamic Stability Problems

by
Asifa Tassaddiq
1,
Aasma Khalid
2,3,
Muhammad Nawaz Naeem
3,
Abdul Ghaffar
4,
Faheem Khan
5,
Samsul Ariffin Abdul Karim
6 and
Kottakkaran Sooppy Nisar
7,*
1
College of Computer and Information Sciences, Majmaah University, Al-Majmaah 11952, Saudi Arabia
2
Department of Mathematics, Government College Women University Faisalabad, Faisalabad 38023, Pakistan
3
Department of Mathematics, Government College University Faisalabad, Faisalabad 38023, Pakistan
4
Department of Mathematical Sciences, BUITEMS, Quetta 87300, Pakistan
5
Department of Mathematics, University of Sargodha, Sargodha 40100, Pakistan
6
Fundamental and Applied Sciences Department and Centre for Smart Grid Energy Research (CSMER), Institute of Autonomous System, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, Seri Iskandar 32610, Perak Darul Ridzuan, Malaysia
7
Department of Mathematics, College of Arts and Sciences, Prince Sattam bin Abdulaziz University, Wadi Aldawaser 11991, Saudi Arabia
*
Author to whom correspondence should be addressed.
Mathematics 2019, 7(11), 1078; https://doi.org/10.3390/math7111078
Submission received: 4 August 2019 / Revised: 27 October 2019 / Accepted: 28 October 2019 / Published: 8 November 2019

Abstract

:
This study deals with the numerical solution of the non-linear differential equations (DEs) arising in the study of hydrodynamics and hydro-magnetic stability problems using a new cubic B-spline scheme (CBS). The main idea is that we have modified the boundary value problems (BVPs) to produce a new system of linear equations. The algorithm developed here is not only for the approximation solutions of the 10th order BVPs but also estimate from 1st derivative to 10th derivative of the exact solution as well. Some examples are illustrated to show the feasibility and competence of the proposed scheme.

1. Introduction

Recent research in the field of hydrodynamic and hydromagnetics stability have found the presence of a family of problems in differential equations (DEs) of a high order, and which have real mathematical interest. There are various approximate (numerical) methods in the literature that have been used for the solution of boundary value problems (BVPs). The existence and uniqueness to finding the solution of higher order BVPs are systematically examined in [1]. The BVPs of higher order DEs have been examined due to their significance and the potential for applications in applied sciences. To find the analytical solutions of such BVPs analytically is very tough and are available in very few cases. Very few researchers have tried the numerical solution of 10th order BVPs. Some of the approximate techniques have been established over the years to the numerical solution for these kinds of BVPs. In [2,3], the authors has solved 10th and 12th order BVPs using the Adomian decomposition method (ADM) involving Green’s function. The homotopy perturbation approach was utilized in [4] to solve BVPs of 10th order. When a uniform magnetic field is applied across the fluid in the direction of gravity, the instability sets now as ordinary convection and it is modeled by 10th order BVPs as discussed in [5]. In [6], established approximate techniques for solving the 10th order non-linear BVPs occurring in thermal instability.
Numerical methods for the solution of non-linear BVPs of order 2 m were found in [7]. An effective numerical procedure DTM for solving some linear and non-linear BVPs of 10th order is discussed in [8]. In [9,10], the BVPs of 9th and 10th order are considered by adopting homotopy perturbation technique and the modified-variational iteration technique. Also the variational iterative technique was adopted in [11] for solving the 10th order BVPs. Wazwaz [12,13,14,15] proposed modified form of ADM for solving 6th, 8th, 10th and 12th order.
The study of non-polynomial spline [16] of 11th degree is a key element to solve 10th order BVPs. In [17], it is depicted that the DEs that describe the 10th order model to incorporate a 3rd order model of enlistment machine, two equations for dynamic power control, two equations for receptive power control, and three equations for edge pitch control. A 10th order nonlinear dynamic model was developed in [18] to turn mobile robots that incorporate slip between the driven wheels and the ground. Based on binary six-point and eight-point approximating subdivision scheme, two collocation algorithms are constructed by [19,20] to find the solution of BVPs. The 4th order linear BVPs using a new cubic B-spline were solved in [21]. Authors explained the 10th and 12th order BVPs by using the Galerkin weighted residual technique in [22]. The 5th, 6th and 8th order linear and non-linear BVPs by using the cubic B-spline scheme (CBS) method were solved in [23,24,25]. The higher (10th and 11th) degree splines were tested in [26,27] for solving 10th order BVPs. In [28] they practiced 2nd order finite difference schemes for the mathematical solutions of the 8th, 10th and 12th order Eigen-value problems. Galerkin method with septic B-spline and quintic B-spline was adopted in [29,30] for solving 10th order BVPs. Quintic B-spline and septic-B spline collocation methods was discussed in [31,32] to find solution of a 10th order BVPs.
For discrete methods, e.g., Adomian decomposition, shooting, homotopy perturbation, finite differences and variational-iterative technique, only give discrete approximate values of the unknown y ( x ) . For fitting curve to data we require further data processing methods. To overcome these disadvantages, we introduced a new CBS scheme for the solution of 10th order BVPs. The algorithm developed here is not only for the approximation solutions of the 10th order boundary value problems(BVPs) employing CBS but also estimate derivatives of 1st order to 10th order (where boundary conditions (BCs) are defined) of the exact solution as well.
The rest of the paper is organized as follows. The construction of CBS is presented in Section 2. In Section 3, the CBS scheme is utilized as an interpolating function in the solution of 10th order nonlinear BVPs. The results and discussion are presented in Section 4. Also some problems are considered in this section to show the efficiency of the CBS scheme. Finally, the concluding remarks are given in the final section.

2. The Construction of CBS

In this section, we construct the CBS basis functions for solving numerically the non-linear equations arising in the study of hydrodynamics and hydro-magnetic stability problems. To find the approximate solution at nodal points defined in the region [ a , b ] . For an interval Ω = [ a , b ] , we divide it into n sub-intervals Ω i = [ κ i , κ i + 1 ] ; i = 0 , 1 , 2 , , n 1 , by the equidistant knots. For this range, we select equidistant points such that
Ω ı = κ ı = a + ı h ,
such that
Ω = { a = κ 0 , , κ n = b } ,
i.e., κ ı = a + ı h , ( ı = 0 , , n ) and h = b a n .
Assume S 3 ( Ω ) = { p ( t ) C 2 [ a , b ] } such that p ( t ) converted to to cubic-polynomial on separately sub interval ( κ ı , κ ı + 1 ) . The basis function is defined as
M ı ( κ ) = 1 6 h 3 ( κ κ ı 2 ) 3 , if κ [ κ ı 2 , κ ı 1 ] , h 3 + 3 h 2 ( κ κ ı 1 ) + 3 h ( κ κ ı 1 ) 2 3 ( κ κ ı 1 ) 3 , if κ [ κ ı 1 , κ ı ] , h 3 + 3 h 2 ( κ ı + 1 κ ) + 3 h ( κ ı + 1 κ ) 2 3 ( κ ı + 1 κ ) 3 , if κ [ κ ı , κ ı + 1 ] , ( κ ı + 2 κ ) 3 , if κ [ κ ı + 1 , κ ı + 2 ] , 0 , otherwise ,
for ( ı = 2 , 3 , 4 , , n 2 ) . Considering one and all M ı ( κ ) is also a piece-wise cubic with knots at Ω , simultaneously M ı ( κ ) S 3 ( Ω ) .
Assume Ψ = { M ı } ; ( ı = 1 , 0 , 1 , 2 n , n + 1 ) be linearly independent and let M 3 ( Ω ) = s p a n Ψ . Thus M 3 ( Ω ) is ( n + 3 ) dimensional and M 3 ( Ω ) = S 3 ( Ω ) . Let s ( κ ) be the cubic-B spline function interpolating at the nodal points and s ( κ ) S 3 ( Ω ) . Then s ( κ ) can be written as
s ( κ ) = ı = 1 n + 1 j ı M ı ( κ ) .
Consequently now for a function w ( κ ) , there happened to be a distinctive cubic-B spline s ( κ ) = ı = 1 n + 1 j ı M ı ( κ ) , satisfying the interpolating conditions:
w ( κ ı ) = s ( κ ı ) = j ı 1 + 4 j ı + j ı + 1 6 ,
for ı = 0 , , n .
The values of M ı ( κ ) , and its derivatives M ı ( 1 ) ( κ ) , M ı ( 2 ) ( κ ) at nodal points are required and these derivatives are tabulated in Table 1.
Assume m ı = s ( 1 ) ( κ ı ) and ı = s ( 2 ) ( κ ı ) then from
m ı = s ( 1 ) ( κ ı ) = w ( 1 ) ( κ ı ) 1 180 h 4 w ( 5 ) ( κ ı ) + O ( h 6 )
w ( 1 ) ( κ ) = s ( 1 ) ( κ ı ) = j ı + 1 j ı 1 2 h
ı = s ( 2 ) ( κ ı ) = w ( 2 ) ( κ ı ) 1 12 h 2 w ( 4 ) ( κ ı ) + 1 360 h 4 w ( 6 ) ( κ ı ) + O ( h 6 )
w ( 2 ) ( κ ) = s ( 2 ) ( κ ı ) = j ı + 1 2 j ı + j ı 1 h 2 ,
ı may be used to determine numerical-difference formulas for w ( 3 ) ( κ ı ) , w ( 4 ) ( κ ı ) such that ( ı = 1 t o n 1 ) , for w ( 5 ) ( κ ı ) , w ( 6 ) ( κ ı ) such that ( ı = 2 t o n 2 ) , for w ( 7 ) ( κ ı ) , w ( 8 ) ( κ ı ) such that ( ı = 3 t o n 3 ) and w ( 9 ) ( κ ı ) , w ( 10 ) ( κ ı ) such that ( ı = 4 t o n 4 ) like so the errors can be obtained by using Taylor-series
ı + 1 ı 1 2 h = s ( 3 ) ( κ ı ) + s ( 3 ) ( κ ı + ) 2 = w ( 3 ) ( κ ı ) + 1 12 h 2 w ( 5 ) ( κ ı ) + O ( h 4 ) ; w ( 3 ) ( κ ) = s ( 3 ) ( κ ı ) = j ı + 2 2 j ı + 1 + 2 j ı 1 j ı 2 2 h 3 , ı + 1 2 ı + ı 1 h 2 = s ( 3 ) ( κ ı ) s ( 3 ) ( κ ı + ) h = w ( 4 ) ( κ ı ) 1 720 h 4 w ( 8 ) ( κ ı ) + O ( h 6 ) ; w ( 4 ) ( κ ) = s ( 4 ) ( κ ı ) = j ı + 2 4 j ı + 1 + 6 j ı 4 j ı 1 + j ı 2 h 4 , ı + 2 2 ı + 1 + 2 ı 1 ı 2 2 h 3 = w ( 5 ) ( κ ı ) + O ( h 2 ) ; w ( 5 ) ( κ ) = s ( 5 ) ( κ ı ) = j ı + 3 4 j ı + 2 + 5 j ı + 1 + 5 j ı 1 + 4 j ı 2 j ı 3 2 h 5 .
Similarly (see [31]),
w ( 6 ) ( κ ı ) = s ( 6 ) ( κ ı ) = j ı + 3 6 j ı + 2 + 15 j ı + 1 20 j ı + 15 j ı 1 6 j ı 2 + j ı 3 h 6 , w ( 7 ) ( κ ı ) = s ( 7 ) ( κ ı ) = j ı + 4 6 j ı + 3 + 14 j ı + 2 14 j ı + 1 + 14 j ı 1 14 j ı 2 + 6 j ı 3 j ı 4 2 h 7 , w ( 8 ) ( κ ı ) = s ( 8 ) ( κ ı ) = 1 h 8 ( j ı + 4 8 j ı + 3 + 28 j ı + 2 56 j ı + 1 + 70 j ı 56 j ı 1 + 28 j ı 2 8 j ı 3 + j ı 4 ) , w ( 9 ) ( κ ı ) = s ( 9 ) ( κ ı ) = 1 2 h 9 ( j ı + 5 8 j ı + 4 + 27 j ı + 3 48 j ı + 2 + 42 j ı + 1 42 j ı 1 + 48 j ı 2 27 j ı 3 + 8 j ı 4 j ı 5 ) .

3. The 10th Order Nonlinear BVPs

In this section, we consider the 10th order nonlinear BVPs arising in the study of hydrodynamics stability and visco-elastic flows.
w ( 10 ) ( κ ) = f ( κ , w ( κ ) , w ( 1 ) ( κ ) , w ( 2 ) ( κ ) , w ( 3 ) ( κ ) , w ( 4 ) ( κ ) , w ( 5 ) ( κ ) , w ( 6 ) ( κ ) , w ( 7 ) ( κ ) , w ( 8 ) ( κ ) , w ( 9 ) ( κ ) ) , κ [ a , b ] ,
with BCs
w ( a ) = λ 0 , w ( 1 ) ( a ) = λ 1 , w ( 2 ) ( a ) = λ 2 , w ( 3 ) ( a ) = λ 3 , w ( 4 ) ( a ) = λ 4 , w ( b ) = χ 0 , w ( 1 ) ( b ) = χ 1 , w ( 2 ) ( b ) = χ 2 , w ( 3 ) ( b ) = χ 3 , w ( 4 ) ( b ) = χ 4 ,
where λ 0 , λ 1 , λ 2 , λ 3 , λ 4 and χ 0 , χ 1 , χ 2 , χ 3 , χ 4 are given real constants, ( a ı ( κ ) ; ı = 1 , 2 , , 10 ) and f is continuous in interval [ a , b ] .
The Taylor, series for w ( 10 ) ( κ ı ) at the preferred collocation points alongside central difference (see [31]), we have
w ( 10 ) ( κ ı ) = 1 h 6 ( w ı + 3 ( 4 ) ( κ ı ) 6 w ı + 2 ( 4 ) ( κ ı ) + 15 w ı + 1 ( 4 ) ( κ ı ) 20 w ı ( 4 ) ( κ ı ) + 15 w ı 1 ( 4 ) ( κ ı ) 6 w ı 2 ( 4 ) ( κ ı ) + w ı 3 ( 4 ) ( κ ı ) ) .
Equation (9) can be written as
ı 2 2 ı 3 + ı 4 h 2 = w ( 4 ) ( κ ı 3 ) 1 720 h 4 w ( 8 ) ( κ ı 3 ) + O ( h 6 ) , ı 1 2 ı 2 + ı 3 h 2 = w ( 4 ) ( κ ı 2 ) 1 720 h 4 w ( 8 ) ( κ ı 2 ) + O ( h 6 ) , ı 2 ı 1 + ı 2 h 2 = w ( 4 ) ( κ ı 1 ) 1 720 h 4 w ( 8 ) ( κ ı 1 ) + O ( h 6 ) , ı + 2 2 ı + 1 + ı h 2 = w ( 4 ) ( κ ı + 1 ) 1 720 h 4 w ( 8 ) ( κ ı + 1 ) + O ( h 6 ) , ı + 3 2 ı + 2 + ı + 1 h 2 = w ( 4 ) ( κ ı + 2 ) 1 720 h 4 w ( 8 ) ( κ ı + 2 ) + O ( h 6 ) , ı + 4 2 ı + 3 + ı + 2 h 2 = w ( 4 ) ( κ ı + 3 ) 1 720 h 4 w ( 8 ) ( κ ı + 3 ) + O ( h 6 ) .
Substituting Equation (13) into Equation (12), we obtain
1 h 8 ( ı + 4 8 ı + 3 + 28 ı + 2 56 ı + 1 + 70 ı 56 ı 1 + 28 ı 2 8 ı 3 + ı 4 ) = w ( 10 ) ( κ ı ) + O ( h 2 ) .
Since ı = j ı + 1 2 j ı + j ı 1 h 2 so, Equation (14) becomes
w ( 10 ) ( κ ı ) = 1 h 8 ( j ı + 5 2 j ı + 4 + j ı + 3 h 2 8 ( j ı + 4 2 j ı + 3 + j ı + 2 h 2 ) + 28 ( j ı + 3 2 j ı + 2 + j ı + 1 h 2 ) 56 ( j ı + 2 2 j ı + 1 + j ı h 2 ) + 70 ( j ı + 1 2 j ı + j ı 1 h 2 ) 56 ( j ı 2 j ı 1 + j ı 2 h 2 ) + 28 ( j ı 1 2 j ı 2 + j ı 3 h 2 ) 8 ( j ı 2 2 j ı 3 + j ı 4 h 2 ) + j ı 3 2 j ı 4 + j ı 5 h 2 ) .
After some simplifications the above equation becomes
w ( 10 ) ( κ ı ) = s ( 10 ) ( κ ı ) = 1 h 10 ( j ı + 5 10 j ı + 4 + 45 j ı + 3 120 j ı + 2 + 210 j ı + 1 252 j ı + 210 j ı 1 120 j ı 2 + 45 j ı 3 10 j ı 4 + j ı 5 ) .
Let w ( κ ı ) = s ( κ ı ) = ı = 1 n + 1 j ı M ı ( κ ı ) be the accurate solution of non-linear 10th order BVPs
w ( 10 ) ( κ ı ) = f ( κ ı , w ( κ ı ) , w ( 1 ) ( κ ı ) , w ( 2 ) ( κ ı ) , w ( 3 ) ( κ ı ) , w ( 4 ) ( κ ı ) , w ( 5 ) ( κ ı ) , w ( 6 ) ( κ ı ) , w ( 7 ) ( κ ı ) , w ( 8 ) ( κ ı ) , w ( 9 ) ( κ ı ) ) , κ ı [ a , b ] .
Imposing Equations (3), (5), (7), (8) and (9) into Equation (17), we have
1 h 10 ( j ı + 5 10 j ı + 4 + 45 j ı + 3 120 j ı + 2 + 210 j ı + 1 252 j ı + 210 j ı 1 120 j ı 2 + 45 j ı 3 10 j ı 4 + j ı 5 ) = f ı ( κ ı , 1 6 ( j ı 1 + 4 j ı + j ı + 1 ) , 1 2 h ( j ı + 1 j ı 1 ) , 1 h 2 ( j ı + 1 2 j ı + j ı 1 ) , 1 2 h 3 ( j ı + 2 2 j ı + 1 + 2 j ı 1 j ı 2 ) , 1 h 4 ( j ı + 2 4 j ı + 1 + 6 j ı 4 j ı 1 + j ı 2 ) , 1 2 h 5 ( j ı + 3 4 j ı + 2 + 5 j ı + 1 + 5 j ı 1 + 4 j ı 2 j ı 3 ) , 1 h 6 ( j ı + 3 6 j ı + 2 + 15 j ı + 1 20 j ı + 15 j ı 1 6 j ı 2 + j ı 3 ) , 1 2 h 7 ( j ı + 4 6 j ı + 3 + 14 j ı + 2 14 j ı + 1 + 14 j ı 1 14 j ı 2 + 6 j ı 3 j ı 4 ) , 1 h 8 ( j ı + 4 8 j ı + 3 + 28 j ı + 2 56 j ı + 1 + 70 j ı 56 j ı 1 + 28 j ı 2 8 j ı 3 + j ı 4 ) , 1 2 h 9 ( j ı + 5 8 j ı + 4 + 27 j ı + 3 48 j ı + 2 + 42 j ı + 1 42 j ı 1 + 48 j ı 2 27 j ı 3 + 8 j ı 4 j ı 5 ) ) , κ [ a , b ] .
Equation (18) we will produce a new system consisting of ( n 7 ) linear equations ( ı = 4 , 5 , , n 4 ) with ( n + 3 ) unknowns j ı where ( ı = 1 , 0 , , n + 1 ) , therefore ten further equations are required. From given BCs at κ = a , we have five equations:
w ( a ) = λ 0 j 1 + 4 j 0 + j 1 = 6 λ 0 w ( 1 ) ( a ) = λ 1 j 1 + j 1 = 2 λ 1 h w ( 2 ) ( a ) = λ 2 j 1 2 j 0 + j 1 = λ 2 h 2 w ( 3 ) ( a ) = λ 3 j 2 2 j 1 + 2 j 1 j 2 = 2 λ 3 h 3 w ( 4 ) ( a ) = λ 4 j 2 4 j 1 + 6 j 0 4 j 1 + j 2 = λ 4 h 4 ,
similarly from κ = b there will be other five equations
w ( b ) = χ 0 j n 1 + 4 j n + j n + 1 = 6 χ 0 w ( 1 ) ( b ) = χ 1 j n 1 + j n + 1 = 2 χ 1 h w ( 2 ) ( b ) = χ 2 j n 1 2 j n + j n + 1 = χ 2 h 2 w ( 3 ) ( b ) = χ 3 j n + 2 2 j n + 1 + 2 j n 1 j n 2 = 2 χ 3 h 3 w ( 4 ) ( b ) = χ 4 j n + 2 4 j n + 1 + 6 j n 4 j n 1 + j n 2 = χ 4 h 4 .
Omitting the order of the error of terms, the exact solution w ( κ ı ) = s ( κ ı ) = ı = 1 n + 1 j ı M ı ( κ ı ) is accomplished by finding solution of the discussed above linear system of ( n + 3 ) equations in ( n + 3 ) unknowns considering the Equations (18)–(20).

4. Convergence Analysis

Let w ^ ( κ ) be the exact solution of the Equations (10)–(12) and also s ^ ( κ ) be the CBS approximation to w ^ ( κ ) . Therefore, we have
w ^ ( κ ı ) = s ^ ( κ ı ) = ı = 1 n + 1 j ı ^ M ı ( κ ı ) ,
where
j ^ = j ^ i m a t h = j ^ 1 , j ^ 0 , j ^ 1 , , j ^ n + 1 T .
Also, we have assume that s ( κ ) be the computed cubic B spline approximation to s ^ ( κ ) , namely
w ( κ ı ) = s ( κ ı ) = i = 1 n + 1 j i M ı ( κ ı ) ,
j = j i = j 1 , j 0 , j 1 , , j n + 1 T .
To approximate the error w ^ ( κ ı ) ) s ^ ( κ ı ) ) we have to estimate error w ^ ( κ ı ) ) s ( κ ı ) ) and w ( κ ı ) ) s ^ ( κ ı ) ) seperately
The system of ( n + 3 ) × ( n + 3 ) matrix can be written as:
B j = G .
Then, we have
B j ^ = G ^
and
B j = G .
Now, by subtracting Equations (22) and (23), we obtain
B ( j j ^ ) = G G ^ ,
where B is an ( n + 3 ) × ( n + 3 ) -dimensional band matrix, and
G = G 1 , G 0 , G 1 , , G n + 1 T ,
where T denoting transpose.
We can write
( j j ^ ) = B 1 ( G G ^ ) .
Taking the infinity norm from Equation (24), we obtain
( j j ^ ) = B 1 G G ^ .
The B-spline M = M ı = { M 1 , M 0 , M 1 , , M n + 1 } satisfy the following property
| i = 1 n + 1 j i M ı ( κ ı ) | 1 .
Using [24]
B 1 G G ^ h 2 .
( j j ^ ) h 2 .
s ( κ ı ) ) s ^ ( κ ı ) = ( j j ^ ) i = 1 n + 1 M ı ( κ ı ) .
s ( κ ı ) s ^ ( κ ı ) = ( j j ^ ) i = 1 n + 1 M ı ( κ ı ) .
s ( κ ı ) s ^ ( κ ı ) ( j j ^ ) | i = 1 n + 1 M ı ( κ ı ) | h 2 .
w ^ ( κ ı ) s ( κ ı ) ρ h 4 .
w ^ ( κ ı ) s ^ ( κ ı ) w ^ ( κ ı ) s ( κ ı ) + s ( κ ı ) s ^ ( κ ı ) .
Using Equations (26) and (27) in Equation (28)
w ^ ( κ ı ) s ^ ( κ ı ) h 2 + ρ h 4 = h 2 .
which proves that this method is second order convergent and w ^ ( κ ) s ^ ( κ ) h 2 .

5. Results and Discussions

To test the accuracy of CBS method, three problems are discussed and compared with the existing methods in this section.

5.1. Problem 1

We consider the following DEs arising in viscoelastic flows and hydrodynamic stability problems as given in [29,31]
w ( 10 ) ( κ ) = 14175 4 ( j + w ( κ ) + 1 ) 11 ; 0 κ 1 ;
subject to BCs;
w 0 = w 1 = 0 , w ( 1 ) 0 = 1 2 = w ( 2 ) 0 , w ( 1 ) 1 = 1 ,
w ( 2 ) 1 = 4 , w ( 3 ) 0 = 3 4 , w ( 3 ) 1 = 12 , w ( 4 ) 0 = 3 2 , w ( 4 ) 1 = 48 .
the exact solution of given equation is w κ = 2 2 κ κ 1 . The values of fifteen unknowns j i from the Equations (18)–(20) are
j 2 = 0.10849167, j 3 = −0.12456626, j 8 = −0.13626667,
j 1 = 0.05166667, j 4 = −0.15061957, j 9 = −0.08666667,
j 0 = −0.00083333, j 5 = −0.16684713, j 10 = −0.0066667,
j 1 = −0.04833333, j 6 = −0.17169449, j 11 = 0.11333333,
j 2 = −0.09000833, j 7 = −0.16277005, j 12 = 0.28773333.
Table 2 and Table 3 analyzed the exact solution and cubic B-spline scheme (CBS) solution of problem 1 at h = 1 10 and h = 1 5 respectively. Figure 1, Figure 2 and Figure 3 analyze the exact solution with cubic B-spline scheme (CBS) solution of problem 1 at h = 1 10 and h = 1 5 graphically. Table 4 analyze the errors at those derivatives where boundary conditions (BCs) are defined in problem 1 at h = 1 10 .

5.2. Problem 2

We consider the following problem as given in [16]
w ( 10 ) ( κ ) = 9 ! ( e 10 w ( κ ) 2 ( 1 + κ ) 10 ) ; 0 κ e 1 / 2 1
subject to BCs;
w 0 = 0 , w e 1 / 2 1 = 1 2 , w ( 1 ) 0 = w ( 2 ) 0 = 1 , w ( 1 ) e 1 / 2 1 = e 1 2 ,
w ( 2 ) e 1 / 2 1 = e 1 , w ( 3 ) 0 = 2 , w ( 3 ) e 1 / 2 1 = 2 e ( 3 2 ) ,
w ( 4 ) 0 = 6 , w ( 4 ) e 1 / 2 1 = 6 e ( 2 ) ,
the exact solution of a given equation is w κ = ln ( 1 + κ ) where the domain [0, e 1 / 2 1 ] for h = 2 i e 1 / 2 1 .
The values of fifteen unknowns j i from Equations (18)–(20) are
j 2 = −0.13805879, j 3 = 0.1782805, j 8 = 0.4183388,
j 1 = −0.0662749, j 4 = 0.2311044, j 9 = 0.4601370,
j 0 = 0.0007014, j 5 = 0.2812925, j 10 = 0.5002580,
j 1 = 0.0634693, j 6 = 0.3290924, j 11 = 0.5388309,
j 2 = 0.1225218, j 7 = 0.3747130, j 12 = 0.57597018.
Table 5 and Table 6 analyzed the exact solution and cubic B-spline scheme (CBS) solution of problem 2 at h = 0.064872 and h = 0.12974426 respectively. Figure 4, Figure 5 and Figure 6 analyze the exact solution with cubic B-spline scheme (CBS) solution of problem 2 at h = 0.064872 and h = 0.12974426 graphically. Table 7 analyze the errors at those derivatives where boundary conditions (BCs) are defined in problem 2 at h = 0.064872 .

5.3. Problem 3

We consider the following equation as given in [29,33]
w ( 10 ) ( κ ) + e κ ( w ( κ ) ) 2 = e 3 κ + e κ ; 0 z 1
subject to BCs;
w 0 = w ( 2 ) 0 = w ( 4 ) 0 = w ( 1 ) 0 = w ( 3 ) 0 = 1 ,
w 0 = w ( 2 ) 0 = w ( 4 ) 0 = w ( 1 ) 0 = w ( 3 ) 0 = e 1
the exact solution of given equation is w κ = e κ . The values of fifteen unknowns j i the Equations (18)–(20) are
j 2 = 1.21938333, j 3 = −0.73961579, j 8 = −0.44858605,
j 1 = 1.10333333, j 4 = −0.66924328, j 9 = 0.405893650,
j 0 = 0.99833333, j 5 = 0.605557470, j 10 = 0.36726630,
j 1 = −0.9033333, j 6 = 0.547923909, j 11 = 0.33231776,
j 2 = −0.5333053, j 7 = 0.495772367, j 12 = 0.30069852.
Table 8 and Table 9 analyzed the exact solution and cubic B-spline scheme (CBS) solution of problem 3 at h = 1 10 and h = 1 5 respectively. Figure 7, Figure 8 and Figure 9 analyze the exact solution with cubic B-spline scheme (CBS) solution of problem 3 at h = 1 10 and h = 1 5 graphically. Table 10 analyze the errors at those derivatives where boundary conditions (BCs) are defined in problem 3 at h = 1 10 .

6. Conclusions

In this study, we present new scheme using CBS of some non-linear differential equations arising in visco-elastic flows and hydrodynamic stability problems. The proper selection for the choice of the scheme and an appropriate of adjustment BCs may cause elasticity for the betterment of the results. The new CBS scheme proposed in this study is very simple to apply in solving the non-linear DEs compared with some existing schemes. An advantage of using the CBS scheme is that it gives a spline function on each new time line which can be applied to achieve the numerical solutions at any stage in the space direction.

Author Contributions

Conceptualization, A.T., A.G. and A.K.; methodology, A.T., A.K. and M.N.N.; software, A.T., A.K., F.K. and K.S.N; formal analysis, S.A.A.K., K.S.N. and F.K.; writing-original draft preparation, A.K., A.G. and S.A.A.K.; writing-review and editing, A.T., K.S.N. and A.G.; visualization, F.K., M.N.N. and A.G.; supervision, M.N.N. and S.A.A.K.; funding acquisition, A.T.

Funding

This research is funded by Deanship of Scientific Research at Majmaah University, Project Number (R-1441-25).

Acknowledgments

The first author Asifa Tassaddiq (A.T) would like to thank Deanship of Scientific Research at Majmaah University, for supporting this work under Project Number (R-1441-25).

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Problem 1 at h = 1 10 .
Figure 1. Problem 1 at h = 1 10 .
Mathematics 07 01078 g001
Figure 2. Problem 1 at h = 1 5 .
Figure 2. Problem 1 at h = 1 5 .
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Figure 3. Problem 1 at h = 1 10 and h = 1 5 .
Figure 3. Problem 1 at h = 1 10 and h = 1 5 .
Mathematics 07 01078 g003
Figure 4. Problem 1 at h = 0.064872 .
Figure 4. Problem 1 at h = 0.064872 .
Mathematics 07 01078 g004
Figure 5. Problem 2 at h = 0.064872 and h = 0.12974426 .
Figure 5. Problem 2 at h = 0.064872 and h = 0.12974426 .
Mathematics 07 01078 g005
Figure 6. Problem 1 at h = 0.12974426 .
Figure 6. Problem 1 at h = 0.12974426 .
Mathematics 07 01078 g006
Figure 7. Problem 1 at h = 1 10 .
Figure 7. Problem 1 at h = 1 10 .
Mathematics 07 01078 g007
Figure 8. Problem 3 at h = 1 10 and h = 1 5 .
Figure 8. Problem 3 at h = 1 10 and h = 1 5 .
Mathematics 07 01078 g008
Figure 9. Problem 1 at h = 1 10 and h = 1 5 .
Figure 9. Problem 1 at h = 1 10 and h = 1 5 .
Mathematics 07 01078 g009
Table 1. Values of M ı ( κ ) and its derivatives.
Table 1. Values of M ı ( κ ) and its derivatives.
M ı κ M ı ( 1 ) κ M ı ( 2 ) κ
κ ı 2 , κ ı + 2 000
κ ı 1   1 / 6 1 / 2 h 1 / h 2
κ ı 4 / 6 0 2 / h 2
κ ı + 1   1 / 6 1 / 2 h 1 / h 2
otherwise000
Table 2. Analyzing exact solution and cubic B-spline scheme (CBS) solution of problem 1 at h = 1 10 .
Table 2. Analyzing exact solution and cubic B-spline scheme (CBS) solution of problem 1 at h = 1 10 .
κ Exact SolutionCBS SolutionAbsolute Error
000 0 × 10 0
0.1−0.0473684−0.04736651.90 0 × 10 06
0.2−0.0888889−0.08888226.67 0 × 10 05
0.3−0.1235294−0.12354883.81 0 × 10 05
0.4−0.1500000−0.15098191.02 0 × 10 04
0.5−0.1666667−0.16695041.72 0 × 10 04
0.6−0.1714286−0.17149922.03 0 × 10 05
0.7−0.1615385−0.16153021.70 0 × 10 06
0.8−0.1333333−0.13331729.16 0 × 10 05
0.9−0.0818182−0.08180002.18 0 × 10 05
100 0 × 10 0
Table 3. Analyzing exact solution and CBS solution of problem 1 at h = 1 5 .
Table 3. Analyzing exact solution and CBS solution of problem 1 at h = 1 5 .
κ Exact SolutionCBS SolutionAbsolute Error of CBS
000 0 × 10 0
0.2−0.0888889−0.08880008.89 0 × 10 05
0.4−0.1500000−0.15002222.98 0 × 10 05
0.6−0.1714286−0.17147781.15 0 × 10 05
0.8−0.1333333−0.13330003.73 0 × 10 05
100 0 × 10 0
Table 4. Errors at derivatives where boundary conditions (BCs) are defined in problem 1 at h = 1 10 .
Table 4. Errors at derivatives where boundary conditions (BCs) are defined in problem 1 at h = 1 10 .
κ CBS-Solution of w ( 1 ) ( κ ) CBS-Solution of w ( 2 ) ( κ ) CBS-Solution of w ( 3 ) ( κ ) CBS-Solution of w ( 4 ) ( κ )
0−0.50.50.751.5
0.1−0.44590.58251.05851.93853
0.2−0.38120.71171.33982.54026
0.3−0.30310.85051.35433.38062
0.4−0.21140.98261.43784.57764
0.5−0.10541.13801.97306.32099
0.60.02041.37723.09948.92485
0.70.17711.75794.662412.92780
0.80.38052.30976.410519.29012
0.90.64803.04008.451729.80422
1141248
Table 5. Analyzing exact solution and CBS-solution of problem 2 at h = 0.064872 .
Table 5. Analyzing exact solution and CBS-solution of problem 2 at h = 0.064872 .
κ Exact SolutionCBS SolutionAbsolute Error of CBS
000 0 × 10 0
0.0650.062854730.06285014.650 ×   10 06
0.130.121991290.12197281.850 ×   10 05
0.1950.177825120.17779143.370 ×   10 05
0.2590.230705700.23066514.060 ×   10 05
0.3240.280929820.28089453.530 ×   10 05
0.3890.328751640.32872922.250 ×   10 05
0.4540.374390530.37438051.000 ×   10 05
0.5190.418037110.41803422.920 ×   10 06
0.5840.459858070.45985755.980 ×   10 07
0.6480.50.5 0 × 10 0
Table 6. Analyzing the exact solution and CBS solution of problem 2 at h = 0.12974426 .
Table 6. Analyzing the exact solution and CBS solution of problem 2 at h = 0.12974426 .
κ Exact SolutionCBS SolutionAbsolute Error of CBS
000 0 × 10 0
0.1300.12199120.12191387.75 0 × 10 05
0.2590.23070570.23048042.25 0 × 10 04
0.3890.32875160.32867737.43 0 × 10 05
0.5190.418037110.41802818.96 0 × 10 06
0.6490.50.5 0 × 10 0
Table 7. Errors at derivatives where BCs are defined in problem 2 at h = 0.064872 .
Table 7. Errors at derivatives where BCs are defined in problem 2 at h = 0.064872 .
κ CBS Solution of w ( 1 ) ( κ ) CBS Solution of w ( 2 ) ( κ ) CBS Solution of w ( 3 ) ( κ ) CBS Solution of w ( 4 ) ( κ )
01−12−6
0.0650.93893−0.882881.67530−4.66533031
0.130.88490−0.782641.42971−3.68168892
0.1950.83690−0.697381.20485−2.94393959
0.2590.79396−0.626321.00104−2.38195984
0.3240.75524−0.567510.83630−1.94791017
0.3890.72004−0.517810.72045−1.60848492
0.4540.68786−0.474030.64400−1.34006674
0.5190.65840−0.434260.58187−1.12562522
0.5840.63139−0.398540.51160−0.95268994
0.6480.60653−0.367880.44626−0.81200035
Table 8. Analyzing exact solution and CBS solution of problem 3 at h = 1 10 .
Table 8. Analyzing exact solution and CBS solution of problem 3 at h = 1 10 .
κ Exact SolutionCBS SolutionAbsolute Error of CBS
0110
0.10.90483740.90484174.25 0 × 10 06
0.20.81873080.81874711.63 0 × 10 05
0.30.74081820.74084833.01 0 × 10 05
0.40.67032000.67035773.77 0 × 10 05
0.50.60653070.60656623.55 0 × 10 05
0.60.54881160.54883762.59 0 × 10 05
0.70.49658530.49659991.46 0 × 10 05
0.80.44932900.44933506.08 0 × 10 06
0.90.40656970.40657121.50 0 × 10 06
10.36787940.36787940
Table 9. Analyzing exact solution and CBS solution of problem 3 at h = 1 5 .
Table 9. Analyzing exact solution and CBS solution of problem 3 at h = 1 5 .
κ Exact SolutionCBSAbsolute Error of CBS
011 0 × 10 0
0.20.81873080.81880006.92 0 × 10 05
0.40.67032000.67051881.99 0 × 10 04
0.60.54881160.54891321.02 0 × 10 04
0.80.44932900.44935252.35 0 × 10 05
10.36787940.3678794 0 × 10 0
Table 10. Errors at derivatives where BCs are defined in problem 3 at h = 1 10 .
Table 10. Errors at derivatives where BCs are defined in problem 3 at h = 1 10 .
κ CBS Solution of w ( 2 ) ( κ ) , w ( 4 ) ( κ ) CBS Solution of w ( 1 ) ( κ ) , w ( 3 ) ( κ )
01−1
0.10.90482409−0.90484731
0.20.81870008−0.81872330
0.30.74077662−0.74079984
0.40.67027318−0.67029640
0.50.60648354−0.60650676
0.60.54876876−0.54879198
0.70.49655070−0.49657392
0.80.44930633−0.44932955
0.90.40656241−0.40658563
10.36787944−0.36787944

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Tassaddiq, A.; Khalid, A.; Naeem, M.N.; Ghaffar, A.; Khan, F.; Karim, S.A.A.; Nisar, K.S. A New Scheme Using Cubic B-Spline to Solve Non-Linear Differential Equations Arising in Visco-Elastic Flows and Hydrodynamic Stability Problems. Mathematics 2019, 7, 1078. https://doi.org/10.3390/math7111078

AMA Style

Tassaddiq A, Khalid A, Naeem MN, Ghaffar A, Khan F, Karim SAA, Nisar KS. A New Scheme Using Cubic B-Spline to Solve Non-Linear Differential Equations Arising in Visco-Elastic Flows and Hydrodynamic Stability Problems. Mathematics. 2019; 7(11):1078. https://doi.org/10.3390/math7111078

Chicago/Turabian Style

Tassaddiq, Asifa, Aasma Khalid, Muhammad Nawaz Naeem, Abdul Ghaffar, Faheem Khan, Samsul Ariffin Abdul Karim, and Kottakkaran Sooppy Nisar. 2019. "A New Scheme Using Cubic B-Spline to Solve Non-Linear Differential Equations Arising in Visco-Elastic Flows and Hydrodynamic Stability Problems" Mathematics 7, no. 11: 1078. https://doi.org/10.3390/math7111078

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