Research Inventy: International Journal Of Engineering And Science
Vol.4, Issue 1 (January 2014), PP 46-51
Issn(e): 2278-4...
Numerical Solution Of Second Order….

III

CONSTRUCTION OF CANONICAL POLYNOMIALS

The construction of Canonical Polynomial...
Numerical Solution Of Second Order….

p Q x  p Q x  ...  p Q x    F x, t Q t dt    k x, t Q t  a
...
Numerical Solution Of Second Order….

y 0  1
and ,
y ' 0  1
For N = 2, we seek the approximate solution

as a trunc...
Numerical Solution Of Second Order….
For the power of x:
(17)
For the power of

:
(18)

By using the condition equations, ...
Numerical Solution Of Second Order….



1 6 1 4
5 4 1
x  x  x 3  2 x 2     x  t 
30
3
3 3 0

Then simplified fu...
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E041046051

  1. 1. Research Inventy: International Journal Of Engineering And Science Vol.4, Issue 1 (January 2014), PP 46-51 Issn(e): 2278-4721, Issn(p):2319-6483, www.researchinventy.com Numerical Solution of Second Order Nonlinear FredholmVolterra Integro Differential Equations by Canonical Basis Function 1, Taiwo, O . A, Ganiyu , 2,K. A and  Okperhie, E. P Department Of Mathematics, University Of Ilorin, Nigeria  Department Of Mathematics And Statistics, Federal Polytechnic, Bida, Nigeria ABSTRACT : This paper deals with the construction of Canonical Polynomials basis function and used to find approximation solutions of Second order nonlinear Fredholm – Volterra Integro Differential Equations. The solutions obtained are compared favorably with the solutions obtained by Cerdik-Yaslan et. al [1]. One of the advantages of the method discussed is that solution is expressed as a truncated Canonicals series, then both the exact and the approximate solutions are easily evaluated for arbitrary values of x in the intervals of consideration to obtain numerical values for both solutions. Finally, some examples of second order nonlinear Fredholm – Volterra Integro Differential Equations are presented to illustrate the method. KEY WORDS: Canonical Polynomials, Nonlinear Fredholm – Volterra integro Differential Equations, Approximate solution I. INTRODUCTION In recent years, there has been a growing interest in the Integro Differential Equations (IDEs). IDEs play an important role in many branches of linear and nonlinear functional analysis and their applications in the theory of engineering, mechanics, physics, chemistry, astronomy, biology, economics, potential theory and electrostatics. Higher order integral differential equations arise in mathematical, applied and engineering sciences, astrophysics, solid state physics, astronomy, fluid dynamics, beam theory etc. to mention a few are usually very difficulty to solve analytically, so numerical method is required. Variational Iteration Method (VIM) is a simple and yet powerful method for solving a wide class of nonlinear problems, first envisioned by He [ 2,3,4,5]. VIM has successfully been applied to many situations. For example, He [4] solved the classical Blasius equation using VIM. He [2] used VIM to give approximate solutions for some well known nonlinear problems. He [3] used VIM to solve the well known Blasius equation. He [5] solved strongly nonlinear equation using VIM. Taiwo [6] used Canonical Polynomials to solve Singularly Perturbed Boundary Value Problems. The idea reported in Taiwo [6] motivated the work reported in this paper in which Canonical Polynomials obtained for Singularly Perturbed Boundary Value Problems are reformulated and used to solve nonlinear Fredholm – Volterra Integro Differential Equations. Some of the advantages of Canonical Polynomials constructed are it is generated recursively, it could be converted to any interval of consideration and it is easy to use and user’s friendly in term of computer implementation. GENERAL NONLINEAR FREDHOLM – VOLTERRA INTEGRO DIFFERENTIAL EQUATION CONSIDERED II. The general nonlinear Fredholm – Volterra Differential Equation considered in the paper is of the form: m P y k 0 k k 1 x 1 1 ( x)  g ( x)  1  F ( x, t ) y (t )dt  2  K ( x, t ) y (t )dt (1) With the mixed conditions m 1 [ a j 0 ij y ( j ) (1)  bij y ( j ) (1)  cij y ( j ) (c) ]   i i  0(1) n y( x) and y(t ) are unknown functions, g ( x), K ( x, t ), F ( x, t ) are smooth functions, Pk , aij , bij , cij , 1 , 2 ,  i are constants or transcendental or hyperbolic functions and P0  0 Where 46 (2)
  2. 2. Numerical Solution Of Second Order…. III CONSTRUCTION OF CANONICAL POLYNOMIALS The construction of Canonical Polynomials is carried out by expanding the left hand side of (1). Thus from (1), we write the left hand side in an operator form as: Ly  P0  P 1 d d2  P2 2  dx dx ...  Pm dm dx m Let, LQr ( x)  x k (3) Then, Lx k  P0 x k  P kxk 1  P2 k (k  1) x k 2  P3k (k  1)( k  2) x k 3  .......... 1 (4) Thus, making use of (3), we have L[ LQk ( x)]  P0 LQk ( x)  P kLQk 1 ( x)  P2 k (k  1) LQk 2 ( x) 1 (5) Hence, making use of (3) in (5), we have Qk ( x)  1 k [ x  P kQk 1 ( x)  P2 k (k  1)Qk 2 ( x)  .......... ] 1 P0 (6) Thus, (6) is the recurrence relation of the Canonical Polynomials. IV. DESCRIPTION OF STANDARD METHOD BY CANONICAL POLYNOMIALS In this section, the Standard method by Canonical Polynomials for solving (1) and (2) is discussed. The method assumed an approximate solution of the form: y ( x )  yn  x   n  a Q ( x) r 0 r (7) r Where n is the degree of approximant, ar (r Polynomials generated recursively by (6). Substituting (7) into (1), we obtain  0) are constants to be determined and Qr (x) are the Canonical n n n r 0 r 0 r 0 P0  a r Qr ( x)  P1  a r Q ' ( x)  P2  a r Qr ' ' ( x)  ..... n n (8)  g ( x)  1  F ( x, t ) a r Qr (t )dt  2  K ( x, t ) a r Qr (t )dt 1 1 r 0 x 1 r 0 This is further simplified to give PO aoQO x   a1Q1 x   a2Q2 x   a3Q3  ...   P a Q  x   a Q  x   a Q  x   a Q   P aoQ 'O  x   a1Q '1  x   a2Q ' 2  x   a3Q '3  ... 1 '' 2 o O 1 '' 1 '' 2 2 3 '' 3   ...     Pm aoQ m O  x   a1Q m1  x   a2Q m 2  x   a3Q m 3  ...  g x   1  F x, t aoQ0 t   a1Q1 t   a2Q2 t   ...  a N QN t dt 1 1   2  k  x, t a o Q0 t   a1Q1 t   a 2 Q2 t   ...  a N Q N t dt 1 1 47 (9)
  3. 3. Numerical Solution Of Second Order…. p Q x  p Q x  ...  p Q x    F x, t Q t dt    k x, t Q t  a   p Q  x   p Q  x   ...  p Q  x     F x, t Q t dt    k x, t Q t  dta   p Q  x   p Q  x   ...  p Q  x     F  x, t Q t dt    k  x, t Q t  dt a Collect like terms in (9), we obtain o o 1 1 2 ' o 1 ' 1 1 2 1 1 1 2 o 1 1 1 1 0 x 2 1 1 1 m 2 m x o 1 m 1 m ' 2 2 1 m o m 1 x 2 1 2 2 1 2     p Q x   p Q ' x   p Q x   ... p Q m x    1 F x, t Q t dt  1 N 2 N m N 1 N  o N  1  aN  g ( x) x  2  k x, t QN (t )dt  1   x  xi , we obtain Thus, (10) is collocated at point p Q x   p Q x   ...  p Q x     F x , t Q t dt    k x , t Q t  a   p Q  x   p Q  x   ...  p Q  x     F  x , t Q t dt    k x , t Q t  a   p Q  x   p Q x   ...  p Q  x     F x , t Q t dt    k  x , t Q t  a ' o o i 1 o i 1 m o m i 1 i 1 ' 1 i m m 1 i 1 2 i 1 ' 2 i m m 2 i 1 2 i o 0 2 2 1 i 1 i 2 1 x 1 1 N m2 1 1 1 b  a i i 1 x  xi  a  2 i 1 ' m  p o Q N  xi   p1Q N  xi   ...  p m Q N  xi   1  Where, o 1 1 o    x i 1 o (10) 1 2  F  xi , t Q N t dt  2  k  xi , t Q N t  a N (11) x 1 , i  1, 2, 3, ...,N - m  1 (12) Thus, substituting (12) into (11) gives rise to N-m+1 algebraic linear equation in (N+1) unknown constants ar r  0. hence, extra m equations are obtained from (2). Altogether, we have (N+1) algebraic linear equation in (N+1) unknown constants. These equations are then solved by Gaussian Elimination Method to obtain the unknown constants which are then substituted into (7) to obtain the approximate solution for the value of N. V. Demonstration of Standard Method by Canonical Basis Function on Examples We solved the Fredholm-Volterra nonlinear Integro Differential equation of the form: Example 1: 1 y ' '  x   xy ' x   xy x   g  x    1 xtyt dt   x 1 Where g x   2 6 1 4 23 5 x  x  x3  2 x 2  x  15 3 15 3 together with the conditions 48 x  2t  y 2 t dt (13)
  4. 4. Numerical Solution Of Second Order…. y 0  1 and , y ' 0  1 For N = 2, we seek the approximate solution as a truncated Canonical series. The values of Therefore, Equation (13) now becomes 2a 2  x ( a1  2a 2 x)  x(a0  a1 x  a 2 ( x 2  2))  g ( x) 1   xt (a0  a1 t  a 2 (t 2  2))dt  1  x 1 ( x  2t )(a0  a1t  a 2 (t 2  2)) 2 dt (14) Thus, (14) is then simplified further and we obtain 2 6 1 4 5 x  x  x3  2x 2  15 2 2 2 a a x 4a a a a 10a 0 a 2 x a2 x4 2 2 2  a1 x  a 0 x  a 0  0 2  a 0 a1 x  0 1  0 2 x 4   3a 0 a 2  1 3 3 3 3 3 6 2 2 5 2 2 6 2 4 a x a 3a a x 2a a x 3a a x 28a1 a 2 2a 2 x 2a x  1  2  1 2  1 2  1 2    2 3 2 10 3 2 15 15 3 2 2 43a 2 x 7 a 2   (15) 15 3 2a 2  x ( a1  2a 2 x)  x(a 0  a1 x  a 2 ( x 2  2))  Comparing the powers of x in (15), we obtain the following: For the constant terms: (16) 49
  5. 5. Numerical Solution Of Second Order…. For the power of x: (17) For the power of : (18) By using the condition equations, we obtain. For (19) For : Implies These equations are then solved and the results obtained are substituted into the approximate solution and after simplification gives the exact solution y 2 ( x)  x 2 1 Example 2 We solved the Fredholm – Volterra Integro differential equation given as y ' ( x)  xy ( x)  g ( x)   x  t y t dt   x  t y 2 t dt 1 0 Where g x   x 0 1 6 1 4 5 4 x  x  x 3  2x 2  x  30 3 3 3 (20) and y0  2 Thus, the approximate solution given in (7) for case N=2 becomes 2 y 2  x    a r Qr  x  (21) r 0 Hence, y 2 x   a0 Q0 x   a1Q1 x   a 2 Q2 x  (22) For this example, Qi  x   x i  iQi 1 x ; i  0 (23) We obtain the following Q0  x   1 Q1 x   x  1 Q2  x   x 2  2 x  2 Q3  x   x 3  3 x 2  6 x  6 (24) Substituting, (24) into (22), we obtained   y 2  x   a 0   x  1a1  x 2  2 x  2 a 2 (25) Putting (25) into (20), after simplification we obtain     a1  2 x  2 a 2  xa 0  x 2  x a1  x 3  2 x 2  2 x a 2  50
  6. 6. Numerical Solution Of Second Order….  1 6 1 4 5 4 1 x  x  x 3  2 x 2     x  t  30 3 3 3 0 Then simplified further, we obtain     1 1 a1  2 x  2a2  xa0  x 2  x a1  x 3  2 x 2  2 x a2   30 x 6  x 4  x 3  2 x 2 3 2 2 4 x 2a 2 a 0  a1  2a 2   a1  2a 2  5 4 2 a 0  a1  2a 2   x  xa 2  x 3 3 12 2 2 2 5 a  2a2 a0  a1  2a2  a x x a 2 a1  2a 2   2   x3 1 30 10 3   We then collected like terms of x and the following sets of equations are obtained. For constant term: a1  2a 2  a0 1 7 4  a1  a 2  2 6 12 3 For power of x: 3 4 5 2a 2  2a0  a1  2a 2  a 2   2 3 3 Therefore, using the condition, we obtain a 0  a1  2a 2  2 These equations are then solved and the results obtained are substituted into the approximation solution and after simplification gives the exact solution y 2 x   x 2  2 VI CONCLUSION The method used in this paper is highly accurate and efficient. At lower degree of N ( degree of approximant used ), the method gives the exact solution for the two examples considered without extra computational cost. Also, the Canonical Polynomials generated are easily programmed and user friendly. REFERENCES [1] [2] [3] [4] [5] [6] Cerdik-Yaslan, H. and Akyus-Dascioglu, A. (2006). Chebyshev Polynomial solution of nonlinear Fredholm Integro Differential Equation, Juornal of Arts and Sciences. Vol. 5, Pp. 89-101. He J . H. (1999). Variational iteration method. A kind of nonlinear analytical technique: some examples. Int. J. Nonlinear Mech. 34(4) Pp. 699-708 He. J . H. (2000) Variational iteration method for autonomous ordinary differential systems. Appl. Math. Comput. 114, 115 -123 He. J. H. (2003. A simple perturbation approach to Blasius equations. Apll. Math. Comput., 140, 217 -222 He. J. H. (2-006). Some asymptotic methods for strongly nonlinear equations. Int. J. Modern Physics. B20, 1141 1199 Taiwo, O .A. (1991). Collocation approximation for singurly perturbed boundary value problems. Ph.D thesis (unpublished) , University of Ilorin, Nigeria. 51

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