Applied Mathematics, 2011, 2, 1243-1251
doi:10.4236/am.2011.210173 Published Online October 2011 (http://www.SciRP.org/journal/am)
Copyright © 2011 SciRes. AM
High Accuracy Arithmetic Average
Discretiz ati on f or Non-Linear Two Point
Boundary Value Problems with a Source
Function in Integral Form
Ranjan K. Mohanty, Deepika Dhall
Department of Mat hematics, Faculty of Mathematical Sciences, University of Delhi, Delhi, India
E-mail: rmohanty@maths.du.ac.in
Received June 17, 2011; revised June 30, 2011; accepted July 6, 2011
Abstract
In this article, we report the derivation of high accuracy finite difference method based on arithmetic average
discretization for the solution of , 0 < x < 1, 0 < s < 1 subject to natural boundary
conditions on a non-uniform mesh. The proposed variable mesh approximation is directly applicable to the
integro-differential equation with singular coefficients. We need not require any special discretization to ob-
tain the solution near the singular point. The convergence analysis of a difference scheme for the diffusion
convection equation is briefly discussed. The presented variable mesh strategy is applicable when the inter-
nal grid points of the solution space are both even and odd in number as compared to the method discussed
by authors in their previous work in which the internal grid points are strictly odd in number. The advantage
of using this new variable mesh strategy is highlighted computationally.

1
0
,,, duFxuu Kxs
 

s
Keywords: Variable Mesh, Arithmetic Average Discretization, Non-Linear Integro-Differential Equation,
Diffusion Equation, Simpson’s 1
3Rd Rule, Singular Coefficients, Burgers’ Equation, Maximum
Absolute Errors
1. Introduction
We consider the non-linear differential equation with a
source function in integral form:

1
0
,,, d,0,1uFxuuKxss xs
 
 
. (1)
The two point boundary conditions associated with (1)
are given by:

0
0,1uu
1
 (2)
where 0
, 1
are finite constants. We assume that K(x, s)
is a real valued function of both variables in the range
0 x, s 1.
Let
 
1
0
,d
I
xKxs
and

,, ,,
F
xuuIxG xuu
Then we may re-write (1) as
,, ,01uGxuu x
 
 (3)
Keller [1] has given the conditions under which the
differential Equation (3) together with the boundary con-
ditions (2) has a unique solution. We assume that these
conditions are satisfied in the problem that we are con-
sidering. In addition, we assume that

60,1ux C
and
4
,0Kxs C,1.
Many physical problems from fluid mechanics, fluid
dynamics, elasticity, magneto-hydrodynamics, plasma
dynamics, oceanography, biological model, boundary
layer theory, …etc are described mathematically by non-
linear integro-differential equations. Davis and Rabi-
nowitz [2], Philips [3], Linz [4], Lakshmikantham and
s
1244 R. K. MOHANTY ET AL.
Rao [5], Atkinson [6], and Agarwal and O’Regan [7]
have discussed various techniques for numerical integra-
tion and methods for approximate solution of integro-
differential equations and their applications to various
physical models. Most of the nonlinear differential equa-
tions cannot be solved analytically. So it is required to
obtain efficient numerical methods. Jain et al. [8] have
discussed variable mesh methods for the solution of two
point nonlinear boundary value problems; however, their
methods are not applicable to differential equations with
singular coefficients. In recent years, Mohanty et al. ([9-
12]) have discussed a family of third order variable mesh
methods for the solution of two point non-linear bound-
ary value problems and obtained convergent solution for
singular problems. More recently, Mohanty and Dhall
[13] have proposed a three-point third order variable
mesh method for the solution of non-linear integro-dif-
ferential Equation (1), which is applicable only when the
internal grid points of the solution region are odd in
number. In this paper, we propose an efficient third order
variable mesh method based on arithmetic average dis-
cretization for the solution of non-linear integro-differ-
ential Equation (1), which is applicable when the internal
grid points of the solution region are both odd and even
in number. In next section, we give mathematical details
of the method. In Section 3, we discuss the application of
the proposed method to an integro-differential equation
with singular coefficients and study the convergence
analysis. In Section 4, we give numerical results to jus-
tify the utility of the proposed new strategy. Final re-
marks are given in Section 5.
2. Mathematical Details of the
Discretization
We discretize the solution region [0,1] with the non-
uniform mesh such that 01 1
01
N
xx x

1N
. Let
11 be the variable mesh size in x-di-
rection, where . Grid points are given by
0
kkk
hxx


i

01k
0
1
ik
k
x
xh

, . The mesh ratio is

11 1iN

10
kkk
hh
. When 1
k
, then it reduces to the
constant mesh case. The off-step points are defined by
1
22
kk
k
k
h
xx
 and 1
22
k
k
k
h
xx
 etc. Let the exact
solution of u(x) at the grid point k
x
be denoted by
and u be the approximate value of .

k
Uuxkk k
Let us construct a numerical method for evaluating the
U
integral

1
0
d
x
x
, where
x
is a real-valued con-
tinuous function in [0,1].
Using the derivation technique discussed in [13], we
obtain a fourth order accurate integral formula based on
Simpson’s 1
3rd rule (see Evans [14]).

1
1
2
1
1
d4
6
0,1, 2,
k
k
xkk
k
x
h
xx
kN

,
k

(4)
where
kk
x

, ,

11kk kk
xxh
 


1
1
11
22 2
k
k
kk
h
xx
 








 , etc.
Then on the variable mesh the value of the integral
 
1
12
01
1
0
1
11
02
ddd
4
6
N
N
x
xx
xx x
Nkkk
k
k
d
x
xxxxxx
h

 





 
x
(5)
can be found by the repeated application of (4).
Now we discuss the third order numerical method based
on arithmetic average discretization for the differential
Equation (3).
At the grid point k
x
, we denote
,,
kkkk k
UGxUU G
 
 (say),
and
,
kk
kk
x
x
GG
uu


 

 

 
.
Using Taylor expansion, from (3), we obtain


11
2
5
11
22
1
1,
32
1
kkkkk
k
kk kk
kk
k
UUU
hGGGO



 




k
h
(6)
We need the following approximations:
11
2
1
2kk
k
UUU

, (7a)
11
2
1
2kk
k
UUU

, (7b)
11
2
1
kk
kkk
UU
h

U
,
(7c)
1
2
1
kk
kk
UUU
h

1
, (7d)
Copyright © 2011 SciRes. AM
R. K. MOHANTY ET AL.
Copyright © 2011 SciRes. AM
1245


22
11
11
1
kkkk
kkk
UUU
h








22
3
11
22
3,
24
1
kk kk kkk
kk
k
h
GGUU Oh

  
 
(9a)
kk
U, (7e)
and let


2
3
11
22
3,
24
1
kkkkkk
kk
k
h
GGUU Oh

  
 
(9b)
1 111
2 222
,,
k kkk
GGxUU
 


. (8)
From (9a) and (9b), it follows that
It is then easy to see that


2
23
11
22
2113 3,
224
IV
kk
kkkkkkkkk kk
kk
hh
GGUUU UUOh

  
 1
(10a)

 
2
23
11
22
1133
224
IV
kk
kkkkkkkkk k
kk
hh
GGUU UUOh
 
 
 ,1
(10b)

23
2,
kk kkkk
UU ahUOh

Now, let 1
 , (12a)
2
11
22
kk k
kk
UUahGG


 

, (11a)


2
3
31 ,
6
1
k
kkkkkk
k
h
UUb UOh

 

 

(12b)
11
22
kkk
kk
UUbhG G



 

, (11b) Further, we define
,,
k kkk
GGxUU
(13)
where “a” and “b” are parameters to be determined.
With the help of (10a) and (10b), from (11a) and (11b),
we obtain and with the help of (12a) and (12b), it follows that


2
23
231
6
k
kk kkkkkkkkk
h
GG ahUbUOh
 
 

 

,1 (14)
Then at each internal grid point xk, the differential Equation (3) is discretized by



2
1111
22
1
1,
32
k
kk
kkkkkkk k
kk
h
UUUG GGTk
 



 


11
N
(15)
where

5
kk
TOh, provided 1
k
.
Now with the help of the approximations (9a), (9b)
and (14), from (6) and (15), we obtain the local trunca-
tion error




4
22
1318 161,
72
k
kkk kkkkkkkkkkk
h
TaUbU


 
 

5
1
Oh
(16)
The proposed numerical method (15) to be of
3
k
Oh ,
the coefficient of in (16) must be zero and we obtain
the values of parameters
4
k
htial equation
 
1
2
2
0
,d,
0, 1
du du
A
rBrufrKrs
dr
dr
rs


s
(17)

22
11
,,
86(1
kk kk
k
ab
 
  

)
where
 
2
,ArBr
rr
and the local truncation error given by (16) becomes

5
kk
TOh, 1
k
.
. For
= 1 or 2, the
equation above represents cylindrical or spherical prob-
lem, respectively. Replacing the variable x by r and ap-
plying the formula (15) to the integro-differential equa-
3. Application to Singular Problems
Consider the linear second order model integro-different- tion (17), we obtain
1246 R. K. MOHANTY ET AL.



2
1111111 1
22222 2
111111
22222 2
13
10,11
2
kk
kkk kkk kkkkk k
kkkkkkkk
kkkkk k
h
UUU AUBUfI
A
UBUfI AUBUfITk
 

 



 







 





N
(18)
where

,,,
kkkkkkkk
UurAArBBrffr 
,
 
1
12
01
1
0
,d ,d
N
N
r
rr
kk kk
rr r
I
IrKrssKrss


 




,

22
11111 111111 1
22222 222222 2
1
8
kkk
kk kkkkk kkkkkkk
h
UUAU BUf IAU BUf I

   
 

 


,


2
11 1111 111111
22 222222 2222
1
61
kkk
kk kkkkk kkkkkk k
k
h
UUAU BUf IAU BUf I

  
 
 
 


,
nd
eme (18) is directly applicable to sin-
gu
he scheme (18), we use the fol-
lo
a

5
kk
TOh.
te that the schNo
lar problem (17) and do not require any fictitious
points outside the solution region to compute the scheme.
The scheme is also applicable when the internal grid
points of the solution region are both even and odd in
number as compared to the scheme discussed by Mo-
hanty and Dhall [13] in which the internal grid points are
strictly odd in number.
For convergence of t
wing approximations:

22
3
1
228
kk kk
kk k
k
hh
k
I
IIIO


 h
, (19a)

2
3
1
228
kk
kkk
k
hh
k
I
IIIOh

 , (19b)

22
3
1
228
kk kk
kk k
k
hh
k
A
AAAO


 h
, (19c)

2
3
1
228
kk
kkk
k
hh
k
A
AAAOh

 . (19d)
Similarly, we can define the approximations for 1
2
k
B
and 1
2
k
f, where
 


,,
,, ,e
kkkk
kk
dd
AArBBr
dr dr
dK
ffrKrs
dr r




tc
and


1
12
01
1
0
,d
,d,
N
N
kk k
r
rr
k
rr r
d
IIrKrss
dr
K
rs s








 
 

1
12
01
1
2
2
0
,d
,d.
N
N
kkk
r
rr
k
rr r
d
I
IrK rs s
dr
K
rs s
 








 
Using the approximations (19) in (18), neglecting high
order terms and simplifying we get the modified scheme
in compact form

1
1
1
10
kkkk k
kkk k
k
s
ub UdiagU
sup UT

 
 (20)
where




2

2
2
22
23
6328
62
12
72
11 ,
48
kkkkk k
kkkkk
kk k
kk
kkkkk
kkk k
kk kkkkk
hhhh
subAAAA
hh
BB
Ah AhAB
ABh

 














Copyright © 2011 SciRes. AM
R. K. MOHANTY ET AL.
1247

   






222
22
22 23
2
1 1
11 11
6643 48
1111 12,
362 48
kkkkk
kkkkkkkkkkk
kkkk kk
kkkkkkkkkk
kkk
kkk
hB
hh hhB
diaghAAAB
Ah Bh
Bh
AA

 
 

kkk
Bh
 

 

 


 



 





22 22
222 3
632 862
11
2,
72 48
kkk kkkkkkkk
kkk kkk k
kk kkkkkkkk
kkkkk
hh hhhh
supAAAABB
1
A
hA
AABh
 
 


 





 



Bh







22
2
22
2
1
13
64
11
1,
12 4
kkkk
kkk
kkk
kkkk kk
kkkk
Bh
hfI
Ah hf Ihf I


 



 



 
kkk

 
 


and
Ine boundary values

5.
kk
TOh
corporating th00
U
, 11N
U
,
can be writ-the difference Equation (20) in ma
ten as
(21)
where
trix form


k
h 0DPU T
,1, 1
kk

D
are tri-diagonal matrices of order
and P = [subk, diagk, supk]
N and


1102 11
,,,,1 T
NNN
sub sup



 


,

T
12
,,,
N
UU U, 12
,,
k
hTT

0, 0,, 0T
0 are vectors.
U


,T
TT

12
,,, T
N
uu u
uU which satisfies
N
and
Let
0DPu
(22)
Let kkk
euU
nce of
12
,,e U
btracting (21) f
be the discretization error (in the
abse round of errors) at the grid point rk and
be the error vector.
), we obtain the error equa-
tion

,T
N
eEu
Surom (22
e

k
hDPET (23)
Let 1k
A
G
, 2k
A
G
, 3k
A
G
 , 1k
BH, 2k
BH
,
3k
B
 3, H1, H2 and HH, where G1, G2, G3 are some
positive constants. If pi, j be the (i, j)th-element of P, then




2
3
, 111,
kkk
hGOhkN

 
(24a)
2
,1 11
1
12
66
k
kk k k
h
pG






2
2 1
k k
hGH
 




2
23
,112 11
1
12 , 21
66
kkk
kkk kk
h
pGhGHGOhk

 


Thus for suffic, the matrix (D r-
educible (see Voung [16]).
,
N
(24b)
kk
h
iently small hk
arga [15] and Y
+ P) is i
r
Let Sk be the sum of elements of the kth-row of (D + P),
then




2
2
23
1
12 23,
666
kk
kk
kkkkkkkkk k
hh
SAhABAO

 





 




1
hk
(25a)




2
2
22
1
112 32,
3
66
6
kk
kk
kkkkkkkkk kk
hh
SAhA BAOhkN

 



 


,
(25b)
Copyright © 2011 SciRes. AM
1248
R. K. MOHANTY ET AL.



3
1,211.
2
k
kk k kk
h
SBOhkN

 
(25c)
2
Let 1*1
min k
kN
GA

, 11
max k
kN
GA

, 1*1
min k
kN
H
B

,
11
max k
kN
H
B

, then 0 < G1* G1 and 0 < H1*
H1
1
G
1
H
.
It is straightforward to show that for sufficiently small
hk, (D + P) is Monotone (see Varga [15] and Young [16]).
Hence (D + P)–1 exists and (D + P)–1 0.
From error Equation (23), we have


1
k
h
 EDPT
for sufficiently small hk, it is easy to show that
(26)
Thus

2
1*
23, 1
6
k
k k
hHk

 , (27a)
k
S

2
1*
32 ,
6
k
kkk
SH
kN


, (27b)

h

2
1,21
k
h
SHkN

 
1*
2
kk k1. (27c)
Since

1

,0
ik
DP and

,
1ik
k
DP . 1
k
S,
1
N
11iN,
hence


1
2
,
1*
16
,1
23
ik kkkk
k
SHh

 
DP (28a)


1
2
,
1*
16
,
32
ik kkkk
kN
SHh

 
DP
Further,
(28b)



1N1
2
21*
12
,
min 1
11
kkkk
kN S
,
21
ik k
H
h
iN


 
DP
(29
For any matrix M, we define
)
,
1
ik
k
m
,
1
max
N
iN
M
where is the (i, k)th-element of M and
,ik
m

1
max
ki
iN
hT

T.
With the help of (28a), (28b), (29), from (26), we ob-
tain



5
2
1*
3
61 1 1
23 3132k
kkk
kk
k
Oh
Hh
Oh







E
(30
This establishes the third order convergence of the
method (20).
merical Results
In this section, we consider another ne
method for the solution of non-linear in
Equation (1) as
)
4. Nu
w variable mesh
tegro-differential




11
2
11
22
23 3
kk
2
4
11
1
12 2
12 2,
11
kkkkk
kk
kk
k
kk k
UUU
hFF
h
22
23 3
kk
k
I
IOh
N



 









(31)
where
k




111
2 222
,,
k kkk
FFxUU
 




,
1
1111
,,FFxUU



,
2222
kkkk 

and
1
 

,d,11 .
kkk
0s
I
IxKxs skN 
The approximations associated with 1
2
k
F
defined by (7a)-(7d). The order of accuracy of the method
(31) is of
are already
2
k
Oh
we replace the i
. For evaluating the integral associated
with (31), ntegral by the trapezoidal rule
(see Evans [14]).
 

1
12
01
1
0
1
1
0
ddd
2
N
N
x
xx
xx x
Nkkk
k
d
x
xxxxxx
h




 
x
(32)
In this section, we have solved two benchmark prob-
lems using the proposed method described by equation
(15) and compared our results with those obtained by
using the variable mesh method discussed by Mohanty
and Dhall [13] only for the cases wheinternal grid
points are odd in number. We have also puted our
ts using uniform mesh (when
n
com
resul 1
k
y be ob
) for all values
e boundary conditions matained using the
exact solution as a test procedure. The linear difference
equation has been solved using a tri-diagonlver,
whereas non-linear difference equations have been solved
using the Newton-Raphson method (see Kelly [17] and
of N. Th
al so
Copyright © 2011 SciRes. AM
R. K. MOHANTY ET AL.
1249
Ev aph
the iterations were stopped when absolute error tolerance
1,
ans [18]). While using the Newton-Rson method,
10–12 was achieved.
The unit interval [0,1] in the space-direction is divided
into (N + 1) points with
0
01 1NN
xxxx
 
where
1kkk
hxx
and
10,1,2,,.
kkk
hh kN

We may write


10 1110
1111212
1NNNNN
NN N
xxxx xxxx
hh hh
 
 
 
 

1
1.
(33)
For simplicity, we consider
k
(a constant), k =
1,
(N + 2), we can compute the value of h1 from (34). This
is the first mesh spacing on the left of the boundary and
the remaining mesh is determined by
2, , N, then from (33) we have
11
1.
1N
h
(34)
By prescribing the total number of mesh points to be
1kk
hh
,
oose the va
k = 1,
2, N. For variable mesh, we chlues of ,
1.2.
All computations were carrg dou-
ble precision arithmetic.
ied out usin
Example 4.1 1
2
22
dd 2
d
d
uu
urr
rr
rr
 

0
2
4e ed,01,
s
rrs
rsr



 
polar coordinates) (35)


(Linear equation in
The exact solution is given by

2
r
ur re
. The
maximum absolute errors are tabulated in Table 1 for
various values of N.
Example 4.2
 
2
22
dd d
2
d
uu u
uu
r2
4
e
dd
r
r
r
rr r
r







 
1
3
0
2
2e2ed,01,
s
rrs
rrrs


r
 
(Model Burgers equation in polar coordinates)
(36)
The exact solution is given by

2e
r
urr
. The maxi-
mum absolute errors are tabulated in Table 2 for various
valuesf N.
o
5. Final Remarks
s
umerical methods of accuracy of based on
ar e discretizations for tlution of the
non-linear integro-differential Equation (1). Mohanty
and Dhall [13] have developed a thi
esh method based on Numerov type
ich is only applicable to the solution space having odd
nuoposed va
ebut applicable to the
lution space having both odd and even number of in-
ternal grid points. In addition, the proposed methods are
directly applicable to singular problems and we do not
require any fictitious points near the boundaries to in-
and appli
tabulate
either in increasing or in de-
creasing order. So it is not possible to estimate the order
of convergence of the proposed method. Order of con-
vergence can be estimated for unifom mesh using the
formula
U
new n
ing three variable mesh points, we have discussed a

3
k
Oh
he soithmetic averagr
rd order variable
discretization, m
wh
mber of grid points. Although the prriable
sh method involve more algebra, m
so
corporate the singular point. The numerical results indi-
cate that the proposed method is computationally nearly
equal to the method discussed in [13]cable to
the solution space with all internal grid points. We have
d maximum absolute errors for different mesh
sizes. Our mesh sizes are

12 12hh1
h2
h
the maximum absolute errors for two grid mesh widths
log logee hh, where and are
e e
1
h and 2
h, respectively. For ex: in Table 2, let us con-
sider the case 1
, 0.01
, N = 30 and N = 60, i.e.
1
1
30
hh
(say) and 2
1
60
hh
(say) and the corre-
sponding maximum absolute errors are 0.3116 (–8) and
0.1978 (–9), respectively. Using the above formula the
Copyright © 2011 SciRes. AM
R. K. MOHANTY ET AL.
1250
Table 1. The maximum absolute errors for Example 4.1.
3
k
Oh -proposed method (20)
2
k
Oh -proposed method (31)
1
2
1
2
N
0.1
0.01
0.1
0.01
0.1
0.01
0.1
0.01
20 0.2062E–4 0.3334E–4 0.2528E–4 0.2800E–3 0.1906E–3 0.4772E–3 0.2040E–3 0.2240E–2
25 0.1519E–4 0.2511E–4
5E–4
0.1810E–4
*0.1
0.9455E–4
6E
34E
*0.1022E–4 *0.9075E–5 *0.1289E–4*0.1618E
4 0.8811E–5 0.1199E–4 0.1116E
0.8989E–5 0.7612E–5 0.9217E–5 0.7880E
23E
0.88745E
29E
88E 112E–3 0.1384E–4 E
28E
24E
7E 78E–4
28E–5 0.981E–4 0.1
888E
64E–5 0.9179E–4 0.1148E–4 0.9831E–4 0.1143E–4
*0.1416E–4 *0.240723E–4*0.937–40.1665E–3 0.1209E–3 0.1783E–3 0.8935E–3
–4 0.1507E–3 0.2864E–4 0.1614E–3 0.3438E–3
–4
–4 0.1402E–3 0.2224E–4 0.1502E–3 0.8741E–4
–4 0.1299E–3 0.1599E–4 0.1391E–3 0.5240E–4
45 *0.8910E–5 *0.7588E–5 *0.9148E–5
–5
*0.78 –50.1238E–3 0.1522E–4 0.1322E–3 0.3338E–4
50 0.8599E–5 0.6423E–5 5E–5 0.63–5 0.1161E–3 0.1451E–4 0.1243E–3 0.1448E–4
55 0.8110E–5
*0.8066E–5
0.5666E–5
*0.5612E–5
0.8420E–5
*0.8366E–5
0.45
*0.44
60 0.7501E–5 0.4892E–5 0.7977E–5 0.28
65 0.7123E–5
*0.7070E–5
0.4088E–5
*0.4024E–5
0.7362E–5
*0.7316E–5
0.25
*0.248
70 0.6699E–5 0.3236E–5 0.6886E–5 0.22
75 0.6128E–5
*0.6084E–5
0.2422E–5
*0.2392E–5
0.6332E–5
*0.6304E–5
0.1907E
*0.1
80 0.5511E–5 0.1772E–5 0.5834E–5 0.16
30 0.1149E–4 0.1216E–4 0.1491E–4 0.42
35 0.1082E–4 0.9128E–5 0.1348E–4 0.1661E
40 0.1030E–
–5
–5 0.10.1188E–3 0.1360–4
–5 0.1059E–3 0.1325E–4 0.1135E–3 0.1284E–4
–5
–5 0.1022E–3 0.120.1092E–3 0.1252E–4
2E–4 0.1227051E–3 0.1216E–4
–5
–5 0.9512E–4 0.1190E–4 0.9926E–4 0.1182E–4
*: Results obtained by using the method discussed in [13].
m absolute errors for Example 4.2Table 2. The maximu.
3
k
h-
O
2
k
Oh -
proposed method (15) proposed method (15) [for uniform mesh 1
k
]
1
2
1
2
N
0.1
0.01
0.1
0.01
0.1
0.01
0.1
0.01
10 0.3582E–5 0.2318E–6 0.4054E–50.2022E–6 0.3318E–6 0.2421E–7 0.3844E–6 0.2100E–7
15 0.4972E–6
*0.4818E–6
0.8959E–7
*0.8872E–7
0.1422E–6
*0.1366E–6
0.8889E–7
*0.8801E–7 0.5756E–7 0.6250E–8 0.7224E–7 0.8181E–8
20 0.1104E–6 0.5934E–7 0.1951E–60.3283E–7 0.1929E–7 0.1412E–8 0.1616E–7 0.1012E–8
25 0.1525E–7
*0.1488E–7
0.2785E–7
*0.2740E–7
0.5790E–7
*0.5720E–7
0.6503E–8
*0.6472E–8 0.7782E–8 0.9215E–9 0.8269E–8 0.5440E–9
30 0.4865E–8 0.1987E–8 0.1354E–70.2173E–8 0.3116E–8 0.3812E–9 0.3880E–8 0.4004E–9
35 0.4133E–8
*0.4096E–8
0.4344E–9
*0.4312E–9
0.8218E–8
*0.8176E–8
0.7437E–9
*0.7414E–9 0.8868E–9 0.5381E–10 0.1614E–8 0.7818E–10
40 0.3373E–8 0.5659E–100.6534E–80.2147E–9 0.8617E–9 0.5733E–11 0.9210E–9 0.1817E–10
45 0.3008E–8
*0.3001E–8
0.4234E–10
*0.4228E–10
0.6166E–8
*0.6122E–8
0.8872E–10
*0.8845E–10 0.5417E–9 0.3230E–11 0.7106E–9 0.7117E–11
50 0.2743E–8 0.2606E–100.5657E–80.5971E–10 0.4413E–9 0.1006E–11 0.4818E–9 0.4343E–11
55 0.2174E–8
*0.2170E–8
0.1918E–10
*0.1911E–10
0.4828E–8
*0.4810E–8
0.4815E–10
*0.4804E–10 0.2830E–9 0.8716E–12 0.3636E–9 0.1156E–11
60 0.1676E–8 0.1210E–100.4138E–80.4104E–10 0.1978E–9 0.7677E–12 0.2442E–9 0.8821E–12
*: Results obtained byethod13]
using the m discussed in [.
Copyright © 2011 SciRes. AM
R. K. MOHANTY ET AL.
1251
order coofn ed
n other cases,
e found that the order of the convergence of the method
for uniform mesh case is nearly e
6. Acknowledgements
The authors thank the anonymous reviewers for
constructive suggestions, which greatly improved the
standf the
This researcporhety
Delhider rnt 01
423.
7. Rrence
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e Plain,
[2] P. J. Davibith ri
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.3.2
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w
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r thei
ard opaper.
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efes
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ournal, Vo
tegro-Differential Eq
3, No. 3, 197
uations,”
pp. 297-300Com
doi:10.1093/comjnl/13 97
[4] P. Linz, “Ar S in
ro-Dif qua N
44.
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