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Unformatted text preview: r i = 2 to n do yi := fi ; bi yi;1 f Backward substitution g yn := yn=an
for i = n ; 1 downto 1 do yi := (yi ; ciyi+1)=ai end Figure 6.3.2: Tridiagonal algorithm
expansion in even powers of h beginning with O(h2) terms. Let's assume that this is the
case. Then, Richardson's extrapolation can be used to both estimate the global error
and to improve the solution. To this end, we calculate two solutions using di erent step
sizes of, e.g., h and h=2. In order to emphasize the dependence of the discrete solution
on step size, let yih denote the nite di erence solution yi at xi = a + ih obtained with
step size h. With the assumed error dependence we have y(a + ih) ; yih = Ch2 + O(h4)
and h=
y(a + ih) ; y2i 2 = C ( h )2 + O(h4):
2 h=
The variable y2i 2 is the nite di erence solution at a + 2i(h=2) = a + ih.
Subtracting the two error equations to eliminate the exact solution yields 4 h=
Ch2 = 3 y2i 2 ; yih] + O(h4):
19 Using this result, we estimate the error in the ner grid solution as
h=
y2i 2 ; yih :
3 h=
y(a + ih) ; y2i 2 Furthermore, h=2
h
h=
i = 1 2 ::: N ;1
yih=2 = y2i 2 + y2i 3; yi
^
is an O(h4) approximation of the solution.
Let us apply Richardson's extrapolation to the simple BVP y00 = y y(0) = 0 y(1) = 1: This problem has the form of (6.3.13) with p(x) = r(x) = 0 and q(x) = ;1. Thus, the
elements of the tridiagonal system (6.3.18) are ai = ;(2 + h2)
bi = 1 i = 1 2 ::: N ;1 i = 2 3 ::: N ; 1 ci = 1 i = 1 2 : : : N ; 2: Centraldi erence solutions with h = 1=10 1=20, the solution by Richardson's extrapolation, and the exact solution
y(x) = sinh x
sinh 1
are shown in Table 6.3.1. Using the error at x = 0:5 as a measure of accuracy, we have
0
jy(0:5) ; y5:1j = 4:26 10;5
0:
jy(0:5) ; y1005j = 1:04 10;5
0:
0
jy105 ; y5:1j = 1:07 10;5 3
jy(0:5) ; y5:05j = 3:3 10;7
^0 These results indicate that
1. the global error of the centered nite di erence solution is approximately O(h2)
since decreasing h by onehalf quarters the error and
2. Richardson's extrapolation furnishes a good approximation of the error while also
improving accuracy.
20 i xi
y(xi)
0 0.00 0.0
1 0.05 0.04256364
2 0.10 0.08523370
3 0.15 0.12811690
4 0.20 0.17132045
5 0.25 0.21495240
6 0.30 0.25912184
7 0.35 0.30393920
8 0.40 0.34951658
9 0.45 0.39596749
10 0.50 0.44340942
11 0.55 0.49195965
12 0.60 0.54174004
13 0.65 0.59287506
14 0.70 0.64549258
15 0.75 0.69972415
16 0.80 0.75570543
17 0.85 0.81357636
18 0.90 0.87348163
19 0.95 0.93557107
20 1.00 1.0
Table 6.3.1: Solution of Example
Richardson's extrapolation. 0.0 yih h=
y2i 2 yih=2
^ 0.0
0.0
0.04256498
0.08524467 0.08523638 0.08523361
0.12812087
0.17134180 0.17132566 0.17132029
0.21495877
0.25915234 0.25912928 0.25912159
0.30394761
0.34955441 0.34952582 0.34951629
0.39597785
0.44345203 0.44341982 0.44340909
0.49197036
0.54178417 0.54175082 0.54173970
0.59288567
0.64553415 0.64550275 0.64549229
0.69973360
0.75573949 0.75571378 0.75570522
0.81358325
0.87350223 0.87348670 0.87348153
0.93557388
1.0
1.0
1.0
6.3.2 using central di erence approximations and As a next step, let us consider a linear BVP with a prescribed Robin boundary
condition, e.g., y00 + p(x)y0 + q(x)y = r(x) a<x<b (6.3.24a) y(a) = A (6.3.24b) y0(b) + Cy(b) = B: (6.3.24c) As distinct from the Dirichlet conditions used in (6.3.1), y(b) is now an unknown. We
could approximate y0(b) by backward di erences and use the discrete version of the
terminal condition (6.3.24c) to determine an approximation of y(b) however, this has
some drawbacks. If rstorder backward di erences (6.3.6) were used to approximate y0(b)
21 y y0 = A h
a = x0 x
x N1 xN = b x N+1 x1 Figure 6.3.3: Domain and discretization used to approximate a Robin terminal condition.
then the boundary condition (6.3.24c) would only be accurate to O(h) while the discrete
approximation of the ODE (6.3.24a) is accurate to O(h2). If higherorder backward
di erences were used to approximate y0(b) then the tridiagonal structure of the discrete
system would be lost.
The usual strategy is to introduce a ctitious external point xN +1 = b + h as shown
in Figure 6.3.3. Extending the solution to this exterior point, we use central di erences
to approximate the terminal condition (6.3.24c) to O(h2) as
yN +1 ; yN ;1 + Cy = B:
(6.3.25a)
N
2h
This does little to solve the problem since we've introduced both another equation
(6.3.25a) and another unknown yN +1. The additional equation that we need is the central
di erence approximation of the ODE (6.3.24a) at x = xN . Thus, using (6.3.16a) with
i = N we have bN yN ;1 + aN yN + cN yN +1 = h2 rN : (6.3.25b) Once again, It is common to eliminate yN +1 by combining (6.3.25a) and (6.3.25b) to
obtain
(bN + cN )yN ;1 + (aN ; 2hCcN )yN = h2rN ; 2hcN B:
22 (6.3.25c) Observing that bN + cN = 2 by use of (6.3.16b), we obtain the tridiagonal system
2
32 3 2 2
3
a1 c1
h r1 ; b1 A
6 b2 a2 c2
7 6 y1 7 6
7
h2 r2
6
7 6 y2 7 6
7
6
76 7 = 6
7...
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 Spring '14
 JosephE.Flaherty

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