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1.2 Forcing Function tex2html_wrap_inline6015

Let us consider another example with the external forcing function is a concentrated loading, according to section (2), we use Dirac delta function to represent the loading.

eqnarray2248

According to (3.2) and (3.3), we decompose our problem into the following problems,

eqnarray2250

and

eqnarray2252

The same as the first example, we only have the particular solution tex2html_wrap_inline6121 . And also we have the same Green's function as (1.1.11), and according to (2.9), then we can have

eqnarray2254

Therefore, the exact solution of the problem (1.2.1) is

eqnarray2256

Using the same notations as (1.1.13) and (1.1.14), the finite difference method for the problem (1.2.1) can be done in the following procedure. Consider

eqnarray2258

By using the property of (2.5), we have

eqnarray2260

We can use the method of finite difference to approximate the derivative and trapezoidal rule to approximate the integral in (1.2.6). Then, we could have

eqnarray2262

Since we can use the average of tex2html_wrap_inline6411 and tex2html_wrap_inline6451 and the average of tex2html_wrap_inline6453 and tex2html_wrap_inline6411 to approximate  and  respectively. Then, we have the following difference equation

eqnarray2264

Imposing the boundary conditions, we can rewrite (1.2.8) to

eqnarray2266

In matrix form, we have

eqnarray2268

where A is an order (n-1) square matrix, u and b are tex2html_wrap_inline6421 column matrices, such that

eqnarray2270

TABLE 2.1

 
h=1/4
.10324725x10-2
-.2.1182702x10-5
.13191358x10-8
-.22654101x10-12
h=1/8
.25652942x10-3
-.1.3115520x10-6
.20388496x10-10
-.17763568x10-14
h=1/16
.64033988x10-4
-.8.1780855x10-8
.31682990x10-12
.41355808x10-14
h=1/32
.16002363x10-4
-.51083332x10-9
.90205621x10-14
-.82989171x10-14
h=1/64
.40002077x10-5
-.31918634x10-10
-.80213614x10-14
 
h=1/128
.10000280x10-5
-.20024260x10-11
   
h=1/256
.25000550x10-6
     

 
 

TABLE 2.2

r(1)
.24846126
.061916179
.015455950
.0078412154
r(2)
.24961655
.062354262
.015539640
 
r(3)
.24990421
.062463681
.028471310
 
r(4)
.24997606
.062483462
   
r(5)
.24999402
.062735328
   
r(6)
.24999850
     

 

For the problem (1.2.1), the forcing function is concentrated at the nodal point x = 1/2 where leads to a singular point, the Table 2.1 and Table 2.2 display the numerical results at this point. The same as problem (1.1.1), we see from Table 2.1 and Table 2.2 that we have a similar result at this singular point. The numerical experimental solutions show that at any nodal point, we have the same asymptotic error expansion as (1.1.19) [See Appendix {B.2a-B.2b]. In addition, when h = 1/256, the finite difference solution gives the error at x = 1/2 tex2html_wrap_inline6477 which is larger than the error of the extrapolated solution obtained from the three solutions corresponding to h = 1/4, 1/8 and 1/16. Although the forcing function can be concentrated at any other nodal points, the numerical solutions also show that we can obtain the same asymptotic error expansion [See Appendix B.2c-B.2h].


nextuppreviouscontents
Next:1.3 Forcing FunctionUp:1 One-dimensional ProblemsPrevious:1.1 Forcing Function
Cheung Sau Hung

Wed Sep 15 10:03:39 HKT 1999