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The new method improves maximum absolute and root mean squared errors of solution values as well as their computational order of convergence.
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The errors of solutions established by ZSimpWin were in the range of 0.92 2.08% for R e, 1.39 2.23% for R i, and 3.30 5.24% for C m.
The errors of approximation solution are listed in Table 1 for (t=0.25) by (3.3) and (3.6).
Considering that absolute errors of approximate solution in given points are small enough, so it follows that the presentation method in this article is right.
Next, we analyze error estimates of solution for scheme (2.6 - 2.8 2.6 - 2.8
Otherwise, go to Step 2. In Step 2 we discretize K within an acceptable error range of solution.
m needs to take all the discrete points of K. Since we discretize K within an acceptable error range of solution, the stopping criterion (K=emptyset) is reasonable.
For example, if the error band of solution is 2δ, (Kin R), then in every iterative process, (m=m+delta) (or (m=m-delta)).
By comparing the relative errors of numerical solutions, we found that the convergence rates of numerical solutions approximate (O(10^{-12} 10^{-12}Nge20), whenh is coNge20ent whichthose obtaised for the theoreticonsistent
It is found that for a ratio of radii less than 0.3, the errors of approximate solutions are generally less than 1%.
Table 1 The errors of numerical solutions at with for.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com