| Literature DB >> 25057507 |
Abstract
We develop the tau-spectral method to solve the time-fractional heat equation (T-FHE) with nonlocal condition. In order to achieve highly accurate solution of this problem, the operational matrix of fractional integration (described in the Riemann-Liouville sense) for shifted Legendre polynomials is investigated in conjunction with tau-spectral scheme and the Legendre operational polynomials are used as the base function. The main advantage in using the presented scheme is that it converts the T-FHE with nonlocal condition to a system of algebraic equations that simplifies the problem. For demonstrating the validity and applicability of the developed spectral scheme, two numerical examples are presented. The logarithmic graphs of the maximum absolute errors is presented to achieve the exponential convergence of the proposed method. Comparing between our spectral method and other methods ensures that our method is more accurate than those solved similar problem.Entities:
Mesh:
Year: 2014 PMID: 25057507 PMCID: PMC4099168 DOI: 10.1155/2014/706296
Source DB: PubMed Journal: ScientificWorldJournal ISSN: 1537-744X
Comparison of our scheme with the IDA [36] at various choices of N, (N = M) for Example 1.
| Our scheme | IDA [ | ||
|---|---|---|---|
|
| MAEs |
| MAEs |
| 6 | 2.541507 · 10−2 | 4 | 2.297695 · 10−1 |
| 8 | 8.774320 · 10−4 | 8 | 5.383793 · 10−2 |
| 10 | 2.118341 · 10−5 | 16 | 1.391800 · 10−2 |
| 12 | 1.832678 · 10−6 | 32 | 3.843610 · 10−3 |
| 14 | 1.037991 · 10−6 | 64 | 1.152111 · 10−3 |
| 16 | 6.590323 · 10−7 | 128 | 3.844224 · 10−4 |
| 18 | 4.383403 · 10−7 | 256 | 1.447756 · 10−4 |
Figure 1Absolute error function at N = M = 18 for Example 1.
Figure 2Absolute error function at N = M = 18 with t = 0.5 for Example 1.
Comparison of our scheme with the IDA [36] at various choices of N and M for Example 2.
| Our scheme | IDA [ | |||||||
|---|---|---|---|---|---|---|---|---|
|
| ν = 0.45 | ν = 0.95 |
|
| ||||
|
| ν = 0.45 | ν = 0.95 |
| ν = 0.45 | ν = 0.95 | |||
| 4 | 1.08 · 10−3 | 1.10 · 10−3 | 2 | 1.46 · 10−2 | 7.45 · 10−3 | 2 | 3.88 · 10−2 | 4.30 · 10−2 |
| 6 | 5.84 · 10−5 | 5.86 · 10−5 | 4 | 7.59 · 10−3 | 4.06 · 10−3 | 4 | 9.51 · 10−3 | 9.47 · 10−3 |
| 8 | 6.33 · 10−6 | 5.01 · 10−6 | 8 | 4.03 · 10−3 | 2.30 · 10−3 | 8 | 3.65 · 10−3 | 2.96 · 10−3 |
| 10 | 1.86 · 10−6 | 1.15 · 10−6 | 16 | 2.24 · 10−3 | 1.41 · 10−3 | 16 | 2.24 · 10−3 | 1.41 · 10−3 |
| 12 | 9.03 · 10−7 | 5.12 · 10−7 | 32 | 1.35 · 10−3 | 9.59 · 10−4 | 32 | 1.89 · 10−3 | 1.02 · 10−3 |
| 14 | 5.07 · 10−7 | 2.81 · 10−7 | 64 | 9.02 · 10−4 | 7.33 · 10−4 | 64 | 1.81 · 10−3 | 9.31 · 10−4 |
| 16 | 3.06 · 10−7 | 1.69 · 10−7 | 128 | 6.78 · 10−4 | 6.19 · 10−4 | 128 | 1.78 · 10−3 | 9.07 · 10−4 |
| 18 | 1.95 · 10−7 | 1.69 · 10−7 | 256 | 5.66 · 10−4 | 5.62 · 10−4 | 256 | 1.78 · 10−3 | 9.01 · 10−4 |
Figure 3Absolute error function at N = M = 20 with γ = 0.45 for Example 2.
Figure 4Absolute error function at N = M = 20 with γ = 0.95 for Example 2.
Figure 5Absolute error function at N = M = 20 with γ = 0.95 for Example 2.