In time, the numerical solution diverges from the true solution and this error due to divergence will become more dominant.
Additionally, the proposed solution measures this error sensitivity through a model and unequally distributes the protection accordingly.
In Figure 2 we display the numerical solution, the error estimate and the residual for.
Figure 21 Problem (3. 18): The numerical solution, the error estimate, and the residual for.
Figure 6 Problem (3. 8): The numerical solution, the error estimate, and the residual for, and.
For this choice of parameters and. Figure 3 Problem (1. 9a - 1.9b): The numerical solution, the error estimate, and the residual for, and.
The associated root is. Figure 10 Problem (3. 8): The numerical solution, the error estimate, and the residual for, and. Figure 11 Problem (3. 8): The numerical solution, the error estimate, and the residual for, and.
Figure 4 Problem (3. 8): The numerical solution, the error estimate, and the residual for, and. Figure 5 Problem (3. 8): The numerical solution, the error estimate, and the residual for, and.
For a convergent solution the error metric, defined as the difference between measured and retrieved intensity, typically reaches a value smaller than 10−3.
With the new solution, the errors of temperature responses can be significantly reduced, which can be 100 times lower.
