Fig.3 Comparison of error assessment method based on h-refinement and k-refinement: (a) isogeometric solution surface with control points; (b) error surface obtained by three h-refinement steps; (c) error surface obtained by three k-refinement steps; (d) exact error color map; (e) color map of error surface in Fig. 3 (b); (f) colormap of error surface in Fig. 3 (c).
where
This completes the proof. □
The approximation error surface e from (4) also has a B-spline form. Different from the method in [16], we perform several k -refinement operations to achieve more accurate results. Though it is much more expensive, we can use it as an error assessment method for isogeometric simulation solutions.
As a summary, the procedure of error assessment method for model problem (1) can be described as follows,
Input: the isogeometric solution $U_h(\mathbf{x})$ over computational domain $\Omega$
Output: the error surface e
Compute $\Delta U_h(\mathbf{x})$ according to Proposition 1;
Solve the isogeometric analysis problem (4) with several $k$-refinement steps;
Output the error surface $e$.
IV. EXAMPLES AND COMPARISONS
In this paper, we test the error assessment methods based on h-refinement and k-refinement for the heat conduction problem (1) with source term
For this problem with boundary condition $U_0(x) = 0$, the exact solution over the computational domain $[0, 3] \times [0, 3]$ is
Fig. 3 illustrates an example over the computational domain $[0,3] \times [0,3]$, which has exact solution for problem (1). The isogeometric solution surface with control points are shown in Fig. 3(a), the error surface obtained by three h-refinement steps is illustrated in Fig. 3 (b), Fig. 3 (c) shows the error