Quasi-interpolation operators based on a cubic spline and applications in SAMR simulations

In this paper, we consider the properties of monotonicity-preserving and global conservation-preserving for interpolation operators. These two properties play important role when interpolation operators used in many real numerical simulations. In order to attain these two aspects, we propose a one-dimensional (1D) new cubic spline, and extend it to two-dimensional (2D) using tensor-product operation. Based on discrete convolution, 1D and 2D quasi-interpolation operators are presented using these functions. Both analysis and numerical results show that the interpolation operators constructed in this paper are monotonic and conservative. In particular, we consider the numerical simulations of 2D Euler equations based on the technique of structured adaptive mesh refinement (SAMR). In SAMR simulations, effective interpolators are needed for information transportation between the coarser/finer meshes. We applied the 2D quasi-interpolation operator to this environment, and the simulation result show the efficiency and correctness of our interpolator.