We propose some new weighted averaging methods for gradient recovery,
and present analytical and numerical investigation on the performance of these
weighted averaging methods. It is shown analytically that the harmonic averaging
yields a superconvergent gradient for any mesh in one-dimension and the rectangular
mesh in two-dimension. Numerical results indicate that these new weighted
averaging methods are better recovered gradient approaches than the simple averaging
and geometry averaging methods under triangular mesh.