First order least squares method with weakly imposed boundary condition for convection dominated diffusion problems

We present and analyze a first order least squares method for convection dominated diffusion problems, which provides robust L2L2 a priori error estimate for the scalar variable even if the given data f∈L2(Ω)f∈L2(Ω). The novel theoretical approach is to rewrite the method in the framework of discontinuous Petrov–Galerkin (DPG) method, and then show numerical stability by using a key equation discovered by Gopalakrishnan and Qiu (2014). This new approach gives an alternative way to do numerical analysis for least squares methods for a large class of differential equations. We also show that the condition number of the global matrix is independent of the diffusion coefficient. A key feature of the method is that there is no stabilization parameter chosen empirically. In addition, Dirichlet boundary condition is weakly imposed. Numerical experiments verify our theoretical results and, in particular, show our way of weakly imposing Dirichlet boundary condition is essential to the design of least squares methods—numerical solutions on subdomains away from interior layers or boundary layers have remarkable accuracy even on coarse meshes, which are unstructured quasi-uniform.