A numerical flux estimates the rate of transfer across a cell face from nearby states. In the finite volume method update, approximates the conservation law flux averaged over the time step; is the transferred amount. For a two-state numerical flux approximating a scalar conservation law with conservation law flux , consistency of a numerical method requires . Thus equal states recover the physical transfer rate. With constant equal-width cells, this also preserves a constant state because its incoming and outgoing numerical fluxes agree.[ref]
Riemann Problems and Jupyter Solutions by David I. Ketcheson, Randall J. LeVeque, and Mauricio J. del Razo. Approximate solvers, §Finite volume methods, consistency paragraph after equation FVupdate
Consistency and shared face flux cancellation answer different questions: matching at equal states approximates the intended equation, while sharing one oriented face value preserves the total. The example periodic upwind finite volume advection uses for , so the arriving state comes from the left. The Godunov numerical flux uses an entropy solution of a local Riemann problem; the Engquist-Osher flux provides a different construction for a scalar conservation law. A monotone conservative scheme uses a numerical flux nondecreasing in its left state and nonincreasing in its right state, together with a time step that makes the complete update monotone. Neither two-state consistency nor conservation by itself supplies that time-step restriction or a general stability or order of a numerical method guarantee.
New to topics? Read the docs here!