def _solve_p_corr(self):
self.uf[:, :], self.vf[:, :], df = self._rhie_chow_interpolate_faces(self.u, self.v, self.p)
mass_source = Source(self.grid.core_shape)
mass_source.b[:, :] = self.rho*np.sum((self.uf*self.grid.core_face_norms[:, :, :, 0] + self.vf*self.grid.core_face_norms[:, :, :, 1]), dtype=float, axis=-1)
self.p_corr_eqn == (DiffusionTerm(self.grid, df, self.rho) == mass_source)
self.p_corr_eqn.iterative_solve(maxiter=100, tol=1e-4)
self._correct(df)
def _solve_momentum(self):
u_source = Source(self.grid.core_shape)
v_source = Source(self.grid.core_shape)
pf = self._interpolate_faces(self.p)
self.dp_x[1:-1, 1:-1], self.dp_y[1:-1, 1:-1] = self._compute_gradient(pf)
u_source.b[:, :] = -self.areas*self.dp_x[1:-1, 1:-1]
v_source.b[:, :] = -self.areas*self.dp_y[1:-1, 1:-1]
self.u_eqn == (AdvectionTerm(self.grid, self.uf, self.vf, self.rho, scheme=self.adv_scheme) - self.laplacian == u_source)
self.v_eqn == (AdvectionTerm(self.grid, self.uf, self.vf, self.rho, scheme=self.adv_scheme) - self.laplacian == v_source)
self.u_eqn.relax(self.omega_momentum)
self.v_eqn.relax(self.omega_momentum)
self.u_eqn.iterative_solve(maxiter=20)
self.v_eqn.iterative_solve(maxiter=20)