Example #1
0
    def test_upwind_example0(self, if_export=False):
        #######################
        # Simple 2d upwind problem with explicit Euler scheme in time
        #######################
        T = 1
        Nx, Ny = 4, 1
        g = structured.CartGrid([Nx, Ny], [1, 1])
        g.compute_geometry()

        advect = upwind.Upwind("transport")
        param = Parameters(g)
        dis = advect.discharge(g, [1, 0, 0])

        b_faces = g.get_all_boundary_faces()
        bc = BoundaryCondition(g, b_faces, ['dir'] * b_faces.size)
        bc_val = np.hstack(([1], np.zeros(g.num_faces - 1)))
        param.set_bc("transport", bc)
        param.set_bc_val("transport", bc_val)

        data = {'param': param, 'discharge': dis}
        data['deltaT'] = advect.cfl(g, data)

        U, rhs = advect.matrix_rhs(g, data)
        OF = advect.outflow(g, data)
        M, _ = mass_matrix.MassMatrix().matrix_rhs(g, data)

        conc = np.zeros(g.num_cells)

        M_minus_U = M - U
        invM, _ = mass_matrix.InvMassMatrix().matrix_rhs(g, data)

        # Loop over the time
        Nt = int(T / data['deltaT'])
        time = np.empty(Nt)
        folder = 'example0'
        production = np.zeros(Nt)
        save = Exporter(g, "conc_EE", folder)
        for i in np.arange(Nt):

            # Update the solution
            production[i] = np.sum(OF.dot(conc))
            conc = invM.dot((M_minus_U).dot(conc) + rhs)
            time[i] = data['deltaT'] * i
            if if_export:
                save.write_vtk({"conc": conc}, time_step=i)

        if if_export:
            save.write_pvd(time)

        known = 1.09375
        assert np.sum(production) == known
Example #2
0
    U_r, rhs_r = coupler_solver.matrix_rhs(gb_r)

    deltaT = np.amin([upwind_solver.cfl(g, d) for g, d in gb])
    deltaT_r = np.amin([upwind_solver.cfl(g, d) for g, d in gb_r])

    T = deltaT * max(Nx, Ny) * 4

    gb.add_node_prop("deltaT", None, deltaT)
    gb_r.add_node_prop("deltaT", None, deltaT_r)

    mass_solver = mass_matrix.MassMatrix()
    coupler_solver = coupler.Coupler(mass_solver)
    M, _ = coupler_solver.matrix_rhs(gb)
    M_r, _ = coupler_solver.matrix_rhs(gb_r)

    inv_mass_solver = mass_matrix.InvMassMatrix()
    coupler_solver = coupler.Coupler(inv_mass_solver)
    invM, _ = coupler_solver.matrix_rhs(gb)
    invM_r, _ = coupler_solver.matrix_rhs(gb_r)

    totDof = np.sum(gb.nodes_prop(gb.nodes(), "dof"))
    totDof_r = np.sum(gb_r.nodes_prop(gb_r.nodes(), "dof"))
    conc = np.zeros(totDof)
    conc_r = np.zeros(totDof_r)

    M_minus_U = M - U
    M_minus_U_r = M_r - U_r

    # Loop over the time
    file_name = "conc"
    file_name_r = "conc_r"
Example #3
0
    def test_upwind_example2(self, if_export=False):
        #######################
        # Simple 2d upwind problem with explicit Euler scheme in time coupled with
        # a Darcy problem
        #######################
        T = 2
        Nx, Ny = 10, 10
        folder = 'example2'

        def funp_ex(pt):
            return -np.sin(pt[0]) * np.sin(pt[1]) - pt[0]

        g = structured.CartGrid([Nx, Ny], [1, 1])
        g.compute_geometry()

        param = Parameters(g)

        # Permeability
        perm = tensor.SecondOrderTensor(g.dim, kxx=np.ones(g.num_cells))
        param.set_tensor("flow", perm)

        # Source term
        param.set_source("flow", np.zeros(g.num_cells))

        # Boundaries
        b_faces = g.get_all_boundary_faces()
        bc = BoundaryCondition(g, b_faces, ['dir'] * b_faces.size)
        bc_val = np.zeros(g.num_faces)
        bc_val[b_faces] = funp_ex(g.face_centers[:, b_faces])
        param.set_bc("flow", bc)
        param.set_bc_val("flow", bc_val)

        # Darcy solver
        data = {'param': param}
        solver = vem_dual.DualVEM("flow")
        D_flow, b_flow = solver.matrix_rhs(g, data)

        solver_source = vem_source.DualSource('flow')
        D_source, b_source = solver_source.matrix_rhs(g, data)

        up = sps.linalg.spsolve(D_flow + D_source, b_flow + b_source)

        p, u = solver.extract_p(g, up), solver.extract_u(g, up)
        P0u = solver.project_u(g, u, data)

        save = Exporter(g, "darcy", folder)

        if if_export:
            save.write_vtk({'pressure': p, "P0u": P0u})

        # Discharge
        dis = u

        # Boundaries
        bc = BoundaryCondition(g, b_faces, ['dir'] * b_faces.size)
        bc_val = np.hstack(([1], np.zeros(g.num_faces - 1)))
        param.set_bc("transport", bc)
        param.set_bc_val("transport", bc_val)

        data = {'param': param, 'discharge': dis}

        # Advect solver
        advect = upwind.Upwind("transport")

        U, rhs = advect.matrix_rhs(g, data)

        data['deltaT'] = advect.cfl(g, data)
        M, _ = mass_matrix.MassMatrix().matrix_rhs(g, data)

        conc = np.zeros(g.num_cells)
        M_minus_U = M - U
        invM, _ = mass_matrix.InvMassMatrix().matrix_rhs(g, data)

        # Loop over the time
        Nt = int(T / data['deltaT'])
        time = np.empty(Nt)
        save.change_name("conc_darcy")
        for i in np.arange(Nt):

            # Update the solution
            conc = invM.dot((M_minus_U).dot(conc) + rhs)
            time[i] = data['deltaT'] * i
            if if_export:
                save.write_vtk({"conc": conc}, time_step=i)

        if if_export:
            save.write_pvd(time)

        known = \
            np.array([9.63168200e-01,   8.64054875e-01,   7.25390695e-01,
                      5.72228235e-01,   4.25640080e-01,   2.99387331e-01,
                      1.99574336e-01,   1.26276876e-01,   7.59011550e-02,
                      4.33431230e-02,   3.30416807e-02,   1.13058617e-01,
                      2.05372538e-01,   2.78382057e-01,   3.14035373e-01,
                      3.09920132e-01,   2.75024694e-01,   2.23163145e-01,
                      1.67386939e-01,   1.16897527e-01,   1.06111312e-03,
                      1.11951850e-02,   3.87907727e-02,   8.38516119e-02,
                      1.36617802e-01,   1.82773271e-01,   2.10446545e-01,
                      2.14651936e-01,   1.97681518e-01,   1.66549151e-01,
                      3.20751341e-05,   9.85780113e-04,   6.07062715e-03,
                      1.99393042e-02,   4.53237556e-02,   8.00799828e-02,
                      1.17199623e-01,   1.47761481e-01,   1.64729339e-01,
                      1.65390555e-01,   9.18585872e-07,   8.08267622e-05,
                      8.47227168e-04,   4.08879583e-03,   1.26336029e-02,
                      2.88705048e-02,   5.27841497e-02,   8.10459333e-02,
                      1.07956484e-01,   1.27665318e-01,   2.51295298e-08,
                      6.29844122e-06,   1.09361990e-04,   7.56743783e-04,
                      3.11384414e-03,   9.04446601e-03,   2.03443897e-02,
                      3.75208816e-02,   5.89595194e-02,   8.11457277e-02,
                      6.63498510e-10,   4.73075468e-07,   1.33728945e-05,
                      1.30243418e-04,   7.01905707e-04,   2.55272292e-03,
                      6.96686157e-03,   1.52290448e-02,   2.78607282e-02,
                      4.40402650e-02,   1.71197497e-11,   3.47118057e-08,
                      1.57974045e-06,   2.13489614e-05,   1.48634295e-04,
                      6.68104990e-04,   2.18444135e-03,   5.58646819e-03,
                      1.17334966e-02,   2.09744728e-02,   4.37822313e-13,
                      2.52373622e-09,   1.83589660e-07,   3.40553325e-06,
                      3.02948532e-05,   1.66504215e-04,   6.45119867e-04,
                      1.90731440e-03,   4.53436628e-03,   8.99977737e-03,
                      1.12627412e-14,   1.84486857e-10,   2.13562387e-08,
                      5.39492977e-07,   6.08223906e-06,   4.05535296e-05,
                      1.84731221e-04,   6.25871542e-04,   1.66459389e-03,
                      3.59980231e-03])

        assert np.allclose(conc, known)