opm-simulators/sim_simple.cpp
2013-05-02 15:16:21 +02:00

233 lines
8.2 KiB
C++

/*
Copyright 2013 SINTEF ICT, Applied Mathematics.
This file is part of the Open Porous Media project (OPM).
OPM is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
OPM is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with OPM. If not, see <http://www.gnu.org/licenses/>.
*/
#include "AutoDiffBlock.hpp"
#include <opm/core/grid.h>
#include <opm/core/grid/GridManager.hpp>
#include <opm/core/props/IncompPropertiesBasic.hpp>
#include <opm/core/utility/Units.hpp>
#include <opm/core/utility/StopWatch.hpp>
#include <opm/core/pressure/tpfa/trans_tpfa.h>
#include <Eigen/UmfPackSupport>
#include <iostream>
/*
Equations for incompressible two-phase flow.
Using s and p as variables:
PV (s_i - s0_i) / dt + sum_{j \in U(i)} f(s_j) v_{ij} + sum_{j in D(i) f(s_i) v_{ij} = qw_i
where
v_{ij} = totmob_ij T_ij (p_i - p_j)
Pressure equation:
sum_{j \in N(i)} totmob_ij T_ij (p_i - p_j) = q_i
*/
/// Contains vectors and sparse matrices that represent subsets or
/// operations on (AD or regular) vectors of data.
struct HelperOps
{
typedef AutoDiff::ForwardBlock<double>::M M;
typedef AutoDiff::ForwardBlock<double>::V V;
/// A list of internal faces.
Eigen::Array<int, Eigen::Dynamic, 1> internal_faces;
/// Extract for each face the difference of its adjacent cells'values.
M ngrad;
/// Extract for each face the average of its adjacent cells' values.
M caver;
/// Extract for each cell the sum of its adjacent faces' (signed) values.
M div;
/// Constructs all helper vectors and matrices.
HelperOps(const UnstructuredGrid& grid)
{
const int nc = grid.number_of_cells;
const int nf = grid.number_of_faces;
// Define some neighbourhood-derived helper arrays.
typedef Eigen::Array<int, Eigen::Dynamic, 1> OneColInt;
typedef Eigen::Array<bool, Eigen::Dynamic, 1> OneColBool;
typedef Eigen::Array<int, Eigen::Dynamic, 2, Eigen::RowMajor> TwoColInt;
typedef Eigen::Array<bool, Eigen::Dynamic, 2, Eigen::RowMajor> TwoColBool;
TwoColInt nb = Eigen::Map<TwoColInt>(grid.face_cells, nf, 2);
// std::cout << "nb = \n" << nb << std::endl;
TwoColBool nbib = nb >= 0;
OneColBool ifaces = nbib.rowwise().all();
const int num_internal = ifaces.cast<int>().sum();
// std::cout << num_internal << " internal faces." << std::endl;
TwoColInt nbi(num_internal, 2);
internal_faces.resize(num_internal);
int fi = 0;
for (int f = 0; f < nf; ++f) {
if (ifaces[f]) {
internal_faces[fi] = f;
nbi.row(fi) = nb.row(f);
++fi;
}
}
// std::cout << "nbi = \n" << nbi << std::endl;
// Create matrices.
ngrad.resize(num_internal, nc);
caver.resize(num_internal, nc);
typedef Eigen::Triplet<double> Tri;
std::vector<Tri> ngrad_tri;
std::vector<Tri> caver_tri;
ngrad_tri.reserve(2*num_internal);
caver_tri.reserve(2*num_internal);
for (int i = 0; i < num_internal; ++i) {
ngrad_tri.emplace_back(i, nbi(i,0), 1.0);
ngrad_tri.emplace_back(i, nbi(i,1), -1.0);
caver_tri.emplace_back(i, nbi(i,0), 0.5);
caver_tri.emplace_back(i, nbi(i,1), 0.5);
}
ngrad.setFromTriplets(ngrad_tri.begin(), ngrad_tri.end());
caver.setFromTriplets(caver_tri.begin(), caver_tri.end());
div = ngrad.transpose();
}
};
int main()
{
typedef AutoDiff::ForwardBlock<double> ADB;
typedef ADB::V V;
typedef ADB::M M;
Opm::time::StopWatch clock;
clock.start();
Opm::GridManager gm(50, 50, 10);
const UnstructuredGrid& grid = *gm.c_grid();
using namespace Opm::unit;
using namespace Opm::prefix;
Opm::IncompPropertiesBasic props(2, Opm::SaturationPropsBasic::Quadratic,
{ 1000.0, 800.0 },
{ 1.0*centi*Poise, 5.0*centi*Poise },
0.2, 100*milli*darcy,
grid.dimensions, grid.number_of_cells);
std::vector<double> htrans(grid.cell_facepos[grid.number_of_cells]);
tpfa_htrans_compute((UnstructuredGrid*)&grid, props.permeability(), htrans.data());
// std::vector<double> trans(grid.number_of_faces);
V trans_all(grid.number_of_faces);
tpfa_trans_compute((UnstructuredGrid*)&grid, htrans.data(), trans_all.data());
const int nc = grid.number_of_cells;
std::vector<int> allcells(nc);
for (int i = 0; i < nc; ++i) {
allcells[i] = i;
}
std::cerr << "Opm core " << clock.secsSinceLast() << std::endl;
// Define neighbourhood-derived operator matrices.
HelperOps ops(grid);
const int num_internal = ops.internal_faces.size();
V transi(num_internal);
for (int fi = 0; fi < num_internal; ++fi) {
transi[fi] = trans_all[ops.internal_faces[fi]];
}
std::cerr << "Topology matrices " << clock.secsSinceLast() << std::endl;
typedef AutoDiff::ForwardBlock<double> ADB;
typedef ADB::V V;
// q
V q(nc);
q.setZero();
q[0] = 1.0;
q[nc-1] = -1.0;
// s - this is explicit now
typedef Eigen::Array<double, Eigen::Dynamic, 2, Eigen::RowMajor> TwoCol;
TwoCol s(nc, 2);
s.leftCols<1>().setZero();
s.rightCols<1>().setOnes();
// totmob - explicit as well
TwoCol kr(nc, 2);
props.relperm(nc, s.data(), allcells.data(), kr.data(), 0);
V krw = kr.leftCols<1>();
V kro = kr.rightCols<1>();
const double* mu = props.viscosity();
V totmob = krw/mu[0] + kro/mu[1];
V totmobf = (ops.caver*totmob.matrix()).array();
// Mobility-weighted transmissibilities per internal face.
// Still explicit, and no upwinding!
V mobtransf = totmobf*transi;
std::cerr << "Property arrays " << clock.secsSinceLast() << std::endl;
// Initial pressure.
V p0(nc,1);
p0.fill(200*Opm::unit::barsa);
// First actual AD usage: defining pressure variable.
std::vector<int> block_pattern = { nc };
// Could actually write { nc } instead of block_pattern below,
// but we prefer a named variable since we will repeat it.
ADB p = ADB::variable(0, p0, block_pattern);
ADB ngradp = ops.ngrad*p;
// We want flux = totmob*trans*(p_i - p_j) for the ij-face.
// We only need to multiply mobtransf and pdiff_face,
// but currently multiplication with constants is not in,
// so we define an AD constant to multiply with.
ADB mobtransf_ad = ADB::constant(mobtransf, block_pattern);
ADB flux = mobtransf_ad*ngradp;
ADB residual = ops.div*flux - ADB::constant(q, block_pattern);
std::cerr << "Construct AD residual " << clock.secsSinceLast() << std::endl;
// std::cout << div << pdiff_face;
// std::cout << div*pdiff_face;
// std::cout << q << std::endl;
// std::cout << residual << std::endl;
// It's the residual we want to be zero. We know it's linear in p,
// so we just need a single linear solve. Since we have formulated
// ourselves with a residual and jacobian we do this with a single
// Newton step (hopefully easy to extend later):
// p = p0 - J(p0) \ R(p0)
// Where R(p0) and J(p0) are contained in residual.value() and
// residual.derived()[0].
Eigen::UmfPackLU<M> solver;
M matr = residual.derivative()[0];
matr.coeffRef(0,0) *= 2.0;
matr.makeCompressed();
solver.compute(residual.derivative()[0]);
// if (solver.info() != Eigen::Succeeded) {
// std::cerr << "Decomposition error!\n";
// return 1;
// }
Eigen::VectorXd x = solver.solve(residual.value().matrix());
// if (solver.info() != Eigen::Succeeded) {
// std::cerr << "Solve failure!\n";
// return 1;
// }
V p_new = p0 - x.array();
std::cerr << "Solve " << clock.secsSinceLast() << std::endl;
std::cout << p_new << std::endl;
}