void ISOP2P1::solveStokes()
{
buildStokesSys();
int n_dof_v = fem_space_v.n_dof();
int n_dof_p = fem_space_p.n_dof();
int n_total_dof = 2 * n_dof_v + n_dof_p;
/// 构建系数矩阵和右端项.
/// 这个存放整体的数值解. 没有分割成 u_h[0], u_h[1] 和 p_h.
Vector<double> x(n_total_dof);
/// 将数值解合并一个向量便于边界处理.
for (int i = 0; i < n_dof_v; ++i)
{
x(i) = v_h[0](i);
x(n_dof_v + i) = v_h[1](i);
}
for (int i = 0; i < n_dof_p; ++i)
x(2 * n_dof_v + i) = p_h(i);
rhs.reinit(n_total_dof);
/// 边界条件一起处理了.
boundaryValueStokes();
/// 矩阵求解.
dealii::SolverControl solver_control (4000000, 1e-14, 1);
SolverMinRes<Vector<double> > minres (solver_control);
StokesPreconditioner preconditioner;
/// 预处理矩阵.
SparseMatrix<double> matrix_vxvx(sp_vxvx);
SparseMatrix<double> matrix_vyvy(sp_vyvy);
/// 这里从 Stokes 取是因为加了边界条件.
for (int i = 0; i < sp_vxvx.n_nonzero_elements(); ++i)
matrix_vxvx.global_entry(i) = matrix.global_entry(index_vxvx[i]);
for (int i = 0; i < sp_vyvy.n_nonzero_elements(); ++i)
matrix_vyvy.global_entry(i) = matrix.global_entry(index_vyvy[i]);
preconditioner.initialize(matrix_vxvx, matrix_vyvy, mat_p_mass);
clock_t t_cost = clock();
minres.solve (matrix, x, rhs, preconditioner);
// minres.solve (matrix, x, rhs, PreconditionIdentity());
t_cost = clock() - t_cost;
std::cout << "time cost: " << (((float)t_cost) / CLOCKS_PER_SEC) << std::endl;
/// 将整体数值解分割成速度和压力.
for (int i = 0; i < n_dof_v; ++i)
{
v_h[0](i) = x(i);
v_h[1](i) = x(i + n_dof_v);
}
for (int i = 0; i < n_dof_p; ++i)
p_h(i) = x(i + 2 * n_dof_v);
/*
/// 矩阵求解.
SparseMatrix<double> mat_BTx(sp_pvx);
SparseMatrix<double> mat_BTy(sp_pvy);
SparseMatrix<double> mat_Bx(sp_vxp);
SparseMatrix<double> mat_By(sp_vyp);
SparseMatrix<double> mat_Ax(sp_vxvx);
SparseMatrix<double> mat_Ay(sp_vyvy);
for (int i = 0; i < sp_vxvx.n_nonzero_elements(); ++i)
mat_Ax.global_entry(i) = matrix.global_entry(index_vxvx[i]);
for (int i = 0; i < sp_vyvy.n_nonzero_elements(); ++i)
mat_Ay.global_entry(i) = matrix.global_entry(index_vyvy[i]);
for (int i = 0; i < sp_pvx.n_nonzero_elements(); ++i)
mat_BTx.global_entry(i) = matrix.global_entry(index_pvx[i]);
for (int i = 0; i < sp_pvy.n_nonzero_elements(); ++i)
mat_BTy.global_entry(i) = matrix.global_entry(index_pvy[i]);
for (int i = 0; i < sp_vxp.n_nonzero_elements(); ++i)
mat_Bx.global_entry(i) = matrix.global_entry(index_vxp[i]);
for (int i = 0; i < sp_vyp.n_nonzero_elements(); ++i)
mat_By.global_entry(i) = matrix.global_entry(index_vyp[i]);
Vector<double> tmp1(n_dof_v);
Vector<double> tmp2(n_dof_v);
Vector<double> rhs_vx(n_dof_v);
Vector<double> rhs_vy(n_dof_v);
Vector<double> rhs_p(n_dof_p);
for (int i = 0; i < n_dof_v; ++i)
{
rhs_vx(i) = rhs(i);
v_h[0](i) = x(i);
rhs_vy(i) = rhs(n_dof_v + i);
v_h[1](i) = x(n_dof_v + i);
}
for (int i = 0; i < n_dof_p; ++i)
{
rhs_p(i) = rhs(2 * n_dof_v + i);
p_h(i) = x(2 * n_dof_v + i);
}
Vector<double> schur_rhs (n_dof_p);
// AMGSolver solverQ(mat_Ax, 1.0e-12, 3, 50, 0.382, 0.25);
AMGSolver solverQ(mat_Ax);
InverseMatrix M(mat_Ax, solverQ);
M.vmult (tmp1, rhs_vx);
M.vmult (tmp2, rhs_vy);
mat_Bx.vmult(schur_rhs, tmp1);
mat_By.vmult_add(schur_rhs, tmp2);
schur_rhs -= rhs_p;
SchurComplement schur_complement(mat_BTx, mat_BTy, mat_Bx, mat_By, M, M);
// SolverControl solver_control_cg (n_dof_p * 2,
// 1e-12*schur_rhs.l2_norm());
SolverControl solver_control_cg (n_dof_p * 20,
1e-15);
// SolverCG<> cg (solver_control_cg);
SolverMinRes<> minres (solver_control_cg);
AMGSolver AQ(mat_p_mass);
ApproxSchurComplement asc(mat_p_mass, AQ);
minres.solve (schur_complement, p_h, schur_rhs, asc);
// cg.solve (schur_complement, p_h, schur_rhs, PreconditionIdentity());
std::cout << solver_control_cg.last_step()
<< " CG Schur complement iterations to obtain convergence."
<< std::endl;
mat_BTx.vmult(tmp1, *dynamic_cast<const Vector<double>* >(&p_h));
mat_BTy.vmult(tmp2, *dynamic_cast<const Vector<double>* >(&p_h));
tmp1 *= -1;
tmp2 *= -1;
tmp1 += rhs_vx;
tmp2 += rhs_vy;
M.vmult(v_h[0], tmp1);
M.vmult(v_h[1], tmp2);
*/
double error;
RealVx accuracy_vx;
error = Functional::L2Error(v_h[0], accuracy_vx, 2);
std::cout << "|| u - u_h ||_L2 = " << error << std::endl;
error = Functional::H1SemiError(v_h[0], accuracy_vx, 1);
std::cout << "|| u - u_h ||_H1 = " << error << std::endl;
RealVy accuracy_vy;
error = Functional::L2Error(v_h[1], accuracy_vy, 2);
std::cout << "|| v - v_h ||_L2 = " << error << std::endl;
error = Functional::H1SemiError(v_h[1], accuracy_vy, 1);
std::cout << "|| v - v_h ||_H1 = " << error << std::endl;
double p_avg = Functional::meanValue(p_h, 2);
RealP accuracy_p(p_avg);
error = Functional::L2Error(p_h, accuracy_p, 2);
std::cout << "|| p - p_h ||_0 = " << error << std::endl;
};
void ISOP2P1::run()
{
/// 初始化.
initialize();
/// 构建 Stokes 系统.
buildStokesSys();
/// 边界条件处理.
boundaryValueStokes();
/// 准备预处理.
StokesPreconditioner preconditioner;
/// 预处理矩阵.
SparseMatrix<double> matrix_vxvx(sp_vxvx);
SparseMatrix<double> matrix_vyvy(sp_vyvy);
/// 这里从 Stokes 取是因为加了边界条件.
for (int i = 0; i < sp_vxvx.n_nonzero_elements(); ++i)
matrix_vxvx.global_entry(i) = matrix.global_entry(index_vxvx[i]);
for (int i = 0; i < sp_vyvy.n_nonzero_elements(); ++i)
matrix_vyvy.global_entry(i) = matrix.global_entry(index_vyvy[i]);
preconditioner.initialize(matrix_vxvx, matrix_vyvy, mat_p_mass);
/// 矩阵求解.
dealii::SolverControl solver_control (4000000, 1e-14, 1);
SolverMinRes<Vector<double> > minres (solver_control);
clock_t t_cost = clock();
minres.solve (matrix, x, rhs, preconditioner);
// minres.solve (matrix, x, rhs, PreconditionIdentity());
t_cost = clock() - t_cost;
std::cout << "time cost: " << (((float)t_cost) / CLOCKS_PER_SEC) << std::endl;
/// 将整体数值解分割成速度和压力.
int n_dof_v = fem_space_v.n_dof();
int n_dof_p = fem_space_p.n_dof();
int n_total_dof = 2 * n_dof_v + n_dof_p;
for (int i = 0; i < n_dof_v; ++i)
{
v_h[0](i) = x(i);
v_h[1](i) = x(i + n_dof_v);
}
for (int i = 0; i < n_dof_p; ++i)
p_h(i) = x(i + 2 * n_dof_v);
/// 数据输出.
outputTecplotP("P0");
outputTecplot("V0");
/// 误差比较.
double error;
RealVx accuracy_vx;
error = Functional::L2Error(v_h[0], accuracy_vx, 2);
std::cout << "|| u - u_h ||_L2 = " << error << std::endl;
error = Functional::H1SemiError(v_h[0], accuracy_vx, 1);
std::cout << "|| u - u_h ||_H1 = " << error << std::endl;
RealVy accuracy_vy;
error = Functional::L2Error(v_h[1], accuracy_vy, 2);
std::cout << "|| v - v_h ||_L2 = " << error << std::endl;
error = Functional::H1SemiError(v_h[1], accuracy_vy, 1);
std::cout << "|| v - v_h ||_H1 = " << error << std::endl;
double p_avg = Functional::meanValue(p_h, 2);
RealP accuracy_p(p_avg);
error = Functional::L2Error(p_h, accuracy_p, 2);
std::cout << "|| p - p_h ||_0 = " << error << std::endl;
};
void ISOP2P1::solveStokes()
{
buildStokesSys();
std::cout << "Stokes system builded." << std::endl;
int n_dof_v = fem_space_v.n_dof();
int n_dof_p = fem_space_p.n_dof();
int n_total_dof = 2 * n_dof_v + n_dof_p;
/// 构建系数矩阵和右端项.
/// 这个存放整体的数值解. 没有分割成 u_h[0], u_h[1] 和 p_h.
Vector<double> x(n_total_dof);
/// 将数值解合并一个向量便于边界处理.
for (int i = 0; i < n_dof_v; ++i)
{
x(i) = v_h[0](i);
x(n_dof_v + i) = v_h[1](i);
}
for (int i = 0; i < n_dof_p; ++i)
x(2 * n_dof_v + i) = p_h(i);
rhs.reinit(n_total_dof);
/// 边界条件一起处理了. 修改了matrix, rhs和x.
boundaryValueStokes(x, t);
std::cout << "Stokes boundary applied." << std::endl;
// /// 矩阵求解.
// dealii::SolverControl solver_control (400000, l_tol * rhs.l2_norm(), 1);
// /// 不完全LU分解.
// dealii::SparseILU<double> preconditioner;
// preconditioner.initialize(matrix);
// /// 求解Stokes方程, MinRes要比GMRES求解器要快很多,
// /// 当矩阵规模稍微大点的时候,GMRES会出现不收敛的情况.
// SolverMinRes<Vector<double> > minres (solver_control);
// SolverGMRES<Vector<double> >::AdditionalData para(1000, false, true);
// /// 不用para算不动, 但是均匀网格下可以不用para,算其它的例子也不用para,是不是跟计算区域有关系？
// SolverGMRES<Vector<double> > gmres(solver_control, para);
// // /// 移动网格和时间发展中，这个预处理失效.
// // StokesPreconditioner preconditioner;
// // /// 预处理矩阵.
// // SparseMatrix<double> matrix_vxvx(sp_vxvx);
// // SparseMatrix<double> matrix_vyvy(sp_vyvy);
// // /// 这里从 Stokes 取是因为加了边界条件.
// // for (int i = 0; i < sp_vxvx.n_nonzero_elements(); ++i)
// // matrix_vxvx.global_entry(i) = matrix.global_entry(index_vxvx[i]);
// // for (int i = 0; i < sp_vyvy.n_nonzero_elements(); ++i)
// // matrix_vyvy.global_entry(i) = matrix.global_entry(index_vyvy[i]);
// // preconditioner.initialize(mat_v_stiff, mat_v_stiff, mat_p_mass);
// clock_t t_cost = clock();
// minres.solve (matrix, x, rhs, PreconditionIdentity());
// // gmres.solve(matrix, x, rhs, preconditioner);
// t_cost = clock() - t_cost;
// std::cout << "time cost: " << (((float)t_cost) / CLOCKS_PER_SEC) << std::endl;
// /// 将整体数值解分割成速度和压力.
// for (int i = 0; i < n_dof_v; ++i)
// {
// v_h[0](i) = x(i);
// v_h[1](i) = x(i + n_dof_v);
// }
// for (int i = 0; i < n_dof_p; ++i)
// p_h(i) = x(i + 2 * n_dof_v);
// /// 计算误差, t为时间参数.
// computeError(t);
// /// debug, 计算惨量的L2 norm。
// Vector<double> res(n_total_dof);
// matrix.vmult(res, x);
// res *= -1;
// res += rhs;
// std::cout << "res_l2norm =" << res.l2_norm() << std::endl;
/// 矩阵求解.
SparseMatrix<double> mat_BTx(sp_pvx);
SparseMatrix<double> mat_BTy(sp_pvy);
SparseMatrix<double> mat_Bx(sp_vxp);
SparseMatrix<double> mat_By(sp_vyp);
SparseMatrix<double> mat_Ax(sp_vxvx);
SparseMatrix<double> mat_Ay(sp_vyvy);
for (int i = 0; i < sp_vxvx.n_nonzero_elements(); ++i)
mat_Ax.global_entry(i) = matrix.global_entry(index_vxvx[i]);
for (int i = 0; i < sp_vyvy.n_nonzero_elements(); ++i)
mat_Ay.global_entry(i) = matrix.global_entry(index_vyvy[i]);
for (int i = 0; i < sp_pvx.n_nonzero_elements(); ++i)
mat_BTx.global_entry(i) = matrix.global_entry(index_pvx[i]);
for (int i = 0; i < sp_pvy.n_nonzero_elements(); ++i)
mat_BTy.global_entry(i) = matrix.global_entry(index_pvy[i]);
for (int i = 0; i < sp_vxp.n_nonzero_elements(); ++i)
mat_Bx.global_entry(i) = matrix.global_entry(index_vxp[i]);
for (int i = 0; i < sp_vyp.n_nonzero_elements(); ++i)
mat_By.global_entry(i) = matrix.global_entry(index_vyp[i]);
/// alp对AMGSolver的初始化影响比较大, 如果取得很小，初始化很快.
double alp = dt * viscosity;
AMGSolver solverQ(mat_Ax, 1.0e-12, 3, 100, 0.382, alp);
// AMGSolver solverQ(mat_Ax);
InverseMatrix AInv(mat_Ax, solverQ);
/// 这里没有对速度质量阵进行边界条件处理.
InverseMatrix QInv(mat_v_mass, solverQ);
SchurComplement schur_complement(mat_BTx, mat_BTy, mat_Bx, mat_By, mat_v_mass, QInv, QInv);
AMGSolver solverP(mat_p_mass);
ApproxSchurComplement asc(mat_p_mass, solverQ);
LSCPreconditioner lsc_preconditioner(mat_BTx, mat_BTy, mat_Bx, mat_By, mat_Ax, mat_Ax, mat_v_mass, schur_complement, asc, QInv,
AInv, AInv);
/// 矩阵求解.
dealii::SolverControl solver_control (400000, l_Euler_tol * rhs.l2_norm(), 0);
SolverMinRes<Vector<double> > minres(solver_control);
minres.solve(matrix, x, rhs, lsc_preconditioner);
/// 将整体数值解分割成速度和压力.
for (int i = 0; i < n_dof_v; ++i)
{
v_h[0](i) = x(i);
v_h[1](i) = x(i + n_dof_v);
}
for (int i = 0; i < n_dof_p; ++i)
p_h(i) = x(i + 2 * n_dof_v);
/// 计算误差, t为时间参数.
computeError(t);
// /// 矩阵求解.
// SparseMatrix<double> mat_BTx(sp_pvx);
// SparseMatrix<double> mat_BTy(sp_pvy);
// SparseMatrix<double> mat_Bx(sp_vxp);
// SparseMatrix<double> mat_By(sp_vyp);
// SparseMatrix<double> mat_Ax(sp_vxvx);
// SparseMatrix<double> mat_Ay(sp_vyvy);
// for (int i = 0; i < sp_vxvx.n_nonzero_elements(); ++i)
// mat_Ax.global_entry(i) = matrix.global_entry(index_vxvx[i]);
// for (int i = 0; i < sp_vyvy.n_nonzero_elements(); ++i)
// mat_Ay.global_entry(i) = matrix.global_entry(index_vyvy[i]);
// for (int i = 0; i < sp_pvx.n_nonzero_elements(); ++i)
// mat_BTx.global_entry(i) = matrix.global_entry(index_pvx[i]);
// for (int i = 0; i < sp_pvy.n_nonzero_elements(); ++i)
// mat_BTy.global_entry(i) = matrix.global_entry(index_pvy[i]);
// for (int i = 0; i < sp_vxp.n_nonzero_elements(); ++i)
// mat_Bx.global_entry(i) = matrix.global_entry(index_vxp[i]);
// for (int i = 0; i < sp_vyp.n_nonzero_elements(); ++i)
// mat_By.global_entry(i) = matrix.global_entry(index_vyp[i]);
// Vector<double> tmp1(n_dof_v);
// Vector<double> tmp2(n_dof_v);
// Vector<double> rhs_vx(n_dof_v);
// Vector<double> rhs_vy(n_dof_v);
// Vector<double> rhs_p(n_dof_p);
// for (int i = 0; i < n_dof_v; ++i)
// {
// rhs_vx(i) = rhs(i);
// v_h[0](i) = x(i);
// rhs_vy(i) = rhs(n_dof_v + i);
// v_h[1](i) = x(n_dof_v + i);
// }
// for (int i = 0; i < n_dof_p; ++i)
// {
// rhs_p(i) = rhs(2 * n_dof_v + i);
// p_h(i) = x(2 * n_dof_v + i);
// }
// Vector<double> schur_rhs (n_dof_p);
// AMGSolver solverQ(mat_Ax);
// InverseMatrix M(mat_Ax, solverQ);
// M.vmult (tmp1, rhs_vx);
// M.vmult (tmp2, rhs_vy);
// mat_Bx.vmult(schur_rhs, tmp1);
// mat_By.vmult_add(schur_rhs, tmp2);
// schur_rhs -= rhs_p;
// SchurComplement schur_complement(mat_BTx, mat_BTy, mat_Bx, mat_By, mat_v_mass, M, M, dt);
// SolverControl solver_control_cg (n_dof_p * 2,
// 1e-12*schur_rhs.l2_norm());
// SolverCG<> cg (solver_control_cg);
// AMGSolver AQ(mat_p_mass);
// ApproxSchurComplement asc(mat_p_mass, AQ);
// cg.solve (schur_complement, p_h, schur_rhs, asc);
// // cg.solve (schur_complement, p_h, schur_rhs, PreconditionIdentity());
// std::cout << solver_control_cg.last_step()
// << " CG Schur complement iterations to obtain convergence."
// << std::endl;
// mat_BTx.vmult(tmp1, *dynamic_cast<const Vector<double>* >(&p_h));
// mat_BTy.vmult(tmp2, *dynamic_cast<const Vector<double>* >(&p_h));
// tmp1 *= -1;
// tmp2 *= -1;
// tmp1 += rhs_vx;
// tmp2 += rhs_vy;
// M.vmult(v_h[0], tmp1);
// M.vmult(v_h[1], tmp2);
// std::cout << "Stokes system solved." << std::endl;
// /// 计算误差, t为时间参数.
// computeError(t);
// /// debug, 计算惨量的L2 norm。
// Vector<double> res(n_total_dof);
// matrix.vmult(res, x);
// res *= -1;
// res += rhs;
// std::cout << "res_l2norm =" << res.l2_norm() << std::endl;
};
void ISOP2P1::stepForwardLinearizedEuler()
{
int n_dof_v = fem_space_v.n_dof();
int n_dof_p = fem_space_p.n_dof();
int n_total_dof = 2 * n_dof_v + n_dof_p;
matrix.reinit(sp_stokes);
/// (0, 0)
for (int i = 0; i < sp_vxvx.n_nonzero_elements(); ++i)
matrix.global_entry(index_vxvx[i]) = viscosity * mat_v_stiff.global_entry(i)
+ (1.0 / dt) * mat_v_mass.global_entry(i);
/// (1, 1)
for (int i = 0; i < sp_vyvy.n_nonzero_elements(); ++i)
matrix.global_entry(index_vyvy[i]) = viscosity * mat_v_stiff.global_entry(i)
+ (1.0 / dt) * mat_v_mass.global_entry(i);
// /// (0, 2)
for (int i = 0; i < sp_pvx.n_nonzero_elements(); ++i)
matrix.global_entry(index_pvx[i]) = mat_pvx_divT.global_entry(i);
// /// (1, 2)
for (int i = 0; i < sp_pvy.n_nonzero_elements(); ++i)
matrix.global_entry(index_pvy[i]) = mat_pvy_divT.global_entry(i);
// /// (2, 0)
for (int i = 0; i < sp_vxp.n_nonzero_elements(); ++i)
matrix.global_entry(index_vxp[i]) = mat_vxp_div.global_entry(i);
// /// (2, 1)
for (int i = 0; i < sp_vyp.n_nonzero_elements(); ++i)
matrix.global_entry(index_vyp[i]) = mat_vyp_div.global_entry(i);
rhs.reinit(n_total_dof);
FEMSpace<double,2>::ElementIterator the_element_v = fem_space_v.beginElement();
FEMSpace<double,2>::ElementIterator end_element_v = fem_space_v.endElement();
FEMSpace<double,2>::ElementIterator the_element_p = fem_space_p.beginElement();
FEMSpace<double,2>::ElementIterator end_element_p = fem_space_p.endElement();
/// 遍历速度单元, 拼装相关系数矩阵和右端项.
for (the_element_v = fem_space_v.beginElement();
the_element_v != end_element_v; ++the_element_v)
{
/// 当前单元信息.
double volume = the_element_v->templateElement().volume();
/// 积分精度, u 和 p 都是 1 次, 梯度和散度 u 都是常数. 因此矩阵拼
/// 装时积分精度不用超过 1 次. (验证一下!)
const QuadratureInfo<2>& quad_info = the_element_v->findQuadratureInfo(4);
std::vector<double> jacobian = the_element_v->local_to_global_jacobian(quad_info.quadraturePoint());
int n_quadrature_point = quad_info.n_quadraturePoint();
std::vector<Point<2> > q_point = the_element_v->local_to_global(quad_info.quadraturePoint());
/// 速度单元信息.
std::vector<std::vector<double> > basis_value_v = the_element_v->basis_function_value(q_point);
std::vector<std::vector<std::vector<double> > > basis_gradient_v = the_element_v->basis_function_gradient(q_point);
std::vector<double> vx_value = v_h[0].value(q_point, *the_element_v);
std::vector<double> vy_value = v_h[1].value(q_point, *the_element_v);
std::vector<double> fx_value = source_v[0].value(q_point, *the_element_v);
std::vector<double> fy_value = source_v[1].value(q_point, *the_element_v);
std::vector<std::vector<double> > vx_gradient = v_h[0].gradient(q_point, *the_element_v);
std::vector<std::vector<double> > vy_gradient = v_h[1].gradient(q_point, *the_element_v);
const std::vector<int>& element_dof_v = the_element_v->dof();
int n_element_dof_v = the_element_v->n_dof();
Element<double, 2> &p_element = fem_space_p.element(index_v2p[the_element_v->index()]);
const std::vector<int>& element_dof_p = p_element.dof();
std::vector<std::vector<std::vector<double> > > basis_gradient_p = p_element.basis_function_gradient(q_point);
std::vector<std::vector<double> > basis_value_p = p_element.basis_function_value(q_point);
int n_element_dof_p = p_element.n_dof();
std::vector<double> p_value = p_h.value(q_point, p_element);
for (int l = 0; l < n_quadrature_point; ++l)
{
double Jxw = quad_info.weight(l) * jacobian[l] * volume;
for (int i = 0; i < n_element_dof_v; ++i)
{
for (int j = 0; j < n_element_dof_v; ++j)
{
double cont = Jxw * (vx_value[l] * basis_gradient_v[j][l][0] +
vy_value[l] * basis_gradient_v[j][l][1]) * basis_value_v[i][l];
matrix.add(element_dof_v[i], element_dof_v[j], cont);
matrix.add(n_dof_v + element_dof_v[i], n_dof_v + element_dof_v[j], cont);
}
/// 右端项. 这里可施加源项和 Neumann 条件.
double rhs_cont = fx_value[l] * basis_value_v[i][l] + (1.0 / dt) * vx_value[l] * basis_value_v[i][l];
rhs_cont *= Jxw;
rhs(element_dof_v[i]) += rhs_cont;
rhs_cont = fy_value[l] * basis_value_v[i][l] + (1.0 / dt ) * vy_value[l] * basis_value_v[i][l];
rhs_cont *= Jxw;
rhs(n_dof_v + element_dof_v[i]) += rhs_cont;
}
}
}
/// 构建系数矩阵和右端项.
/// 这个存放整体的数值解. 没有分割成 u_h[0], u_h[1] 和 p_h.
Vector<double> x(n_total_dof);
for (int i = 0; i < n_dof_v; ++i)
{
x(i) = v_h[0](i);
x(i + n_dof_v) = v_h[1](i);
}
for (int i = 0; i < n_dof_p; ++i)
x(i + 2 * n_dof_v) = p_h(i);
boundaryValueStokes(x);
/// 矩阵求解.
SparseMatrix<double> mat_Axx(sp_vxvx);
SparseMatrix<double> mat_Ayy(sp_vyvy);
SparseMatrix<double> mat_BTx(sp_pvx);
SparseMatrix<double> mat_BTy(sp_pvy);
for (int i = 0; i < sp_vxvx.n_nonzero_elements(); ++i)
mat_Axx.global_entry(i) = matrix.global_entry(index_vxvx[i]);
for (int i = 0; i < sp_vyvy.n_nonzero_elements(); ++i)
mat_Ayy.global_entry(i) = matrix.global_entry(index_vyvy[i]);
for (int i = 0; i < sp_pvx.n_nonzero_elements(); ++i)
mat_BTx.global_entry(i) = matrix.global_entry(index_pvx[i]);
for (int i = 0; i < sp_pvy.n_nonzero_elements(); ++i)
mat_BTy.global_entry(i) = matrix.global_entry(index_pvy[i]);
std::cout << "Precondition matrix builded!" << std::endl;
// NSPreconditioner preconditioner_ns;
// preconditioner_ns.initialize(mat_Axx,
// mat_Ayy,
// mat_BTx,
// mat_BTy,
// mat_p_mass);
clock_t t_cost = clock();
dealii::SolverControl solver_control (4000000, l_tol, check);
SolverGMRES<Vector<double> >::AdditionalData para(2000, false, true);
SolverGMRES<Vector<double> > gmres (solver_control, para);
gmres.solve (matrix, x, rhs, PreconditionIdentity());
t_cost = clock() - t_cost;
std::cout << "time cost: " << (((float)t_cost) / CLOCKS_PER_SEC) << std::endl;
/// 将整体数值解分割成速度和压力.
for (int i = 0; i < n_dof_v; ++i)
{
v_h[0](i) = x(i);
v_h[1](i) = x(i + n_dof_v);
}
for (int i = 0; i < n_dof_p; ++i)
p_h(i) = x(i + 2 * n_dof_v);
};
