Stokes incompressible 2D
In this example we try to solve the 2D stokes equation for incompressible fluid with Reynold number = 0
Such equation require the inversion of a system. We will show how to produce such system and solve it using Finite differences with staggered grid. The system of equation to solve is the following
\[ \eta \partial^{2}_{x} v_x + \eta \partial^{2}_{y} v_x - \partial_{x} P = 0 \]
\[ \eta \partial^{2}_{x} v_y + \eta \partial^{2}_{y} v_y - \partial_{y} P = 0 \]
\[ \partial_{x} v_x + \partial_{y} v_y = 0 \]
\( v_x = 0 \quad v_y = 1 \) at x = L
\( v_x = 0 \quad v_y = 0 \) otherwise
General Model properties
In order to do this we have to define a structure that contain the main information about the system
#include "Grid/grid_dist_id.hpp"
#include "Matrix/SparseMatrix.hpp"
#include "Vector/Vector.hpp"
#include "FiniteDifference/FDScheme.hpp"
#include "FiniteDifference/util/common.hpp"
#include "FiniteDifference/eq.hpp"
#include "Solvers/umfpack_solver.hpp"
#include "Solvers/petsc_solver.hpp"
{
static const unsigned int dims = 2;
static const unsigned int nvar = 3;
static const bool boundary[];
typedef float stype;
};
const bool lid_nn::boundary[] = {NON_PERIODIC,NON_PERIODIC};
This class decompose a space into sub-sub-domains and distribute them across processors.
Sparse Matrix implementation.
Sparse Matrix implementation stub object when OpenFPM is compiled with no linear algebra support.
This is a distributed grid.
[Definition of the system]
System of equation modeling
We model the equations. This part will change in the near future to use template expression parsing and simplify the process of defining equations.
\( \eta v_x \nabla v_x = eta\_lap\_vx \quad \nabla = \partial^{2}_{x} + \partial^{2}_{y} \) Step1
\( \partial_{x} P = p\_x \) Step 2
\( -p\_x = m\_ p\_ x \) Step 3
\( eta\_lap\_vx - m\_p\_x \) Step4. This is the first equation in the system
The second equation definition is similar to the first one
\( \partial^{forward}_{x} v_x = dx\_vx \) Step5
\( \partial^{forward}_{y} v_y = dy\_vy \) Step6
\( dx\_vx + dy\_vy \) Step 7. This is the third equation in the system
{
typedef void const_field;
static float val() {return 1.0;}
};
constexpr unsigned int v[] = {0,1};
constexpr unsigned int P = 2;
constexpr unsigned int ic = 2;
constexpr int x = 0;
constexpr int y = 1;
Derivative second order on h (spacing)
Test structure used for several test.
[Definition of the system]
It ancapsulate the minus operation.
It model an expression expr1 * expr2.
It model an expression expr1 + ... exprn.
In case of boundary conditions and staggered grid we need a particular set of equations at boundaries. Explain in detail is out of the scope of this example, but to qualitatively have an idea consider the following staggered cell
\verbatim
+--$--+
| |
# * #
| |
0--$--+
= velocity(x)
$ = velocity(y)
As we can see several properties has different position in the cell. Consider we want to impose \(v_y = 0\) on \(x=0\). Because there are not points at \(x = 0\) we have to interpolate between $ of this cell and $ of the previous cell on y Averaging using the Avg operator. The same apply for \(v_x\) on \(y=0\). Similar arguments can be done for other boundaries in order to finally reach a well defined system
#define EQ_1 0
#define EQ_2 1
#define EQ_3 2
Initialization
After model our equation we:
- Initialize the library
- Define some useful constants
- define Ghost size
- Non-periodic boundary conditions
- Padding domain expansion
Padding and Ghost differ in the fact the padding extend the domain. Ghost is an extension for each sub-domain
openfpm_init(&argc,&argv);
constexpr int velocity = 0;
constexpr int pressure = 1;
long int sz[] = {96,32};
size_t szu[2];
szu[0] = (size_t)sz[0];
szu[1] = (size_t)sz[1];
This class represent an N-dimensional box.
Class that contain Padding information on each direction positive and Negative direction.
Distributed grid that store the solution
- See also
- Grid instantiation
Solving the system above require the solution of a system like that
\( Ax = b \quad x = A^{-1}b\)
where A is the system the discretize the left hand side of the equations + boundary conditions and b discretize the right hand size + boundary conditions
FDScheme is the object that we use to produce the Matrix A and the vector b. Such object require the maximum extension of the stencil
Impose the equation on the domain
Here we impose the system of equation, we start from the incompressibility Eq imposed in the bulk with the exception of the first point {0,0} and than we set P = 0 in {0,0}, why we are doing this is again mathematical to have a well defined system, an intuitive explanation is that P and P + c are both solution for the incompressibility equation, this produce an ill-posed problem to make it well posed we set one point in this case {0,0} the pressure to a fixed constant for convenience P = 0
The best way to understand what we are doing is to draw a smaller example like 8x8. Considering that we have one additional point on the left for padding we have a grid 9x9. If on each point we have v_x v_y and P unknown we have 9x9x3 = 243 unknown. In order to fully determine and unique solution we have to impose 243 condition. The code under impose (in the case of 9x9) between domain and bulk 243 conditions.
fd.impose(
ic_eq(),0.0, EQ_3, {0,0},{sz[0]-2,sz[1]-2},
true);
fd.impose(
Prs(), 0.0, EQ_3, {0,0},{0,0});
fd.impose(
vx_eq(),0.0, EQ_1, {1,0},{sz[0]-2,sz[1]-2});
fd.impose(
vy_eq(),0.0, EQ_2, {0,1},{sz[0]-2,sz[1]-2});
fd.impose(
v_x(),0.0, EQ_1, {0,0},{0,sz[1]-2});
fd.impose(
avg_vy_f(),0.0, EQ_2 , {-1,0},{-1,sz[1]-1});
fd.impose(
v_x(),0.0, EQ_1, {sz[0]-1,0},{sz[0]-1,sz[1]-2});
fd.impose(
avg_vy(),1.0, EQ_2, {sz[0]-1,0},{sz[0]-1,sz[1]-1});
fd.impose(
avg_vx_f(),0.0, EQ_1, {0,-1},{sz[0]-1,-1});
fd.impose(
v_y(), 0.0, EQ_2, {0,0},{sz[0]-2,0});
fd.impose(
avg_vx(),0.0, EQ_1, {0,sz[1]-1},{sz[0]-1,sz[1]-1});
fd.impose(
v_y(), 0.0, EQ_2, {0,sz[1]-1},{sz[0]-2,sz[1]-1});
fd.impose(
Prs(), 0.0, EQ_3, {-1,-1},{sz[0]-1,-1});
fd.impose(
Prs(), 0.0, EQ_3, {-1,sz[1]-1},{sz[0]-1,sz[1]-1});
fd.impose(
Prs(), 0.0, EQ_3, {-1,0},{-1,sz[1]-2});
fd.impose(
Prs(), 0.0, EQ_3, {sz[0]-1,0},{sz[0]-1,sz[1]-2});
fd.impose(
v_x(), 0.0, EQ_1, {-1,-1},{-1,sz[1]-1});
fd.impose(
v_y(), 0.0, EQ_2, {-1,-1},{sz[0]-1,-1});
Solve the system of equation
Once we imposed all the equations we can retrieve the Matrix A and the vector b and pass these two element to the solver. In this example we are using a serial direct solver Umfpack.
auto x = solver.
solve(fd.getA(),fd.getB());
stub when library compiled without eigen
static Vector< T > solve(const SparseMatrix< T, id_type, impl > &A, const Vector< T, impl > &b)
stub solve
Copy the solution on the grid and write on VTK
Once we have the solution we copy it on the grid
fd.template copy<velocity,pressure>(x,{0,0},{sz[0]-1,sz[1]-1},g_dist);
g_dist.write("lid_driven_cavity_p_umfpack");
Finalize
At the very end of the program we have always to de-initialize the library
Full code
#include "Grid/grid_dist_id.hpp"
#include "Matrix/SparseMatrix.hpp"
#include "Vector/Vector.hpp"
#include "FiniteDifference/FDScheme.hpp"
#include "FiniteDifference/util/common.hpp"
#include "FiniteDifference/eq.hpp"
#include "Solvers/umfpack_solver.hpp"
#include "Solvers/petsc_solver.hpp"
{
static const unsigned int dims = 2;
static const unsigned int nvar = 3;
static const bool boundary[];
typedef float stype;
};
const bool lid_nn::boundary[] = {NON_PERIODIC,NON_PERIODIC};
{
typedef void const_field;
static float val() {return 1.0;}
};
constexpr unsigned int v[] = {0,1};
constexpr unsigned int P = 2;
constexpr unsigned int ic = 2;
constexpr int x = 0;
constexpr int y = 1;
#define EQ_1 0
#define EQ_2 1
#define EQ_3 2
#include "Vector/vector_dist.hpp"
#include "data_type/aggregate.hpp"
int main(int argc, char* argv[])
{
openfpm_init(&argc,&argv);
constexpr int velocity = 0;
constexpr int pressure = 1;
long int sz[] = {96,32};
size_t szu[2];
szu[0] = (size_t)sz[0];
szu[1] = (size_t)sz[1];
fd.impose(
ic_eq(),0.0, EQ_3, {0,0},{sz[0]-2,sz[1]-2},
true);
fd.impose(
Prs(), 0.0, EQ_3, {0,0},{0,0});
fd.impose(
vx_eq(),0.0, EQ_1, {1,0},{sz[0]-2,sz[1]-2});
fd.impose(
vy_eq(),0.0, EQ_2, {0,1},{sz[0]-2,sz[1]-2});
fd.impose(
v_x(),0.0, EQ_1, {0,0},{0,sz[1]-2});
fd.impose(
avg_vy_f(),0.0, EQ_2 , {-1,0},{-1,sz[1]-1});
fd.impose(
v_x(),0.0, EQ_1, {sz[0]-1,0},{sz[0]-1,sz[1]-2});
fd.impose(
avg_vy(),1.0, EQ_2, {sz[0]-1,0},{sz[0]-1,sz[1]-1});
fd.impose(
avg_vx_f(),0.0, EQ_1, {0,-1},{sz[0]-1,-1});
fd.impose(
v_y(), 0.0, EQ_2, {0,0},{sz[0]-2,0});
fd.impose(
avg_vx(),0.0, EQ_1, {0,sz[1]-1},{sz[0]-1,sz[1]-1});
fd.impose(
v_y(), 0.0, EQ_2, {0,sz[1]-1},{sz[0]-2,sz[1]-1});
fd.impose(
Prs(), 0.0, EQ_3, {-1,-1},{sz[0]-1,-1});
fd.impose(
Prs(), 0.0, EQ_3, {-1,sz[1]-1},{sz[0]-1,sz[1]-1});
fd.impose(
Prs(), 0.0, EQ_3, {-1,0},{-1,sz[1]-2});
fd.impose(
Prs(), 0.0, EQ_3, {sz[0]-1,0},{sz[0]-1,sz[1]-2});
fd.impose(
v_x(), 0.0, EQ_1, {-1,-1},{-1,sz[1]-1});
fd.impose(
v_y(), 0.0, EQ_2, {-1,-1},{sz[0]-1,-1});
auto x = solver.
solve(fd.getA(),fd.getB());
fd.template copy<velocity,pressure>(x,{0,0},{sz[0]-1,sz[1]-1},g_dist);
g_dist.write("lid_driven_cavity_p_umfpack");
openfpm_finalize();
}