The Two- and Three-Dimensional Navier-Stokes Equations

Background

The Navier-Stokes equations describe the motion of a fluid. In order to derive the Navier-Stokes equations we assume that a fluid is a continuum (not made of individual particles, but rather a continuous substance) and that mass and momentum are conserved. After making some assumptions and using Newton’s second law on an incompressible fluid particle, the Navier-Stokes equations can be derived in their entirety. All details are omitted since there are many sources of this information, two sources that are particularly clear are Tritton^[1] and Doering and Gibbon^[2]; Gallavotti^[3] should also be noted for introducing both mathematical and physical aspects of these equations, and Uecker^[4] includes a quick derivation and some example Fourier Spectral Matlab codes. For a more detailed introduction to spectral methods for the Navier-Stokes equations see Canuto et al.^[5]^[6]. The incompressible Navier-Stokes equations are

\rho \left({\frac {\partial \mathbf {u} }{\partial t}}+\mathbf {u} \cdot \nabla \mathbf {u} \right)=-\nabla p+\mu \Delta \mathbf {u} +\mathbf {f}

( 1)

\nabla \cdot \mathbf {u} =0

.

( 2)

In these equations, $\rho$ is density, $\mathbf {u} (x,y,z)=(u,v,w)$ is the velocity with components in the $x$ , $y$ and $z$ directions, $p$ is pressure field, $\mu$ is dynamic viscosity (constant in incompressible case) and $\mathbf {f}$ is a body force (force that acts through out the volume). Equation 1 represents conservation of momentum and eq. 2 is the continuity equation which represents conservation of mass for an incompressible fluid.

The Two-Dimensional Case

We will first consider the two-dimensional case. A difficulty in simulating the incompressible Navier-Stokes equations is the numerical satisfaction of the incompressibility constraint in eq. 2 , this is sometimes referred to as a divergence free condition or a solenoidal constraint. To automatically satisfy this incompressibility constraint in two dimensions, where

$\mathbf {u} (x,y)=\left(u(x,y),v(x,y)\right)$

it is possible to re-write the equations using a different formulation, the stream-function vorticity formulation. In this case, we let

$u={\frac {\partial \psi }{\partial y}}$

and

$v=-{\frac {\partial \psi }{\partial x}}$

where $\psi (x,y)$ is the streamfunction. Level curves of the streamfunction represent streamlines (A streamline is a continuous curve along which the instantaneous velocity is tangent, see Tritton^[7] for more on this.) of the fluid field. Note that

$\nabla \cdot \mathbf {u} ={\frac {\partial u}{\partial x}}+{\frac {\partial v}{\partial y}}={\frac {\partial ^{2}\psi }{\partial x\partial y}}-{\frac {\partial ^{2}\psi }{\partial y\partial x}}=0$ ,

so eq. 2 is automatically satisfied. Making this change of variables, we obtain a single scalar partial differential equation by taking the curl of the momentum equation, eq. 1 . We define the vorticity $\omega$ , so that

$\omega =\nabla \times \mathbf {u} ={\frac {\partial v}{\partial x}}-{\frac {\partial u}{\partial y}}=-\Delta \psi$

and eq. 1 becomes

${\frac {\partial }{\partial x}}\left[\rho \left({\frac {\partial v}{\partial t}}+u{\frac {\partial v}{\partial x}}+v{\frac {\partial v}{\partial y}}\right)\right]-{\frac {\partial }{\partial y}}\left[\rho \left({\frac {\partial u}{\partial t}}+u{\frac {\partial u}{\partial x}}+v{\frac {\partial u}{\partial y}}\right)\right]$ $={\frac {\partial }{\partial x}}\left[\mu \left({\frac {\partial ^{2}v}{\partial x^{2}}}+{\frac {\partial ^{2}v}{\partial y^{2}}}\right)+fy\right]-{\frac {\partial }{\partial y}}\left[\mu \left({\frac {\partial ^{2}u}{\partial x^{2}}}+{\frac {\partial ^{2}u}{\partial y^{2}}}\right)+fx\right]$

where $fx$ and $fy$ represent the $x$ and $y$ components of the force $\mathbf {f}$ . Since the flow is divergence free,

${\frac {\partial u}{\partial x}}=-{\frac {\partial v}{\partial y}}$

and so can simplify the nonlinear term to get

${\frac {\partial }{\partial x}}\left[\left(u{\frac {\partial v}{\partial x}}+v{\frac {\partial v}{\partial y}}\right)\right]-{\frac {\partial }{\partial y}}\left[\left(u{\frac {\partial u}{\partial x}}+v{\frac {\partial u}{\partial y}}\right)\right]$

$={\frac {\partial u}{\partial x}}{\frac {\partial v}{\partial x}}+u{\frac {\partial ^{2}v}{\partial x^{2}}}+{\frac {\partial v}{\partial x}}{\frac {\partial v}{\partial y}}+v{\frac {\partial ^{2}v}{\partial x\partial y}}-{\frac {\partial u}{\partial y}}{\frac {\partial u}{\partial x}}-u{\frac {\partial ^{2}u}{\partial x\partial y}}-{\frac {\partial v}{\partial y}}{\frac {\partial u}{\partial y}}-v{\frac {\partial ^{2}u}{\partial y^{2}}}$

$=u\left({\frac {\partial ^{2}v}{\partial x^{2}}}-{\frac {\partial ^{2}u}{\partial x\partial y}}\right)+v\left({\frac {\partial ^{2}v}{\partial x\partial y}}-{\frac {\partial ^{2}u}{\partial ^{2}y}}\right)$ .

We finally obtain

\rho \left({\frac {\partial \omega }{\partial t}}+u{\frac {\partial \omega }{\partial x}}+v{\frac {\partial \omega }{\partial y}}\right)=\mu \Delta \omega +{\frac {\partial fy}{\partial x}}-{\frac {\partial fx}{\partial y}}

( 3)

and

\Delta \psi =-\omega

.

( 4)

Note that in this formulation, the Navier-Stokes equation is like a forced heat equation for the vorticity with a nonlocal and nonlinear term. We can take advantage of this structure in finding numerical solutions by modifying our numerical programs which give approximate solutions to the heat equation.

A simple time discretization for this equation is the Crank-Nicolson method, where the nonlinear terms are solved for using fixed point iteration. A tutorial on convergence of time discretization schemes for the Navier-Stokes equations can be found in Temam^[8]. The time discretized equations become

\rho \left[{\frac {\omega ^{n+1,k+1}-\omega ^{n}}{\delta t}}\right.

( 5)

$\left.+{\frac {1}{2}}\left(u^{n+1,k}{\frac {\partial \omega ^{n+1,k}}{\partial x}}+v^{n+1,k}{\frac {\partial \omega ^{n+1,k}}{\partial y}}+u^{n}{\frac {\partial \omega ^{n}}{\partial x}}+v^{n}{\frac {\partial \omega ^{n}}{\partial y}}\right)\right]$

$={\frac {\mu }{2}}\Delta \left(\omega ^{n+1,k+1}+\omega ^{n}\right)+\left.\left({\frac {\partial fx}{\partial y}}-{\frac {\partial fy}{\partial x}}\right)\right|_{t=(n+0.5)\delta t}$ ,

and

\Delta \psi ^{n+1,k+1}=-\omega ^{n+1,k+1}

,

( 6)

$u^{n+1,k+1}={\frac {\partial \psi ^{n+1,k+1}}{\partial y}}$ ,

$v^{n+1,k+1}=-{\frac {\partial \psi ^{n+1,k+1}}{\partial x}}$ .

In these equations, the superscript $n$ denotes the timestep and the superscript $k$ denotes the iterate. Another choice of time discretization is the implicit midpoint rule which gives,

\rho \left[{\frac {\omega ^{n+1,k+1}-\omega ^{n}}{\delta t}}\right.

( 7)

$\left.+\left({\frac {u^{n+1,k}+u^{n}}{2}}\right){\frac {\partial }{\partial x}}\left({\frac {\omega ^{n+1,k}+\omega ^{n}}{2}}\right)+\left({\frac {v^{n+1,k}+v^{n}}{2}}\right){\frac {\partial }{\partial y}}\left({\frac {\omega ^{n+1,k}+\omega ^{n}}{2}}\right)\right]$

$={\frac {\mu }{2}}\Delta \left(\omega ^{n+1,k+1}+\omega ^{n}\right)+\left.\left({\frac {\partial fx}{\partial y}}-{\frac {\partial fy}{\partial x}}\right)\right|_{t=(n+0.5)\delta t}$ ,

and

\Delta \psi ^{n+1,k+1}=-\omega ^{n+1,k+1}

,

( 8)

$u^{n+1,k+1}={\frac {\partial \psi ^{n+1,k+1}}{\partial y}}$ ,

$v^{n+1,k+1}=-{\frac {\partial \psi ^{n+1,k+1}}{\partial x}}$ .

The Three-Dimensional Case

Here $\mathbf {u} =(u(x,y,z,t),v(x,y,z,t),w(x,y,z,t))$ – unfortunately, it is not clear if this equation has a unique solution for reasonable boundary conditions and initial data. Numerical methods so far seem to indicate that the solution is unique, but in the absence of a proof, we caution the reader that we are fearless engineers writing gigantic codes that are supposed to produce solutions to the Navier-Stokes equations when what we are really studying is the output of the algorithm which we hope will tell us something about these equations (This is paraphrased from Gallavoti^[9] – in practice, although the mathematical foundations for this are uncertain, these codes do seem to give information about the motion of nearly incompressible fluids in many, although not all situations of practical interest. Further information on this aspect of these equations can be found in Doering and Gibbon^[10].

We will again consider simulations with periodic boundary conditions to make it easy to apply the Fourier transform. This also makes it easier to enforce the incompressibility constraint by using an idea due to Orszag and Patterson^[11] and also explained in Canuto et al.^[12]^[13] . If we take the divergence of the Navier-Stokes equations, we get $\nabla \cdot \left(\mathbf {u} \cdot \nabla \mathbf {u} \right)=-\Delta p$ because $\nabla \cdot \mathbf {u} =0$ . Hence ${}p=-\Delta ^{-1}\left[\nabla \cdot \left(\mathbf {u} \cdot \nabla \mathbf {u} \right)\right]$ where $\Delta ^{-1}$ is defined using the Fourier transform, thus if $f(x,y,z)$ is a mean zero, periodic scalar field and ${\hat {f}}$ is its Fourier transform, then ${\widehat {\Delta ^{-1}f}}=-{\frac {\hat {f}}{k_{x}^{2}+k_{y}^{2}+k_{z}^{2}}}$ where $k_{x}$ , $k_{y}$ and $k_{z}$ are the wavenumbers. The Navier-Stokes equations then become

{\frac {\partial \mathbf {u} }{\partial t}}={\frac {1}{\text{Re}}}\Delta \mathbf {u} -\mathbf {u} \cdot \nabla \mathbf {u} +\nabla \Delta ^{-1}\left[\nabla \cdot \left(\mathbf {u} \cdot \nabla \mathbf {u} \right)\right]

,

( 9)

for which the incompressibility constraint is satisfied, provided the initial data satisfy the incompressibility constraint.

To discretize 9 in time, we will use the implicit midpoint rule. This gives,

{\frac {\mathbf {u} ^{n+1}-\mathbf {u} ^{n}}{\delta t}}={}{\frac {0.5}{\text{Re}}}\Delta \left(\mathbf {u} ^{n+1}+\mathbf {u} ^{n}\right)-0.25\left(\mathbf {u} ^{n+1}+\mathbf {u} ^{n}\right)\cdot \nabla \left(\mathbf {u} ^{n+1}+\mathbf {u} ^{n}\right)

( 10)

$+0.25\nabla \left[\Delta ^{-1}\left(\nabla \cdot \left[\left(\mathbf {u} ^{n+1}+\mathbf {u} ^{n}\right)\cdot \nabla \left(\mathbf {u} ^{n+1}+\mathbf {u} ^{n}\right)\right]\right)\right]$ .

It is helpful to test the correctness of the programs by comparing them to an exact solution. Shapiro^[14] has found the following exact solution which is a good test for meteorological hurricane simulation programs, as well as for Navier-Stokes solvers with periodic boundary conditions

$u=-{\frac {A}{k^{2}+l^{2}}}\left[\lambda l\cos(kx)\sin(ly)\sin(mz)+mk\sin(kx)\cos(ly)\cos(mz)\right]\exp \left(-{\frac {\lambda ^{2}t}{\text{Re}}}\right)$

$v={\frac {A}{k^{2}+l^{2}}}\left[\lambda k\sin(kx)\cos(ly)\sin(mz)-ml\cos(kx)\sin(ly)\cos(mz)\right]\exp \left(-{\frac {\lambda ^{2}t}{\text{Re}}}\right)$

$w=A\cos(kx)\cos(ly)\sin(mz)\exp \left(-{\frac {\lambda ^{2}t}{\text{Re}}}\right)$

where the constant $\lambda ={\sqrt {k^{2}+l^{2}+m^{2}}}$ and $l$ , $k$ and $m$ are constants choosen with the restriction that the solutions are periodic in space. Further examples of such solutions can be found in Majda and Bertozzi^[15].

Serial Programs

We first write Matlab programs to demonstrate how to solve these equations on a single processor. The first program uses Crank-Nicolson timestepping to solve the two-dimensional Navier-Stokes equations and is in listing A . To test the program, following Laizet and Lamballais^[16] we use the exact Taylor-Green vortex solution on $(x,y)\in [0,1]\times [0,1]$ with periodic boundary conditions given by

${}u(x,y,t)=\sin(2\pi x)\cos(2\pi y)\exp(-8\pi ^{2}\mu t)$

$v(x,y,t)=-\cos(2\pi x)\sin(2\pi y)\exp(-8\pi ^{2}\mu t)$ .

( A)

A Matlab program which finds a numerical solution to the 2D Navier Stokes equation Code download

% Numerical solution of the 2D incompressible Navier-Stokes on a
% Square Domain [0,1]x[0,1] using a Fourier pseudo-spectral method
% and Crank-Nicolson timestepping. The numerical solution is compared to
% the exact Taylor-Green Vortex solution of the Navier-Stokes equations
%
%Periodic free-slip boundary conditions and Initial conditions:
    %u(x,y,0)=sin(2*pi*x)cos(2*pi*y)
    %v(x,y,0)=-cos(2*pi*x)sin(2*pi*y)
%Analytical Solution:
    %u(x,y,t)=sin(2*pi*x)cos(2*pi*y)exp(-8*pi^2*t/Re)
    %v(x,y,t)=-cos(2*pi*x)sin(2*pi*y)exp(-8*pi^2*t/Re)
clear all; format compact; format short; clc; clf;

Re=1;%Reynolds number

%grid
Nx=64; h=1/Nx; x=h*(1:Nx);
Ny=64; h=1/Ny; y=h*(1:Ny)';
[xx,yy]=meshgrid(x,y);

%initial conditions
u=sin(2*pi*xx).*cos(2*pi*yy);
v=-cos(2*pi*xx).*sin(2*pi*yy);
u_y=-2*pi*sin(2*pi*xx).*sin(2*pi*yy);
v_x=2*pi*sin(2*pi*xx).*sin(2*pi*yy);
omega=v_x-u_y;

dt=0.0025; t(1)=0; tmax=.1;
nplots=ceil(tmax/dt);

%wave numbers for derivatives
k_x=2*pi*(1i*[(0:Nx/2-1) 0 1-Nx/2:-1]');
k_y=2*pi*(1i*[(0:Ny/2-1) 0 1-Ny/2:-1]);
k2x=k_x.^2;
k2y=k_y.^2;

%wave number grid for multiplying matricies
[kxx,kyy]=meshgrid(k2x,k2y);
[kx,ky]=meshgrid(k_x,k_y);

% use a high tolerance so time stepping errors
% are not dominated by errors in solution to nonlinear
% system
tol=10^(-10);

%compute \hat{\omega}^{n+1,k}
omegahat=fft2(omega);
%nonlinear term
nonlinhat=fft2(u.*ifft2(omegahat.*kx)+v.*ifft2(omegahat.*ky));
for i=1:nplots
    chg=1;
    % save old values
    uold=u; vold=v; omegaold=omega; omegacheck=omega;
    omegahatold=omegahat; nonlinhatold=nonlinhat;
    while chg>tol
        %nonlinear {n+1,k}
        nonlinhat=fft2(u.*ifft2(omegahat.*kx)+v.*ifft2(omegahat.*ky));
       
        %Crank–Nicolson timestepping
        omegahat=((1/dt + 0.5*(1/Re)*(kxx+kyy)).*omegahatold...
            -.5*(nonlinhatold+nonlinhat))...
            ./(1/dt -0.5*(1/Re)*(kxx+kyy));
        
        %compute \hat{\psi}^{n+1,k+1}
        psihat=-omegahat./(kxx+kyy);
        
        %NOTE: kxx+kyy has to be zero at the following points to avoid a
        % discontinuity. However, we suppose that the streamfunction has
        % mean value zero, so we set them equal to zero
        psihat(1,1)=0;
        psihat(Nx/2+1,Ny/2+1)=0;
        psihat(Nx/2+1,1)=0;
        psihat(1,Ny/2+1)=0;
        
        %computes {\psi}_x by differentiation via FFT
        dpsix = real(ifft2(psihat.*kx));
        %computes {\psi}_y by differentiation via FFT
        dpsiy = real(ifft2(psihat.*ky));
        
        u=dpsiy; %u^{n+1,k+1}
        v=-dpsix; %v^{n+1,k+1}
        
        %\omega^{n+1,k+1}
        omega=ifft2(omegahat);
        % check for convergence
        chg=max(max(abs(omega-omegacheck)))
        % store omega to check for convergence of next iteration
        omegacheck=omega;
    end
     t(i+1)=t(i)+dt;
     uexact_y=-2*pi*sin(2*pi*xx).*sin(2*pi*yy).*exp(-8*pi^2*t(i+1)/Re);
     vexact_x=2*pi*sin(2*pi*xx).*sin(2*pi*yy).*exp(-8*pi^2*t(i+1)/Re);
     omegaexact=vexact_x-uexact_y;
     figure(1); pcolor(omega); xlabel x; ylabel y;
     title Numerical; colorbar; drawnow;
     figure(2); pcolor(omegaexact); xlabel x; ylabel y;
     title Exact; colorbar; drawnow;
     figure(3); pcolor(omega-omegaexact); xlabel x; ylabel y;
     title Error; colorbar; drawnow;
end

( Ap)

A Python program which finds a numerical solution to the 2D Navier-Stokes equation. Code download

#!/usr/bin/env python
"""
Numerical solution of the 2D incompressible Navier-Stokes on a
Square Domain [0,1]x[0,1] using a Fourier pseudo-spectral method
and Crank-Nicolson timesteping. The numerical solution is compared to
the exact Taylor-Green Vortex solution of the Navier-Stokes equations

Periodic free-slip boundary conditions and Initial conditions:
u(x,y,0)=sin(2*pi*x)cos(2*pi*y)
v(x,y,0)=-cos(2*pi*x)sin(2*pi*y)
Analytical Solution:
u(x,y,t)=sin(2*pi*x)cos(2*pi*y)exp(-8*pi^2*nu*t)
v(x,y,t)=-cos(2*pi*x)sin(2*pi*y)exp(-8*pi^2*nu*t)
"""

import math
import numpy
import matplotlib.pyplot as plt
from mayavi import mlab
import time

# Grid
N=64; h=1.0/N
x = [h*i for i in xrange(1,N+1)]
y = [h*i for i in xrange(1,N+1)]
numpy.savetxt('x.txt',x)

xx=numpy.zeros((N,N), dtype=float)
yy=numpy.zeros((N,N), dtype=float)

for i in xrange(N):
    for j in xrange(N):
        xx[i,j] = x[i]
        yy[i,j] = y[j]


dt=0.0025; t=0.0; tmax=0.10
#nplots=int(tmax/dt)
Rey=1

u=numpy.zeros((N,N), dtype=float)
v=numpy.zeros((N,N), dtype=float)
u_y=numpy.zeros((N,N), dtype=float)
v_x=numpy.zeros((N,N), dtype=float)
omega=numpy.zeros((N,N), dtype=float)
# Initial conditions
for i in range(len(x)):
    for j in range(len(y)):
        u[i][j]=numpy.sin(2*math.pi*x[i])*numpy.cos(2*math.pi*y[j])
        v[i][j]=-numpy.cos(2*math.pi*x[i])*numpy.sin(2*math.pi*y[j])
        u_y[i][j]=-2*math.pi*numpy.sin(2*math.pi*x[i])*numpy.sin(2*math.pi*y[j])
        v_x[i][j]=2*math.pi*numpy.sin(2*math.pi*x[i])*numpy.sin(2*math.pi*y[j])
        omega[i][j]=v_x[i][j]-u_y[i][j]

src = mlab.imshow(xx,yy,omega,colormap='jet')
mlab.scalarbar(object=src)
mlab.xlabel('x',object=src)
mlab.ylabel('y',object=src)


# Wavenumber
k_x = 2*math.pi*numpy.array([complex(0,1)*n for n in range(0,N/2) \
+ [0] + range(-N/2+1,0)])
k_y=k_x

kx=numpy.zeros((N,N), dtype=complex)
ky=numpy.zeros((N,N), dtype=complex)
kxx=numpy.zeros((N,N), dtype=complex)
kyy=numpy.zeros((N,N), dtype=complex)

for i in xrange(N):
    for j in xrange(N):
        kx[i,j] = k_x[i]
        ky[i,j] = k_y[j]
        kxx[i,j] = k_x[i]**2
        kyy[i,j] = k_y[j]**2

tol=10**(-10)
psihat=numpy.zeros((N,N), dtype=complex)
omegahat=numpy.zeros((N,N), dtype=complex)
omegahatold=numpy.zeros((N,N), dtype=complex)
nlhat=numpy.zeros((N,N), dtype=complex)
nlhatold=numpy.zeros((N,N), dtype=complex)
dpsix=numpy.zeros((N,N), dtype=float)
dpsiy=numpy.zeros((N,N), dtype=float)
omegacheck=numpy.zeros((N,N), dtype=float)
omegaold=numpy.zeros((N,N), dtype=float)
temp=numpy.zeros((N,N), dtype=float)
omegahat=numpy.fft.fft2(omega)
nlhat=numpy.fft.fft2(u*numpy.fft.ifft2(omegahat*kx)+\
v*numpy.fft.ifft2(omegahat*ky))
while (t<=tmax):
    chg=1.0

    # Save old values
    uold=u
    vold=v
    omegaold=omega
    omegacheck=omega
    omegahatold = omegahat
    nlhatold=nlhat
    
    while(chg>tol):
        # nolinear {n+1,k}
        nlhat=numpy.fft.fft2(u*numpy.fft.ifft2(omegahat*kx)+\
        v*numpy.fft.ifft2(omegahat*ky))

        # Crank-Nicolson timestepmath.ping
        omegahat=((1/dt + 0.5*(1/Rey)*(kxx+kyy))*omegahatold \
        -0.5*(nlhatold+nlhat)) \
        /(1/dt -0.5*(1/Rey)*(kxx+kyy))

        psihat=-omegahat/(kxx+kyy)
        psihat[0][0]=0
        psihat[N/2][N/2]=0
        psihat[N/2][0]=0
        psihat[0][N/2]=0

        dpsix = numpy.real(numpy.fft.ifft2(psihat*kx))
        dpsiy = numpy.real(numpy.fft.ifft2(psihat*ky))
        u=dpsiy
        v=-1.0*dpsix
        
        omega=numpy.real(numpy.fft.ifft2(omegahat))
        temp=abs(omega-omegacheck)
        chg=numpy.max(temp)
        print(chg)
        omegacheck=omega
    t+=dt
    src.mlab_source.scalars = omega
 
omegaexact=numpy.zeros((N,N), dtype=float)
for i in range(len(x)):
    for j in range(len(y)):
        uexact_y=-2*math.pi*numpy.sin(2*math.pi*x[i])*numpy.sin(2*math.pi*x[j])\
        *numpy.exp(-8*(math.pi**2)*t/Rey)
        vexact_x=2*math.pi*numpy.sin(2*math.pi*x[i])*numpy.sin(2*math.pi*y[j])\
        *numpy.exp(-8*(math.pi**2)*t/Rey)
        omegaexact[i][j]=vexact_x-uexact_y
numpy.savetxt('Error.txt',abs(omegaexact-omega))

The second program uses the implicit midpoint rule to do timestepping for the three-dimensional Navier-Stokes equations and it is in listing B . It also takes the Taylor-Green vortex as its initial condition since this has been extensively studied, and so provides a baseline case to compare results against.

( B)

A Matlab program which finds a numerical solution to the 3D Navier Stokes equation Code download

% A program to solve the 3D Navier stokes equations with periodic boundary
% conditions. The program is based on the Orszag-Patterson algorithm as
% documented on pg. 98 of C. Canuto, M.Y. Hussaini, A. Quarteroni and
% T.A. Zhang "Spectral Methods: Evolution to Complex Geometries and
% Applications to Fluid Dynamics" Springer (2007)
%
% The exact solution used to check the numerical method is in
% A. Shapiro "The use of an exact solution of the Navier-Stokes equations
% in a validation test of a three-dimensional nonhydrostatic numerical
% model" Monthly Weather Review vol. 121 pp. 2420-2425 (1993)

clear all; format compact; format short;
set(0,'defaultaxesfontsize',30,'defaultaxeslinewidth',.7,...
    'defaultlinelinewidth',6,'defaultpatchlinewidth',3.7,...
    'defaultaxesfontweight','bold')

% set up grid
tic
Lx = 1; % period 2*pi*L
Ly = 1; % period 2*pi*L
Lz = 1; % period 2*pi*L
Nx = 64; % number of harmonics
Ny = 64; % number of harmonics
Nz = 64; % number of harmonics
Nt = 10; % number of time slices
dt = 0.2/Nt; % time step
t=0; % initial time
Re = 1.0; % Reynolds number
tol=10^(-10);
% initialise variables
x = (2*pi/Nx)*(-Nx/2:Nx/2 -1)'*Lx; % x coordinate
kx = 1i*[0:Nx/2-1 0 -Nx/2+1:-1]'/Lx; % wave vector
y = (2*pi/Ny)*(-Ny/2:Ny/2 -1)'*Ly; % y coordinate
ky = 1i*[0:Ny/2-1 0 -Ny/2+1:-1]'/Ly; % wave vector
z = (2*pi/Nz)*(-Nz/2:Nz/2 -1)'*Lz; % y coordinate
kz = 1i*[0:Nz/2-1 0 -Nz/2+1:-1]'/Lz; % wave vector
[xx,yy,zz]=meshgrid(x,y,z);
[kxm,kym,kzm]=meshgrid(kx,ky,kz);
[k2xm,k2ym,k2zm]=meshgrid(kx.^2,ky.^2,kz.^2);

% initial conditions for Taylor-Green vortex
% theta=0;
% u=(2/sqrt(3))*sin(theta+2*pi/3)*sin(xx).*cos(yy).*cos(zz);
% v=(2/sqrt(3))*sin(theta-2*pi/3)*cos(xx).*sin(yy).*cos(zz);
% w=(2/sqrt(3))*sin(theta)*cos(xx).*cos(yy).*sin(zz);

% exact solution
sl=1; sk=1; sm=1; lamlkm=sqrt(sl.^2+sk.^2+sm.^2);
u=-0.5*(lamlkm*sl*cos(sk*xx).*sin(sl*yy).*sin(sm.*zz)...
            +sm*sk*sin(sk*xx).*cos(sl*yy).*cos(sm.*zz))...
            .*exp(-t*(lamlkm^2)/Re);
        
v=0.5*(lamlkm*sk*sin(sk*xx).*cos(sl*yy).*sin(sm.*zz)...
            -sm*sl*cos(sk*xx).*sin(sl*yy).*cos(sm.*zz))...
            *exp(-t*(lamlkm^2)/Re);
      
w=cos(sk*xx).*cos(sl*yy).*sin(sm*zz)*exp(-t*(lamlkm^2)/Re);

uhat=fftn(u);
vhat=fftn(v);
what=fftn(w);

ux=ifftn(uhat.*kxm);uy=ifftn(uhat.*kym);uz=ifftn(uhat.*kzm);
vx=ifftn(vhat.*kxm);vy=ifftn(vhat.*kym);vz=ifftn(vhat.*kzm);
wx=ifftn(what.*kxm);wy=ifftn(what.*kym);wz=ifftn(what.*kzm);

% calculate vorticity for plotting
omegax=wy-vz; omegay=uz-wx; omegaz=vx-uy;
omegatot=omegax.^2+omegay.^2+omegaz.^2;
figure(1); clf; n=0;
subplot(2,2,1); title(['omega x ',num2str(n*dt)]);
p1 = patch(isosurface(x,y,z,omegax,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.3);
p2 = patch(isocaps(x,y,z,omegax,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.1);
        isonormals(omegax,p1); lighting phong;
xlabel('x'); ylabel('y'); zlabel('z');
axis equal; axis square; view(3); colorbar;
subplot(2,2,2); title(['omega y ',num2str(n*dt)]);
p1 = patch(isosurface(x,y,z,omegay,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.3);
p2 = patch(isocaps(x,y,z,omegay,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.1);
        isonormals(omegay,p1); lighting phong;
xlabel('x'); ylabel('y'); zlabel('z');
axis equal; axis square; view(3); colorbar;
subplot(2,2,3); title(['omega z ',num2str(n*dt)]);
p1 = patch(isosurface(x,y,z,omegaz,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.3);
p2 = patch(isocaps(x,y,z,omegaz,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.1);
        isonormals(omegaz,p1); lighting phong;
xlabel('x'); ylabel('y'); zlabel('z');
axis equal; axis square; view(3); colorbar;
subplot(2,2,4); title(['|omega|^2 ',num2str(n*dt)]);
p1 = patch(isosurface(x,y,z,omegatot,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.3);
p2 = patch(isocaps(x,y,z,omegatot,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.1);
        isonormals(omegatot,p1); lighting phong;
xlabel('x'); ylabel('y'); zlabel('z'); colorbar;
axis equal; axis square; view(3);


for n=1:Nt
    uold=u; uxold=ux; uyold=uy; uzold=uz;
    vold=v; vxold=vx; vyold=vy; vzold=vz;
    wold=w; wxold=wx; wyold=wy; wzold=wz;
    rhsuhatfix=(1/dt+(0.5/Re)*(k2xm+k2ym+k2zm)).*uhat;
    rhsvhatfix=(1/dt+(0.5/Re)*(k2xm+k2ym+k2zm)).*vhat;
    rhswhatfix=(1/dt+(0.5/Re)*(k2xm+k2ym+k2zm)).*what;
    chg=1; t=t+dt;
    while (chg>tol)
        nonlinu=0.25*((u+uold).*(ux+uxold)...
                      +(v+vold).*(uy+uyold)...
                      +(w+wold).*(uz+uzold));
        nonlinv=0.25*((u+uold).*(vx+vxold)...
                      +(v+vold).*(vy+vyold)...
                      +(w+wold).*(vz+vzold));
        nonlinw=0.25*((u+uold).*(wx+wxold)...
                      +(v+vold).*(wy+wyold)...
                      +(w+wold).*(wz+wzold));
        nonlinuhat=fftn(nonlinu);
        nonlinvhat=fftn(nonlinv);
        nonlinwhat=fftn(nonlinw);
        phat=-1.0*(kxm.*nonlinuhat+kym.*nonlinvhat+kzm.*nonlinwhat)...
            ./(k2xm+k2ym+k2zm+0.1^13);
        uhat=(rhsuhatfix-nonlinuhat-kxm.*phat)...
            ./(1/dt - (0.5/Re)*(k2xm+k2ym+k2zm));
        vhat=(rhsvhatfix-nonlinvhat-kym.*phat)...
            ./(1/dt - (0.5/Re)*(k2xm+k2ym+k2zm));
        what=(rhswhatfix-nonlinwhat-kzm.*phat)...
            ./(1/dt - (0.5/Re)*(k2xm+k2ym+k2zm));
        ux=ifftn(uhat.*kxm);uy=ifftn(uhat.*kym);uz=ifftn(uhat.*kzm);
        vx=ifftn(vhat.*kxm);vy=ifftn(vhat.*kym);vz=ifftn(vhat.*kzm);
        wx=ifftn(what.*kxm);wy=ifftn(what.*kym);wz=ifftn(what.*kzm);
        utemp=u; vtemp=v; wtemp=w;
        u=ifftn(uhat); v=ifftn(vhat); w=ifftn(what);
        chg=max(abs(utemp-u))+max(abs(vtemp-v))+max(abs(wtemp-w));
    end
    % calculate vorticity for plotting
    omegax=wy-vz; omegay=uz-wx; omegaz=vx-uy;
    omegatot=omegax.^2+omegay.^2+omegaz.^2;
    figure(1); clf;
    subplot(2,2,1); title(['omega x ',num2str(t)]);
    p1 = patch(isosurface(x,y,z,omegax,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.3);
    p2 = patch(isocaps(x,y,z,omegax,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.1);
        isonormals(omegax,p1); lighting phong;
    xlabel('x'); ylabel('y'); zlabel('z');
    axis equal; axis square; view(3); colorbar;
    subplot(2,2,2); title(['omega y ',num2str(t)]);
    p1 = patch(isosurface(x,y,z,omegay,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.3);
    p2 = patch(isocaps(x,y,z,omegay,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.1);
        isonormals(omegay,p1); lighting phong;
    xlabel('x'); ylabel('y'); zlabel('z');
    axis equal; axis square; view(3); colorbar;
    subplot(2,2,3); title(['omega z ',num2str(t)]);
    p1 = patch(isosurface(x,y,z,omegaz,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.3);
    p2 = patch(isocaps(x,y,z,omegaz,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.1);
        isonormals(omegaz,p1); lighting phong;
    xlabel('x'); ylabel('y'); zlabel('z');
    axis equal; axis square; view(3); colorbar;
    subplot(2,2,4); title(['|omega|^2 ',num2str(t)]);
    p1 = patch(isosurface(x,y,z,omegatot,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.3);
    p2 = patch(isocaps(x,y,z,omegatot,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.1);
        isonormals(omegatot,p1); lighting phong;
    xlabel('x'); ylabel('y'); zlabel('z'); colorbar;
    axis equal; axis square; view(3);
end
toc

uexact=-0.5*(lamlkm*sl*cos(sk*xx).*sin(sl*yy).*sin(sm.*zz)...
            +sm*sk*sin(sk*xx).*cos(sl*yy).*cos(sm.*zz))...
            .*exp(-t*(lamlkm^2)/Re);
        
vexact=0.5*(lamlkm*sk*sin(sk*xx).*cos(sl*yy).*sin(sm.*zz)...
            -sm*sl*cos(sk*xx).*sin(sl*yy).*cos(sm.*zz))...
            *exp(-t*(lamlkm^2)/Re);
      
wexact=cos(sk*xx).*cos(sl*yy).*sin(sm*zz)*exp(-t*(lamlkm^2)/Re);


error= max(max(max(abs(u-uexact))))+...
        max(max(max(abs(v-vexact))))+...
        max(max(max(abs(w-wexact))))

( Bp)

A Python program which finds a numerical solution to the 3D Navier-Stokes equation. Code download

#!/usr/bin/env python
"""
A program to solve the 3D Navier Stokes equations using the
implicit midpoint rule 

The program is based on the Orszag-Patterson algorithm as documented on pg. 98 
of C. Canuto, M.Y. Hussaini, A. Quarteroni and T.A. Zhang 
"Spectral Methods: Evolution to Complex Geometries and Applications to Fluid Dynamics" 
Springer (2007)

The exact solution used to check the numerical method is in
A. Shapiro "The use of an exact solution of the Navier-Stokes equations
in a validation test of a three-dimensional nonhydrostatic numerical
model" Monthly Weather Review vol. 121 pp. 2420-2425 (1993)

More information on visualization can be found on the Mayavi
website, in particular:
http://github.enthought.com/mayavi/mayavi/mlab.html
which was last checked on 6 April 2012

"""

import math
import numpy
from mayavi import mlab
import matplotlib.pyplot as plt
import time


# Grid
Lx=1.0 	    	# Period 2*pi*Lx
Ly=1.0 	    	# Period 2*pi*Ly
Lz=1.0 	    	# Period 2*pi*Lz
Nx=64 	    	# Number of harmonics
Ny=64	    	# Number of harmonics
Nz=64 	    	# Number of harmonics
Nt=20 	    	# Number of time slices
tmax=0.2   	# Maximum time
dt=tmax/Nt  	# time step
t=0.0	    	# initial time
Rey=1.0      	# Reynolds number
tol=0.1**(10) 	# tolerance for fixed point iterations

x = [i*2.0*math.pi*(Lx/Nx) for i in xrange(-Nx/2,1+Nx/2)]
y = [i*2.0*math.pi*(Ly/Ny) for i in xrange(-Ny/2,1+Ny/2)]
z = [i*2.0*math.pi*(Lz/Nz) for i in xrange(-Nz/2,1+Nz/2)]
k_x = (1.0/Lx)*numpy.array([complex(0,1)*n for n in range(0,Nx/2) \
+ [0] + range(-Nx/2+1,0)])
k_y = (1.0/Ly)*numpy.array([complex(0,1)*n for n in range(0,Ny/2) \
+ [0] + range(-Ny/2+1,0)])
k_z = (1.0/Lz)*numpy.array([complex(0,1)*n for n in range(0,Nz/2) \
+ [0] + range(-Nz/2+1,0)])

kxm=numpy.zeros((Nx,Ny,Nz), dtype=complex)
kym=numpy.zeros((Nx,Ny,Nz), dtype=complex)
kzm=numpy.zeros((Nx,Ny,Nz), dtype=complex)
k2xm=numpy.zeros((Nx,Ny,Nz), dtype=float)
k2ym=numpy.zeros((Nx,Ny,Nz), dtype=float)
k2zm=numpy.zeros((Nx,Ny,Nz), dtype=float)
xx=numpy.zeros((Nx,Ny,Nz), dtype=float)
yy=numpy.zeros((Nx,Ny,Nz), dtype=float)
zz=numpy.zeros((Nx,Ny,Nz), dtype=float)


for i in xrange(Nx):
    for j in xrange(Ny):
        for k in xrange(Nz):
            kxm[i,j,k] = k_x[i]
            kym[i,j,k] = k_y[j]
            kzm[i,j,k] = k_z[k]
            k2xm[i,j,k] = numpy.real(k_x[i]**2)
            k2ym[i,j,k] = numpy.real(k_y[j]**2)
            k2zm[i,j,k] = numpy.real(k_z[k]**2)
            xx[i,j,k] = x[i]
            yy[i,j,k] = y[j]
            zz[i,j,k] = z[k]
        

# allocate arrays
u=numpy.zeros((Nx,Ny,Nz), dtype=float)
uold=numpy.zeros((Nx,Ny,Nz), dtype=float)
v=numpy.zeros((Nx,Ny,Nz), dtype=float)
vold=numpy.zeros((Nx,Ny,Nz), dtype=float)
w=numpy.zeros((Nx,Ny,Nz), dtype=float)
wold=numpy.zeros((Nx,Ny,Nz), dtype=float)

uexact=numpy.zeros((Nx,Ny,Nz), dtype=float)
vexact=numpy.zeros((Nx,Ny,Nz), dtype=float)
wexact=numpy.zeros((Nx,Ny,Nz), dtype=float)

utemp=numpy.zeros((Nx,Ny,Nz), dtype=float)
vtemp=numpy.zeros((Nx,Ny,Nz), dtype=float)
wtemp=numpy.zeros((Nx,Ny,Nz), dtype=float)

omegax=numpy.zeros((Nx,Ny,Nz), dtype=float)
omegay=numpy.zeros((Nx,Ny,Nz), dtype=float)
omegaz=numpy.zeros((Nx,Ny,Nz), dtype=float)
omegatot=numpy.zeros((Nx,Ny,Nz), dtype=float)

ux=numpy.zeros((Nx,Ny,Nz), dtype=float)
uy=numpy.zeros((Nx,Ny,Nz), dtype=float)
uz=numpy.zeros((Nx,Ny,Nz), dtype=float)
vx=numpy.zeros((Nx,Ny,Nz), dtype=float)
vy=numpy.zeros((Nx,Ny,Nz), dtype=float)
vz=numpy.zeros((Nx,Ny,Nz), dtype=float)
wx=numpy.zeros((Nx,Ny,Nz), dtype=float)
wy=numpy.zeros((Nx,Ny,Nz), dtype=float)
wz=numpy.zeros((Nx,Ny,Nz), dtype=float)

uxold=numpy.zeros((Nx,Ny,Nz), dtype=float)
uyold=numpy.zeros((Nx,Ny,Nz), dtype=float)
uzold=numpy.zeros((Nx,Ny,Nz), dtype=float)
vxold=numpy.zeros((Nx,Ny,Nz), dtype=float)
vyold=numpy.zeros((Nx,Ny,Nz), dtype=float)
vzold=numpy.zeros((Nx,Ny,Nz), dtype=float)
wxold=numpy.zeros((Nx,Ny,Nz), dtype=float)
wyold=numpy.zeros((Nx,Ny,Nz), dtype=float)
wzold=numpy.zeros((Nx,Ny,Nz), dtype=float)

nonlinu=numpy.zeros((Nx,Ny,Nz), dtype=float)
nonlinv=numpy.zeros((Nx,Ny,Nz), dtype=float)
nonlinw=numpy.zeros((Nx,Ny,Nz), dtype=float)

uhat=numpy.zeros((Nx,Ny,Nz), dtype=complex)
what=numpy.zeros((Nx,Ny,Nz), dtype=complex)
vhat=numpy.zeros((Nx,Ny,Nz), dtype=complex)
phat=numpy.zeros((Nx,Ny,Nz), dtype=complex)
temphat=numpy.zeros((Nx,Ny,Nz), dtype=complex)

rhsuhatfix=numpy.zeros((Nx,Ny,Nz), dtype=complex)
rhswhatfix=numpy.zeros((Nx,Ny,Nz), dtype=complex)
rhsvhatfix=numpy.zeros((Nx,Ny,Nz), dtype=complex)

nonlinuhat=numpy.zeros((Nx,Ny,Nz), dtype=complex)
nonlinvhat=numpy.zeros((Nx,Ny,Nz), dtype=complex)
nonlinwhat=numpy.zeros((Nx,Ny,Nz), dtype=complex)

tdata=numpy.zeros((Nt), dtype=float)

# initial conditions for Taylor-Green Vortex
#theta=0.0
#u=(2.0/(3.0**0.5))*numpy.sin(theta+2.0*math.pi/3.0)*numpy.sin(xx)*numpy.cos(yy)*numpy.cos(zz)
#v=(2.0/(3.0**0.5))*numpy.sin(theta-2.0*math.pi/3.0)*numpy.cos(xx)*numpy.sin(yy)*numpy.cos(zz)
#w=(2.0/(3.0**0.5))*numpy.sin(theta)*numpy.cos(xx)*numpy.cos(yy)*numpy.sin(zz)

# Exact solution
sl=1
sk=1
sm=1
lamlkm=(sl**2.0+sk**2.0+sm**2.0)**0.5 
u=-0.5*(lamlkm*sl*numpy.cos(sk*xx)*numpy.sin(sl*yy)*numpy.sin(sm*zz) \
+sm*sk*numpy.sin(sk*xx)*numpy.cos(sl*yy)*numpy.cos(sm*zz))*numpy.exp(-t*(lamlkm**2.0)/Rey)
v= 0.5*(lamlkm*sk*numpy.sin(sk*xx)*numpy.cos(sl*yy)*numpy.sin(sm*zz) \
-sm*sl*numpy.cos(sk*xx)*numpy.sin(sl*yy)*numpy.cos(sm*zz))*numpy.exp(-t*(lamlkm**2.0)/Rey)
w= numpy.cos(sk*xx)*numpy.cos(sl*yy)*numpy.sin(sm*zz)*numpy.exp(-t*(lamlkm**2.0)/Rey)

uhat=numpy.fft.fftn(u)
vhat=numpy.fft.fftn(v)
what=numpy.fft.fftn(w)

temphat=kxm*uhat
ux=numpy.real(numpy.fft.ifftn(temphat))
temphat=kym*uhat
uy=numpy.real(numpy.fft.ifftn(temphat))
temphat=kzm*uhat
uz=numpy.real(numpy.fft.ifftn(temphat))

temphat=kxm*vhat
vx=numpy.real(numpy.fft.ifftn(temphat))
temphat=kym*vhat
vy=numpy.real(numpy.fft.ifftn(temphat))
temphat=kzm*vhat
vz=numpy.real(numpy.fft.ifftn(temphat))

temphat=kxm*what
wx=numpy.real(numpy.fft.ifftn(temphat))
temphat=kym*what
wy=numpy.real(numpy.fft.ifftn(temphat))
temphat=kzm*what
wz=numpy.real(numpy.fft.ifftn(temphat))

# Calculate vorticity for plotting

omegax=wy-vz
omegay=uz-wx
omegaz=vx-uy
omegatot=omegax**2.0 + omegay**2.0 + omegaz**2.0


#src=mlab.contour3d(xx,yy,zz,u,colormap='jet',opacity=0.1,contours=4)
src = mlab.pipeline.scalar_field(xx,yy,zz,omegatot,colormap='YlGnBu')
mlab.pipeline.iso_surface(src, contours=[omegatot.min()+0.1*omegatot.ptp(), ], \
   colormap='YlGnBu',opacity=0.85)
mlab.pipeline.iso_surface(src, contours=[omegatot.max()-0.1*omegatot.ptp(), ], \
   colormap='YlGnBu',opacity=1.0)
mlab.pipeline.image_plane_widget(src,plane_orientation='z_axes', \
                            slice_index=Nz/2,colormap='YlGnBu', \
                            opacity=0.01)
mlab.pipeline.image_plane_widget(src,plane_orientation='y_axes', \
                            slice_index=Ny/2,colormap='YlGnBu', \
                            opacity=0.01)
mlab.pipeline.image_plane_widget(src,plane_orientation='x_axes', \
                            slice_index=Nx/2,colormap='YlGnBu', \
                            opacity=0.01)
mlab.scalarbar()
mlab.xlabel('x',object=src)
mlab.ylabel('y',object=src)
mlab.zlabel('z',object=src)



t=0.0
tdata[0]=t
#solve pde and plot results
for n in xrange(Nt):
	uold=u
	uxold=ux
	uyold=uy
	uzold=uz
	vold=v
	vxold=vx
	vyold=vy
	vzold=vz
	wold=w
	wxold=wx
	wyold=wy
	wzold=wz
	rhsuhatfix=(1.0/dt + (0.5/Rey)*(k2xm+k2ym+k2zm))*uhat
	rhsvhatfix=(1.0/dt + (0.5/Rey)*(k2xm+k2ym+k2zm))*vhat
	rhswhatfix=(1.0/dt + (0.5/Rey)*(k2xm+k2ym+k2zm))*what
	chg=1.0
	t=t+dt
	while(chg>tol):
		nonlinu=0.25*((u+uold)*(ux+uxold)+(v+vold)*(uy+uyold)+(w+wold)*(uz+uzold))
		nonlinv=0.25*((u+uold)*(vx+vxold)+(v+vold)*(vy+vyold)+(w+wold)*(vz+vzold))
		nonlinw=0.25*((u+uold)*(wx+wxold)+(v+vold)*(wy+wyold)+(w+wold)*(wz+wzold))
		nonlinuhat=numpy.fft.fftn(nonlinu)
		nonlinvhat=numpy.fft.fftn(nonlinv)
		nonlinwhat=numpy.fft.fftn(nonlinw)
		phat=-1.0*(kxm*nonlinuhat+kym*nonlinvhat+kzm*nonlinwhat)/(k2xm+k2ym+k2zm+0.1**13)
		uhat=(rhsuhatfix-nonlinuhat-kxm*phat)/(1.0/dt - (0.5/Rey)*(k2xm+k2ym+k2zm))
		vhat=(rhsvhatfix-nonlinvhat-kym*phat)/(1.0/dt - (0.5/Rey)*(k2xm+k2ym+k2zm))
		what=(rhswhatfix-nonlinwhat-kzm*phat)/(1.0/dt - (0.5/Rey)*(k2xm+k2ym+k2zm))

		temphat=kxm*uhat
		ux=numpy.real(numpy.fft.ifftn(temphat))
		temphat=kym*uhat
		uy=numpy.real(numpy.fft.ifftn(temphat))
		temphat=kzm*uhat
		uz=numpy.real(numpy.fft.ifftn(temphat))

		temphat=kxm*vhat
		vx=numpy.real(numpy.fft.ifftn(temphat))
		temphat=kym*vhat
		vy=numpy.real(numpy.fft.ifftn(temphat))
		temphat=kzm*vhat
		vz=numpy.real(numpy.fft.ifftn(temphat))

		temphat=kxm*what
		wx=numpy.real(numpy.fft.ifftn(temphat))
		temphat=kym*what
		wy=numpy.real(numpy.fft.ifftn(temphat))
		temphat=kzm*what
		wz=numpy.real(numpy.fft.ifftn(temphat))

		utemp=u
		vtemp=v
		wtemp=w
		u=numpy.real(numpy.fft.ifftn(uhat))
		v=numpy.real(numpy.fft.ifftn(vhat))
		w=numpy.real(numpy.fft.ifftn(what))

		chg=numpy.max(abs(u-utemp))+numpy.max(abs(v-vtemp))+numpy.max(abs(w-wtemp))
		
	# calculate vorticity for plotting
	omegax=wy-vz
	omegay=uz-wx
	omegaz=vx-uy
	omegatot=omegax**2.0 + omegay**2.0 + omegaz**2.0
	src.mlab_source.scalars = omegatot
	tdata[n]=t

       
uexact=-0.5*(lamlkm*sl*numpy.cos(sk*xx)*numpy.sin(sl*yy)*numpy.sin(sm*zz) \
+ sm*sk*numpy.sin(sk*xx)*numpy.cos(sl*yy)*numpy.cos(sm*zz))*numpy.exp(-t*(lamlkm**2.0)/Rey)
vexact= 0.5*(lamlkm*sk*numpy.sin(sk*xx)*numpy.cos(sl*yy)*numpy.sin(sm*zz) \
- sm*sl*numpy.cos(sk*xx)*numpy.sin(sl*yy)*numpy.cos(sm*zz))*numpy.exp(-t*(lamlkm**2.0)/Rey)
wexact= numpy.cos(sk*xx)*numpy.cos(sl*yy)*numpy.sin(sm*zz)*numpy.exp(-t*(lamlkm**2.0)/Rey)

err=numpy.max(abs(u-uexact))+numpy.max(abs(v-vexact))+numpy.max(abs(w-wexact))
print(err)

Exercises

Show that for the Taylor-Green vortex solution, the nonlinear terms in the two-dimensional Navier-Stokes equations cancel out exactly.
Write a Matlab program that uses the implicit midpoint rule instead of the Crank-Nicolson method to obtain a solution to the 2D Navier-Stokes equations. Compare your numerical solution with the Taylor-Green vortex solution.
Write a Fortran program that uses the implicit midpoint rule instead of the Crank-Nicolson method to obtain a solution to the 2D Navier-Stokes equations. Compare your numerical solution with the Taylor-Green vortex solution.
Write a Matlab program that uses the Crank-Nicolson method instead of the implicit midpoint rule to obtain a solution to the 3D Navier-Stokes equations.
Write a Fortran program that uses the Crank-Nicolson method instead of the implicit midpoint rule to obtain a solution to the 3D Navier-Stokes equations.
The Navier-Stokes equations as written in eqs. 3 and 4 also satisfy further integral properties. In particular show that
1. ${\frac {\rho }{2}}{\frac {\mathrm {d} }{\mathrm {d} t}}\lVert \omega \rVert _{l^{2}}^{2}=-\mu \lVert \nabla \omega \rVert _{l^{2}}^{2},$ where $\lVert \omega \rVert _{l^{2}}^{2}=\int \int (\omega )^{2}\mathrm {d} x\mathrm {d} y$ and $\lVert \nabla \omega \rVert _{l^{2}}^{2}=\int \int (\nabla \omega )\cdot (\nabla \omega )\mathrm {d} x\mathrm {d} y.$ HINT: multiply the Eq. 3 by $\omega$ then integrate by parts.
2. Show that part (a) implies that $\lVert \omega (t=T)\rVert _{l^{2}}^{2}-\lVert \omega (t=0)\rVert _{l^{2}}^{2}=-\mu \int _{0}^{T}\lVert \nabla \omega \rVert _{l^{2}}^{2}\mathrm {d} t$
3. Part (b) gives a property one can check when integrating the 2D Navier-Stokes equations. We now show that the implicit midpoint rule satisfies an analogous property. Multiply eq. 7 by $0.5(\omega ^{n+1}+\omega ^{n})$ , integrate by parts in space, then sum over time to deduce that $\lVert \omega ^{N}\rVert _{l^{2}}^{2}-\lVert \omega ^{0}\rVert _{l^{2}}^{2}=-{\frac {\mu }{4}}\sum _{n=0}^{N-1}\lVert \nabla (\omega ^{n}+\omega ^{n+1})\rVert _{l^{2}}^{2}\delta t$ .
4. Deduce that this implies that the implicit midpoint rule time stepping method is unconditionally stable, provided the nonlinear terms can be solved for^[17].

Parallel Programs: OpenMP

Rather than give fully parallelized example programs, we instead give a simple implementation in Fortran of the Crank-Nicolson and implicit midpoint rule algorithms for the two-dimensional and three dimensional Navier-Stokes equations that were presented in Matlab. The program for the two-dimensional equations is presented in listing C and an example Matlab script to plot the resulting vorticity fields is in listing D . This program is presented in listing E and an example Matlab script to plot the resulting vorticity fields is in listing F .

( C)

A Fortran program to solve the 2D Navier-Stokes equations Code download

PROGRAM main
!--------------------------------------------------------------------
!
!
! PURPOSE
!
! This program numerically solves the 2D incompressible Navier-Stokes
! on a Square Domain [0,1]x[0,1] using pseudo-spectral methods and
! Crank-Nicolson timestepping. The numerical solution is compared to
! the exact Taylor-Green Vortex Solution.
!
! Periodic free-slip boundary conditions and Initial conditions:
! u(x,y,0)=sin(2*pi*x)cos(2*pi*y)
! v(x,y,0)=-cos(2*pi*x)sin(2*pi*y)
! Analytical Solution:
! u(x,y,t)=sin(2*pi*x)cos(2*pi*y)exp(-8*pi^2*nu*t)
! v(x,y,t)=-cos(2*pi*x)sin(2*pi*y)exp(-8*pi^2*nu*t)
!
! .. Parameters ..
! Nx = number of modes in x - power of 2 for FFT
! Ny = number of modes in y - power of 2 for FFT
! Nt = number of timesteps to take
! Tmax = maximum simulation time
! FFTW_IN_PLACE = value for FFTW input
! FFTW_MEASURE = value for FFTW input
! FFTW_EXHAUSTIVE = value for FFTW input
! FFTW_PATIENT = value for FFTW input
! FFTW_ESTIMATE = value for FFTW input
! FFTW_FORWARD = value for FFTW input
! FFTW_BACKWARD = value for FFTW input
! pi = 3.14159265358979323846264338327950288419716939937510d0
! mu = viscosity
! rho = density
! .. Scalars ..
! i = loop counter in x direction
! j = loop counter in y direction
! n = loop counter for timesteps direction
! allocatestatus = error indicator during allocation
! count = keep track of information written to disk
! iol = size of array to write to disk
! start = variable to record start time of program
! finish = variable to record end time of program
! count_rate = variable for clock count rate
! planfx = Forward 1d fft plan in x
! planbx = Backward 1d fft plan in x
! planfy = Forward 1d fft plan in y
! planby = Backward 1d fft plan in y
! dt = timestep
! .. Arrays ..
! u = velocity in x direction
! uold = velocity in x direction at previous timestep
! v = velocity in y direction
! vold = velocity in y direction at previous timestep
! u_y = y derivative of velocity in x direction
! v_x = x derivative of velocity in y direction
! omeg = vorticity in real space
! omegold = vorticity in real space at previous
! iterate
! omegcheck = store of vorticity at previous iterate
! omegoldhat = 2D Fourier transform of vorticity at previous
! iterate
! omegoldhat_x = x-derivative of vorticity in Fourier space
! at previous iterate
! omegold_x = x-derivative of vorticity in real space
! at previous iterate
! omegoldhat_y = y-derivative of vorticity in Fourier space
! at previous iterate
! omegold_y = y-derivative of vorticity in real space
! at previous iterate
! nlold = nonlinear term in real space
! at previous iterate
! nloldhat = nonlinear term in Fourier space
! at previous iterate
! omeghat = 2D Fourier transform of vorticity
! at next iterate
! omeghat_x = x-derivative of vorticity in Fourier space
! at next timestep
! omeghat_y = y-derivative of vorticity in Fourier space
! at next timestep
! omeg_x = x-derivative of vorticity in real space
! at next timestep
! omeg_y = y-derivative of vorticity in real space
! at next timestep
! .. Vectors ..
! kx = fourier frequencies in x direction
! ky = fourier frequencies in y direction
! kxx = square of fourier frequencies in x direction
! kyy = square of fourier frequencies in y direction
! x = x locations
! y = y locations
! time = times at which save data
! name_config = array to store filename for data to be saved
! fftfx = array to setup x Fourier transform
! fftbx = array to setup y Fourier transform
! REFERENCES
!
! ACKNOWLEDGEMENTS
!
! ACCURACY
!
! ERROR INDICATORS AND WARNINGS
!
! FURTHER COMMENTS
! This program has not been optimized to use the least amount of memory
! but is intended as an example only for which all states can be saved
!--------------------------------------------------------------------
! External routines required
!
! External libraries required
! FFTW3 -- Fast Fourier Transform in the West Library
! (http://www.fftw.org/)
! declare variables

IMPLICIT NONE
INTEGER(kind=4), PARAMETER :: Nx=256	
INTEGER(kind=4), PARAMETER :: Ny=256	
REAL(kind=8), PARAMETER	:: dt=0.00125	
REAL(kind=8), PARAMETER	&
:: pi=3.14159265358979323846264338327950288419716939937510
REAL(kind=8), PARAMETER	:: rho=1.0d0
REAL(kind=8), PARAMETER	:: mu=1.0d0	
REAL(kind=8), PARAMETER	::	tol=0.1d0**10	
REAL(kind=8)	::	chg	
INTEGER(kind=4), PARAMETER	::	nplots=50
REAL(kind=8), DIMENSION(:), ALLOCATABLE	::	time
COMPLEX(kind=8), DIMENSION(:), ALLOCATABLE	:: kx,kxx	
COMPLEX(kind=8), DIMENSION(:), ALLOCATABLE	:: ky,kyy	
REAL(kind=8), DIMENSION(:), ALLOCATABLE	:: x	
REAL(kind=8), DIMENSION(:), ALLOCATABLE	:: y	
COMPLEX(kind=8), DIMENSION(:,:), ALLOCATABLE	:: &
u,uold,v,vold,u_y,v_x,omegold, omegcheck, omeg,&
omegoldhat, omegoldhat_x, omegold_x,&	
omegoldhat_y, omegold_y, nlold, nloldhat,&
omeghat, omeghat_x, omeghat_y, omeg_x, omeg_y,&
nl, nlhat, psihat, psihat_x, psi_x, psihat_y, psi_y
REAL(kind=8),DIMENSION(:,:), ALLOCATABLE	::	uexact_y,vexact_x,omegexact
INTEGER(kind=4)	:: i,j,k,n, allocatestatus, count, iol
INTEGER(kind=4)	::	start, finish, count_rate
INTEGER(kind=4), PARAMETER :: FFTW_IN_PLACE = 8, FFTW_MEASURE = 0, &
FFTW_EXHAUSTIVE = 8, FFTW_PATIENT = 32, &
                     FFTW_ESTIMATE = 64
INTEGER(kind=4),PARAMETER :: FFTW_FORWARD = -1, FFTW_BACKWARD=1	
COMPLEX(kind=8), DIMENSION(:,:), ALLOCATABLE	:: fftfx,fftbx
INTEGER(kind=8)	:: planfxy,planbxy
CHARACTER*100	:: name_config

CALL system_clock(start,count_rate)	
ALLOCATE(time(1:nplots),kx(1:Nx),kxx(1:Nx),ky(1:Ny),kyy(1:Ny),x(1:Nx),y(1:Ny),&
u(1:Nx,1:Ny),uold(1:Nx,1:Ny),v(1:Nx,1:Ny),vold(1:Nx,1:Ny),u_y(1:Nx,1:Ny),&
v_x(1:Nx,1:Ny),omegold(1:Nx,1:Ny),omegcheck(1:Nx,1:Ny), omeg(1:Nx,1:Ny),&
omegoldhat(1:Nx,1:Ny),omegoldhat_x(1:Nx,1:Ny), omegold_x(1:Nx,1:Ny), &
omegoldhat_y(1:Nx,1:Ny),omegold_y(1:Nx,1:Ny), nlold(1:Nx,1:Ny), nloldhat(1:Nx,1:Ny),&
omeghat(1:Nx,1:Ny), omeghat_x(1:Nx,1:Ny), omeghat_y(1:Nx,1:Ny), omeg_x(1:Nx,1:Ny),&
omeg_y(1:Nx,1:Ny), nl(1:Nx,1:Ny), nlhat(1:Nx,1:Ny), psihat(1:Nx,1:Ny), &
psihat_x(1:Nx,1:Ny), psi_x(1:Nx,1:Ny), psihat_y(1:Nx,1:Ny), psi_y(1:Nx,1:Ny),&
uexact_y(1:Nx,1:Ny), vexact_x(1:Nx,1:Ny), omegexact(1:Nx,1:Ny),fftfx(1:Nx,1:Ny),&
fftbx(1:Nx,1:Ny),stat=AllocateStatus)	
IF (AllocateStatus .ne. 0) STOP
PRINT *,'allocated space'

! set up ffts
CALL dfftw_plan_dft_2d_(planfxy,Nx,Ny,fftfx(1:Nx,1:Ny),fftbx(1:Nx,1:Ny),&
     FFTW_FORWARD,FFTW_EXHAUSTIVE)
CALL dfftw_plan_dft_2d_(planbxy,Nx,Ny,fftbx(1:Nx,1:Ny),fftfx(1:Nx,1:Ny),&
FFTW_BACKWARD,FFTW_EXHAUSTIVE)

! setup fourier frequencies in x-direction
DO i=1,1+Nx/2
kx(i)= 2.0d0*pi*cmplx(0.0d0,1.0d0)*REAL(i-1,kind(0d0))
END DO
kx(1+Nx/2)=0.0d0
DO i = 1,Nx/2 -1
kx(i+1+Nx/2)=-kx(1-i+Nx/2)
END DO
DO i=1,Nx
kxx(i)=kx(i)*kx(i)
END DO
DO i=1,Nx
x(i)=REAL(i-1,kind(0d0))/REAL(Nx,kind(0d0))
END DO

! setup fourier frequencies in y-direction
DO j=1,1+Ny/2
ky(j)= 2.0d0*pi*cmplx(0.0d0,1.0d0)*REAL(j-1,kind(0d0))
END DO
ky(1+Ny/2)=0.0d0
DO j = 1,Ny/2 -1
ky(j+1+Ny/2)=-ky(1-j+Ny/2)
END DO
DO j=1,Ny
kyy(j)=ky(j)*ky(j)
END DO
DO j=1,Ny
y(j)=REAL(j-1,kind(0d0))/REAL(Ny,kind(0d0))
END DO
PRINT *,'Setup grid and fourier frequencies'


DO j=1,Ny
DO i=1,Nx
u(i,j)=sin(2.0d0*pi*x(i))*cos(2.0d0*pi*y(j))
v(i,j)=-cos(2.0d0*pi*x(i))*sin(2.0d0*pi*y(j))
u_y(i,j)=-2.0d0*pi*sin(2.0d0*pi*x(i))*sin(2.0d0*pi*y(j))
v_x(i,j)=2.0d0*pi*sin(2.0d0*pi*x(i))*sin(2.0d0*pi*y(j))
omeg(i,j)=v_x(i,j)-u_y(i,j)
END DO
END DO

! Vorticity to Fourier Space
CALL dfftw_execute_dft_(planfxy,omeg(1:Nx,1:Ny),omeghat(1:Nx,1:Ny))	

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
!!!!!!!!!!!!!!!Initial nonlinear term !!!!!!!!!!!!!!!!!!!!!!!!
    !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
! obtain \hat{\omega}_x^{n,k}
DO j=1,Ny
omeghat_x(1:Nx,j)=omeghat(1:Nx,j)*kx(1:Nx)
END DO
! obtain \hat{\omega}_y^{n,k}
DO i=1,Nx
omeghat_y(i,1:Ny)=omeghat(i,1:Ny)*ky(1:Ny)
END DO
! convert to real space
CALL dfftw_execute_dft_(planbxy,omeghat_x(1:Nx,1:Ny),omeg_x(1:Nx,1:Ny))
CALL dfftw_execute_dft_(planbxy,omeghat_y(1:Nx,1:Ny),omeg_y(1:Nx,1:Ny))
! compute nonlinear term in real space
DO j=1,Ny
nl(1:Nx,j)=u(1:Nx,j)*omeg_x(1:Nx,j)/REAL(Nx*Ny,kind(0d0))+&
v(1:Nx,j)*omeg_y(1:Nx,j)/REAL(Nx*Ny,kind(0d0))	
END DO
CALL dfftw_execute_dft_(planfxy,nl(1:Nx,1:Ny),nlhat(1:Nx,1:Ny))
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
time(1)=0.0d0
PRINT *,'Got initial data, starting timestepping'
DO n=1,nplots
chg=1
! save old values
uold(1:Nx,1:Ny)=u(1:Nx,1:Ny)
vold(1:Nx,1:Ny)=v(1:Nx,1:Ny)
omegold(1:Nx,1:Ny)=omeg(1:Nx,1:Ny)
omegcheck(1:Nx,1:Ny)=omeg(1:Nx,1:Ny)	
omegoldhat(1:Nx,1:Ny)=omeghat(1:Nx,1:Ny)
nloldhat(1:Nx,1:Ny)=nlhat(1:Nx,1:Ny)
DO WHILE (chg>tol)
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
!!!!!!!!!!!!!!nonlinear fixed (n,k+1)!!!!!!!!!!!!!!!!!!!!!!!!!
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
! obtain \hat{\omega}_x^{n+1,k}
DO j=1,Ny
omeghat_x(1:Nx,j)=omeghat(1:Nx,j)*kx(1:Nx)
END DO
! obtain \hat{\omega}_y^{n+1,k}
DO i=1,Nx
omeghat_y(i,1:Ny)=omeghat(i,1:Ny)*ky(1:Ny)
END DO
! convert back to real space
CALL dfftw_execute_dft_(planbxy,omeghat_x(1:Nx,1:Ny),omeg_x(1:Nx,1:Ny))
CALL dfftw_execute_dft_(planbxy,omeghat_y(1:Nx,1:Ny),omeg_y(1:Nx,1:Ny))
! calculate nonlinear term in real space
DO j=1,Ny
nl(1:Nx,j)=u(1:Nx,j)*omeg_x(1:Nx,j)/REAL(Nx*Ny,kind(0d0))+&
v(1:Nx,j)*omeg_y(1:Nx,j)/REAL(Nx*Ny,kind(0d0))
END DO
! convert back to fourier
CALL dfftw_execute_dft_(planfxy,nl(1:Nx,1:Ny),nlhat(1:Nx,1:Ny))
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

! obtain \hat{\omega}^{n+1,k+1} with Crank Nicolson timestepping
DO j=1,Ny
omeghat(1:Nx,j)=( (1.0d0/dt+0.5d0*(mu/rho)*(kxx(1:Nx)+kyy(j)))&
*omegoldhat(1:Nx,j) - 0.5d0*(nloldhat(1:Nx,j)+nlhat(1:Nx,j)))/&
(1.0d0/dt-0.5d0*(mu/rho)*(kxx(1:Nx)+kyy(j)))
END DO

! calculate \hat{\psi}^{n+1,k+1}
DO j=1,Ny
psihat(1:Nx,j)=-omeghat(1:Nx,j)/(kxx(1:Nx)+kyy(j))
END DO
psihat(1,1)=0.0d0
psihat(Nx/2+1,Ny/2+1)=0.0d0
psihat(Nx/2+1,1)=0.0d0
psihat(1,Ny/2+1)=0.0d0

! obtain \psi_x^{n+1,k+1} and \psi_y^{n+1,k+1}
DO j=1,Ny
psihat_x(1:Nx,j)=psihat(1:Nx,j)*kx(1:Nx)
END DO
CALL dfftw_execute_dft_(planbxy,psihat_x(1:Nx,1:Ny),psi_x(1:Nx,1:Ny))
DO i=1,Nx
psihat_y(i,1:Ny)=psihat(i,1:Ny)*ky(1:Ny)
END DO
CALL dfftw_execute_dft_(planbxy,psihat_y(1:Ny,1:Ny),psi_y(1:Ny,1:Ny))
DO j=1,Ny
psi_x(1:Nx,j)=psi_x(1:Nx,j)/REAL(Nx*Ny,kind(0d0))
psi_y(1:Nx,j)=psi_y(1:Nx,j)/REAL(Nx*Ny,kind(0d0))
END DO	

! obtain \omega^{n+1,k+1}
CALL dfftw_execute_dft_(planbxy,omeghat(1:Nx,1:Ny),omeg(1:Nx,1:Ny))
DO j=1,Ny
omeg(1:Nx,j)=omeg(1:Nx,j)/REAL(Nx*Ny,kind(0d0))
END DO

! obtain u^{n+1,k+1} and v^{n+1,k+1} using stream function (\psi) in real space
DO j=1,Ny
u(1:Nx,j)=psi_y(1:Nx,j)
v(1:Nx,j)=-psi_x(1:Nx,j)
END DO	

! check for convergence
chg=maxval(abs(omeg-omegcheck))
! saves {n+1,k+1} to {n,k} for next iteration
omegcheck=omeg
END DO
time(n+1)=time(n)+dt
PRINT *,'TIME ',time(n+1)
END DO
DO j=1,Ny
DO i=1,Nx
uexact_y(i,j)=-2.0d0*pi*sin(2.0d0*pi*x(i))*sin(2.0d0*pi*y(j))*&
exp(-8.0d0*mu*(pi**2)*nplots*dt)
vexact_x(i,j)=2.0d0*pi*sin(2.0d0*pi*x(i))*sin(2.0d0*pi*y(j))*&
exp(-8.0d0*mu*(pi**2)*nplots*dt)
omegexact(i,j)=vexact_x(i,j)-uexact_y(i,j)
END DO
END DO
name_config = 'omegafinal.datbin'
INQUIRE(iolength=iol) omegexact(1,1)
OPEN(unit=11,FILE=name_config,form="unformatted", access="direct",recl=iol)
count = 1	
DO j=1,Ny
DO i=1,Nx
WRITE(11,rec=count) REAL(omeg(i,j),KIND(0d0))
count=count+1
END DO
END DO
CLOSE(11)

name_config = 'omegaexactfinal.datbin'
OPEN(unit=11,FILE=name_config,form="unformatted", access="direct",recl=iol)
count = 1	
DO j=1,Ny
DO i=1,Nx
WRITE(11,rec=count) omegexact(i,j)
count=count+1
END DO
END DO
CLOSE(11)

name_config = 'xcoord.dat'
OPEN(unit=11,FILE=name_config,status="UNKNOWN")
REWIND(11)
DO i=1,Nx
WRITE(11,*) x(i)
END DO
CLOSE(11)

name_config = 'ycoord.dat'
OPEN(unit=11,FILE=name_config,status="UNKNOWN")
REWIND(11)
DO j=1,Ny
WRITE(11,*) y(j)
END DO
CLOSE(11)

CALL dfftw_destroy_plan_(planfxy)
CALL dfftw_destroy_plan_(planbxy)
CALL dfftw_cleanup_()

DEALLOCATE(time,kx,kxx,ky,kyy,x,y,&
u,uold,v,vold,u_y,v_x,omegold, omegcheck, omeg, &
omegoldhat, omegoldhat_x, omegold_x,&	
omegoldhat_y, omegold_y, nlold, nloldhat,&
omeghat, omeghat_x, omeghat_y, omeg_x, omeg_y,&
nl, nlhat, psihat, psihat_x, psi_x, psihat_y, psi_y,&
uexact_y,vexact_x,omegexact, &
fftfx,fftbx,stat=AllocateStatus)	
IF (AllocateStatus .ne. 0) STOP
PRINT *,'Program execution complete'
END PROGRAM main

( D)

A Matlab program to plot the vorticity fields and error produced by listing C Code download

% A program to create a plot of the computed results
% from the 2D Matlab Navier-Stokes solver

clear all; format compact, format short,
set(0,'defaultaxesfontsize',14,'defaultaxeslinewidth',.7,...
    'defaultlinelinewidth',2,'defaultpatchlinewidth',3.5);

% Load data
% Get coordinates
X=load('xcoord.dat');
Y=load('ycoord.dat');
% find number of grid points
Nx=length(X);
Ny=length(Y);

% reshape coordinates to allow easy plotting
[xx,yy]=ndgrid(X,Y);

%
% Open file and dataset using the default properties.
%
FILENUM=['omegafinal.datbin'];
FILEEXA=['omegaexactfinal.datbin'];
fidnum=fopen(FILENUM,'r');
[fnamenum,modenum,mformatnum]=fopen(fidnum);
fidexa=fopen(FILEEXA,'r');
[fnameexa,modeexa,mformatexa]=fopen(fidexa);
Num=fread(fidnum,Nx*Ny,'double',mformatnum);
Exa=fread(fidexa,Nx*Ny,'double',mformatexa);
Num=reshape(Num,Nx,Ny);
Exa=reshape(Exa,Nx,Ny);
% close files
fclose(fidnum);
fclose(fidexa);
%
% Plot data on the screen.
%
figure(2);clf;
subplot(3,1,1); contourf(xx,yy,Num);
title(['Numerical Solution ']);
colorbar; axis square;
subplot(3,1,2); contourf(xx,yy,Exa);
title(['Exact Solution ']);
colorbar; axis square;
subplot(3,1,3); contourf(xx,yy,Exa-Num);
title(['Error']);
colorbar; axis square;
drawnow;

( E)

A Fortran program to solve the 3D Navier-Stokes equations Code download

PROGRAM main	
!-----------------------------------------------------------------------------------
!
!
! PURPOSE
!
! This program numerically solves the 3D incompressible Navier-Stokes
! on a Cubic Domain [0,2pi]x[0,2pi]x[0,2pi] using pseudo-spectral methods and
! Implicit Midpoint rule timestepping. The numerical solution is compared to
! an exact solution reported by Shapiro
!
! Analytical Solution:
! u(x,y,z,t)=-0.25*(cos(x)sin(y)sin(z)+sin(x)cos(y)cos(z))exp(-t/Re)
! v(x,y,z,t)= 0.25*(sin(x)cos(y)sin(z)-cos(x)sin(y)cos(z))exp(-t/Re)
! w(x,y,z,t)= 0.5*cos(x)cos(y)sin(z)exp(-t/Re)
!
! .. Parameters ..
! Nx = number of modes in x - power of 2 for FFT
! Ny = number of modes in y - power of 2 for FFT
! Nz = number of modes in z - power of 2 for FFT
! Nt = number of timesteps to take
! Tmax = maximum simulation time
! FFTW_IN_PLACE = value for FFTW input
! FFTW_MEASURE = value for FFTW input
! FFTW_EXHAUSTIVE = value for FFTW input
! FFTW_PATIENT = value for FFTW input
! FFTW_ESTIMATE = value for FFTW input
! FFTW_FORWARD = value for FFTW input
! FFTW_BACKWARD = value for FFTW input
! pi = 3.14159265358979323846264338327950288419716939937510d0
! Re = Reynolds number
! .. Scalars ..
! i = loop counter in x direction
! j = loop counter in y direction
! k = loop counter in z direction
! n = loop counter for timesteps direction
! allocatestatus = error indicator during allocation
! count = keep track of information written to disk
! iol = size of array to write to disk
! start = variable to record start time of program
! finish = variable to record end time of program
! count_rate = variable for clock count rate
! planfxyz = Forward 3d fft plan
! planbxyz = Backward 3d fft plan
! dt = timestep
! .. Arrays ..
! u = velocity in x direction
! v = velocity in y direction
! w = velocity in z direction
! uold = velocity in x direction at previous timestep
! vold = velocity in y direction at previous timestep
! wold = velocity in z direction at previous timestep
! ux = x derivative of velocity in x direction
! uy = y derivative of velocity in x direction
! uz = z derivative of velocity in x direction
! vx = x derivative of velocity in y direction
! vy = y derivative of velocity in y direction
! vz = z derivative of velocity in y direction
! wx = x derivative of velocity in z direction
! wy = y derivative of velocity in z direction
! wz = z derivative of velocity in z direction
! uxold = x derivative of velocity in x direction
! uyold = y derivative of velocity in x direction
! uzold = z derivative of velocity in x direction
! vxold = x derivative of velocity in y direction
! vyold = y derivative of velocity in y direction
! vzold = z derivative of velocity in y direction
! wxold = x derivative of velocity in z direction
! wyold = y derivative of velocity in z direction
! wzold = z derivative of velocity in z direction
! omeg = vorticity in real space
! omegold = vorticity in real space at previous
! iterate
! omegcheck = store of vorticity at previous iterate
! omegoldhat = 2D Fourier transform of vorticity at previous
! iterate
! omegoldhat_x = x-derivative of vorticity in Fourier space
! at previous iterate
! omegold_x = x-derivative of vorticity in real space
! at previous iterate
! omegoldhat_y = y-derivative of vorticity in Fourier space
! at previous iterate
! omegold_y = y-derivative of vorticity in real space
! at previous iterate
! nlold = nonlinear term in real space
! at previous iterate
! nloldhat = nonlinear term in Fourier space
! at previous iterate
! omeghat = 2D Fourier transform of vorticity
! at next iterate
! omeghat_x = x-derivative of vorticity in Fourier space
! at next timestep
! omeghat_y = y-derivative of vorticity in Fourier space
! at next timestep
! omeg_x = x-derivative of vorticity in real space
! at next timestep
! omeg_y = y-derivative of vorticity in real space
! at next timestep
! .. Vectors ..
! kx = fourier frequencies in x direction
! ky = fourier frequencies in y direction
! kz = fourier frequencies in z direction
! x = x locations
! y = y locations
! z = y locations
! time = times at which save data
! name_config = array to store filename for data to be saved
!
! REFERENCES
!
! A. Shapiro " The use of an exact solution of the Navier-Stokes equations
! in a validation test of a three-dimensional nonhydrostatic numerical model"
! Monthly Weather Review vol. 121, 2420-2425, (1993).
!
! ACKNOWLEDGEMENTS
!
! ACCURACY
!
! ERROR INDICATORS AND WARNINGS
!
! FURTHER COMMENTS
!
! This program has not been optimized to use the least amount of memory
! but is intended as an example only for which all states can be saved
!
!--------------------------------------------------------------------------------
! External routines required
!
! External libraries required
! FFTW3 -- Fast Fourier Transform in the West Library
! (http://www.fftw.org/)
IMPLICIT NONE	
    !declare variables
    INTEGER(kind=4), PARAMETER :: Nx=64
INTEGER(kind=4), PARAMETER :: Ny=64
INTEGER(kind=4), PARAMETER :: Nz=64
    INTEGER(kind=4), PARAMETER :: Lx=1
INTEGER(kind=4), PARAMETER :: Ly=1
INTEGER(kind=4), PARAMETER :: Lz=1
INTEGER(kind=4), PARAMETER	:: Nt=20
REAL(kind=8), PARAMETER	:: dt=0.2d0/Nt
REAL(kind=8), PARAMETER	:: Re=1.0d0	
REAL(kind=8), PARAMETER	:: tol=0.1d0**10
REAL(kind=8), PARAMETER	:: theta=0.0d0

REAL(kind=8), PARAMETER	&
:: pi=3.14159265358979323846264338327950288419716939937510d0
REAL(kind=8), PARAMETER	::	ReInv=1.0d0/REAL(Re,kind(0d0))
REAL(kind=8), PARAMETER	:: dtInv=1.0d0/REAL(dt,kind(0d0))
REAL(kind=8)	:: scalemodes,chg,factor
REAL(kind=8), DIMENSION(:), ALLOCATABLE	:: x, y, z, time
COMPLEX(kind=8), DIMENSION(:,:,:), ALLOCATABLE	:: u, v, w,&
ux, uy, uz,&
vx, vy, vz,&
wx, wy, wz,&
uold, uxold, uyold, uzold,&
vold, vxold, vyold, vzold,&
wold, wxold, wyold, wzold,&
  utemp, vtemp, wtemp, temp_r

COMPLEX(kind=8), DIMENSION(:), ALLOCATABLE	:: kx, ky, kz	
COMPLEX(kind=8), DIMENSION(:,:,:), ALLOCATABLE	:: uhat, vhat, what,&
rhsuhatfix, rhsvhatfix,&
rhswhatfix, nonlinuhat,&
nonlinvhat, nonlinwhat,&
phat,temp_c
REAL(kind=8), DIMENSION(:,:,:), ALLOCATABLE :: realtemp
!FFTW variables
INTEGER(kind=4)	:: ierr
INTEGER(kind=4), PARAMETER :: FFTW_IN_PLACE = 8,&
FFTW_MEASURE = 0,&
FFTW_EXHAUSTIVE = 8,&
FFTW_PATIENT = 32,&
                     FFTW_ESTIMATE = 64
INTEGER(kind=4),PARAMETER :: FFTW_FORWARD = -1,&
FFTW_BACKWARD=1	
INTEGER(kind=8)	:: planfxyz,planbxyz

!variables used for saving data and timing
INTEGER(kind=4)	:: count, iol
INTEGER(kind=4)	:: i,j,k,n,t,allocatestatus
INTEGER(kind=4)	:: ind, numberfile
CHARACTER*100	:: name_config
INTEGER(kind=4)	::	start, finish, count_rate

    PRINT *,'Grid:',Nx,'X',Ny,'Y',Nz,'Z'
PRINT *,'dt:',dt	
ALLOCATE(x(1:Nx),y(1:Ny),z(1:Nz),time(1:Nt+1),u(1:Nx,1:Ny,1:Nz),&
  v(1:Nx,1:Ny,1:Nz), w(1:Nx,1:Ny,1:Nz), ux(1:Nx,1:Ny,1:Nz),&
uy(1:Nx,1:Ny,1:Nz), uz(1:Nx,1:Ny,1:Nz), vx(1:Nx,1:Ny,1:Nz),&
vy(1:Nx,1:Ny,1:Nz), vz(1:Nx,1:Ny,1:Nz), wx(1:Nx,1:Ny,1:Nz),&
wy(1:Nx,1:Ny,1:Nz), wz(1:Nx,1:Ny,1:Nz), uold(1:Nx,1:Ny,1:Nz),&
uxold(1:Nx,1:Ny,1:Nz), uyold(1:Nx,1:Ny,1:Nz), uzold(1:Nx,1:Ny,1:Nz),&
vold(1:Nx,1:Ny,1:Nz), vxold(1:Nx,1:Ny,1:Nz), vyold(1:Nx,1:Ny,1:Nz),&
vzold(1:Nx,1:Ny,1:Nz), wold(1:Nx,1:Ny,1:Nz), wxold(1:Nx,1:Ny,1:Nz),&
wyold(1:Nx,1:Ny,1:Nz), wzold(1:Nx,1:Ny,1:Nz), utemp(1:Nx,1:Ny,1:Nz),&
  vtemp(1:Nx,1:Ny,1:Nz), wtemp(1:Nx,1:Ny,1:Nz), temp_r(1:Nx,1:Ny,1:Nz),&
kx(1:Nx),ky(1:Ny),kz(1:Nz),uhat(1:Nx,1:Ny,1:Nz), vhat(1:Nx,1:Ny,1:Nz),&
what(1:Nx,1:Ny,1:Nz), rhsuhatfix(1:Nx,1:Ny,1:Nz),&
  rhsvhatfix(1:Nx,1:Ny,1:Nz), rhswhatfix(1:Nx,1:Ny,1:Nz),&
  nonlinuhat(1:Nx,1:Ny,1:Nz), nonlinvhat(1:Nx,1:Ny,1:Nz),&
  nonlinwhat(1:Nx,1:Ny,1:Nz), phat(1:Nx,1:Ny,1:Nz),temp_c(1:Nx,1:Ny,1:Nz),&
realtemp(1:Nx,1:Ny,1:Nz), stat=AllocateStatus)	
IF (AllocateStatus .ne. 0) STOP
PRINT *,'allocated space'

CALL dfftw_plan_dft_3d_(planfxyz,Nx,Ny,Nz,temp_r(1:Nx,1:Ny,1:Nz),&
temp_c(1:Nx,1:Ny,1:Nz),FFTW_FORWARD,FFTW_ESTIMATE)
CALL dfftw_plan_dft_3d_(planbxyz,Nx,Ny,Nz,temp_c(1:Nx,1:Ny,1:Nz),&
temp_r(1:Nx,1:Ny,1:Nz),FFTW_BACKWARD,FFTW_ESTIMATE)
PRINT *,'Setup 3D FFTs'

! setup fourier frequencies in x-direction
DO i=1,Nx/2+1
kx(i)= cmplx(0.0d0,1.0d0)*REAL(i-1,kind(0d0))/Lx
END DO
kx(1+Nx/2)=0.0d0
DO i = 1,Nx/2 -1
kx(i+1+Nx/2)=-kx(1-i+Nx/2)
END DO
ind=1
DO i=-Nx/2,Nx/2-1
x(ind)=2.0d0*pi*REAL(i,kind(0d0))*Lx/REAL(Nx,kind(0d0))
ind=ind+1
END DO
! setup fourier frequencies in y-direction
DO j=1,Ny/2+1
ky(j)= cmplx(0.0d0,1.0d0)*REAL(j-1,kind(0d0))/Ly
END DO
ky(1+Ny/2)=0.0d0
DO j = 1,Ny/2 -1
ky(j+1+Ny/2)=-ky(1-j+Ny/2)
END DO
ind=1
DO j=-Ny/2,Ny/2-1
y(ind)=2.0d0*pi*REAL(j,kind(0d0))*Ly/REAL(Ny,kind(0d0))
ind=ind+1
END DO
! setup fourier frequencies in z-direction
DO k=1,Nz/2+1
kz(k)= cmplx(0.0d0,1.0d0)*REAL(k-1,kind(0d0))/Lz
END DO
kz(1+Nz/2)=0.0d0
DO k = 1,Nz/2 -1
kz(k+1+Nz/2)=-kz(1-k+Nz/2)
END DO
ind=1
DO k=-Nz/2,Nz/2-1
z(ind)=2.0d0*pi*REAL(k,kind(0d0))*Lz/REAL(Nz,kind(0d0))
ind=ind+1
END DO
scalemodes=1.0d0/REAL(Nx*Ny*Nz,kind(0d0))
PRINT *,'Setup grid and fourier frequencies'

!initial conditions for Taylor-Green vortex
! factor=2.0d0/sqrt(3.0d0)
! DO k=1,Nz; DO j=1,Ny; DO i=1,Nx
! u(i,j,k)=factor*sin(theta+2.0d0*pi/3.0d0)*sin(x(i))*cos(y(j))*cos(z(k))
! END DO; END DO; END DO
! DO k=1,Nz; DO j=1,Ny; DO i=1,Nx
! v(i,j,k)=factor*sin(theta-2.0d0*pi/3.0d0)*cos(x(i))*sin(y(j))*cos(z(k))
! END DO ; END DO ; END DO
! DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
! w(i,j,k)=factor*sin(theta)*cos(x(i))*cos(y(j))*sin(z(k))
! END DO ; END DO ; END DO

! Initial conditions for exact solution
time(1)=0.0d0
factor=sqrt(3.0d0)
DO k=1,Nz; DO j=1,Ny; DO i=1,Nx
u(i,j,k)=-0.5*( factor*cos(x(i))*sin(y(j))*sin(z(k))&
+sin(x(i))*cos(y(j))*cos(z(k)) )*exp(-(factor**2)*time(1)/Re)
END DO; END DO; END DO
DO k=1,Nz; DO j=1,Ny; DO i=1,Nx
v(i,j,k)=0.5*( factor*sin(x(i))*cos(y(j))*sin(z(k))&
-cos(x(i))*sin(y(j))*cos(z(k)) )*exp(-(factor**2)*time(1)/Re)
END DO ; END DO ; END DO
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
w(i,j,k)=cos(x(i))*cos(y(j))*sin(z(k))*exp(-(factor**2)*time(1)/Re)
END DO ; END DO ; END DO

CALL dfftw_execute_dft_(planfxyz,u(1:Nx,1:Ny,1:Nz),uhat(1:Nx,1:Ny,1:Nz))
CALL dfftw_execute_dft_(planfxyz,v(1:Nx,1:Ny,1:Nz),vhat(1:Nx,1:Ny,1:Nz))
CALL dfftw_execute_dft_(planfxyz,w(1:Nx,1:Ny,1:Nz),what(1:Nx,1:Ny,1:Nz))

! derivative of u with respect to x, y, and z
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_c(i,j,k)=uhat(i,j,k)*kx(i)*scalemodes
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planbxyz,temp_c(1:Nx,1:Ny,1:Nz),ux(1:Nx,1:Ny,1:Nz))
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_c(i,j,k)=uhat(i,j,k)*ky(j)*scalemodes
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planbxyz,temp_c(1:Nx,1:Ny,1:Nz),uy(1:Nx,1:Ny,1:Nz))
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_c(i,j,k)=uhat(i,j,k)*kz(k)*scalemodes
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planbxyz,temp_c(1:Nx,1:Ny,1:Nz),uz(1:Nx,1:Ny,1:Nz))

! derivative of v with respect to x, y, and z
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_c(i,j,k)=vhat(i,j,k)*kx(i)*scalemodes
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planbxyz,temp_c(1:Nx,1:Ny,1:Nz),vx(1:Nx,1:Ny,1:Nz))
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_c(i,j,k)=vhat(i,j,k)*ky(j)*scalemodes
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planbxyz,temp_c(1:Nx,1:Ny,1:Nz),vy(1:Nx,1:Ny,1:Nz))
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_c(i,j,k)=vhat(i,j,k)*kz(k)*scalemodes
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planbxyz,temp_c(1:Nx,1:Ny,1:Nz),vz(1:Nx,1:Ny,1:Nz))

! derivative of w with respect to x, y, and z
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_c(i,j,k)=what(i,j,k)*kx(i)*scalemodes
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planbxyz,temp_c(1:Nx,1:Ny,1:Nz),wx(1:Nx,1:Ny,1:Nz))
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_c(i,j,k)=what(i,j,k)*ky(j)*scalemodes
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planbxyz,temp_c(1:Nx,1:Ny,1:Nz),wy(1:Nx,1:Ny,1:Nz))
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_c(i,j,k)=what(i,j,k)*kz(k)*scalemodes
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planbxyz,temp_c(1:Nx,1:Ny,1:Nz),wz(1:Nx,1:Ny,1:Nz))
! save initial data
time(1)=0.0
n=0
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
realtemp(i,j,k)=REAL(wy(i,j,k)-vz(i,j,k),KIND=8)
END DO ; END DO ; END DO
name_config='./data/omegax'
CALL savedata(Nx,Ny,Nz,n,name_config,realtemp)
!omegay
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
realtemp(i,j,k)=REAL(uz(i,j,k)-wx(i,j,k),KIND=8)
END DO ; END DO ; END DO
name_config='./data/omegay'
CALL savedata(Nx,Ny,Nz,n,name_config,realtemp)
!omegaz
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
realtemp(i,j,k)=REAL(vx(i,j,k)-uy(i,j,k),KIND=8)
END DO ; END DO ; END DO
name_config='./data/omegaz'
CALL savedata(Nx,Ny,Nz,n,name_config,realtemp)

DO n=1,Nt
!fixed point
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
uold(i,j,k)=u(i,j,k)
uxold(i,j,k)=ux(i,j,k)
uyold(i,j,k)=uy(i,j,k)
uzold(i,j,k)=uz(i,j,k)
END DO ; END DO ; END DO
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
vold(i,j,k)=v(i,j,k)
vxold(i,j,k)=vx(i,j,k)
vyold(i,j,k)=vy(i,j,k)
vzold(i,j,k)=vz(i,j,k)
END DO ; END DO ; END DO
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
wold(i,j,k)=w(i,j,k)
wxold(i,j,k)=wx(i,j,k)
wyold(i,j,k)=wy(i,j,k)
wzold(i,j,k)=wz(i,j,k)
END DO ; END DO ; END DO
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
rhsuhatfix(i,j,k) = (dtInv+(0.5d0*ReInv)*&
(kx(i)*kx(i)+ky(j)*ky(j)+kz(k)*kz(k)))*uhat(i,j,k)
END DO ; END DO ; END DO
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
rhsvhatfix(i,j,k) = (dtInv+(0.5d0*ReInv)*&
(kx(i)*kx(i)+ky(j)*ky(j)+kz(k)*kz(k)))*vhat(i,j,k)
END DO ; END DO ; END DO
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
rhswhatfix(i,j,k) = (dtInv+(0.5d0*ReInv)*&
(kx(i)*kx(i)+ky(j)*ky(j)+kz(k)*kz(k)))*what(i,j,k)
END DO ; END DO ; END DO
chg=1
DO WHILE (chg .gt. tol)
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_r(i,j,k)=0.25d0*((u(i,j,k)+uold(i,j,k))*(ux(i,j,k)+uxold(i,j,k))&
+(v(i,j,k)+vold(i,j,k))*(uy(i,j,k)+uyold(i,j,k))&
+(w(i,j,k)+wold(i,j,k))*(uz(i,j,k)+uzold(i,j,k)))
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planfxyz,temp_r(1:Nx,1:Ny,1:Nz),nonlinuhat(1:Nx,1:Ny,1:Nz))
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_r(i,j,k)=0.25d0*((u(i,j,k)+uold(i,j,k))*(vx(i,j,k)+vxold(i,j,k))&
+(v(i,j,k)+vold(i,j,k))*(vy(i,j,k)+vyold(i,j,k))&
+(w(i,j,k)+wold(i,j,k))*(vz(i,j,k)+vzold(i,j,k)))
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planfxyz,temp_r(1:Nx,1:Ny,1:Nz),nonlinvhat(1:Nx,1:Ny,1:Nz))
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_r(i,j,k)=0.25d0*((u(i,j,k)+uold(i,j,k))*(wx(i,j,k)+wxold(i,j,k))&
+(v(i,j,k)+vold(i,j,k))*(wy(i,j,k)+wyold(i,j,k))&
+(w(i,j,k)+wold(i,j,k))*(wz(i,j,k)+wzold(i,j,k)))
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planfxyz,temp_r(1:Nx,1:Ny,1:Nz),nonlinwhat(1:Nx,1:Ny,1:Nz))
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
phat(i,j,k)=-1.0d0*( kx(i)*nonlinuhat(i,j,k)&
+ky(j)*nonlinvhat(i,j,k)&
+kz(k)*nonlinwhat(i,j,k))&
/(kx(i)*kx(i)+ky(j)*ky(j)+kz(k)*kz(k)+0.1d0**13)
END DO ; END DO ; END DO

DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
uhat(i,j,k)=(rhsuhatfix(i,j,k)-nonlinuhat(i,j,k)-kx(i)*phat(i,j,k))/&
(dtInv-(0.5d0*ReInv)*(kx(i)*kx(i)+ky(j)*ky(j)+kz(k)*kz(k))) !*scalemodes
END DO ; END DO ; END DO
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
vhat(i,j,k)=(rhsvhatfix(i,j,k)-nonlinvhat(i,j,k)-ky(j)*phat(i,j,k))/&
(dtInv-(0.5d0*ReInv)*(kx(i)*kx(i)+ky(j)*ky(j)+kz(k)*kz(k))) !*scalemodes
END DO ; END DO ; END DO
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
what(i,j,k)=(rhswhatfix(i,j,k)-nonlinwhat(i,j,k)-kz(k)*phat(i,j,k))/&
(dtInv-(0.5d0*ReInv)*(kx(i)*kx(i)+ky(j)*ky(j)+kz(k)*kz(k))) !*scalemodes
END DO ; END DO ; END DO

! derivative of u with respect to x, y, and z
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_c(i,j,k)=uhat(i,j,k)*kx(i)*scalemodes
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planbxyz,temp_c(1:Nx,1:Ny,1:Nz),ux(1:Nx,1:Ny,1:Nz))
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_c(i,j,k)=uhat(i,j,k)*ky(j)*scalemodes
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planbxyz,temp_c(1:Nx,1:Ny,1:Nz),uy(1:Nx,1:Ny,1:Nz))
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_c(i,j,k)=uhat(i,j,k)*kz(k)*scalemodes
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planbxyz,temp_c(1:Nx,1:Ny,1:Nz),uz(1:Nx,1:Ny,1:Nz))

! derivative of v with respect to x, y, and z
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_c(i,j,k)=vhat(i,j,k)*kx(i)*scalemodes
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planbxyz,temp_c(1:Nx,1:Ny,1:Nz),vx(1:Nx,1:Ny,1:Nz))
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_c(i,j,k)=vhat(i,j,k)*ky(j)*scalemodes
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planbxyz,temp_c(1:Nx,1:Ny,1:Nz),vy(1:Nx,1:Ny,1:Nz))
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_c(i,j,k)=vhat(i,j,k)*kz(k)*scalemodes
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planbxyz,temp_c(1:Nx,1:Ny,1:Nz),vz(1:Nx,1:Ny,1:Nz))

! derivative of w with respect to x, y, and z
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_c(i,j,k)=what(i,j,k)*kx(i)*scalemodes
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planbxyz,temp_c(1:Nx,1:Ny,1:Nz),wx(1:Nx,1:Ny,1:Nz))
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_c(i,j,k)=what(i,j,k)*ky(j)*scalemodes
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planbxyz,temp_c(1:Nx,1:Ny,1:Nz),wy(1:Nx,1:Ny,1:Nz))
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
temp_c(i,j,k)=what(i,j,k)*kz(k)*scalemodes
END DO ; END DO ; END DO
CALL dfftw_execute_dft_(planbxyz,temp_c(1:Nx,1:Ny,1:Nz),wz(1:Nx,1:Ny,1:Nz))

DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
utemp(i,j,k)=u(i,j,k)
END DO ; END DO ; END DO
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
vtemp(i,j,k)=v(i,j,k)
END DO ; END DO ; END DO
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
wtemp(i,j,k)=w(i,j,k)
END DO ; END DO ; END DO

CALL dfftw_execute_dft_(planbxyz,uhat(1:Nx,1:Ny,1:Nz),u(1:Nx,1:Ny,1:Nz))
CALL dfftw_execute_dft_(planbxyz,vhat(1:Nx,1:Ny,1:Nz),v(1:Nx,1:Ny,1:Nz))
CALL dfftw_execute_dft_(planbxyz,what(1:Nx,1:Ny,1:Nz),w(1:Nx,1:Ny,1:Nz))

DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
u(i,j,k)=u(i,j,k)*scalemodes
END DO ; END DO ; END DO
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
v(i,j,k)=v(i,j,k)*scalemodes
END DO ; END DO ; END DO
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
w(i,j,k)=w(i,j,k)*scalemodes
END DO ; END DO ; END DO
chg =maxval(abs(utemp-u))+maxval(abs(vtemp-v))+maxval(abs(wtemp-w))
PRINT *,'chg:',chg
END DO
time(n+1)=n*dt
PRINT *,'time',n*dt
!NOTE: utemp, vtemp, and wtemp are just temporary space that can be used
! instead of creating new arrays.
!omegax
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
realtemp(i,j,k)=REAL(wy(i,j,k)-vz(i,j,k),KIND=8)
END DO ; END DO ; END DO
name_config='./data/omegax'
CALL savedata(Nx,Ny,Nz,n,name_config,realtemp)
!omegay
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
realtemp(i,j,k)=REAL(uz(i,j,k)-wx(i,j,k),KIND=8)
END DO ; END DO ; END DO
name_config='./data/omegay'
CALL savedata(Nx,Ny,Nz,n,name_config,realtemp)
!omegaz
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
realtemp(i,j,k)=REAL(vx(i,j,k)-uy(i,j,k),KIND=8)
END DO ; END DO ; END DO
name_config='./data/omegaz'
CALL savedata(Nx,Ny,Nz,n,name_config,realtemp)
END DO

name_config = './data/tdata.dat'
OPEN(unit=11,FILE=name_config,status="UNKNOWN")
REWIND(11)
DO n=1,1+Nt
WRITE(11,*) time(n)
END DO
CLOSE(11)

name_config = './data/xcoord.dat'
OPEN(unit=11,FILE=name_config,status="UNKNOWN")
REWIND(11)
DO i=1,Nx
WRITE(11,*) x(i)
END DO
CLOSE(11)

name_config = './data/ycoord.dat'
OPEN(unit=11,FILE=name_config,status="UNKNOWN")
REWIND(11)
DO j=1,Ny
WRITE(11,*) y(j)
END DO
CLOSE(11)

name_config = './data/zcoord.dat'
OPEN(unit=11,FILE=name_config,status="UNKNOWN")
REWIND(11)
DO k=1,Nz
WRITE(11,*) z(k)
END DO
CLOSE(11)
PRINT *,'Saved data'

! Calculate error in final numerical solution
DO k=1,Nz; DO j=1,Ny; DO i=1,Nx
utemp(i,j,k)=u(i,j,k) -&
(-0.5*( factor*cos(x(i))*sin(y(j))*sin(z(k))&
+sin(x(i))*cos(y(j))*cos(z(k)) )*exp(-(factor**2)*time(Nt+1)/Re))
END DO; END DO; END DO
DO k=1,Nz; DO j=1,Ny; DO i=1,Nx
vtemp(i,j,k)=v(i,j,k) -&
(0.5*( factor*sin(x(i))*cos(y(j))*sin(z(k))&
-cos(x(i))*sin(y(j))*cos(z(k)) )*exp(-(factor**2)*time(Nt+1)/Re))
END DO ; END DO ; END DO
DO k=1,Nz ; DO j=1,Ny ; DO i=1,Nx
wtemp(i,j,k)=w(i,j,k)-&
(cos(x(i))*cos(y(j))*sin(z(k))*exp(-(factor**2)*time(Nt+1)/Re))
END DO ; END DO ; END DO
chg=maxval(abs(utemp))+maxval(abs(vtemp))+maxval(abs(wtemp))
PRINT*,'The error at the final timestep is',chg

CALL dfftw_destroy_plan_(planfxyz)
CALL dfftw_destroy_plan_(planbxyz)
DEALLOCATE(x,y,z,time,u,v,w,ux,uy,uz,vx,vy,vz,wx,wy,wz,uold,uxold,uyold,uzold,&
vold,vxold,vyold,vzold,wold,wxold,wyold,wzold,utemp,vtemp,wtemp,&
temp_r,kx,ky,kz,uhat,vhat,what,rhsuhatfix,rhsvhatfix,&
  rhswhatfix,phat,nonlinuhat,nonlinvhat,nonlinwhat,temp_c,&
realtemp,stat=AllocateStatus)	
IF (AllocateStatus .ne. 0) STOP
PRINT *,'Program execution complete'
END PROGRAM main

( F)

A Matlab program to plot the vorticity fields produced by listing E Code download

% A program to create a plot of the computed results
% from the 3D Fortran Navier-Stokes solver
clear all; format compact; format short;
set(0,'defaultaxesfontsize',30,'defaultaxeslinewidth',.7,...
    'defaultlinelinewidth',6,'defaultpatchlinewidth',3.7,...
    'defaultaxesfontweight','bold')
% Load data
% Get coordinates
tdata=load('./data/tdata.dat');
x=load('./data/xcoord.dat');
y=load('./data/ycoord.dat');
z=load('./data/zcoord.dat');
nplots = length(tdata);

Nx = length(x); Nt = length(tdata);
Ny = length(y); Nz = length(z);

% reshape coordinates to allow easy plotting
[yy,xx,zz]=meshgrid(x,y,z);

for i =1:nplots
    %
    % Open file and dataset using the default properties.
    %
    FILEX=['./data/omegax',num2str(9999999+i),'.datbin'];
    FILEY=['./data/omegay',num2str(9999999+i),'.datbin'];
    FILEZ=['./data/omegaz',num2str(9999999+i),'.datbin'];
    FILEPIC=['./data/pic',num2str(9999999+i),'.jpg'];
    fid=fopen(FILEX,'r');
    [fname,mode,mformat]=fopen(fid);
    omegax=fread(fid,Nx*Ny*Nz,'real*8');
    omegax=reshape(omegax,Nx,Ny,Nz);
    fclose(fid);
    fid=fopen(FILEY,'r');
    [fname,mode,mformat]=fopen(fid);
    omegay=fread(fid,Nx*Ny*Nz,'real*8');
    omegay=reshape(omegay,Nx,Ny,Nz);
    fclose(fid);
    fid=fopen(FILEZ,'r');
    [fname,mode,mformat]=fopen(fid);
    omegaz=fread(fid,Nx*Ny*Nz,'real*8');
    omegaz=reshape(omegaz,Nx,Ny,Nz);
    fclose(fid);
    %
    % Plot data on the screen.
    %
    omegatot=omegax.^2+omegay.^2+omegaz.^2;
    figure(100); clf;
    subplot(2,2,1); title(['omega x ',num2str(tdata(i))]);
    p1 = patch(isosurface(xx,yy,zz,omegax,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.3);
    p2 = patch(isocaps(xx,yy,zz,omegax,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.1);
        isonormals(omegax,p1); lighting phong;
    xlabel('x'); ylabel('y'); zlabel('z');
    axis equal; axis square; view(3); colorbar;
    subplot(2,2,2); title(['omega y ',num2str(tdata(i))]);
    p1 = patch(isosurface(xx,yy,zz,omegay,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.3);
    p2 = patch(isocaps(xx,yy,zz,omegay,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.1);
        isonormals(omegay,p1); lighting phong;
    xlabel('x'); ylabel('y'); zlabel('z');
    axis equal; axis square; view(3); colorbar;
    subplot(2,2,3); title(['omega z ',num2str(tdata(i))]);
    p1 = patch(isosurface(xx,yy,zz,omegaz,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.3);
    p2 = patch(isocaps(xx,yy,zz,omegaz,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.1);
        isonormals(omegaz,p1); lighting phong;
    xlabel('x'); ylabel('y'); zlabel('z');
    axis equal; axis square; view(3); colorbar;
    subplot(2,2,4); title(['|omega|^2 ',num2str(tdata(i))]);
    p1 = patch(isosurface(xx,yy,zz,omegatot,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.3);
    p2 = patch(isocaps(xx,yy,zz,omegatot,.0025),...
            'FaceColor','interp','EdgeColor','none','FaceAlpha',0.1);
        isonormals(omegatot,p1); lighting phong;
    xlabel('x'); ylabel('y'); zlabel('z'); colorbar;
    axis equal; axis square; view(3);
saveas(100,FILEPIC);

end

Exercises

Verify that the program in listing C is second order accurate in time.
Use OpenMP directives to parallelize the example Fortran code for the two-dimensional Navier Stokes equations. Try and make it as efficient as possible.
Write another code which uses threaded FFTW to do the Fast Fourier transforms. This code should have a similar structure to the program listing at http://en.wikibooks.org/wiki/Parallel_Spectral_Numerical_Methods/The_Cubic_Nonlinear_Schrodinger_Equation#equation_G .
Use OpenMP directives to parallelize the example Fortran code for the three-dimensional Navier-Stokes equations in listing E . Try and make it as efficient as possible.
Write another code which uses threaded FFTW to do the Fast Fourier transforms for the three-dimensional Navier-Stokes equations. This code should have a similar structure to the program in listing at http://en.wikibooks.org/wiki/Parallel_Spectral_Numerical_Methods/The_Cubic_Nonlinear_Schrodinger_Equation#equation_J .

Parallel Programs: MPI

For this section, we will use the library 2DECOMP&FFT available from http://www.2decomp.org/index.html. The website includes some examples which indicate how this library should be used, in particular the sample code at http://www.2decomp.org/case_study1.html is a very helpful indication of how one converts a code that uses FFTW to one that uses MPI and the aforementioned library.

The code for this is very similar to the serial code in listing C . For completeness and to allow one to see how to parallelize other programs, we include it. The program uses the library 2DECOMP&FFT. One difference between this program and the serial program is that a subroutine is included to write out data. Since this portion of the calculation is repeated several times, the program becomes more readable when the repeated code is placed in a subroutine. The subroutine is also generic enough that it can be reused in other programs, saving program developers time.

( G)

A parallel MPI Fortran program to solve the 3D Navier-Stokes equations Code download

PROGRAM main	
!-----------------------------------------------------------------------------------
!
!
! PURPOSE
!
! This program numerically solves the 3D incompressible Navier-Stokes
! on a Cubic Domain [0,2pi]x[0,2pi]x[0,2pi] using pseudo-spectral methods and
! Implicit Midpoint rule timestepping. The numerical solution is compared to
! an exact solution reported by Shapiro
!
! Analytical Solution:
! u(x,y,z,t)=-0.25*(cos(x)sin(y)sin(z)+sin(x)cos(y)cos(z))exp(-t/Re)
! v(x,y,z,t)= 0.25*(sin(x)cos(y)sin(z)-cos(x)sin(y)cos(z))exp(-t/Re)
! w(x,y,z,t)= 0.5*cos(x)cos(y)sin(z)exp(-t/Re)
!
! .. Parameters ..
! Nx = number of modes in x - power of 2 for FFT
! Ny = number of modes in y - power of 2 for FFT
! Nz = number of modes in z - power of 2 for FFT
! Nt = number of timesteps to take
! Tmax = maximum simulation time
! FFTW_IN_PLACE = value for FFTW input
! FFTW_MEASURE = value for FFTW input
! FFTW_EXHAUSTIVE = value for FFTW input
! FFTW_PATIENT = value for FFTW input
! FFTW_ESTIMATE = value for FFTW input
! FFTW_FORWARD = value for FFTW input
! FFTW_BACKWARD = value for FFTW input
! pi = 3.14159265358979323846264338327950288419716939937510d0
! Re = Reynolds number
! .. Scalars ..
! i = loop counter in x direction
! j = loop counter in y direction
! k = loop counter in z direction
! n = loop counter for timesteps direction
! allocatestatus = error indicator during allocation
! count = keep track of information written to disk
! iol = size of array to write to disk
! start = variable to record start time of program
! finish = variable to record end time of program
! count_rate = variable for clock count rate
! planfxyz = Forward 3d fft plan
! planbxyz = Backward 3d fft plan
! dt = timestep
! .. Arrays ..
! u = velocity in x direction
! v = velocity in y direction
! w = velocity in z direction
! uold = velocity in x direction at previous timestep
! vold = velocity in y direction at previous timestep
! wold = velocity in z direction at previous timestep
! ux = x derivative of velocity in x direction
! uy = y derivative of velocity in x direction
! uz = z derivative of velocity in x direction
! vx = x derivative of velocity in y direction
! vy = y derivative of velocity in y direction
! vz = z derivative of velocity in y direction
! wx = x derivative of velocity in z direction
! wy = y derivative of velocity in z direction
! wz = z derivative of velocity in z direction
! uxold = x derivative of velocity in x direction
! uyold = y derivative of velocity in x direction
! uzold = z derivative of velocity in x direction
! vxold = x derivative of velocity in y direction
! vyold = y derivative of velocity in y direction
! vzold = z derivative of velocity in y direction
! wxold = x derivative of velocity in z direction
! wyold = y derivative of velocity in z direction
! wzold = z derivative of velocity in z direction
! utemp = temporary storage of u to check convergence
! vtemp = temporary storage of u to check convergence
! wtemp = temporary storage of u to check convergence
! temp_r = temporary storage for untransformed variables
! uhat = Fourier transform of u
! vhat = Fourier transform of v
! what = Fourier transform of w
! rhsuhatfix = Fourier transform of righthand side for u for timestepping
! rhsvhatfix = Fourier transform of righthand side for v for timestepping
! rhswhatfix = Fourier transform of righthand side for w for timestepping
! nonlinuhat = Fourier transform of nonlinear term for u
! nonlinvhat = Fourier transform of nonlinear term for u
! nonlinwhat = Fourier transform of nonlinear term for u
! phat = Fourier transform of nonlinear term for pressure, p
! temp_c = temporary storage for Fourier transforms
! realtemp = Real storage
!
! .. Vectors ..
! kx = fourier frequencies in x direction
! ky = fourier frequencies in y direction
! kz = fourier frequencies in z direction
! x = x locations
! y = y locations
! z = y locations
! time = times at which save data
! name_config = array to store filename for data to be saved
!
! REFERENCES
!
! A. Shapiro " The use of an exact solution of the Navier-Stokes equations
! in a validation test of a three-dimensional nonhydrostatic numerical model"
! Monthly Weather Review vol. 121, 2420-2425, (1993).
!
! ACKNOWLEDGEMENTS
!
! ACCURACY
!
! ERROR INDICATORS AND WARNINGS
!
! FURTHER COMMENTS
!
! This program has not been optimized to use the least amount of memory
! but is intended as an example only for which all states can be saved
!
!--------------------------------------------------------------------------------
! External routines required
!
! External libraries required
! 2DECOMP&FFT -- Fast Fourier Transform in the West Library
! (http://2decomp.org/)

USE decomp_2d
USE decomp_2d_fft
USE decomp_2d_io
USE MPI
IMPLICIT NONE	
! declare variables
    INTEGER(kind=4), PARAMETER :: Nx=256
INTEGER(kind=4), PARAMETER :: Ny=256
INTEGER(kind=4), PARAMETER :: Nz=256
    INTEGER(kind=4), PARAMETER :: Lx=1
INTEGER(kind=4), PARAMETER :: Ly=1
INTEGER(kind=4), PARAMETER :: Lz=1
INTEGER(kind=4), PARAMETER	:: Nt=20
REAL(kind=8), PARAMETER	:: dt=0.05d0/Nt
REAL(kind=8), PARAMETER	:: Re=1.0d0	
REAL(kind=8), PARAMETER	:: tol=0.1d0**10
REAL(kind=8), PARAMETER	:: theta=0.0d0

REAL(kind=8), PARAMETER	&
:: pi=3.14159265358979323846264338327950288419716939937510d0
REAL(kind=8), PARAMETER	::	ReInv=1.0d0/REAL(Re,kind(0d0))
REAL(kind=8), PARAMETER	:: dtInv=1.0d0/REAL(dt,kind(0d0))
REAL(kind=8)	:: scalemodes,chg,factor
REAL(kind=8), DIMENSION(:), ALLOCATABLE	:: x, y, z, time,mychg,allchg
COMPLEX(kind=8), DIMENSION(:,:,:), ALLOCATABLE	:: u, v, w,&
ux, uy, uz,&
vx, vy, vz,&
wx, wy, wz,&
uold, uxold, uyold, uzold,&
vold, vxold, vyold, vzold,&
wold, wxold, wyold, wzold,&
  utemp, vtemp, wtemp, temp_r

COMPLEX(kind=8), DIMENSION(:), ALLOCATABLE	:: kx, ky, kz	
COMPLEX(kind=8), DIMENSION(:,:,:), ALLOCATABLE	:: uhat, vhat, what,&
rhsuhatfix, rhsvhatfix,&
rhswhatfix, nonlinuhat,&
nonlinvhat, nonlinwhat,&
phat,temp_c
REAL(kind=8), DIMENSION(:,:,:), ALLOCATABLE :: realtemp
! MPI and 2DECOMP variables
TYPE(DECOMP_INFO)	:: decomp
INTEGER(kind=MPI_OFFSET_KIND) :: filesize, disp
INTEGER(kind=4)	:: p_row=0, p_col=0, numprocs, myid, ierr	

! variables used for saving data and timing
INTEGER(kind=4)	:: count, iol
INTEGER(kind=4)	:: i,j,k,n,t,allocatestatus
INTEGER(kind=4)	:: ind, numberfile
CHARACTER*100	:: name_config
INTEGER(kind=4)	:: start, finish, count_rate

! initialisation of 2DECOMP&FFT
CALL MPI_INIT(ierr)
CALL MPI_COMM_SIZE(MPI_COMM_WORLD, numprocs, ierr)
CALL MPI_COMM_RANK(MPI_COMM_WORLD, myid, ierr)
! do automatic domain decomposition
CALL decomp_2d_init(Nx,Ny,Nz,p_row,p_col)
! get information about domain decomposition choosen
CALL decomp_info_init(Nx,Ny,Nz,decomp)
! initialise FFT library
CALL decomp_2d_fft_init
IF (myid.eq.0) THEN
PRINT *,'Grid:',Nx,'X',Ny,'Y',Nz,'Z'
PRINT *,'dt:',dt
END IF
ALLOCATE(x(1:Nx),y(1:Ny),z(1:Nz),time(1:Nt+1),mychg(1:3),allchg(1:3),&
u(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
  v(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
  w(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
  ux(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
uy(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
uz(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
vx(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
vy(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
vz(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
wx(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
wy(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
wz(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
uold(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
uxold(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
uyold(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
uzold(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
vold(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
vxold(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
vyold(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
vzold(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
wold(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
wxold(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
wyold(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
wzold(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
utemp(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
  vtemp(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
  wtemp(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
  temp_r(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)),&
kx(1:Nx),ky(1:Ny),kz(1:Nz),&
uhat(decomp%zst(1):decomp%zen(1),&
    decomp%zst(2):decomp%zen(2),&
    decomp%zst(3):decomp%zen(3)),&
vhat(decomp%zst(1):decomp%zen(1),&
    decomp%zst(2):decomp%zen(2),&
    decomp%zst(3):decomp%zen(3)),&
what(decomp%zst(1):decomp%zen(1),&
    decomp%zst(2):decomp%zen(2),&
    decomp%zst(3):decomp%zen(3)),&
rhsuhatfix(decomp%zst(1):decomp%zen(1),&
    decomp%zst(2):decomp%zen(2),&
    decomp%zst(3):decomp%zen(3)),&
  rhsvhatfix(decomp%zst(1):decomp%zen(1),&
    decomp%zst(2):decomp%zen(2),&
    decomp%zst(3):decomp%zen(3)),&
  rhswhatfix(decomp%zst(1):decomp%zen(1),&
    decomp%zst(2):decomp%zen(2),&
    decomp%zst(3):decomp%zen(3)),&
  nonlinuhat(decomp%zst(1):decomp%zen(1),&
    decomp%zst(2):decomp%zen(2),&
    decomp%zst(3):decomp%zen(3)),&
  nonlinvhat(decomp%zst(1):decomp%zen(1),&
    decomp%zst(2):decomp%zen(2),&
    decomp%zst(3):decomp%zen(3)),&
  nonlinwhat(decomp%zst(1):decomp%zen(1),&
    decomp%zst(2):decomp%zen(2),&
    decomp%zst(3):decomp%zen(3)),&
  phat(decomp%zst(1):decomp%zen(1),&
    decomp%zst(2):decomp%zen(2),&
    decomp%zst(3):decomp%zen(3)),&
  temp_c(decomp%zst(1):decomp%zen(1),&
    decomp%zst(2):decomp%zen(2),&
    decomp%zst(3):decomp%zen(3)),&
realtemp(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)), stat=AllocateStatus)	
IF (AllocateStatus .ne. 0) STOP
IF (myid.eq.0) THEN
PRINT *,'allocated space'
END IF	

! setup fourier frequencies in x-direction
DO i=1,Nx/2+1
kx(i)= cmplx(0.0d0,1.0d0)*REAL(i-1,kind(0d0))/Lx
END DO
kx(1+Nx/2)=0.0d0
DO i = 1,Nx/2 -1
kx(i+1+Nx/2)=-kx(1-i+Nx/2)
END DO
ind=1
DO i=-Nx/2,Nx/2-1
x(ind)=2.0d0*pi*REAL(i,kind(0d0))*Lx/REAL(Nx,kind(0d0))
ind=ind+1
END DO
! setup fourier frequencies in y-direction
DO j=1,Ny/2+1
ky(j)= cmplx(0.0d0,1.0d0)*REAL(j-1,kind(0d0))/Ly
END DO
ky(1+Ny/2)=0.0d0
DO j = 1,Ny/2 -1
ky(j+1+Ny/2)=-ky(1-j+Ny/2)
END DO
ind=1
DO j=-Ny/2,Ny/2-1
y(ind)=2.0d0*pi*REAL(j,kind(0d0))*Ly/REAL(Ny,kind(0d0))
ind=ind+1
END DO
! setup fourier frequencies in z-direction
DO k=1,Nz/2+1
kz(k)= cmplx(0.0d0,1.0d0)*REAL(k-1,kind(0d0))/Lz
END DO
kz(1+Nz/2)=0.0d0
DO k = 1,Nz/2 -1
kz(k+1+Nz/2)=-kz(1-k+Nz/2)
END DO
ind=1
DO k=-Nz/2,Nz/2-1
z(ind)=2.0d0*pi*REAL(k,kind(0d0))*Lz/REAL(Nz,kind(0d0))
ind=ind+1
END DO
scalemodes=1.0d0/REAL(Nx*Ny*Nz,kind(0d0))
IF (myid.eq.0) THEN
PRINT *,'Setup grid and fourier frequencies'
END IF	

!initial conditions for Taylor-Green vortex
! factor=2.0d0/sqrt(3.0d0)
! DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
! u(i,j,k)=factor*sin(theta+2.0d0*pi/3.0d0)*sin(x(i))*cos(y(j))*cos(z(k))
! END DO; END DO; END DO
! DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
! v(i,j,k)=factor*sin(theta-2.0d0*pi/3.0d0)*cos(x(i))*sin(y(j))*cos(z(k))
! END DO ; END DO ; END DO
! DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
! w(i,j,k)=factor*sin(theta)*cos(x(i))*cos(y(j))*sin(z(k))
! END DO ; END DO ; END DO

time(1)=0.0d0
factor=sqrt(3.0d0)
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
u(i,j,k)=-0.5*( factor*cos(x(i))*sin(y(j))*sin(z(k))&
+sin(x(i))*cos(y(j))*cos(z(k)) )*exp(-(factor**2)*time(1)/Re)
END DO; END DO; END DO
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
v(i,j,k)=0.5*( factor*sin(x(i))*cos(y(j))*sin(z(k))&
-cos(x(i))*sin(y(j))*cos(z(k)) )*exp(-(factor**2)*time(1)/Re)
END DO ; END DO ; END DO
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
w(i,j,k)=cos(x(i))*cos(y(j))*sin(z(k))*exp(-(factor**2)*time(1)/Re)
END DO ; END DO ; END DO

CALL decomp_2d_fft_3d(u,uhat,DECOMP_2D_FFT_FORWARD)
CALL decomp_2d_fft_3d(v,vhat,DECOMP_2D_FFT_FORWARD)
CALL decomp_2d_fft_3d(w,what,DECOMP_2D_FFT_FORWARD)

! derivative of u with respect to x, y, and z
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
temp_c(i,j,k)=uhat(i,j,k)*kx(i)*scalemodes
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_c,ux,DECOMP_2D_FFT_BACKWARD)	
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
temp_c(i,j,k)=uhat(i,j,k)*ky(j)*scalemodes
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_c,uy,DECOMP_2D_FFT_BACKWARD)	
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
temp_c(i,j,k)=uhat(i,j,k)*kz(k)*scalemodes
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_c,uz,DECOMP_2D_FFT_BACKWARD)	

! derivative of v with respect to x, y, and z
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
temp_c(i,j,k)=vhat(i,j,k)*kx(i)*scalemodes
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_c,vx,DECOMP_2D_FFT_BACKWARD)	
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
temp_c(i,j,k)=vhat(i,j,k)*ky(j)*scalemodes
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_c,vy,DECOMP_2D_FFT_BACKWARD)	
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
temp_c(i,j,k)=vhat(i,j,k)*kz(k)*scalemodes
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_c,vz,DECOMP_2D_FFT_BACKWARD)	

! derivative of w with respect to x, y, and z
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
temp_c(i,j,k)=what(i,j,k)*kx(i)*scalemodes
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_c,wx,DECOMP_2D_FFT_BACKWARD)	
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
temp_c(i,j,k)=what(i,j,k)*ky(j)*scalemodes
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_c,wy,DECOMP_2D_FFT_BACKWARD)	
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
temp_c(i,j,k)=what(i,j,k)*kz(k)*scalemodes
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_c,wz,DECOMP_2D_FFT_BACKWARD)	
! save initial data
n=0
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
realtemp(i,j,k)=REAL(wy(i,j,k)-vz(i,j,k),KIND=8)
END DO ; END DO ; END DO
name_config='./data/omegax'
CALL savedata(Nx,Ny,Nz,n,name_config,realtemp,decomp)
!omegay
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
realtemp(i,j,k)=REAL(uz(i,j,k)-wx(i,j,k),KIND=8)
END DO ; END DO ; END DO
name_config='./data/omegay'
CALL savedata(Nx,Ny,Nz,n,name_config,realtemp,decomp)
!omegaz
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
realtemp(i,j,k)=REAL(vx(i,j,k)-uy(i,j,k),KIND=8)
END DO ; END DO ; END DO
name_config='./data/omegaz'
CALL savedata(Nx,Ny,Nz,n,name_config,realtemp,decomp)
        
!start timer
CALL system_clock(start,count_rate)
DO n=1,Nt
!fixed point
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
uold(i,j,k)=u(i,j,k)
uxold(i,j,k)=ux(i,j,k)
uyold(i,j,k)=uy(i,j,k)
uzold(i,j,k)=uz(i,j,k)
END DO ; END DO ; END DO
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
vold(i,j,k)=v(i,j,k)
vxold(i,j,k)=vx(i,j,k)
vyold(i,j,k)=vy(i,j,k)
vzold(i,j,k)=vz(i,j,k)
END DO ; END DO ; END DO
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
wold(i,j,k)=w(i,j,k)
wxold(i,j,k)=wx(i,j,k)
wyold(i,j,k)=wy(i,j,k)
wzold(i,j,k)=wz(i,j,k)
END DO ; END DO ; END DO
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
                        rhsuhatfix(i,j,k) = (dtInv+(0.5*ReInv)*(kx(i)*kx(i)+ky(j)*ky(j)+kz(k)*kz(k)))*uhat(i,j,k)
END DO ; END DO ; END DO
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
rhsvhatfix(i,j,k) = (dtInv+(0.5*ReInv)*(kx(i)*kx(i)+ky(j)*ky(j)+kz(k)*kz(k)))*vhat(i,j,k)
END DO ; END DO ; END DO
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
rhswhatfix(i,j,k) = (dtInv+(0.5*ReInv)*(kx(i)*kx(i)+ky(j)*ky(j)+kz(k)*kz(k)))*what(i,j,k)
END DO ; END DO ; END DO
chg=1
DO WHILE (chg .gt. tol)
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
temp_r(i,j,k)=0.25d0*((u(i,j,k)+uold(i,j,k))*(ux(i,j,k)+uxold(i,j,k))&
+(v(i,j,k)+vold(i,j,k))*(uy(i,j,k)+uyold(i,j,k))&
+(w(i,j,k)+wold(i,j,k))*(uz(i,j,k)+uzold(i,j,k)))
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_r,nonlinuhat,DECOMP_2D_FFT_FORWARD)
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
temp_r(i,j,k)=0.25d0*((u(i,j,k)+uold(i,j,k))*(vx(i,j,k)+vxold(i,j,k))&
+(v(i,j,k)+vold(i,j,k))*(vy(i,j,k)+vyold(i,j,k))&
+(w(i,j,k)+wold(i,j,k))*(vz(i,j,k)+vzold(i,j,k)))
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_r,nonlinvhat,DECOMP_2D_FFT_FORWARD)
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
temp_r(i,j,k)=0.25d0*((u(i,j,k)+uold(i,j,k))*(wx(i,j,k)+wxold(i,j,k))&
+(v(i,j,k)+vold(i,j,k))*(wy(i,j,k)+wyold(i,j,k))&
+(w(i,j,k)+wold(i,j,k))*(wz(i,j,k)+wzold(i,j,k)))
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_r,nonlinwhat,DECOMP_2D_FFT_FORWARD)
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
phat(i,j,k)=-1.0d0*( kx(i)*nonlinuhat(i,j,k)&
+ky(j)*nonlinvhat(i,j,k)&
+kz(k)*nonlinwhat(i,j,k))&
/(kx(i)*kx(i)+ky(j)*ky(j)+kz(k)*kz(k)+0.1d0**13)
END DO ; END DO ; END DO

DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
uhat(i,j,k)=(rhsuhatfix(i,j,k)-nonlinuhat(i,j,k)-kx(i)*phat(i,j,k))/&
(dtInv-(0.5d0*ReInv)*(kx(i)*kx(i)+ky(j)*ky(j)+kz(k)*kz(k))) !*scalemodes
END DO ; END DO ; END DO
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
vhat(i,j,k)=(rhsvhatfix(i,j,k)-nonlinvhat(i,j,k)-ky(j)*phat(i,j,k))/&
(dtInv-(0.5d0*ReInv)*(kx(i)*kx(i)+ky(j)*ky(j)+kz(k)*kz(k))) !*scalemodes
END DO ; END DO ; END DO
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
what(i,j,k)=(rhswhatfix(i,j,k)-nonlinwhat(i,j,k)-kz(k)*phat(i,j,k))/&
(dtInv-(0.5d0*ReInv)*(kx(i)*kx(i)+ky(j)*ky(j)+kz(k)*kz(k))) !*scalemodes
END DO ; END DO ; END DO

! derivative of u with respect to x, y, and z
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
temp_c(i,j,k)=uhat(i,j,k)*kx(i)*scalemodes
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_c,ux,DECOMP_2D_FFT_BACKWARD)	
DO k=decomp%zst(3),decomp%zen(3); DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
temp_c(i,j,k)=uhat(i,j,k)*ky(j)*scalemodes
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_c,uy,DECOMP_2D_FFT_BACKWARD)	
DO k=decomp%zst(3),decomp%zen(3); DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
temp_c(i,j,k)=uhat(i,j,k)*kz(k)*scalemodes
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_c,uz,DECOMP_2D_FFT_BACKWARD)	

! derivative of v with respect to x, y, and z
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
temp_c(i,j,k)=vhat(i,j,k)*kx(i)*scalemodes
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_c,vx,DECOMP_2D_FFT_BACKWARD)	
DO k=decomp%zst(3),decomp%zen(3); DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
temp_c(i,j,k)=vhat(i,j,k)*ky(j)*scalemodes
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_c,vy,DECOMP_2D_FFT_BACKWARD)	
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
temp_c(i,j,k)=vhat(i,j,k)*kz(k)*scalemodes
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_c,vz,DECOMP_2D_FFT_BACKWARD)	

! derivative of w with respect to x, y, and z
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
temp_c(i,j,k)=what(i,j,k)*kx(i)*scalemodes
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_c,wx,DECOMP_2D_FFT_BACKWARD)	
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
temp_c(i,j,k)=what(i,j,k)*ky(j)*scalemodes
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_c,wy,DECOMP_2D_FFT_BACKWARD)	
DO k=decomp%zst(3),decomp%zen(3) ; DO j=decomp%zst(2),decomp%zen(2) ; DO i=decomp%zst(1),decomp%zen(1)
temp_c(i,j,k)=what(i,j,k)*kz(k)*scalemodes
END DO ; END DO ; END DO
CALL decomp_2d_fft_3d(temp_c,wz,DECOMP_2D_FFT_BACKWARD)	

DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
utemp(i,j,k)=u(i,j,k)
END DO ; END DO ; END DO
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
vtemp(i,j,k)=v(i,j,k)
END DO ; END DO ; END DO
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
wtemp(i,j,k)=w(i,j,k)
END DO ; END DO ; END DO

CALL decomp_2d_fft_3d(uhat,u,DECOMP_2D_FFT_BACKWARD)	
CALL decomp_2d_fft_3d(vhat,v,DECOMP_2D_FFT_BACKWARD)	
CALL decomp_2d_fft_3d(what,w,DECOMP_2D_FFT_BACKWARD)	

DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
u(i,j,k)=u(i,j,k)*scalemodes
END DO ; END DO ; END DO
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
v(i,j,k)=v(i,j,k)*scalemodes
END DO ; END DO ; END DO
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
w(i,j,k)=w(i,j,k)*scalemodes
END DO ; END DO ; END DO
mychg(1) =maxval(abs(utemp-u))
mychg(2) =maxval(abs(vtemp-v))
mychg(3) =maxval(abs(wtemp-w))
CALL MPI_ALLREDUCE(mychg,allchg,3,MPI_DOUBLE_PRECISION,MPI_MAX,MPI_COMM_WORLD,ierr)
chg=allchg(1)+allchg(2)+allchg(3)
IF (myid.eq.0) THEN
PRINT *,'chg:',chg
END IF
END DO
time(n+1)=n*dt

                !goto 5100
IF (myid.eq.0) THEN
PRINT *,'time',n*dt
END IF

                !save omegax, omegay, and omegaz
!omegax
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
realtemp(i,j,k)=REAL(wy(i,j,k)-vz(i,j,k),KIND=8)
END DO ; END DO ; END DO
name_config='./data/omegax'
CALL savedata(Nx,Ny,Nz,n,name_config,realtemp,decomp)
!omegay
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
realtemp(i,j,k)=REAL(uz(i,j,k)-wx(i,j,k),KIND=8)
END DO ; END DO ; END DO
name_config='./data/omegay'
CALL savedata(Nx,Ny,Nz,n,name_config,realtemp,decomp)
!omegaz
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
realtemp(i,j,k)=REAL(vx(i,j,k)-uy(i,j,k),KIND=8)
END DO ; END DO ; END DO
name_config='./data/omegaz'
CALL savedata(Nx,Ny,Nz,n,name_config,realtemp,decomp)
                !5100 continue
END DO
CALL system_clock(finish,count_rate)

        IF (myid.eq.0) then
PRINT *, 'Program took', REAL(finish-start)/REAL(count_rate), 'for main timestepping loop'
        END IF

IF (myid.eq.0) THEN
name_config = './data/tdata.dat'
OPEN(unit=11,FILE=name_config,status="UNKNOWN")
REWIND(11)
DO n=1,1+Nt
WRITE(11,*) time(n)
END DO
CLOSE(11)

name_config = './data/xcoord.dat'
OPEN(unit=11,FILE=name_config,status="UNKNOWN")
REWIND(11)
DO i=1,Nx
WRITE(11,*) x(i)
END DO
CLOSE(11)	

name_config = './data/ycoord.dat'
OPEN(unit=11,FILE=name_config,status="UNKNOWN")
REWIND(11)
DO j=1,Ny
WRITE(11,*) y(j)
END DO
CLOSE(11)

name_config = './data/zcoord.dat'
OPEN(unit=11,FILE=name_config,status="UNKNOWN")
REWIND(11)
DO k=1,Nz
WRITE(11,*) z(k)
END DO
CLOSE(11)
PRINT *,'Saved data'
END IF

! Calculate error in final numerical solution
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
utemp(i,j,k)=u(i,j,k) -&
(-0.5*( factor*cos(x(i))*sin(y(j))*sin(z(k))&
+sin(x(i))*cos(y(j))*cos(z(k)) )*exp(-(factor**2)*time(Nt+1)/Re))
END DO; END DO; END DO
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
vtemp(i,j,k)=v(i,j,k) -&
(0.5*( factor*sin(x(i))*cos(y(j))*sin(z(k))&
-cos(x(i))*sin(y(j))*cos(z(k)) )*exp(-(factor**2)*time(Nt+1)/Re))
END DO ; END DO ; END DO
DO k=decomp%xst(3),decomp%xen(3); DO j=decomp%xst(2),decomp%xen(2); DO i=decomp%xst(1),decomp%xen(1)
wtemp(i,j,k)=w(i,j,k)-&
(cos(x(i))*cos(y(j))*sin(z(k))*exp(-(factor**2)*time(Nt+1)/Re))
END DO ; END DO ; END DO
mychg(1) = maxval(abs(utemp))
mychg(2) = maxval(abs(vtemp))
mychg(3) = maxval(abs(wtemp))
CALL MPI_ALLREDUCE(mychg,allchg,3,MPI_DOUBLE_PRECISION,MPI_MAX,MPI_COMM_WORLD,ierr)
chg=allchg(1)+allchg(2)+allchg(3)
IF (myid.eq.0) THEN
PRINT*,'The error at the final timestep is',chg
END IF

        ! clean up
   CALL decomp_2d_fft_finalize
   CALL decomp_2d_finalize

DEALLOCATE(x,y,z,time,mychg,allchg,u,v,w,ux,uy,uz,vx,vy,vz,wx,wy,wz,uold,uxold,uyold,uzold,&
vold,vxold,vyold,vzold,wold,wxold,wyold,wzold,utemp,vtemp,wtemp,&
temp_r,kx,ky,kz,uhat,vhat,what,rhsuhatfix,rhsvhatfix,&
  rhswhatfix,phat,nonlinuhat,nonlinvhat,nonlinwhat,temp_c,&
realtemp,stat=AllocateStatus)	
IF (AllocateStatus .ne. 0) STOP
IF (myid.eq.0) THEN
PRINT *,'Program execution complete'
END IF
CALL MPI_FINALIZE(ierr)	

END PROGRAM main

( H)

A subroutine to save real array data for the parallel MPI Fortran program to solve the 3D Navier-Stokes equations Code download

SUBROUTINE savedata(Nx,Ny,Nz,plotnum,name_config,field,decomp)
!--------------------------------------------------------------------
!
!
! PURPOSE
!
! This subroutine saves a three dimensional real array in binary
! format
!
! INPUT
!
! .. Scalars ..
! Nx = number of modes in x - power of 2 for FFT
! Ny = number of modes in y - power of 2 for FFT
! Nz = number of modes in z - power of 2 for FFT
! plotnum = number of plot to be made
! .. Arrays ..
! field = real data to be saved
! name_config = root of filename to save to
!
! .. Output ..
! plotnum = number of plot to be saved
! .. Special Structures ..
! decomp = contains information on domain decomposition
! see http://www.2decomp.org/ for more information
! LOCAL VARIABLES
!
! .. Scalars ..
! i = loop counter in x direction
! j = loop counter in y direction
! k = loop counter in z direction
! count = counter
! iol = size of file
! .. Arrays ..
! number_file = array to hold the number of the plot
!
! REFERENCES
!
! ACKNOWLEDGEMENTS
!
! ACCURACY
!
! ERROR INDICATORS AND WARNINGS
!
! FURTHER COMMENTS
!--------------------------------------------------------------------
! External routines required
!
! External libraries required
! 2DECOMP&FFT -- Domain decomposition and Fast Fourier Library
! (http://www.2decomp.org/index.html)
! MPI library
USE decomp_2d
USE decomp_2d_fft
USE decomp_2d_io
IMPLICIT NONE
INCLUDE 'mpif.h'
! Declare variables
INTEGER(KIND=4), INTENT(IN)	:: Nx,Ny,Nz
INTEGER(KIND=4), INTENT(IN)	:: plotnum
TYPE(DECOMP_INFO), INTENT(IN)	:: decomp
REAL(KIND=8), DIMENSION(decomp%xst(1):decomp%xen(1),&
    decomp%xst(2):decomp%xen(2),&
    decomp%xst(3):decomp%xen(3)), &
    INTENT(IN) :: field
CHARACTER*100, INTENT(IN)	:: name_config
INTEGER(kind=4)	:: i,j,k,iol,count,ind
CHARACTER*100	:: number_file

! create character array with full filename
ind = index(name_config,' ') - 1
WRITE(number_file,'(i0)') 10000000+plotnum
number_file = name_config(1:ind)//number_file
ind = index(number_file,' ') - 1
number_file = number_file(1:ind)//'.datbin'	
CALL decomp_2d_write_one(1,field,number_file)

END SUBROUTINE savedata

( I)

A makefile to compile the parallel MPI Fortran program to solve the 3D Navier-Stokes equations Code download

COMPILER = mpif90
decompdir= ../2decomp_fft
FLAGS = -O0

DECOMPLIB = -I${decompdir}/include -L${decompdir}/lib -l2decomp_fft
LIBS = #-L${FFTW_LINK} -lfftw3 -lm
SOURCES = NavierStokes3DfftIMR.f90 savedata.f90

ns3d: $(SOURCES)
${COMPILER} -o ns3d $(FLAGS) $(SOURCES) $(LIBS) $(DECOMPLIB)

clean:
rm -f *.o
rm -f *.mod
clobber:
rm -f ns3d

Other publicly available programs for solving the Navier-Stokes Equations

There are several other publicly available Fast Fourier Transform based programs for solving the Navier Stokes equations. These include:

HIT 3d available from http://code.google.com/p/hit3d/

Tarang available from http://turbulencehub.org/index.php/codes/tarang/

SpectralDNS available from https://github.com/spectralDNS

and

Turbo available from http://aqua.ulb.ac.be/home/?page_id=50

Exercises

Use 2DECOMP&FFT to write a two dimensional Navier-Stokes solver. The library is built to do three dimensional FFTs, however by choosing one of the arrays to have only one entry, the library can then do two dimensional FFTs on a distributed memory machine.
Uecker^[18] describes the expected power law scaling for the power spectrum of the enstrophy^[19] in two dimensional isotropic turbulence. Look up Uecker^[20] and then try to produce numerical data which verifies the power scaling law over as many decades of wavenumber space as are feasible on the computational resources you have access to. A recent overview of research work in this area can be found in Boffetta and Ecke^[21]. Fornberg^[22] discusses how to calculate power spectra.
If we set $\mu =0$ the Navier Stokes equations become the Euler equations. Try to use the implicit midpoint rule and/or the Crank-Nicolson methods to simulate the Euler equations in either two or three dimensions. See if you can find good iterative schemes to do this, you may need to use Newton iteration. An introduction to the Euler equations is in Majda and Bertozzi^[23].
The Taylor-Green vortex flow initial conditions have been studied as a possible flow that could have a blow up in the maximum value of the absolute value of the gradient of the velocity at a point for the Euler and Navier-Stokes equations. In many of these simulations, symmetries have been used to get higher effective resolutions, see for example Cichowlas and Brachet^[24]. Consider using the Kida-Pelz and/or Taylor-Green vortex as initial conditions for the Euler equations and adding non-symmetric perturbations. If you are unable to get an implicit time-stepping scheme to work, consider using an explicit scheme such as a Runge-Kutta method. How does the flow evolve in comparison to previous studies in the literature? An introduction to blow up for the Euler equations is in Majda and Bertozzi^[25].
The three dimensional program we have written is not the most efficient since one can use a real to complex transform to halve the work done. Implement a real to complex transform in one of the Navier-Stokes programs.
The programs we have written can also introduce some aliasing errors. By reading a book on spectral methods, such as Canuto et al.^[26]^[27], find out what aliasing errors are. Explain why the strategy explained in Johnstone^[28] can reduce aliasing errors.
See if you can find other open source Fast Fourier Transform based solvers for the Naiver-Stokes equations and add them to the list above.

Notes

↑ Tritton (1988)
↑ Doering and Gibbon (1995)
↑ Gallavotti (2002)
↑ Uecker
↑ Canuto et al (2006)
↑ Canuto et al (2007)
↑ Tritton (1988)
↑ Temam (2001)
↑ Gallavotti (2002)
↑ Doering and Gibbon (1995)
↑ Orszag and Patterson (1972)
↑ Canuto et al (2006)
↑ Canuto et al (2007)
↑ Shapiro (1993)
↑ Majda and Bertozzi (2002)
↑ Laizet and Lamballais (2009)
↑ We have not demonstrated convergence of the spatial discretization, so this result assumes that the spatial discretization has not been done.
↑ Uecker (2009)
↑ The enstrophy is the square of the vorticity.
↑ Uecker (2009)
↑ Boffetta and Ecke (2012)
↑ Fornberg (1977)
↑ Majda and Bertozzi (2002)
↑ Cichowlas and Brachet (2005)
↑ Majda and Bertozzi (2012)
↑ Canuto et al (2006)
↑ Canuto et al (2007)
↑ Johnstone (2012)

References

Boffetta, G.; Ecke, R.E. (2012). "Two-Dimensional Turbulence". Annual Review of Fluid Mechanics. 44: 427–451.

Canuto, C.; Hussaini, M.Y.; Quarteroni, A.; Zang, T.A. (2006). Spectral Methods: Fundamentals in Single Domains. Springer.

Canuto, C.; Hussaini, M.Y.; Quarteroni, A.; Zang, T.A. (2007). Spectral Methods: Evolution to Complex Geometries and Applications to Fluid Dynamics. Springer.

Cichowlas, C.; Brachet, M.-E. (2005). "Evolution of complex singularities in Kida-Pelz and Taylor-Green inviscid flows". Fluid Dynamics Research. 36: 239–248.

Doering, C.R.; Gibbon, J.D. (1995). Applied Analysis of the Navier-Stokes Equations. Cambridge University Press.

Fornberg, B. (1977). "A numerical study of 2-D turbulence". Journal of Computational Physics. 25: 1–31.

Gallavotti, G. (2002). Foundations of Fluid Dynamics. Springer.

Gottlieb, D.; Orszag, S.A. (1977). Numerical Analysis of Spectral Methods: Theory and Applications. SIAM.

Johnstone, R. (2012). "Improved Scaling for Direct Numerical Simulations of Turbulence". HECTOR distributed Computational Science and Engineering Report. {{cite web}}: Cite has empty unknown parameter: |coauthors= (help)

Laizet, S.; Lamballais, E. (2009). "High-order compact schemes for incompressible flows: A simple and efficient method with quasi-spectral accuracy". Journal of Computational Physics. 238: 5989–6015.

Bertozzi, A.L. (2002). Vorticity and Incompressible Flow. Cambridge University Press.

Orszag, S.A.; Patterson Jr., G.S. (1979). Physical Review Letters. 28 (2): 76–79. {{cite journal}}: Missing or empty |title= (help)

Peyret, R. (2002). Spectral Methods for Incompressible Viscous Flow. Springer.

Shapiro, A (1993). "The use of an exact solution of the Navier-Stokes equations in a validation test of a three-dimensional nonhydrostatic numerical model". Monthly Weather Review. 121: 2420–2425. {{cite journal}}: Cite has empty unknown parameter: |coauthors= (help)

Temam, R. (2001). Navier-Stokes Equations (Third ed.). American Mathematical Society.

Tritton, D.J. (1988). Physical Fluid Dynamics. Clarendon Press.

Uecker, H. A short ad hoc introduction to spectral methods for parabolic PDE and the Navier-Stokes equations. {{cite book}}: Cite has empty unknown parameter: |coauthors= (help)

[1] Tritton (1988)

[2] Doering and Gibbon (1995)

[3] Gallavotti (2002)

[4] Uecker

[5] Canuto et al (2006)

[6] Canuto et al (2007)

[7] Tritton (1988)

[8] Temam (2001)

[9] Gallavotti (2002)

[10] Doering and Gibbon (1995)

[11] Orszag and Patterson (1972)

[12] Canuto et al (2006)

[13] Canuto et al (2007)

[14] Shapiro (1993)

[15] Majda and Bertozzi (2002)

[16] Laizet and Lamballais (2009)

[17] We have not demonstrated convergence of the spatial discretization, so this result assumes that the spatial discretization has not been done.

[18] Uecker (2009)

[19] The enstrophy is the square of the vorticity.

[20] Uecker (2009)

[21] Boffetta and Ecke (2012)

[22] Fornberg (1977)

[23] Majda and Bertozzi (2002)

[24] Cichowlas and Brachet (2005)

[25] Majda and Bertozzi (2012)

[26] Canuto et al (2006)

[27] Canuto et al (2007)

[28] Johnstone (2012)

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