Week 7 - Simulation of a 1D Super-sonic nozzle flow simulation using Macormack Method

AIM: The main goal of this challenge is to simulate the isentropic flow through a quasi 1D subsonic-supersonic nozzle by deriving both the conservative and non-conservative form of governing equations and solve them by using the MacCormacks's techniques using MATLAB.

Problem Statement:

Determine the steady-state temperature distribution for the flow-field variables and to investigate the difference between the two forms of governing equations by comparing their solutions along with the plots stated below.

1. Steady-State distribution of primitive variable inside the nozzle.
2. Time-wise variation of the primitive variable.
3. Variation of Mass rate distribution inside the nozzle at different time steps during the time-marching process.
4. Comparision of Normalized mass flow rate distributions of both forms.     

Theory:

    The flow at the inlet to the nozzle arrives from the reservoir where the pressure and temperature are denoted by Po and to. The cross-sectional area of the reservoir is very large and hence the fluid velocity is very low. The flow expands from subsonic to supersonic flow, whereas the velocity of the fluid at the throat is equal to the sonic velocity. Any numerical solution of isentropic flow though a quasi 1D subsonic-supersonic nozzle is unreasonable, while analytic solution exists for these kind of problems. However we are trying here to establish the broadened capability of CFD in various streams rather in representing the approximated form of anayltic solution. Here, we implement the numerical solution with Conservative and Non-Conservative forms.

                                   

Governing Equations are marched in terms of PDE for both forms in order to use Time Marching solution for the problem. These forms represent in numerical aspect only, if we analytic all the methods are same. The integral form of governing equations should be converted into corresponding PDE form such that the PDE can be numerically solved to obtain the primitive variables such as velocity, density, temperature, pressure and so on. A control volume of negligible dimensions(tending to zero) is selected and the above integral form of governing equation is applied to CV and solved to obtain both conservative and non-conservative form of PDE.    

Non Conservative Form:

Conservative Form:

 

 

Non Dimensional Quantities:

Also as part of the problem setup we represent quantites in terms of non-dimensional quantities.

The prime in the above equations represents the non-dimensional form of governing equation. Non-dimensional form of Navier stokes equation can ease the analysis of the problem and it reduces the number of parameters. The difference between the conservative and non-conservative form of governing equation is that both forms give the same analytical solution but the different numerical output. Conservative form provides accurate results and it can provide better results in the presence of shocks or discontinuities. 

Steps for solving the Nozzle flow problem:

•  Meshing:

The given 1D domain is divided into n number of elements. For Nozzle flow problem the length of nozzle is chosen as 3 and the length is divided into 30 elements.

•  Discretization:  

The PDE is discretized and solved for the points in the domain. Maccormack method is used for discretizing the equation. Maccormack method gives better results for the hyperbolic equation and it is also called as a shock-capturing method. These methods can provide stable solutions in the presence of shock. Hence they are used in nozzle flow problems. In Maccormack method combination of both forward and backward differencing schemes can be used to solve for the primitive variables. Non-conservative and conservative form of governing equations are solved by using this method.

• Solve:

1. Initial Condition:
2. Boundry Condition:

                                               

Nozzle diagram: Since the problem setup is 1D, we consider only distribution in x-axis. Here Nozzle can be split into two sections

• Convergent Section 
• Divergent Section

                                           

MacCarmack method:

To discretize the numerical solution we use the technique called MacCarmack method. The MacCormack method is a variation of the two-step Lax-Wendroff Scheme but is much simpler in application.

The application of MacCormack method proceeds in two steps; a predictor step which is followed by a corrector step.

Steps involved in Maccormack method

• Predictor step(forward differencing)
• Solution update
• Corrector step( Backward differencing)
• Determining the average of the time derivative
•  Final solution update 

• Predictor step: In the predictor step, a "provisional" value of  at time level  (denoted by ) is estimated obtained by replacing the spatial and temporal derivatives in the previous first order equation using Forward Difference Scheme.  is used for Timestep.
• Corrector step: In the corrector step, the predicted value  is corrected according to the equation. Note that the corrector step uses Backward Difference Scheme for spatial derivative. The time-step used in the corrector step is  in contrast to the  used in the predictor step.

Main Program:

clear all
close all
clc

%solving 1D supersonic nozzle flow

%inputs
%No. of grid points    
n = 31;             
gamma = 1.4;
x = linspace(0,3,n);
dx = x(2) - x(1);

%No. of time step
nt = 1400;

%Courant Number
C = 0.5;            


% Non Conservative Form
tic;
[Mass_flow_rate_NC, Pressure_NC, Mach_number_NC, rho_NC, v_NC, T_NC, rho_throat_NC, v_throat_NC, T_throat_NC, Mass_flow_rate_throat_NC, Pressure_throat_NC, Mach_number_throat_NC] = Non_conservative_form(x, dx, n, gamma, nt, C);
Time_elapsed_NC = toc;
fprintf('Time Elasped for Non Conservative form: %0.4f', Time_elapsed_NC);
hold on

%plot 
%Timestep variation of properties at throat area in Non Conservative form
figure(2)

%Density
subplot(4,1,1)
plot(linspace(1,nt,nt),rho_throat_NC,'color','k')
ylabel('Density')
legend({'Density at throat'});
axis([0 1400 0 1.3]);
grid minor;
title('Timestep variation at throat area - NON CONSERVATIVE FORM')

%Temperature
subplot(4,1,2)
plot(linspace(1,nt,nt),T_throat_NC,'color','r')
ylabel('Temperature')
legend({'Temperature at throat'});
axis([0 1400 0.6 1]);
grid on;

%Pressure
subplot(4,1,3)
plot(linspace(1,nt,nt),Pressure_throat_NC,'color','c')
ylabel('Pressure')
legend({'Pressure at throat'});
axis([0 1400 0.4 1.1]);
grid on

%Mach Number
subplot(4,1,4)
plot(linspace(1,nt,nt),Mach_number_throat_NC,'color','m')
xlabel('Timesteps')
ylabel('Mach Number')
legend({'Mach Number at throat'});
axis([0 1400 0.6 1.4]);
grid on


%Steady state simulation for primitve values for Non Conservative form
figure(3);
%Density

subplot(4,1,1);
plot(x,rho_NC,'color','y')
ylabel('Density')
legend({'Density'});
axis([0 3 0 1])
grid minor;
title('Variation of Flow Rate Distribution - NON CONSERVATIVE')

%Temperature
subplot(4,1,2);
plot(x,T_NC,'color','c')
ylabel('Temperature')
legend({'Temperature'});
axis([0 3 0 1])
grid on

%Pressure
subplot(4,1,3);
plot(x,Pressure_NC,'color','g')
ylabel('Pressure')
legend({'Pressure'});
axis([0 3 0 1])
grid on

%Mach number
subplot(4,1,4);
plot(x,Mach_number_NC,'color','y')
xlabel('Nozzle Length')
ylabel('Mach number')
legend({'Mach number'});
axis([0 3 0 4])
grid on


%conservative form function
tic;
[Mass_flow_rate_C, Pressure_C, Mach_number_C, rho_C, v_C, T_C, rho_throat_C, v_throat_C, T_throat_C, Mass_flow_rate_throat_C, Pressure_throat_C, Mach_number_throat_C] = Conservative_form(x, dx, n, gamma, nt, C);
Time_elasped_C = toc;
fprintf('Time Elasped for Conservative form: %0.4f', Time_elasped_C);

%plot
%Timestep variation of properties at throat area in Conservative form
figure(5)

%Density
subplot(4,1,1)
plot(rho_throat_C,'color','m')
ylabel('Density')
legend({'Density at throat'});
axis([0 1400 0 1]);
grid on
title('Timestep variation at throat area - CONSERVATIVE FORM')

%Temperature
subplot(4,1,2)
plot(T_throat_C,'color','c')
ylabel('Temperature')
legend({'Temperature at throat'});
axis([0 1400 0.6 1]);
grid on

%Pressure
subplot(4,1,3)
plot(Pressure_throat_C,'color','g')
ylabel('Pressure')
legend({'Pressure at throat'});
axis([0 1400 0.2 0.8]);
grid on

%Mach Number
subplot(4,1,4)
plot(Mach_number_throat_C,'color','y')
xlabel('Timesteps')
ylabel('Mach Number')
legend({'Mach Number at throat'});
axis([0 1400 0.6 1.4]);
grid on


%Steady state simulation for primitve values for Non Conservative form
figure(6);

%Density 
subplot(4,1,1);
plot(x,rho_C,'color','m')
ylabel('Density')
legend({'Density'});
axis([0 3 0 1])
grid on
title('Variation of Flow Rate Distribution - CONSERVATIVE FORM')

%Temperature 
subplot(4,1,2);
plot(x,T_C,'color','c')
ylabel('Temperature')
legend({'Temperature'});
axis([0 3 0 1])
grid on

%Pressure
subplot(4,1,3);
plot(x,Pressure_C,'color','g')
ylabel('Pressure')
legend({'Pressure'});
axis([0 3 0 1])
grid on

%Mach number
subplot(4,1,4);
plot(x,Mach_number_C,'color','y')
xlabel('Nozzle Length')
ylabel('Mach number')
legend({'Mach number'});
axis([0 3 0 4])
grid on


%comparison of Normalized Mass Flow Rate of both forms
figure(7)
hold on
plot(x,Mass_flow_rate_NC,'r','linewidth',1.25)
hold on;
plot(x,Mass_flow_rate_C,'k','linewidth',1.25)
hold on;
grid on

legend('Non Conservative','Conservative');
xlabel('Length of the Domain')
ylabel('Mass Flow Rate')
title('Comparison of Normalized Mass Flow Rate of both forms')

Function For Non Conservative Form:

%Function for Non Conservative form

function [Mass_flow_rate_NC, Pressure_NC, Mach_number_NC, rho_NC, v_NC, T_NC, rho_throat_NC, v_throat_NC, T_throat_NC, Mass_flow_rate_throat_NC, Pressure_throat_NC, Mach_number_throat_NC] = Non_conservative_form(x, dx, n, gamma, nt, C)

%Calculate Intial Profiles
rho_NC = 1 - 0.3146*x;
T_NC = 1 - 0.2341*x;
v_NC = (0.1 + 1.09*x).*T_NC.^0.5;

%Area & Throat profiles
a = 1 + 2.2*(x - 1.5).^2;
throat = find(a==1);


%Outer Time Loop
for k = 1:nt
    
    %Time-step control
    dt = min(C.*dx./(sqrt(T_NC) + v_NC));
    
    %Saving Old Values
    rho_old = rho_NC;
    T_old = T_NC;
    v_old = v_NC;
    

    %Predictor Method
    for j = 2:n-1
        
        %Simplifying the Equation's spatial terms
        dv_dx = (v_NC(j + 1) - v_NC(j))/dx;
        drho_dx = (rho_NC(j + 1) - rho_NC(j))/dx;
        dT_dx = (T_NC(j + 1) - T_NC(j))/dx;
        dlog_a_dx = (log(a(j + 1)) - log(a(j)))/dx;
        
        %Continuity Equation
        drho_dt_P(j) = -rho_NC(j)*dv_dx - rho_NC(j)*v_NC(j)*dlog_a_dx - v_NC(j)*drho_dx;
        
        %Momentum Equation
        dv_dt_P(j) = -v_NC(j)*dv_dx - (1/gamma)*(dT_dx + (T_NC(j)*drho_dx/rho_NC(j)));
        
        %Energy Equation
        dT_dt_P(j) = -v_NC(j)*dT_dx - (gamma - 1)*T_NC(j)*(dv_dx + v_NC(j)*dlog_a_dx);
        
        
        %Solution Update
        rho_NC(j) = rho_NC(j) + drho_dt_P(j)*dt;
        v_NC(j) = v_NC(j) + dv_dt_P(j)*dt;
        T_NC(j) = T_NC(j) + dT_dt_P(j)*dt;
        
    end
    
    
    %Corrector Method
    for j = 2:n-1
        
        %Simplifying the Equation's spatial terms
        dv_dx = (v_NC(j) - v_NC(j - 1))/dx;
        drho_dx = (rho_NC(j) - rho_NC(j - 1))/dx;
        dT_dx = (T_NC(j) - T_NC(j - 1))/dx;
        dlog_a_dx = (log(a(j)) - log(a(j - 1)))/dx;
        
        %Continuity Equation
        drho_dt_C(j) = - rho_NC(j)*dv_dx - rho_NC(j)*v_NC(j)*dlog_a_dx - v_NC(j)*drho_dx;
        
        %Momentum Equation
        dv_dt_C(j) = - v_NC(j)*dv_dx - (1/gamma)*(dT_dx + (T_NC(j)*drho_dx/rho_NC(j)));
        
        %Energy Equation
        dT_dt_C(j) = - v_NC(j)*dT_dx - (gamma - 1)*T_NC(j)*(dv_dx + v_NC(j)*dlog_a_dx);
       
    end
    
    %Compute Average Time derivative
    drho_dt = 0.5.*(drho_dt_P + drho_dt_C);
    dv_dt = 0.5.*(dv_dt_P + dv_dt_C);
    dT_dt = 0.5.*(dT_dt_P + dT_dt_C);
    
    %Final Solution Update
    for i = 2:n-1
        rho_NC(i) = rho_old(i) + drho_dt(i)*dt;
        v_NC(i) = v_old(i) + dv_dt(i)*dt;
        T_NC(i) = T_old(i) + dT_dt(i)*dt;
        
    end
    
    %Applying Boundary Conditions

    %At Inlet
    rho_NC(1) = 1;
    v_NC(1) = 2*v_NC(2) - v_NC(3);
    T_NC(1) = 1;
    
    %At Outlet
    rho_NC(n) = 2*rho_NC(n-1) - rho_NC(n - 2);
    v_NC(n) = 2*v_NC(n - 1) - v_NC(n - 2);
    T_NC(n) = 2*T_NC(n - 1) - T_NC(n - 2);
    
    
    %Defining Mass flow rate, Pressure and Mach number
    Mass_flow_rate_NC = rho_NC.*a.*v_NC;
    Pressure_NC = rho_NC.*T_NC;
    Mach_number_NC = (v_NC./sqrt(T_NC));
    
    %Calculating Variables at throat section
    rho_throat_NC(k) = rho_NC(throat);
    T_throat_NC(k) = T_NC(throat);
    v_throat_NC(k) = v_NC(throat);
    Mass_flow_rate_throat_NC(k) = Mass_flow_rate_NC(throat);
    Pressure_throat_NC(k) = Pressure_NC(throat);
    Mach_number_throat_NC(k) = Mach_number_NC(throat);
    
    
    %Plotting
    %Comparison of non-dimensional Mass flow rates at different time steps
    figure(1);
    if k == 50
       plot(x, Mass_flow_rate_NC, 'm', 'linewidth', 1.25);
       hold on
    elseif k == 100
       plot(x, Mass_flow_rate_NC, 'c', 'linewidth', 1.25);
       hold on
    elseif k == 200
       plot(x, Mass_flow_rate_NC, 'g', 'linewidth', 1.25);
       hold on
    elseif k == 400
       plot(x, Mass_flow_rate_NC, 'y', 'linewidth', 1.25);
       hold on
    elseif k == 800
       plot(x, Mass_flow_rate_NC, 'k', 'linewidth', 1.25);
       hold on
    end
    
    %Label
    title('Mass flow rates at different Timesteps - NON CONSERVATIVE FORM)')
    xlabel('Distance')
    ylabel('Mass flow rate')
    legend({'50^t^h Timestep','100^t^h Timestep','200^t^h Timestep','400^t^h Timestep','800^t^h Timestep'})
    axis([0 3 0 2])
    grid on
    
end

end

Function for Conservative Form:

%Function for Conservative form

function [Mass_flow_rate_C, Pressure_C, Mach_number_C,  rho_C, v_C, T_C, rho_throat_C, v_throat_C, T_throat_C, Mass_flow_rate_throat_C, Pressure_throat_C, Mach_number_throat_C] = Conservative_form(x, dx, n, gamma, nt, C)

%Determining Initial profile of Density and Temperature
for i = 1:n
    
    if (x(i) >= 0 && x(i) <= 0.5)
        rho_C(i) = 1;
        T_C(i) = 1;
    elseif (x(i) >= 0.5 && x(i) <= 1.5)
        rho_C(i) = 1 - 0.366*(x(i) - 0.5);
        T_C(i) = 1 - 0.167*(x(i) - 0.5);
    elseif (x(i) >= 1.5 && x(i) <= 3)
        rho_C(i) = 0.634 - 0.3879*(x(i) - 1.5);
        T_C(i) = 0.833 - 0.3507*(x(i) - 1.5);
    end
    
end

%Area & Throat profiles
a = 1 + 2.2*(x - 1.5).^2;
throat = find(a==1);

%Initial profile fot Velocity and Pressure
v_C = 0.59./(rho_C.*a);
Pressure_C = rho_C.*T_C;

%Calculate the Initial Solution Vectors(U)
U1 = rho_C.*a;
U2 = rho_C.*a.*v_C;
U3 = rho_C.*a.*(T_C./(gamma - 1)) + ((gamma/2).*v_C.^2);


%Outer Time Loop
for k =1:nt
    
    %Time-step control
    dt = min(C.*dx./(sqrt(T_C) + v_C));
    
    %Saving Old Values
    U1_old = U1;
    U2_old = U2;
    U3_old = U3;

    %Calculating the Flux vector(F)
    F1 = U2;
    F2 = ((U2.^2)./U1) + ((gamma - 1)/gamma)*(U3 - (gamma/2)*((U2.^2)./U1));
    F3 = ((gamma*U2.*U3)./U1) - (gamma*(gamma - 1)*((U2.^3)./(2*U1.^2)));
    
    
    %Predictor Method
    for j = 2:n-1
    
        %Calculating the Source term(J)
        J2(j) = (1/gamma)*rho_C(j)*T_C(j)*((a(j + 1) - a(j))/dx);
        
        
        %Continuity Equation
        dU1_dt_P(j) = -((F1(j + 1) - F1(j))/dx);
        
        %Momentum Equation
        dU2_dt_P(j) = -((F2(j + 1) - F2(j))/dx) + J2(j);
        
        %Energy Equation
        dU3_dt_P(j) = -((F3(j + 1) - F3(j))/dx);
        
        
        %Updating New values
        U1(j) = U1(j) + dU1_dt_P(j)*dt;
        U2(j) = U2(j) + dU2_dt_P(j)*dt;
        U3(j) = U3(j) + dU3_dt_P(j)*dt;
        
    end
    
    %Updating Flux vectors
    F1 = U2;
    F2 = ((U2.^2)./U1) + ((gamma - 1)/gamma)*(U3 - ((gamma*0.5*(U2.^2))./(U1)));
    F3 = ((gamma*U2.*U3)./U1) - ((gamma*0.5*(gamma - 1)*(U2.^3))./(U1.^2));

    
    %Corrector Method
    for j = 2:n-1
        
        %Updating the Source term(J)
        J2(j) = (1/gamma)*rho_C(j)*T_C(j)*((a(j) - a(j - 1))/dx);

        %Simplifying the Equation's spatial terms
        dU1_dt_C(j) = -((F1(j) - F1(j - 1))/dx);
        dU2_dt_C(j) = -((F2(j) - F2(j - 1))/dx) + J2(j);
        dU3_dt_C(j) = -((F3(j) - F3(j - 1))/dx);

    end

    %Compute Average Time derivative
    dU1_dt = 0.5*(dU1_dt_P + dU1_dt_C);
    dU2_dt = 0.5*(dU2_dt_P + dU2_dt_C);
    dU3_dt = 0.5*(dU3_dt_P + dU3_dt_C);

    %Final Solution Update
    for i = 2:n-1
        U1(i) = U1_old(i) + dU1_dt(i)*dt;
        U2(i) = U2_old(i) + dU2_dt(i)*dt;
        U3(i) = U3_old(i) + dU3_dt(i)*dt;
        
    end
    
    
    %Applying Boundary Conditions

    %At Inlet
    U1(1) = rho_C(1)*a(1);
    U2(1) = 2*U2(2) - U2(3);
    
    v_C(1) = U2(1)./U1(1);
    U3(1) = U1(1)*((T_C(1)/(gamma - 1)) + ((gamma/2)*(v_C(1)).^2));
    
    %At Outlet
    U1(n) = 2*U1(n - 1) - U1(n - 2);
    U2(n) = 2*U2(n - 1) - U2(n - 2);
    U3(n) = 2*U3(n - 1) - U3(n - 2);
    
    %Final Primitive value update
    rho_C = U1./a;
    v_C = U2./U1;
    T_C = (gamma - 1)*((U3./U1 - (gamma/2)*(v_C).^2));
    
    %Defining Mass flow rate, Pressure and Mach number
    Mass_flow_rate_C = rho_C.*a.*v_C;
    Pressure_C = rho_C.*T_C;
    Mach_number_C = (v_C./sqrt(T_C));
    
    %Calculating Variables at throat section
    rho_throat_C(k) = rho_C(throat);
    T_throat_C(k) = T_C(throat);
    v_throat_C(k) = v_C(throat);
    Mass_flow_rate_throat_C(k) = Mass_flow_rate_C(throat);
    Pressure_throat_C(k) = Pressure_C(throat);
    Mach_number_throat_C(k) = Mach_number_C(throat);

    %Plotting
    %Comparison of non-dimensional Mass flow rates at different time steps
    figure(4)
    if k == 50
       plot(x, Mass_flow_rate_C, 'm', 'linewidth', 1.25);
       hold on
    elseif k == 100
       plot(x, Mass_flow_rate_C, 'c', 'linewidth', 1.25);
       hold on
    elseif k == 200
       plot(x, Mass_flow_rate_C, 'g', 'linewidth', 1.25);
       hold on
    elseif k == 400
       plot(x, Mass_flow_rate_C, 'y', 'linewidth', 1.25);
       hold on
    elseif k == 800
       plot(x, Mass_flow_rate_C, 'k', 'linewidth', 1.25);
       hold on
    end
           
    
    %Label
    title('Mass flow rates at different Timesteps - CONSERVATIVE FORM')
    xlabel('Distance')
    ylabel('Mass flow rate')
    legend({'50^t^h Timestep','100^t^h Timestep','200^t^h Timestep','400^t^h Timestep','800^t^h Timestep'})
    axis([0 3 0.4 1])
    grid on
    
end

end

Outputs:

Time steps variation of primitive variable at Throat area:

Non Conservative Form:

Conservative Form:

Observation:

By observing above plots we can conclude that initial variations observed in Non Conservative form for a certain period of time makes it consume higher amount of time to acheive stable solution when compared to Conservative form.

Variation of Mass flow rate distribution inside the nozzle at different time steps during the time-marching process:

Non Conservative form:

Conservative form:

Observation:

By observing above plots we can conclude that we could see that both the forms are in same phase giving the exact same solution for all the values.

Mass flow rates at different Timesteps:

Non Conservative form:

Conservative form:

Observation:

By observing above plots we can conclude that Mass Flow Rate at different Time steps along the Distance oscillates initially, however the solution becomes stable after the 400th Timestep for both the forms attaining a constant value.

Comparison of Normalized mass flow rate distributions of both forms:

Observation:

By observing above plot we can conclude that Eventhough the final solution of both the forms are almost similar, the Non Conservative form oscillates much when compared to Conservative form. The latter also gives almost stable solution along the length. By this we can conclude that Conservative form attains stability in lesser number of iterations with earliest time and from the graph, we can see that the mass flow rate is preserved and shows stability for conservative form rather than the non-conservative form. This is because the mass flow rate is the primitive variable for the conservative form. But in non-conservative form, the primitive variables are density, velocity and so on. The mass flow rate is calculated separately for non-conservative form.

Grid independence test and comparing the final results:

      

The grid independence test is a process used to find the optimal grid condition that has the smallest number of grids without generating a difference in the numerical results based on the evaluation of various grid conditions. This image shows that the program written is independent of grid points in mesh. Also it can be seen that non-conservative solutions give more accurate results than the conservative solution. This happens because the residuals that remain after each time step are reduced faster in non-conservative form.

Conclusion:

Both forms have their own merits and demerits and one should choose the form according to requirements. The non-conservative form produces accurate results for the primitive variable and the conservative form gives better results for the flux variable/vectors. Cumulating all the above results we can evidently conclude that Conservative form converges slightly faster than Non Conservative form offering stable solution along the simulation. Yet both the forms are dependable in calculating the solutions which is almost precise.