evaluateHeatFlux

Evaluate heat flux of a thermal solution at nodal or arbitrary spatial locations

Description

example

[qx,qy] = evaluateHeatFlux(thermalresults,xq,yq) returns the heat flux for a thermal problem at the 2-D points specified in xq and yq. This syntax is valid for both the steady-state and transient thermal models.

example

[qx,qy,qz] = evaluateHeatFlux(thermalresults,xq,yq,zq) returns the heat flux for a thermal problem at the 3-D points specified in xq, yq, and zq. This syntax is valid for both the steady-state and transient thermal models.

example

[___] = evaluateHeatFlux(thermalresults,querypoints) returns the heat flux for a thermal problem at the 2-D or 3-D points specified in querypoints. This syntax is valid for both the steady-state and transient thermal models.

example

[___] = evaluateHeatFlux(___,iT) returns the heat flux for a thermal problem at the times specified in iT. You can specify iT after the input arguments in any of the previous syntaxes.

The first dimension of qx, qy, and, in the 3-D case, qz corresponds to query points. The second dimension corresponds to time steps iT.

example

[qx,qy] = evaluateHeatFlux(thermalresults) returns the heat flux for a 2-D problem at the nodal points of the triangular mesh. The first dimension of qx and qy represents the node indices. The second dimension represents time steps.

example

[qx,qy,qz] = evaluateHeatFlux(thermalresults) returns the heat flux for a 3-D thermal problem at the nodal points of the tetrahedral mesh. The first dimension of qx, qy, and qz represents the node indices. The second dimension represents time steps.

Examples

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For a 2-D steady-state thermal model, evaluate heat flux at the nodal locations and at the points specified by x and y coordinates.

Create a thermal model for steady-state analysis.

thermalmodel = createpde('thermal');

Create the geometry and include it in the model.

R1 = [3,4,-1,1,1,-1,1,1,-1,-1]';
g = decsg(R1,'R1',('R1')');
geometryFromEdges(thermalmodel,g);
pdegplot(thermalmodel,'EdgeLabels','on')
xlim([-1.5 1.5])
axis equal

Assuming that this geometry represents an iron plate, the thermal conductivity is 79.5W/(mK).

thermalProperties(thermalmodel,'ThermalConductivity',79.5,'Face',1);

Apply a constant temperature of 500 K to the bottom of the plate (edge 3). Also, assume that the top of the plate (edge 1) is insulated, and apply convection on the two sides of the plate (edges 2 and 4).

thermalBC(thermalmodel,'Edge',3,'Temperature',500);
thermalBC(thermalmodel,'Edge',1,'HeatFlux',0);
thermalBC(thermalmodel,'Edge',[2 4], ...
                       'ConvectionCoefficient',25, ...
                       'AmbientTemperature',50);

Mesh the geometry and solve the problem.

generateMesh(thermalmodel);
results = solve(thermalmodel)
results = 
  SteadyStateThermalResults with properties:

    Temperature: [1541x1 double]
     XGradients: [1541x1 double]
     YGradients: [1541x1 double]
     ZGradients: []
           Mesh: [1x1 FEMesh]

Evaluate heat flux at the nodal locations.

[qx,qy] = evaluateHeatFlux(results);

figure
pdeplot(thermalmodel,'FlowData',[qx qy])

Create a grid specified by x and y coordinates, and evaluate heat flux to the grid.

v = linspace(-0.5,0.5,11);
[X,Y] = meshgrid(v);

[qx,qy] = evaluateHeatFlux(results,X,Y);

Reshape the qTx and qTy vectors, and plot the resulting heat flux.

qx = reshape(qx,size(X));
qy = reshape(qy,size(Y));
figure
quiver(X,Y,qx,qy)

Alternatively, you can specify the grid by using a matrix of query points.

querypoints = [X(:) Y(:)]';
[qx,qy] = evaluateHeatFlux(results,querypoints);

qx = reshape(qx,size(X));
qy = reshape(qy,size(Y));
figure
quiver(X,Y,qx,qy)

For a 3-D steady-state thermal model, evaluate heat flux at the nodal locations and at the points specified by x, y, and z coordinates.

Create a thermal model for steady-state analysis.

thermalmodel = createpde('thermal');

Create the following 3-D geometry and include it in the model.

importGeometry(thermalmodel,'Block.stl'); 
pdegplot(thermalmodel,'FaceLabels','on','FaceAlpha',0.5)
title('Copper block, cm')
axis equal

Assuming that this is a copper block, the thermal conductivity of the block is approximately 4W/(cmK).

thermalProperties(thermalmodel,'ThermalConductivity',4);

Apply a constant temperature of 373 K to the left side of the block (face 1) and a constant temperature of 573 K to the right side of the block (face 3).

thermalBC(thermalmodel,'Face',1,'Temperature',373);
thermalBC(thermalmodel,'Face',3,'Temperature',573);

Apply a heat flux boundary condition to the bottom of the block.

thermalBC(thermalmodel,'Face',4,'HeatFlux',-20);

Mesh the geometry and solve the problem.

generateMesh(thermalmodel);
thermalresults = solve(thermalmodel)
thermalresults = 
  SteadyStateThermalResults with properties:

    Temperature: [12691x1 double]
     XGradients: [12691x1 double]
     YGradients: [12691x1 double]
     ZGradients: [12691x1 double]
           Mesh: [1x1 FEMesh]

Evaluate heat flux at the nodal locations.

[qx,qy,qz] = evaluateHeatFlux(thermalresults);

figure
pdeplot3D(thermalmodel,'FlowData',[qx qy qz])

Create a grid specified by x, y, and z coordinates, and evaluate heat flux to the grid.

[X,Y,Z] = meshgrid(1:26:100,1:6:20,1:11:50);

[qx,qy,qz] = evaluateHeatFlux(thermalresults,X,Y,Z);

Reshape the qx, qy, and qz vectors, and plot the resulting heat flux.

qx = reshape(qx,size(X));
qy = reshape(qy,size(Y));
qz = reshape(qz,size(Z));
figure
quiver3(X,Y,Z,qx,qy,qz)

Alternatively, you can specify the grid by using a matrix of query points.

querypoints = [X(:) Y(:) Z(:)]';
[qx,qy,qz] = evaluateHeatFlux(thermalresults,querypoints);

qx = reshape(qx,size(X));
qy = reshape(qy,size(Y));
qz = reshape(qz,size(Z));
figure
quiver3(X,Y,Z,qx,qy,qz)

Solve a 2-D transient heat transfer problem on a square domain, and compute heat flow across a convective boundary.

Create a thermal model for this problem.

thermalmodel = createpde('thermal','transient');

Create the geometry and include it in the model.

g = @squareg;
geometryFromEdges(thermalmodel,g);
pdegplot(thermalmodel,'EdgeLabels','on')
xlim([-1.2 1.2])
ylim([-1.2 1.2])
axis equal

Assign the following thermal properties: thermal conductivity is 100W/(mC), mass density is 7800kg/m3, and specific heat is 500J/(kgC).

thermalProperties(thermalmodel,'ThermalConductivity',100, ...
                               'MassDensity',7800, ...
                               'SpecificHeat',500);

Apply insulated boundary conditions on three edges and the free convection boundary condition on the right edge.

thermalBC(thermalmodel,'Edge',[1 3 4],'HeatFlux',0);
thermalBC(thermalmodel,'Edge',2,...
                       'ConvectionCoefficient',5000, ...
                       'AmbientTemperature',25);

Set the initial conditions: uniform room temperature across domain and higher temperature on the top edge.

thermalIC(thermalmodel,25);
thermalIC(thermalmodel,100,'Edge',1);

Generate a mesh and solve the problem using 0:1000:200000 as a vector of times.

generateMesh(thermalmodel);
tlist = 0:1000:200000;
thermalresults = solve(thermalmodel,tlist)
thermalresults = 
  TransientThermalResults with properties:

      Temperature: [1541x201 double]
    SolutionTimes: [1x201 double]
       XGradients: [1541x201 double]
       YGradients: [1541x201 double]
       ZGradients: []
             Mesh: [1x1 FEMesh]

Create a grid specified by x and y coordinates, and evaluate heat flux to the grid.

v = linspace(-1,1,11);
[X,Y] = meshgrid(v);

[qx,qy] = evaluateHeatFlux(thermalresults,X,Y,1:length(tlist));

Reshape qx and qy, and plot the resulting heat flux for the 25th solution step.

tlist(25)
ans = 24000
figure
quiver(X(:),Y(:),qx(:,25),qy(:,25));
xlim([-1,1])
axis equal

Solve the heat transfer problem for the following 2-D geometry consisting of a square and a diamond made of different materials. Compute the heat flux, and plot it as a vector field.

Create a thermal model for transient analysis.

thermalmodel = createpde('thermal','transient');

Create the geometry and include it in the model.

SQ1 = [3; 4; 0; 3; 3; 0; 0; 0; 3; 3];
D1 = [2; 4; 0.5; 1.5; 2.5; 1.5; 1.5; 0.5; 1.5; 2.5];
gd = [SQ1 D1];
sf = 'SQ1+D1';
ns = char('SQ1','D1');
ns = ns';
dl = decsg(gd,sf,ns);
geometryFromEdges(thermalmodel,dl);
pdegplot(thermalmodel,'EdgeLabels','on','FaceLabels','on')
xlim([-1.5 4.5])
ylim([-0.5 3.5])
axis equal

For the square region, assign the following thermal properties: thermal conductivity is 10W/(mC), mass density is 2kg/m3, and specific heat is 0.1J/(kgC).

thermalProperties(thermalmodel,'ThermalConductivity',10, ...
                               'MassDensity',2, ...
                               'SpecificHeat',0.1, ...
                               'Face',1);

For the diamond-shaped region, assign the following thermal properties: thermal conductivity is 2W/(mC), mass density is 1kg/m3, and specific heat is 0.1J/(kgC).

thermalProperties(thermalmodel,'ThermalConductivity',2, ...
                               'MassDensity',1, ...
                               'SpecificHeat',0.1, ...
                               'Face',2);

Assume that the diamond-shaped region is a heat source with the density of 4W/m3.

internalHeatSource(thermalmodel,4,'Face',2);

Apply a constant temperature of 0C to the sides of the square plate.

thermalBC(thermalmodel,'Temperature',0,'Edge',[1 2 7 8]);

Set the initial temperature to 0C.

thermalIC(thermalmodel,0);

Mesh the geometry and solve the problem.

generateMesh(thermalmodel);

The dynamic for this problem is very fast: the temperature reaches steady state in about 0.1 seconds. To capture the interesting part of the dynamics, set the solution time to logspace(-2,-1,10). This gives 10 logarithmically spaced solution times between 0.01 and 0.1. Solve the equation.

tlist = logspace(-2,-1,10);
thermalresults = solve(thermalmodel,tlist);
temp = thermalresults.Temperature;

Compute the heat flux density. Plot the solution with isothermal lines using a contour plot, and plot the heat flux vector field using arrows.

[qTx,qTy] = evaluateHeatFlux(thermalresults);

figure
pdeplot(thermalmodel,'XYData',temp(:,10),'Contour','on', ...
                     'FlowData',[qTx(:,10) qTy(:,10)], ...
                     'ColorMap','hot')

Input Arguments

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Solution of a thermal problem, specified as a SteadyStateThermalResults object or a TransientThermalResults object. Create thermalresults using the solve function.

Example: thermalresults = solve(thermalmodel)

x-coordinate query points, specified as a real array. evaluateHeatFlux evaluates the heat flux at the 2-D coordinate points [xq(i) yq(i)] or at the 3-D coordinate points [xq(i) yq(i) zq(i)]. So xq, yq, and (if present) zq must have the same number of entries.

evaluateHeatFlux converts query points to column vectors xq(:), yq(:), and (if present) zq(:). It returns the heat flux in a form of a column vector of the same size. To ensure that the dimensions of the returned solution are consistent with the dimensions of the original query points, use reshape. For example, use qx = reshape(qx,size(xq)).

Data Types: double

y-coordinate query points, specified as a real array. evaluateHeatFlux evaluates the heat flux at the 2-D coordinate points [xq(i) yq(i)] or at the 3-D coordinate points [xq(i) yq(i) zq(i)]. So xq, yq, and (if present) zq must have the same number of entries.

evaluateHeatFlux converts query points to column vectors xq(:), yq(:), and (if present) zq(:). It returns the heat flux in a form of a column vector of the same size. To ensure that the dimensions of the returned solution is consistent with the dimensions of the original query points, use reshape. For example, use qy = reshape(qy,size(yq)).

Data Types: double

z-coordinate query points, specified as a real array. evaluateHeatFlux evaluates the heat flux at the 3-D coordinate points [xq(i) yq(i) zq(i)]. So xq, yq, and zq must have the same number of entries.

evaluateHeatFlux converts query points to column vectors xq(:), yq(:), and (if present) zq(:). It returns the heat flux in a form of a column vector of the same size. To ensure that the dimensions of the returned solution is consistent with the dimensions of the original query points, use reshape. For example, use qz = reshape(qz,size(zq)).

Data Types: double

Query points, specified as a real matrix with two rows for 2-D geometry or three rows for 3-D geometry. evaluateHeatFlux evaluates the heat flux at the coordinate points querypoints(:,i), so each column of querypoints contains exactly one 2-D or 3-D query point.

Example: For 2-D geometry, querypoints = [0.5 0.5 0.75 0.75; 1 2 0 0.5]

Data Types: double

Time indices, specified as a vector of positive integers. Each entry in iT specifies a time index.

Example: iT = 1:5:21 specifies every fifth time-step up to 21.

Data Types: double

Output Arguments

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x-component of the heat flux, returned as an array. The first array dimension represents the node index. The second array dimension represents the time step.

For query points that are outside the geometry, qx = NaN.

y-component of the heat flux, returned as an array. The first array dimension represents the node index. The second array dimension represents the time step.

For query points that are outside the geometry, qy = NaN.

z-component of the heat flux, returned as an array. The first array dimension represents the node index. The second array dimension represents the time step.

For query points that are outside the geometry, qz = NaN.

Introduced in R2017a