interpolateTemperature
Interpolate temperature in thermal result at arbitrary spatial locations
Syntax
Description
returns the interpolated temperature values at the 2-D points specified in
Tintrp
= interpolateTemperature(thermalresults
,xq
,yq
)xq
and yq
for a steady-state thermal
model.
returns the interpolated temperature values at the 3-D points specified in
Tintrp
= interpolateTemperature(thermalresults
,xq
,yq
,zq
)xq
, yq
, and zq
for a
steady-state thermal model.
returns the interpolated temperature values at the points in
Tintrp
= interpolateTemperature(thermalresults
,querypoints
)querypoints
for a steady-state thermal model.
Examples
Interpolate Temperatures in 2-D Steady-State Thermal Problem
Create and plot a square geometry.
R1 = [3,4,-1,1,1,-1,1,1,-1,-1]'; g = decsg(R1, 'R1', ('R1')'); pdegplot(g,EdgeLabels="on") xlim([-1.1,1.1]) ylim([-1.1,1.1])
Create an femodel
object for steady-state thermal analysis and include the geometry into the model.
model = femodel(AnalysisType="thermalSteady", ... Geometry=g);
Assuming that this is an iron plate, assign a thermal conductivity of 79.5 W/(m*K). For steady-state analysis, you do not need to assign mass density or specific heat values.
model.MaterialProperties = ...
materialProperties(ThermalConductivity=79.5);
Apply a constant temperature of 300 K to the bottom of the plate (edge 3).
model.EdgeBC(3) = edgeBC(Temperature=300);
Apply convection on the two sides of the plate (edges 2 and 4).
model.EdgeLoad([2 4]) = ... edgeLoad(ConvectionCoefficient=25,... AmbientTemperature=50);
Mesh the geometry and solve the problem.
model = generateMesh(model); R = solve(model)
R = SteadyStateThermalResults with properties: Temperature: [1529x1 double] XGradients: [1529x1 double] YGradients: [1529x1 double] ZGradients: [] Mesh: [1x1 FEMesh]
The solver finds the values of temperatures and temperature gradients at the nodal locations. To access these values, use R.Temperature
, R.XGradients
, and so on. For example, plot the temperatures at nodal locations.
figure; pdeplot(R.Mesh,XYData=R.Temperature,... Contour="on",ColorMap="hot");
Interpolate the resulting temperatures to a grid covering the central portion of the geometry, for x
and y
from -0.5
to 0.5
.
v = linspace(-0.5,0.5,11); [X,Y] = meshgrid(v); Tintrp = interpolateTemperature(R,X,Y);
Reshape the Tintrp
vector and plot the resulting temperatures.
Tintrp = reshape(Tintrp,size(X)); figure contourf(X,Y,Tintrp) colormap(hot) colorbar
Alternatively, you can specify the grid by using a matrix of query points.
querypoints = [X(:),Y(:)]'; Tintrp = interpolateTemperature(R,querypoints);
Interpolate Temperature for a 3-D Steady-State Thermal Problem
Create an femodel
object for steady-state thermal analysis and include a block geometry into the model.
model = femodel(AnalysisType="thermalSteady", ... Geometry="Block.stl");
Plot the geometry.
pdegplot(model.Geometry,FaceLabels="on",FaceAlpha=0.5) title("Copper block, cm")
Assuming that this is a copper block, the thermal conductivity of the block is approximately 4 W/(cm*K).
model.MaterialProperties = ...
materialProperties(ThermalConductivity=4);
Apply a constant temperature of 373 K to the left side of the block (edge 1) and a constant temperature of 573 K at the right side of the block.
model.FaceBC(1) = faceBC(Temperature=373); model.FaceBC(3) = faceBC(Temperature=573);
Apply a heat flux boundary condition to the bottom of the block.
model.FaceLoad(4) = faceLoad(Heat=-20);
Mesh the geometry and solve the problem.
model = generateMesh(model); R = solve(model)
R = SteadyStateThermalResults with properties: Temperature: [12822x1 double] XGradients: [12822x1 double] YGradients: [12822x1 double] ZGradients: [12822x1 double] Mesh: [1x1 FEMesh]
The solver finds the values of temperatures and temperature gradients at the nodal locations. To access these values, use results.Temperature
, results.XGradients
, and so on. For example, plot temperatures at nodal locations.
pdeplot3D(R.Mesh,ColorMapData=R.Temperature)
Create a grid specified by x
, y
, and z
coordinates and interpolate temperatures to the grid.
[X,Y,Z] = meshgrid(1:16:100,1:6:20,1:7:50); Tintrp = interpolateTemperature(R,X,Y,Z);
Create a contour slice plot for fixed values of the y
coordinate.
Tintrp = reshape(Tintrp,size(X)); figure contourslice(X,Y,Z,Tintrp,[],1:6:20,[]) xlabel("x") ylabel("y") zlabel("z") xlim([1,100]) ylim([1,20]) zlim([1,50]) axis equal view(-50,22) colorbar
Alternatively, you can specify the grid by using a matrix of query points.
querypoints = [X(:),Y(:),Z(:)]'; Tintrp = interpolateTemperature(R,querypoints);
Create a contour slice plot for four fixed values of the z
coordinate.
Tintrp = reshape(Tintrp,size(X)); figure contourslice(X,Y,Z,Tintrp,[],[],1:7:50) xlabel("x") ylabel("y") zlabel("z") xlim([1,100]) ylim([1,20]) zlim([1,50]) axis equal view(-50,22) colorbar
Temperatures at Convective Boundary
Solve a 2-D transient heat transfer problem on a square domain and compute temperatures at the convective boundary.
Create and plot a square geometry.
g = @squareg;
pdegplot(g,EdgeLabels="on")
xlim([-1.1,1.1])
ylim([-1.1,1.1])
Create an femodel
object for transient thermal analysis and include the geometry into the model.
model = femodel(AnalysisType="thermalTransient", ... Geometry=g);
Assign the following thermal properties:
Thermal conductivity is 100 W/(m*C)
Mass density is 7800 kg/m^3
Specific heat is 500 J/(kg*C)
model.MaterialProperties = ... materialProperties(ThermalConductivity=100,... MassDensity=7800,... SpecificHeat=500);
Apply a convection boundary condition on the right edge.
model.EdgeLoad(2) = ... edgeLoad(ConvectionCoefficient=5000,... AmbientTemperature=25);
Set the initial conditions: uniform room temperature across domain and higher temperature on the left edge.
model.FaceIC = faceIC(Temperature=25); model.EdgeIC(4) = edgeIC(Temperature=100);
Generate a mesh and solve the problem using 0:1000:200000
as a vector of times.
model = generateMesh(model); tlist = 0:1000:200000; R = solve(model,tlist);
Define a line at convection boundary and compute temperature gradients across that line.
X = -1:0.1:1; Y = ones(size(X)); Tintrp = interpolateTemperature(R,X,Y,1:length(tlist));
Plot the interpolated temperature Tintrp
along the x
axis for the following values from the time interval tlist
.
figure t = 51:50:201; p = gobjects(size(t)); for i = 1:numel(t) p(i) = plot(X,Tintrp(:,t(i)), ... DisplayName="T="+tlist(t(i))); hold on end legend(p) xlabel("x") ylabel("Tintrp")
Input Arguments
thermalresults
— Solution of thermal problem
SteadyStateThermalResults
object | TransientThermalResults
object
Solution of thermal problem, specified as a SteadyStateThermalResults
object or
a TransientThermalResults
object.
Create thermalresults
using
solve
.
xq
— x-coordinate query points
real array
x-coordinate query points, specified as a real array.
interpolateTemperature
evaluates temperatures 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.
interpolateTemperature
converts query points to
column vectors xq(:)
, yq(:)
, and (if
present) zq(:)
. It returns temperatures in the 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 Tintrp =
reshape(Tintrp,size(xq))
.
Data Types: double
yq
— y-coordinate query points
real array
y-coordinate query points, specified as a real array.
interpolateTemperature
evaluates temperatures 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.
Internally, interpolateTemperature
converts query
points to the column vector yq(:)
.
Data Types: double
zq
— z-coordinate query points
real array
z-coordinate query points, specified as a real array.
interpolateTemperature
evaluates temperatures at
the 3-D coordinate points [xq(i),yq(i),zq(i)]
. So
xq
, yq
, and
zq
must have the same number of entries. Internally,
interpolateTemperature
converts query points to the
column vector zq(:)
.
Data Types: double
querypoints
— Query points
real matrix
Query points, specified as a real matrix with either two rows for 2-D
geometry, or three rows for 3-D geometry. interpolateTemperature
evaluates temperatures 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
iT
— Time indices
vector of positive integers
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
Tintrp
— Temperatures at query points
array
Temperatures at query points, returned as an array. For query points that
are outside the geometry, Tintrp
=
NaN
.
Version History
Introduced in R2017a
See Also
Objects
Functions
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