The assignment for measuring the heat transfer coefficient from a single low profile package was handed out in class.
There was a small bug that might cause aveAgilentDataGUI
to hang. An updated version of
aveAgilentDataGUI is now available on the web
page for MATLAB codes for the class. As usual, I recommend
downloading the
entire zip archive
of codes to get the latest version of all the files.
The archive does not contain the three files linked
below for data reduction
Also note that sometimes Benchlink will write a text file with
an incomplete last line. If that happens you will get an error
message from aveAgilentDataGUI that looks like this:
Error in loadColData:
number of data points = 26617 does not equal nrow*ncol
data: nrow = 831.781250 ncol = 32
The solution is to open the data file (the file exported by Benchlink) and delete the incomplete last line from the bottom.
Use the following MATLAB code and sample data file as a start on the data reduction. The mfiles are not finished! You will have to add code.
getBlockData.mgetBlockData.m
reads the MAT file exported by aveAgilentDataGUI
and converts thermocouple voltages and thermistor resistance to
temperature. The uncertainties in the sensor data are also
computed and returned to the calling program. To complete this
function you will need to (1) add lines in the code to convert
other voltages to temperatures, including computing averages
of temperatures; and (2) add more variable names to the return
argument list. Think first, then write code.
Make a list on paper of the variables you will need for
data reduction. Any of these variables that are temperatures
(along with their uncertainties) should be computed in
getBlockData and returned in the output argument
list of getBlockData.
reduceBlock.mreduceBlock.m
calls getBlockData
and peforms data reduction to compute the heat transfer coefficient.
Again, think first, then write code. The
data reduction formulas you developed for the homework
assignment should appear in the reduceBlock
function. Better yet, I recommend that you write
another function, say htc.m that has the single task
of computing the heat transfer coefficients given all
of the input temperatures and geometric variables. That
function would have a similar role to nozzleFlow.m
for the flow bench data reduction. The advantage of a separate
htc function is that it makes the sequential perturbation
calculation easy and clean to implement.
sampleBlockData.matsampleBlockData.mat
is a MAT file will averaged data from two measurements of heat transfer
coefficient. You can use sampleBlockData.mat
to learn how getBlockData and reduceBlock
work. You will use your own data file with your modified
versions of getBlockData and reduceBlock.
The grading rubric will be posted later. This lab will not have a formal lab report.