"The
real time data gathering provided by the HT14 software is a very
good feature especially when temperature transients are involved,
but getting the data into an Excel spreadsheet makes the equipment
much more of an experimental platform and exploratory tool,"
he said.
Students export their data to a spreadsheet package developed by
Dr. Zampino. This contains a more extensive heat transfer analysis
of the experimental data. The students use the spreadsheet to analyze
and report the data in tabular and graphical formats.
The basic function of the spreadsheet is to take the experimental
data and perform a conservation of energy analysis, determine the
percentage of the total heat transport by radiation and convection,
determine the experimental Nusselt number for the heat transfer,
and the Reynolds number for the air flow. The experimental Nusselt
number is compared to one obtained using an empirical correlation.
"The key is to plot the Nusselt number as a function
of the Reynolds numbers and compare with empirical correlations,"
said Marc."Students use their text books and even research
papers to obtain empirical correlations."
Another of several examples his students use is to plot the percentages
of radiation and convection heat transfer against the Reynolds number
of the airflow. This produces two curves which crossover at a specific
Reynolds number.

This
plot graphically illustrates how radiation and convection are competing
forms of heat transfer, with radiation dominating at low air speeds,
and eventually convection becoming the dominant mode of heat transfer.
Performing this experiment at multiple power levels (i.e. thermal
loads) shows that the crossover point between the two heat transfer
modes shifts with Reynolds number. Using an external spreadsheet
with the HT14 provides the opportunity for students to investigate
subtle secondary phenomena by the ability to plot the data in various
ways and to determine empirical correlation for the trends they
see.
The HT14 apparatus is also used to investigate natural convection
with an analysis similar to that for forced convection. However,
in this case, the students determine the Grashof number instead
of the Reynolds number, illustrating the difference between airflow
induced by buoyancy forces rather than by a pressure gradient. For
advanced investigation, students can couple the results from the
natural and forced convection experiments and the transition from
natural to forced convection.
Dr. Zampino uses these techniques with a senior level class already
conversant with heat transfer and fluids, with experimental teams
limited to two or three students.
" We do the experiments quickly by taking only a small set
of data which I collect and add to a larger data set. I distribute
the larger data set over the web and the class works as a group
with the collective data set." he said. "This promotes
a sense of involvement for the students as they are part of an ongoing
project which I am directing."
"The
use of collective data sets, helps students to develop their spreadsheet
skills, since they have to analyze data more efficiently. It also
allows them to use statistical analysis and regression techniques."
