Miniature model Heat Exchanger.
A small heat exchanger was being used alongside a much bigger one to act as a surrogate that could be
checked for its behaviour to make estimates of what might be going on inside the big one.
The idea was that by running the small exchanger with the same metal walls, same fluid,
same wall temperatures and heat flux rate, and same Reynold's number as the real one, it
would foul up in the same way. Then, if calibrated to measure the heat transfer
coefficients, it could act as a monitor on process conditions and operational economics
for its big brother.
Problems appear
In principle it's easy. In practice a lot of problems arose. The small exchanger
needed only low flow rates which were difficult to measure because the dirt and debris in
the process water (it was a cooling system), would block up any moving components or
orifice plate in the narrow pipes. In the big exchanger it went by with no trouble. We
could measure the heat flux into the little exchanger as an electrical power input, but
the physical construction meant that the walls had significant dynamic lags for
temperature changes.The biggest problem came from the need to make the device give a good
estimate of heat transfer reduction due to fouling even though the flow rate could vary
over a wide range.
 
Construction.
In the diagrams the cross section shows a heater jacket round A, B C
quadrants. The water flows through the little hole in the middle. Asymmetry was a
potential problem. The ring of bolt holes in the construction made some difference to the heat
transfer. The conductance model has all the interesting stuff included in G3. The dynamic
model, having thermal capacity at the nodes, allowed us to understand the way the
external power controller (not shown) responded to changes when told to provide either
constant heat flux or constant temperature (which had to be estimated) at the wall.
Another problem to sort out was the effect of the conduction along the entry and
exit pipes that affected the measurements of inlet and outlet water temperatures. Because
we were looking for small diffeences, thermocouple matching and calibration also became an
issue.
Extracting the answer.
The idea is that the resistance to heat flux comes from the metal (not much),
from the fouling layer and from the boundary layer, where the transition from zero
velocity at the wall surface to full stream velocity takes place.We were, as usual dealing
with turbulent flow. Ideally the model system should measure the temperature drop
between wall and fluid and compare it to heat flux to get a reading of heat transfer
coefficient. Then the trick is to assign the total resistance between the various
contributors. The metal is pretty much a constant thermal resistance, the fouling is the
unknown and so we need to know the contribution from the boundary layer, assuming we can
measure flow.
Tests and a working system.
When we tested the system for measured heat transfer at variable flow we
expected the effects of flow to match the textbook ideas of Reynold's analogy. Well, it
did, sort of. But, it wasn't good enough for use in an instrument. McCann developed
mathematical models of the process which allowed for Reynolds number and Prandtl number
changes, using essentially the Dittus and Boelter correlation, with the exponent 0.4
on Pr for heating of fluid). This was merged into a form that could be used to create
calibration curves for the instrument at two levels. At the simplest level, an assumed
power law dependence on flow was taken which gave a good first indication for a model
exchanger. If test data over a range of flows and temperatures was available then the
mathematical model could be refined for the particular device. We also devised a means of
doing away with the flow meter.
Eventually, under pressure as it were, we were able to generate
calibration curves from initial running data of a newly installed device even when the
controller for the heat input was misbehaving. It took a bit of work with Mathcad but came
out well in the end.
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Invitation. McCann can help if you have a
design or operational problem that needs some technical support that is outside your
team's experience, some quantitative assessment of what is really the cause of the
difficulties, some design alternatives or just a fresh look by an intelligent
interrogator.
If you have a problem with the behaviour of a market sector, plant, process or item of
equipment and would like to get a quantitative handle on it to improve yield or optimise
performance, then contact us. We are always ready to give a little time
to discuss a new puzzle, in confidence,
of course. We'll only worry about fees
when we have some defined work. We can be flexible
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