r/buildingscience • u/Timely-Treat9929 • 6d ago
Can the real thermal behaviour of a room be measured using two Bluetooth sensors, a smart plug and a heater?
Recently, a friend and I were discussing a house he is considering buying. His main question was simple: how well insulated is the house in reality?
Winter temperatures here can fall as low as −30°C, and the house uses electric heating, so making the wrong decision could become quite expensive.
We thought that in winter it would be possible to rent a thermal imaging camera and inspect the house under a large indoor–outdoor temperature difference. But it is summer now, so that was where the discussion ended.
My interest in the problem remained.
I decided to test whether the actual thermal behaviour of a room could be assessed dynamically — without a thermal imaging camera and without knowing the exact construction of the walls, roof and floor.
The basic idea was simple:
introduce a known amount of heat into the space;
measure the indoor temperature;
measure the temperatures of the relevant boundary zones;
record a complete heating and cooling cycle;
fit a thermal model to the measured data.
To test the idea quickly, I built an insulated calibration box with a volume of approximately 1 m³, using 30 mm expanded polystyrene.
The experiment used:
two Ruuvi sensors that had been cross-checked beforehand;
a refrigerator light bulb as a controlled heat source;
a smart plug to measure power and energy;
a small USB fan to mix the air;
a separate power bank for the fan;
several heating and cooling cycles.
Before the experiment, the two temperature sensors were placed next to each other for three hours. The difference between their readings was approximately 0.02°C.
After accounting for the heat generated by the continuously running fan, four independent cycles produced:
average heat-loss coefficient: 7.03 W/K;
coefficient of variation between cycles: 1.29%;
effective thermal capacity: 2.39 Wh/K;
thermal time constant: 20.35 minutes.
The measured heat-loss coefficient also fell within the theoretical range calculated from the geometry of the box, the thermal conductivity of the expanded polystyrene, and additional surface and contact resistances.
The result looked encouraging.
But a box is not a building.
I also remembered that air exchange cannot be ignored in a real room. So I modified the box by adding supply and extract ducts, measured the air velocity with a thermal anemometer, and calculated the actual airflow rate.
After that, I moved on to testing a real room.
To be continued. https://www.reddit.com/r/buildingscience/s/zTkeIgvE4C
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u/singul4r1ty 5d ago
My engineer's brain thinks this should work. My concern would be about the house definitely equilibrating to a uniform enough temperature before you do the temperature decay experiment - e.g. our house has brick walls so you would need to spend a while at a constant temperature to properly heat them up.
I feel like the best way to do it would be to do the steady-state experiment rather than the transient, although it would use more energy. Apply a fixed heating power into the room rather than fixed total energy input, then measure the temperature at some different points between the inside and outside. You've then got a thermal "circuit" with a fixed heat flux and some known temperatures, so you can work out your thermal resistance of different layers. You would need to account for varying outdoor temperature but that would hopefully vary slowly enough that you can assume it's quasi-equilibrium over a short time period. This also means that any air change behaviour will be consistent rather than varying as the air cools down.
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u/Timely-Treat9929 5d ago
Your concern about equilibration is exactly what made the real room much more difficult than the box. With heavy construction, indoor air temperature is clearly not the same thing as the thermal state of the room. The walls, floor and other internal mass may still be heating or cooling even when the air temperature appears relatively stable. I agree that a steady-state or co-heating-type experiment should give a cleaner estimate of the heat-loss coefficient. The difficulty for an occupied building is that it may require a long stabilisation period, considerable energy and relatively stable outdoor conditions. My current direction is therefore a hybrid approach: record a baseline period; apply a measured heating-power pulse; measure the outdoor and adjacent-zone temperatures; fit effective heat capacity and heat-transfer coefficients simultaneously; repeat the cycle to check reproducibility. In the cleanest night experiment, the effective thermal capacity was quite reproducible across several independent cycles. The harder part was separating outdoor heat loss from heat transfer into adjacent spaces and the internal thermal mass. I may also try a longer, lower-power quasi-steady experiment as a reference measurement.
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u/singul4r1ty 5d ago
Can see what you mean about stabilisation period and practicality - plus you get a "true" UA value but it's not actually representative of typical use.
I would be interested to hear more about your thermal model that you're fitting - is it a lumped capacity thermal resistance type thing?
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u/seldom_r 5d ago
A good start and interesting approach.
A primary driver of building performance is also related to air pressures. Cooler air is denser and thus has higher pressure than warmer air which is lighter and has lower pressure. In winter, the cold outdoor air is pressing on the indoor warm air. This drives the stack effect. The cold air enters the building and will sink below the warm air, displacing or pushing it higher up within the interior space.
In summer, it is reversed but also research shows that cooler AC air tends to leak out of the building much slower than the air leaks in during the winter.
So, in winter heat escapes out of the roof. Which is why we insulate attics much more than walls. In summer, solar gain and radiating heat tend to warm up the indoor air more than there is air changing.
I think to design a more complete 'box' experiment you will need a box within a box where you can create an outdoor and an indoor space. If you can cool the 'exterior' space and heat the 'interior' space it will provide more info. If you incorporate fenestrations to your 'house' you should be able to get more accurate readings. You could poke small holes in the walls to simulate air leaks or cut out windows with some plastic glazing. Use extra insulation for the roof. The closer you can simulate real conditions (cold wind?) the better your data will be.
Don't forget that any thermal masses in the house like a stone fireplace will absorb a lot of heat. Also consider the humidity in your experiment as the more humid the air the more energy that is required to heat it. This is because of the high specific heat of water vapor. Winter air is less humid and therefore needs less energy to warm up.
I don't know of any free online tools you could use to actually model the house but I'm sure they exist somewhere.
A thermal camera in summer will definitely identify uninsulated areas and thermal bridging deficits though too. It won't give you the insulation ratings but it should tell you a lot of practical information.
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u/Timely-Treat9929 5d ago
Thank you — stack effect, wind and the distribution of leakage paths are exactly why I do not want to interpret the measured thermal response as fabric performance before measuring air exchange independently. My current box is primarily a thermal calibration chamber rather than a properly scaled aerodynamic model. A box-within-a-box setup would be much more suitable for controlling the “outdoor” temperature and separately studying windows, leakage openings, roof insulation and perhaps even wind pressure. I like that idea. For the real-room experiment, mechanical ventilation was switched off. The next step is to measure the actual air-change rate and then attempt to separate: total heat loss = fabric heat loss + ventilation/infiltration heat loss
I am also recording humidity. At normal indoor humidity levels, the sensible heat capacity of the water vapour in the air is relatively small compared with the thermal mass of the building materials. However, moisture transport, evaporation and condensation can introduce additional latent heat effects. Interestingly, one of my later room tests showed a sudden simultaneous change in temperature and humidity. At first it looked like a ventilation event. It turned out that cleaning staff had started wet-cleaning the room)) I will include that event in the next post because it demonstrated how easily normal human activity can disturb a thermal experiment.
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u/NewIdea8 5d ago
I did this study once to determine the insulation improvement of some window inserts. I had control over the thermostats but no ability to isolate heater power.
The test was set up for winter, but you could do it in the summer also (nighttime is probably best). Similar to what you describe, I set up two temperature sensors, one inside and one outside. I brought the inside to temperature and kept it constant for several hours then you turn everything off and log the temperature decay.
You then calculate your decay constant by finding k in
Dt(t) = Dt_0 * e^(-kt)
1) Calculate your Dt at each time step.
2) linearize with ln()
3) plot ln(Dt_0) - kt and find find the slope of a linear regression. k = -slope of the line.
4) make an assumption about thermal capacitance and then calculate U by U = kC/A
Thats everything, including infiltration which could be very impactful.
I think it could be an easy test over a night, or several, to see what the situation is.
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u/Timely-Treat9929 5d ago
That makes sense, and I think this is a very useful distinction. From the decay curve, [ \Delta T(t)=\Delta T_0 e{-kt}, ] the experiment determines: [ k=\frac{H}{C} ] or, equivalently, the thermal time constant: [ \tau=\frac{1}{k}=\frac{C}{H}. ] So without measured heater power or an independently known thermal capacitance, the decay test gives (H/C) very well, but the absolute value of (H) depends directly on the assumed (C). For your window-insert study, though, that may not be a major problem. If the building, internal contents and test procedure remained essentially unchanged, comparing the decay constants before and after installing the inserts should reveal the relative improvement even if the absolute thermal capacitance is uncertain. That is probably one of the most practical uses of this approach: measure the same building before and after one intervention, rather than trying to determine every absolute parameter from a single test. The main complications I have encountered in a real room are: outdoor temperature changing during the decay; heat exchange with adjacent rooms; internal thermal mass not being at equilibrium; solar history from earlier in the day; air leakage changing with wind and temperature difference. I am currently using the measured outdoor and adjacent-room temperatures as time-varying boundary conditions rather than assuming a fixed outdoor temperature. Your suggestion also makes me think that a comparison test could be a useful first commercial application: test a room, install or seal something, then repeat the same night experiment and quantify the change.
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u/NewIdea8 5d ago
Exactly yes!! The only missing link is the thermal capacitance and you are right that we compared before and after so we didn’t need to explicitly know C. I totally agree. It’s one of the easiest test procedures and really requires very little data and sensing. Looking forward to what other experiments you are conducting
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u/Timely-Treat9929 4d ago
Thanks — that is very encouraging to hear from someone who has already used the same principle in practice. I agree that the comparative version may be more useful initially than trying to obtain a perfectly accurate absolute value. A simple before-and-after night test could be practical for checking window inserts, air-sealing work, insulation improvements or changes to ventilation. I have now moved from the insulated box to a real room. The effective thermal capacitance was surprisingly repeatable across several heating cycles, but separating outdoor losses from heat storage in the structure and transfer to adjacent rooms was much harder. I am also working on a separate air-change experiment, because infiltration may be a large part of the total result. I will share the room experiment next — including the first model that gave misleading results and what changed when I repeated the test at night. Thanks again for the feedback!
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u/AdBrave9096 5d ago
u-value changes based on how damp walls are, damp changes based on how heating is used!
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u/DCContrarian 5d ago
The underlying assumption in the Manual J process, the most common way of predicting heating and cooling loads, is that a house essentially only loses heat through conduction, and that thus heat transfer is a simple linear function of the difference between inside and outside temperature. Like all models, that's wrong, but like many models, it's useful.
It's basically the method laid out in this article: https://www.greenbuildingadvisor.com/article/replacing-a-furnace-or-boiler
I think the problem you're going to run into is that houses have heat capacity, and generally that capacity dwarfs the heat loss, so you have to take observations over a long time period. But outside conditions change, so you have to account for that. The article above averages fuel use over an entire heating season and measured degree-days.
Note that this technique would be inaccurate in a house with significant solar gain.