Posts Tagged ‘EWI’

In the bleak midwinter

January 19, 2021

So here we are in the bleak mid-winter – the place that everyone with External Wall Insulation loves to be.

As I remain-at-home-to-protect-the-NHS-and-save-lives I have spent a great deal of time staring at the following graph which shows the impact of the triple-glazing and External Wall Insulation.

Click for a larger vsrsion. Plotted in blue against the left-hand axis, the average daily consumption of gas (kWh per day) This is shown against the left-hand axis. Plotted in green against the right -hand axis is the average difference of the outside temperature from 19 °C (°C).

The graph shows two quantities plotted versus the number of days since the start of 2019.

  • In blue, I have plotted the average daily consumption of gas (kWh per day)
    • This is shown against the left-hand axis
  • In green, I have plotted the average difference of the outside temperature from 19 °C (°C)
    • This is shown against the right-hand axis

The dotted red line shows the weather now (circled in green) is colder than it was at this time two years ago.

However the amount of gas (circled in blue) that I am using to maintain the temperature of the house is now about half what was then: just over 50 kWh per day now versus just over 100 kWh per day then.

The carbon dioxide emissions associated with heating the house look set to be about 1.25 tonnes this winter – still a terrible figure – but much lower than 3 tonnes emitted in the winter of 2018/2019.

To go further we need to ditch the gas boiler and switch to a heat pump. Hopefully we will achieve this in the summer and then we can reasonably hope that next winter we will lower the carbon dioxide emissions associated with heating the house to about 0.4 tonnes – just 13% of what it was in 2018/2019.

 

 

External Wall Insulation: Day-by-Day analysis

January 1, 2021

Happy New Year 2021!

Please note:

  • A list of related articles is given at the end
  • This article was amended around 12 hours after it was posted to take account of heating effect of the people living in the house!
  • Thanks to Ed, Simon and Geoff for noticing. And caring!

At around the time that the External Wall Insulation (EWI) was being applied to my house, I also had my electricity and gas meters upgraded to “Smart Meters”.

This gave me access to daily readings of gas and electricity consumption in kilowatt hours (kWh). I could get these readings in two ways.

  • The hand-held readout unit shows daily readings for the last 7 days.
  • After 3 days, the readings became available on the EDF web site, either to view directly as histograms, or to download as a spreadsheet.
  • Readings could be downloaded as daily data month-by-month, or half-hourly for any particular day.

From analysing this daily data I discovered something so obvious it was surprising!

What does the data look like?

The graph below shows the daily gas consumption (kWh gas consumed) plotted versus day-of-the-year

Click for a larger version. Graph showing daily gas consumption (in kWh) versus day of the year 2020

Initially I did not quite trust this new-fangled technology so I also plotted my weekly gas consumption readings expressed as a daily average. These are shown as solid blue lines on the above graph. Taking parallel overlapping readings showed me that in general I could trust the readings. Also shown are the 7 weeks of the EWI installation.

The daily readings do appear to generally make sense, but there were two days – days 298 and 329 – where gas consumption appears to have been zero: I think these are mis-readings.

To put the vertical scale into context, 24 kWh is the energy used by a 1 kW heater left on all day. So the vertical scale (100 kWh/day) is equivalent to just over 4 kW of continuous heating.

Each kWh of gas consumed results in the release of around 0.2 kg of carbon dioxide. So the full-scale 100 kWh/day would be equivalent to 20 kg per day of carbon dioxide. Total emissions over the period shown are just over 500 kg – more than half a tonne!

Weather

Whether the graph above represents good performance or not depends on how cold the weather was.

Our internal thermostat is set to 19 °C and so I assess the temperature ‘demand’ as being the difference between 19 °C and the average daily external temperature.

Below I have plotted the gas consumption data against the left-hand-axis, and additionally plotted temperature demand data against the right-hand axis.

Click for a larger version. Graph showing daily gas consumption (in kWh : left-hand axis) and temperature demand (in °C :right-hand axis) plotted versus day of the year 2020

The first thing to notice is how closely the curves correlate. Unsurprisingly, gas consumption directly follows temperature ‘demand’.

The second thing to notice is that after day 312, the gas consumption curve is much lower down: – there is a clear ‘gap’ between the temperature demand data and the gas consumption data.

Day 312 marked the point where the kitchen roof was sealed, marking the sealing of the building envelope.

Taking data only from Day 312 onward should allow me to assess the building performance by plotting gas consumption versus temperature demand. This graph is plotted below.

Click for a larger version. Graph showing daily gas consumption (in kWh) versus temperature demand (in °C). Notice that the best-fit line does not go through the origin.

The data make a pleasing straight line, something which is rarely a coincidence. But two things are puzzling.

  • The first puzzle is that the graph does not go through zero – or even near it! This implies that when the average daily temperature is 15 °C outside we require no heating!
  • The second puzzle is that the slope is 4.6 kWh per day per degree Celsius which is equivalent to 192 W/°C. This is considerably more than the 134 W/°C that appeared to describe the weekly data that I showed in my previous post.

The first puzzling thing 

I think the answer to the first point is that I have assumed that the heating inside the house is only due to gas consumption but in fact there are other sources of heating.

The electrical energy used in the house also warms the house. Indeed, in one perspective, one can view all electrical appliances as heaters, each with its own additional functionality as a computer, a light, or a radio etc.

So in the graph below I have plotted daily [gas + electricity] consumption versus demand. The data have the same slope – because electricity consumption is roughly constant day upon day – but the intercept is now closer to zero – indicating zero demand with an external temperature deficit of 2 °C. But this is still not zero.

Click for a larger version. Graph showing daily gas consumption + daily electricity consumption (in kWh) versus temperature demand (in °C). Notice that the best-fit line is closer to the origin.

However there are two more corrections. Over the period plotted, my newly-installed solar panels were generating on average 2.4 kWh per day, 60% of which (1.4 kWh) was used in the house rather than exported.

This 1.4 kWh/day does not show up on the electricity meter. Including this additional term we arrive at the graph below. This suggests zero demand with an external temperature deficit of 1.5 °C.

Click for a larger version. Graph showing daily gas consumption + daily electricity consumption + solar energy (in kWh) versus temperature demand (in °C). Notice that the best-fit line is even closer to the origin.

Finally, (and thanks to Ed, Simon and Geoff for pointing this out) we need to take account of the heating by the two human beings living in the house.

My wife and I each eat a nominal 2000 kilocalories per day (8.4 megajoules per day) and most of that energy ends up as heat. This 8.4 MJ per day corresponds to 2.3 kWh per day each i.e. we are each roughly  equivalent to a 100 W heater. So in a very real sense, our love will keep us warm. Allowing for this effect the best fit line now passes very close to the origin.

Click for a larger version. Graph showing daily gas consumption + daily electricity consumption + solar energy + body heat (in kWh) versus temperature demand (in °C). Notice that the best-fit line is even closer to the origin.

The best-fit line still describes the trend of the data well, but is now (within plausible experimental uncertainty) consistent with my belief that there should not be an offset.

Overall, I take this data as evidence for the validity of the obvious: that the heat from all the electrical appliances and the people in the house really does heat the house. I have known this intellectually, but this is the first time I have ever seen specific evidence that this is the case.

So I find this both completely obvious, but also somehow surprising – because I wasn’t looking for it!

The second puzzling thing 

  • So taking account of the first puzzling thing, I conclude – from analysing around 50 days of data – that the house takes 4.6 kWh/day/°C [192 W/°C] to maintain 19 °C.
  • But in the previous blog I concluded – from analysing two year’s worth of weekly data – that the house performed better, requiring less than 3.2 kWh/day/°C [134 W/°C] to maintain 19 °C.

Which of these do I believe? Sadly, I believe the worse of these two estimates.

The model in the previous blog article took no account of roughly 10 kWh/day of electrical heating or the 2 x 2.4 kWh/day of body heating by my wife and I. While this may not have been significant a couple of winters ago when we used almost 100 kWh/day in winter, it is significant now that daily gas consumption is only (roughly) 35 kWh/day.

Thermal Models #1 and #2

So I have now made a new thermal model Model#2 – which incorporates the electrical heating.

The graph below compares the two models #1 (- – -) and #2 (- – -). They both predict the gas consumption in terms of the weather, and a parameter that describes the house insulation. But Model #2 takes account of the fact that electrical power dissipation and human bodies also heat the house.

Average Daily gas consumption in KWh per day for the last two years. Also shown are two models. Model#1  (- – -) predicts gas consumption based on the average temperature ‘demand’. Model#2  (- – -) predicts the same thing but takes account of the heating of the house by (a) electrical appliances estimated at 400 W continuously or 9.6 4.8 kWh/day. The constants of proportionality for each model are changed to allow the model to match the gas consumption in the winters of 2018/19 and 2019/20. Click for a larger version.

Overall Model#2 is slightly better than Model #1 at matching the gas consumption data – but more importantly it is based on the basic reality that electrical appliances and body heat really do heat the house!

The models differ in the constants of proportionality that they require to describe the thermal insulation. In the graph above I have changed the constant of proportionality around Day 250 – when most windows were triple-glazed – and around Day 660 – when the EWI commenced.

  • In the winter of 2018/2019 model#1 suggests it took 280 W ( 6.7 kWh/day) of continuous power for each 1 °C above the external temperature.
    • Using model#2 the data is better described by a figure of 350 W ( 8.4 kWh/day) per °C
  • In the winter of 2019/2020 model#1 suggests it took 240 W of continuous power (5.7 kWh/day) for each 1 °C above the external temperature
    • Using model#2 the data is better described by a figure of 300 W ( 7.2 kWh/day) per °C
  • In this winter of 2020/2021 I had hoped the EWI would mean I needed only 134 W (3.2 kWh/day) of continuous power for each 1 °C above the external temperature.
    • Using model#2 the data is better described by a figure of 192 W ( 4.6 kWh/day) per °C

Summary

Looking at daily data, I found that a graph of gas consumption versus temperature demand did not go near the origin unless I took account of the heating due to the electrical appliances and the people living in the house.

  • Although this is obvious, this is the first time I have ever seen data which demonstrated this to be the case.
  • Essentially, I have turned my house into a calorimeter!

Taking account of this suggests that my house currently requires 192 W to heat it 1 °C above external temperature. This is 43% higher than 134 W/°C I had hoped for.

One obvious factor which I had not considered until it was pointed out in the comments on this article is that gas boilers are not 100% efficient. Typically, they are only around 90% efficient.

I will consider the impact of this effect, and other possible explanations in another article – watch this space!

Previous articles on this topic

2020

2019

 

External Wall Insulation: How well is it working?

December 23, 2020

How well is my External Wall Insulation (EWI) working?

I am so glad you asked. The EWI installation by Be Constructive was completed in November and at this point in the winter, it appears to have reduced gas consumption by “about 50%.”

In this article I will show you the results of my measurements so far and explain how I made this estimate.

You can find previous articles on this topic listed at the end of this article.

Measurement#1: Reading the Gas Meter

In my house, we use a gas boiler for hot water, room-heating via radiators, and for cooking. I have been reading the gas meter weekly for the last two years or so (see graph below) and the strong seasonal variation is associated almost entirely with heating the house in winter.

Gas consumption in KWh per day for the last two years. The data are averaged over 5 weeks to smooth out the noise. The pink boxes show the dates of key interventions which I think affected gas consumption Click for a larger version.

It is pretty clear that this winter I am using considerably less gas than in previous winters. Also we can see a decline in gas consumption after day 660 when the installation of the External Wall Insulation (EWI) began.

To put the scale in context, using 24 kWh per day is equivalent to having a 1 kW heater on for 24 h. So the peak demand of just over 100 kWh/day is equivalent to having a 4.2 kW heater running all day.

But perhaps the lower gas consumption is due to milder weather?

Measurement#2: Reading the External Temperature

To check for this I can plot the temperature ‘demand’ alongside the gas consumption. The demand is shown on the right-hand axis.

In case you haven’t seen these two curves plotted together before, I will just note how strong the correlation is.

With my wife’s consent, I have kept the thermostat location and setting (19 °C) the same for this period. So I plot how many degrees below 19 °C the external weekly temperature falls.

Gas consumption in KWh per day for the last two years as shown above. and average temperature ‘demand’ shown against the right-hand axis. The data are averaged over 5 weeks to smooth out the noise. The pink boxes show the dates of key interventions which I think affected gas consumption Click for a larger version.

This winter the temperature ‘demand’ so far appears to be similar to last winter with average temperatures around 8 °C i.e. 19 – 8 = 11 °C of demand.

But instead of 70 kWh per day of gas, I am using just under 40 kWh/day. So gas consumption appears to be about 43% lower.

However we use around 5 kWh of gas on cooking and water heating even in summer – so the space heating performance appears to be improved from 65 kWh per day to 35 kWh/day, i.e. the gas used for heating directly appears to be about 47% lower.

But the uncertainties on this figure are sufficient that I think “about half” covers it for now. I really need a whole winter of performance to get a better figure.

Thermal Model

Finally I can make a model (– – –) that predicts the gas consumption in terms of the weather, and a parameter that describes the house insulation.

Gas consumption in KWh per day as shown in the first graph, and a model (– – –) which tries to predict gas consumption based on the average temperature ‘demand’ shown in the second graph. The constant of proportionality for the model is changed to allow the model to match the gas consumption in the winters of 2018/19 and 2019/20. The constant for the current winter is based on what I had been hoping for.  Click for a larger version.

The model (– – –) assumes that the gas consumption is composed of two parts.

  • A year-round consumption of 5 kWh per day (equivalent to a continuous 208 W) on cooking and hot-water heating.
  • A weather-dependent part that is proportional to how far below 19 °C the external temperature falls.

The weather-dependent part has a constant of proportionality which describes how much gas power is used for each degree Celsius that the external temperature falls below 19 °C.

In the graph above I have changed the constant of proportionality around Day 250 – when most windows were triple-glazed – and around Day 660 – when the EWI commenced.

  • In the winter of 2018/2019 it took 280 W of continuous power for each 1 °C above the external temperature.
    • This corresponds to 6.7 kWh/day for each 1 °C above the external temperature.
  • In the winter of 2019/2020 it took 240 W of continuous power for each 1 °C above the external temperature.
    • This corresponds to 5.7 kWh/day for each 1 °C above the external temperature.
  • In this winter of 2020/2021 I hoped the EWI would mean I needed only 134 W of continuous power for each 1 °C above the external temperature.
    • This corresponds to 3.2 kWh/day for each 1 °C above the external temperature.

Looking at this winter’s data so far, the actual gas consumption is below the model (– – –) suggesting that the insulation is performing better than expected. The constant of proportionality is probably close to 120 W of continuous power for each 1 °C above the external temperature (or 3.2 kWh/day for each 1 °C above the external temperature).

So how well is my External Wall Insulation (EWI) working?

  • It’s performing roughly how I anticipated.

And so as the year ticks over I will add this project to the small pile of ‘Good things that happened in 2020’.

But I have – unwisely perhaps – been making more measurements – recording temperature and gas consumption day-by-day. And these more detailed measurements have been making me think I might not have understood things fully.

But all that is material for another article.

For now I wish anyone who has read this far, a Happy Christmas and a much improved 2021.

 

Previous articles on this topic

2020

2019

 

External Wall Insulation: How well does it work?

November 16, 2020

Be Constructive will probably finish my External Wall Insulation (EWI) in just a day or two, but I am already trying to see its effect, even as they apply the last coats of render.

So “How well does it work?”

I won’t have a definitive answer until later in the winter, but this article describes the procedures I am using and you can look at the preliminary data and come to your own – preliminary – conclusions.

The data  

I have written about this before (here, here, here and here!) but please allow me to recap.

To work out how well the EWI is working I measure two things:

  • the difference between external and internal temperatures, and
  • the amount of gas I use each day or each week.

For the last two years I have done this weekly – even I find it too tedious to read the gas meter every day!

But a few weeks ago – in the same week as the EWI work started – I switched to using a ‘smart meter’ and this allows me to download a spreadsheet with daily gas (and electricity) consumption. So now I can work with either daily or weekly averages of gas consumption.

I can then get either the daily or weekly average temperatures from the weather station I have in my back garden. If you don’t have a weather station in your garden then you can use data from nearby stations on the Weather Underground (Link: Zoom in to find weather stations near you).

So how do I use the daily and weekly data to estimate how well the EWI is working?

Weekly data

The graphs below are complex so I will describe each element in turn.

We start with my average daily gas consumption (blue squares) since November 2018. I have averaged the data over 5 weeks to remove anomalously cold or warm weeks. This makes it easier to view the general trend of the data.

My average daily gas consumption (in kWh/day) over the last two years. Click for a larger version and see the text for details.

The data are plotted versus days since the start of 2019, and several events which I think might have affected gas consumption are shown in pink.

  • Triple Glazing of most windows.
  • Installation of a chimney sheep.
  • Triple Glazing of remaining windows.
  • External Wall Insulation (EWI).

Notice that in the summers, gas consumption falls to around 5 kWh/day due to water heating and cooking, but that increases in the winter to as high as 100 kWh/day. It is the temperature-dependent part of this consumption that I think is related to the effectiveness of the insulation in the house.

Next we have a graph of the difference between the internal temperature (nominally 19 °C) and the average weekly external temperature over the same period. This is the ‘demand’ to which the gas central heating responds. Again, I have averaged the data over 5 weeks.

This data is plotted (green circles) on the same graph as the gas data, but should be read against the right-hand axis. Plotting the data in this way shows that the gas consumption is obviously related to external temperature.

Average daily gas consumption (in kWh) over the last two years in blue plotted against the left-hand axis and the difference of the average external temperature from 19 °C in green plotted against the right-hand axis. Click for a larger version and see the text for details.

It’s clear from the similarities between the two curves that the variation in winter gas consumption is due to the external temperature. I mention this extremely obvious fact because I was personally surprised by how similar the two curves were.

Model

My model of my house tries to predict the gas consumption based on knowledge of the weather, and a single parameter that describes all the ways that heat flows out of the house. This parameter tells me how many watts of heating power I need to keep the house 1 °C above the outside temperature. In case you are interested, the equations which summarise this are given in the figure below.

The mathematical model – in case you care. In the green background the heating power is expressed in kWh/day and in the blue background the heating power is expressed in W. Click for a larger version.

Initially I matched the model to the data using what is known in statistics as “the null hypothesis“i.e. I assume that nothing I have done has made any difference. So:

  • I adjusted the heat loss parameter of the model to match the data in the middle of the winter of 2018-2019.
  • The best fit is made by assuming I use roughly 280 W of gas heating for each °C that the external temperature fell below 19 °C. (That’s 6.7 kWh per day per °C)

The red dotted line (- – – ) shows the modelled gas consumption assuming that nothing I have done has made any difference. Click for a larger view.

With this assumption, it is clear that the model overestimates the gas consumption in subsequent winters: so it looks like the actions I took did have some effect i.e. the same demand has led to lower gas consumption. Phew.

To estimate how big an effect I modified the model so that the effectiveness of the insulation could be changed at two points: day 244 and day 657 shown as vertical pink lines in the graph below.

The red dotted line (- – – ) shows the modelled gas consumption assuming that the thermal performance of the house has improved from 280 W/°C in winter 2018/2019 to 240 W/°C in winter 2019/2020, to 134 W/°C in the current winter 2020/21 . Click for a larger view.

  • For the first section I assumed that I needed to use 280 W of gas heating for each °C that the external temperature fell below 19 °C.
  • For the second section I assumed that I needed to use only 240 W of gas heating for each °C that the external temperature fell below 19 °C – about 15% less.
  • For the final section – i.e. currently – I anticipate that I will need to use only 134 W of gas heating for each °C that the external temperature falls below 19 °C.

You can see that in the current winter (day 650 onwards) there is not yet enough data to say which value of heat loss parameter will best match the data.

Looking at previous years, the model does not match the data well in spring and summer – so I don’t feel I can definitively estimate the heat loss parameter until winter is fully upon us.

But the estimate of 134 W/°C – less than half what it was two years ago – does not (at this stage) look unreasonable.

Daily Data

I can apply the same model to the smart-meter data that I download from EDF which gives me my daily gas consumption. I can then compare this directly with the daily average temperature.

I expect this daily data to show added variability when compared to the weekly-averaged data because:

  • The ‘constant term’ – in my case roughly 200 W or 4.8 kWh per day – due to use of gas for cooking and heating water may look constant when averaged over 5 weeks. But it likely fluctuates from day-to day depending how much cooking or hot water is used.
  • In the short term, heat can be stored and released from the fabric of the building.
  • During the EWI works, there have been many days during which doors were open.

Also I must confess to a metrological faux pas in this article by using two units to describe the effectiveness of the insulation: watts (W) and kilowatt hours per day (kWh/day). Both are valid choices, but I will make penance for having used mixed units by showing graphs below in both sets of units!

With these caveats in mind, let’s look at the data.

Daily gas consumption in kWh/day (left-hand axis) and temperature demand (right-hand axis). The straight lines show weekly averages. Click for a larger version.

Daily gas consumption in terms of average power (W) (left-hand axis) and temperature demand (right-hand axis). The straight lines show weekly averages. Click for a larger version.

Notice the strong day-to-day correlation between gas consumption and average external temperature deficit.

I guess it is this strong correlation that allows gas supply companies to order the correct amount of gas in advance.

But the day-to-day data have oddities. For example, on some days the gas consumption seems anomalously low (e.g. days 298, 304 and 307), and on others anomalously high (e.g. days 294, 310).

Bearing these anomalies in mind we can divide the gas consumption data by the temperature deficit data to give the gas power per °C of ‘demand’. These graphs are shown below.

Gas power (in kWh/day) per °C of demand. The straight lines show weekly averages and the double line (===) shows the running average (±3 days). The dotted red line (– – – ) shows the level I hope to achieve. Click for a larger version.

Gas power (in W) per °C of demand. The straight lines show weekly averages and the double line (===) shows the running average (±3 days). The dotted red line (– – – ) shows the level I hope to achieve. Click for a larger version.

The daily data show too much variability to allow easy interpretation. But looking at the running average and the week-to-week data it looks like there is a trend downwards towards improved thermal performance over the course of the EWI works

However there are considerable uncertainties.

  • These data take no account of the non-thermal use of gas.
    • For example, heating 50 litres of water a day from 10 °C to 50 °C would use 2.3 kWh/day, the energy of which would substantially go down the drain
  • Similarly, at these low power levels, I should probably be taking account of:
    • The roughly 11 kWh/day of electrical power that we consume.
    • The roughly 4 kWh of heating provided by the warm bodies of myself and my wife.

So…

So it will take time before I can definitively evaluate the effect of the EWI. But by spring 2021, I suspect that I will have stared at the data long enough that the best way to analyse the data will have become clear to me. I hope so!

The reason it matters is that next year I plan to stop using the gas boiler altogether and switch to using an air source heat pump. Before spending yet more money on that I am keen to try to anticipate the likely demand so I can pick the right model!

Meanwhile, I am positively enjoying the EWI. I don’t know if this is a psychological effect of spending large amounts of money on something – or a genuine sensation caused by a more stable temperature and – I think – reduced air leakage.

And although still clad in scaffolding, the house itself is beginning to look rather smart. I’ll be sure to post some pictures when the Be Constructive team have left.

 

External Wall Insulation: the project begins…

October 15, 2020

I just wanted to take a moment to let people know that amidst the world’s problems, good stuff is happening.

And for me that good stuff is the start of installation of my long-awaited External Wall Insulation.

The idea of insulating a house from the outside is very simple in principle. In fact it is obvious. But in practice there are many steps required to ensure a weather-proof installation that will look smart when finished and last for a long time. That’s why I have hired the professionals at Be Constructive to do it!

Here are some pictures of the project in progress.

The back of my house. Click for a larger view

The picture above shows the general view of the back of the house with the insulation partially applied. Notice the dark red paint on the existing wall which enhances the adhesion of the insulation and the way the insulation is carefully cut out around the windows and the external tap and water drain.

The picture below shows the external tap and drain which have been extended beyond the thickness of the insulation. Expanding foam has been used to keep the system air-tight.

Detail showing the way the external pipes are extended to allow for the insulation. Click for larger version.

The picture below shows more detail of the window including the protective films applied during construction. You can see white ‘webbing’ around the windows which is called an ‘APU bead’ and its clever function (described in this video) is to give a neat seal between the window and the render.

Details of the insulation around a window. Click for a larger version.

The picture below details of the way the insulation is initially applied to the wall. The insulation consists of two boards of 50 mm thick Kingspan K5 which have been glued together to make a ‘dual-board’ which is 100 mm thick. This ‘dual-board’ is then stuck to the wall using an adhesive mortar. When this is dry – perhaps tomorrow? – the boards will be mechanically fixed to the wall using low thermal conductivity supports.

Details of the way the insulation is initially stuck to the wall. Click for a larger version.

Having considered this for this for such a long time, I am very excited to finally be making progress.

Within a few months I will find out whether or not my calculations were correct! I will keep you updated.

Previous articles on this topic

2020

2019

Intuition and Experience

June 23, 2020

Or how thermal modelling taught me to appreciate the obvious.

It is a special kind of pleasure to find one’s intuition about something to be seriously wrong.

I recall the pleasure at learning what happened when one dropped a stretched slinky spring – check out the video if you haven’t seen it.

And concerning the pandemic I am still realising that despite being well-informed and numerate, I really have no intuition about what is happening. On 27th March I wrote “Well, I didn’t see this coming” – and on 25th April – with 10,000 deaths I thought we were ‘about halfway‘. 

But even much closer to home – in the realm of thermal physics – I can still get things spectacularly wrong. Which brings us to today’s case in point.

External Wall Insulation 

For some time now I have been on a quest to reduce the carbon footprint of my house: just heating the house has led to a shameful 2.5 tonnes of CO2 emissions per year.

So I have made a thermal model of the house and identified a sequence of steps to achieve as close to carbon-neutral operation as is feasible. Those steps are:

  • Triple Glazing
  • Draught-proofing
  • External Wall Insulation
  • Possible mechanical air flow with heat recovery
  • Replace gas boiler with heat pump
  • Add solar panels and a battery

Steps one and two are almost complete and my measurements show that they have had the expected 10% reduction in heat flow – more on how I estimated this in a follow up article.

Now I have been considering external wall insulation. As this authoritative literature review makes clear, it is difficult to assess the performance of heat transfer through walls, and so it is difficult to assess the effectiveness of EWI. So in addition to the long term energy monitoring that I undertake, I thought it would be useful to do a specific experiment to test heat flow through my walls

My External Wall Insulation Experiment

I thought I would install some EWI with embedded temperature sensors to try to understand the likely effect. 

So back in January I bought two 50 mm thick polystyrene panels and stuck to them to the external wall of the house with temperature loggers monitoring the internal temperature, the external temperature and the temperature at the junction between the wall and the insulation.

Click for a larger view

I set the loggers to monitor every 10 minutes and left them for the month of February during which external night-time temperatures reached 0 °C. The data are shown below:

Data showing the internal (red), external (blue) and interface (green) temperatures measured every 10 minutes during the month of February 2020. Click for a larger view.

When I recovered the data I discovered that to my surprise, the 100 mm thick external wall insulation appeared to make almost no difference! The temperature underneath the insulation was much closer than I expected to the external temperature!

I was puzzled.

Then the reason dawned on me. I had used to my “intuition” to assume that having a panel 450 mm high and 1000 mm wide was a enough area to minimise “edge-effects”. 

My “intuition” told me that heat flow would be perpendicular to the wall: like this:

Click for a larger view

But I was wrong. The heat flow is much more like this:

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In retrospect, the reason is easy to appreciate. The thermal conductivity of brick is around 0.8 W/m/K but the thermal conductivity of polystyrene is 24 times lower. In fact the insulating properties of polystyrene are so good – and so different to the properties of brick – that heat from the house  reach the external environment more easily by flowing “upwards” through 225 mm of brick than it can “outwards” through 100 mm of polystyrene.

Just to be sure, I then wrote an elaborate two-dimensional simulation to verify my new experience-based “understanding”. Or dare I call it, my new “experience-based intuition”? And sure enough the model showed clearly that heat was flowing easily through the walls.

The model considered a 500 mm x 500 mm cross-section of the wall as being made 60 x 60 =3600 small elements, each just 8.3 mm square.

It then considered second-by-second the heat flow from each element into its neighbours, depending on their relative temperatures, and the thermal conductivity and heat capacity of brick, air or polystyrene. After about an hour of run time, several days of real time had been simulated.

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I arranged to colour the elements of the model by their temperature in 0.2 °C steps to produce contours. This showed clearly that in the region of the interface sensor, much more heat was flowing vertically along the wall and around the polystyrene, than was flowing “outward” through it.

My Conclusions

I have come to three conclusions.

Firstly, and most generally, my capacity for stupidity is depth-less and humiliating: Intuition is only useful when combined with experience.

Secondly, I have been reminded that measurement is what connects us to reality – it is indifferent to our predispositions or expectations. That’s why I love it!

Thirdly, I will just have to insulate the entire house and then measure the effect! I will write later about my plan to achieve that.

And finally, I have been reminded of the ingenuity of my colleagues at NPL who built systems for actually measuring properly what I have tried so inexpertly to measure – heat flow through building structures.

As building insulation and windows have improved, it has become harder and harder to make actual measurements of the thermal performance of building elements as opposed to making (possibly optimistic?) calculations.

But my NPL colleagues persisted until their unique facility was put in a skip a couple years ago. Really? Indeed. Sadly, NPL management couldn’t think of a way to make money from it!


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