Sunday, 26 July 2020
Wigton stained glass: why time is not symmetric
Look at the dove in this stained glass in St Mary's Church. Is it about to land or has it just taken off? From this still image it is impossible to tell. In that regard the situation is symmetric. It reminded me that in Physics, there is spatial symmetry in the laws but time has a direction.
Saturday, 25 July 2020
What is a seiche?
In 2013 I posted about an observation that the wind seemed to be driving the water of a lake to one end - I wondered about more water piling up at one end than the other. http://wigtonphysics.blogspot.com/2013/12/what-happens-to-all-that-water.html I was reading the wonderful old natural history book above and got a clue. They say that when the wind stops blowing, you get a low frequency oscillation of water backwards and forwards. The signifance in the book is that this mixes up fixed temperature layers in the water in a way that is significant to the organisms that live in the water. A bit of research shows that the phenomenon has a name: SEICHE https://oceanservice.noaa.gov/facts/seiche.html#:~:text=Seiches%20are%20typically%20caused%20when,for%20hours%20or%20even%20days. I think that the bit referred to in the book is probably an "internal seiche" https://link.springer.com/referenceworkentry/10.1007%2F978-1-4020-4410-6_160#:~:text=An%20internal%20seiche%20is%20a,opposite%20direction%20(Figure%201).
because this directly wobbles the layer that divides the upper mixed layer from the calm deep water beneath.
because this directly wobbles the layer that divides the upper mixed layer from the calm deep water beneath.
Thursday, 23 July 2020
Ductile near Birmingham
Ductile has been a word for which I've seen different definitions over the years. One was that it meant that a material could be pulled into a wire. Another was that it could undergo plastic deformation before breaking, which is important in enginnering because the material can absorb quite a bit of energy before breaking. There is some warning. https://en.wikipedia.org/wiki/Ductility mentions that this is due to metallic bonds and the way that atoms can slide past each other. But cast iron is brittle for that reason and steel has carbon inserted so that the layers can't slide over each other as easily. https://www.reliance-foundry.com/blog/difference-cast-iron-wrought#gref talks about cast iron having a heterogeneous internal structure which creates stress points. It talks about it having a high carbon content. So I've learned somehting new. Cast iron has more carbon in it than steel.
Wednesday, 22 July 2020
This week's updated Covid graph
I wasn't expecting to get data this week because of controversy about the figures being reported but it turns out that the Office for National Statistics (ONS) and the government department have different criteria for what to record. I have been using the ONS data. They explain the difference here https://www.ons.gov.uk/peoplepopulationandcommunity/healthandsocialcare/causesofdeath/articles/comparisonofweeklydeathoccurrencesinenglandandwales/uptoweekending03july2020#comparisons My log graph is still impressively straight.
What's a riffle? Ben Gill, Ennerdale
We were on Crag Fell in Ennerdale when I found this notice at the top of a precipitous stream called Ben Gill.
A bit of research found this https://www.therrc.co.uk/2011%20Conference/Poster%20-%20Quinlan.pdf Section 3 mentions sensors being put into a riffle. I'd never heard of one. I looked it up and found that it seems to be a shallow section in the flow of a stream, probably with a pool behind it. I'm wondering whether I found one that they had artifically created. However, this is shallow and narrow rather than shallow and wide so is perhaps a nozzle instead. So not a riffle but at least I know to look out for them now.Saturday, 18 July 2020
Weekly Covid log graph update and the upcoming data correction
I added the data point for the week that ended on 15 July. A 7-day rolling mean of 77 kept my line straight. Yesterday it was announced that new data was being suspended because of a controversy over what was being reported. Today I read in The Times that the deaths that might be removed from the statistics might account for 10% so I multiplied the numbers by 0.9 and replotted the graph - orange line above. Of course the gradient remains unchanged. If those deaths represent a fixed fraction then the numbers will not come down at a faster rate; they will just reach the bottom sooner because they started from lower. Since the issue is about people who had Covid and died over 28 days later, it won't quite be a constant factor though. More should have entered the statistics as time has gone by. This might change the gradient part way through.
Monday, 13 July 2020
Effective R number
It turns out that the R number that the government puts out is not the number who can potentially be infected by one person but the number who are actually being infected on average. I posted about the intrinsic "basic reproduction number" Ro and realised that this can never go below 1. Then I found this very clear explanation, not peer reviewed but written early in the outbreak. https://www.cebm.net/covid-19/when-will-it-be-over-an-introduction-to-viral-reproduction-numbers-r0-and-re/ It made a lot of sense to me. So there is an "effective reproduction number" Re and this is what the government are publishing. It gives an equation linking the two R numbers:
Re=Ro(1-Pi)
Where Pi is the proportion of the population who have developed immunity.
So if Ro=2.4, as has been assumed and Re is about 0.8 at the moment, you get Pi = 0.67. In other words, it would give two thirds of the population as being immune. This surely can't be the case. It must mean that the various distancing methods have worked to make the numbers be the same as if we were immune - a sort of virtual herd immunity. I think in Physics we'd call that an unstable equilibrium. It is nicely balanced but the removal of a key prop keeping it balanced would upset the current decline. Makes me keen to maintain the distancing measures.
Re=Ro(1-Pi)
Where Pi is the proportion of the population who have developed immunity.
So if Ro=2.4, as has been assumed and Re is about 0.8 at the moment, you get Pi = 0.67. In other words, it would give two thirds of the population as being immune. This surely can't be the case. It must mean that the various distancing methods have worked to make the numbers be the same as if we were immune - a sort of virtual herd immunity. I think in Physics we'd call that an unstable equilibrium. It is nicely balanced but the removal of a key prop keeping it balanced would upset the current decline. Makes me keen to maintain the distancing measures.
Friday, 10 July 2020
Using LED lights to set gel nail polish
I was intrigued by this machine which uses light emitting diodes to make gel nail polish set.
It turns out that the trick is that they emit ultra-violet light.
https://www.miladypro.com/home/b/nails/archive/2017/11/10/the-difference-between-uv-and-led-nail-dryers#:~:text=LED%20lights%20work%20similarly%2C%20but,cure%20much%20faster%20than%20UV.
The UV has the energy to get the molecules in the gel to turn into long polymer molecules - molecules made of repeating identical sections. This makes them turn from small molecules in a liquid to hard molecules in a solid. No mention of whether or not it is a cross-linking polymer but a little consultation of Google suggests it probably is.
Sadly not my nails! Thanks, Lydia.
It turns out that the trick is that they emit ultra-violet light.
https://www.miladypro.com/home/b/nails/archive/2017/11/10/the-difference-between-uv-and-led-nail-dryers#:~:text=LED%20lights%20work%20similarly%2C%20but,cure%20much%20faster%20than%20UV.
The UV has the energy to get the molecules in the gel to turn into long polymer molecules - molecules made of repeating identical sections. This makes them turn from small molecules in a liquid to hard molecules in a solid. No mention of whether or not it is a cross-linking polymer but a little consultation of Google suggests it probably is.
Sadly not my nails! Thanks, Lydia.
Thursday, 9 July 2020
Year 10 Acceleration equation experiment
Here's the data we need to work out the speed:
1. I lined up the 0cm end of the ruler with one side of the tin.
2. Then I looked straight down on the reading on the other side of the tin.
Notice that it doesn't look like the 0cm end is lined up correctly anymore. This is an example of parallax error. It is really lined up but doesn't look like it when you change the angle.
3. Here is the time for the diamter of the tin breaking the infra-red beam
4. We can now use velocity = distance/time to calculate the velocity of the tin at B in the original picture, at the bottom of the slope.
5. Next we need an equation:
6. We know the final velocity at B and the initial velocity at A. If we want to calcuclate the acceleration all we need to know is the distance that the tin rolled down the slope. There was a danger of parallax error at the bottom of the slope because the light gate was well above the ruler and I could read it at the wrong angle. So I used a smaller ruler to make sure that 0cm on my big ruler lined up the the light gate.
Then I looked at the top of the slope and got this reading for the distance the can rolled.
7. I put all of the readings into metres and calculated. I foundout that the acceleration was 1.4 m/s/s.
8. Then I realised that as the tin rolled along the floor it slowed down and stopped. I reaised that I could use the same equation to calculate the deceleration from B to C below.
All I had to do was to measure how far it rolled along the floor. Here's the reading
9. Friction caused it to decelerate and stop. This time I got -0.46 m/s/s. The minus sign means slowing down not speeding up. Acceleration is a vector so it can be negative as well as positive.
Wednesday, 8 July 2020
Covid graph update and the constant ratio property
This week the 7-day rolling average for Covid deaths reported in the UK is 87. I have added it to the graph. The gradient is the same as last week so the trend continues and the R-squared value is slightly higher so the trend is more certain.
Another way of assessing exponential decay is to look for a constant ratio property. This is when you do the current data point divided by the previous data point. The answer should be the same all the way down. Here's what I got:
The numbers have fluctuated a bit but the current mean ratio is 0.823. If the trend continues the prediction is that the 7-day rolling mean should be 72 this time next week.
Another way of assessing exponential decay is to look for a constant ratio property. This is when you do the current data point divided by the previous data point. The answer should be the same all the way down. Here's what I got:
The numbers have fluctuated a bit but the current mean ratio is 0.823. If the trend continues the prediction is that the 7-day rolling mean should be 72 this time next week.
Tuesday, 7 July 2020
Half-life experiment
Radioactive decay is a random process. The nuclei of the atoms of radioactive elements are unstable and can fall apart at any moment sending out radioactivity. This is called radioactive decay. You can't predict which nucleus will decay next in the same way that you can't know for certain whether one coin will come up heads or tails. But if you have a lot of coins or a lot of atoms then you can start to predict what will happen overall.
For this experiment I took 20 identical coins. I scooped them up into both hands and jangled them around to make them random before dumping them on the table.
I removed any that were "heads". They had "decayed and were no longer radioactive. I counted what was left.
Then I scooped up what was left and jangled them in both hands before dumping them on the table. I removed the heads and counted the rest and so on. For each throw, I wrote down how many I counted. In theory, you'd expect the number left to halve each throw. So we can't say which coins will be removed - it's random - but we can predict that half of them will be removed. You can't predict for an individual but you can predict for a large group. That's what half-life is for radioactivity.
In class I normally use 6-sided wooden cubes that I call dice. One side of each cube is marked. I do the same experiment but remove the ones that come out marked side up each time.
For this experiment I took 20 identical coins. I scooped them up into both hands and jangled them around to make them random before dumping them on the table.
I removed any that were "heads". They had "decayed and were no longer radioactive. I counted what was left.
Then I scooped up what was left and jangled them in both hands before dumping them on the table. I removed the heads and counted the rest and so on. For each throw, I wrote down how many I counted. In theory, you'd expect the number left to halve each throw. So we can't say which coins will be removed - it's random - but we can predict that half of them will be removed. You can't predict for an individual but you can predict for a large group. That's what half-life is for radioactivity.
In class I normally use 6-sided wooden cubes that I call dice. One side of each cube is marked. I do the same experiment but remove the ones that come out marked side up each time.
This time the chance of one being removed is much lower. It takes longer for the numbers to go down - more throws before the numbers halves. We'd say that the dice have a longer half-life than the coins.
Monday, 6 July 2020
A second momentum experiment
I went back and did an experiment with different masses. In the first experiment I rolled a half-sized tin into a full-sized one. They rolled but not far. Half the amount of momentum shared between one and half masses should mean that they move on at about one third the speed of the small tin coming off the slope.
I then did the experiment the other way round. You can tell from the photo clipped from a video that the tins are still moving. They ended up out of shot. The big tin leaves the slope with more momentum which it shares with the small tine. The resultant common speed is much larger.A big tin and a small tin will not leave the same ramp at the same speed. There are several issues there that will need some further exploring.
Friday, 3 July 2020
Momentum experiment
Any moving object has MOMENTUM. Momentum tells you how hard it is to stop a moving object. The higher the momentum, the harder to stop. You calculcate momentum by doing momentum = mass x velocity.
I got two identical tins from the kitchen. The more solid the contents, the better the experiment because if the liquid inside can slosh around, it can affect the movement of the tin.
I put tin A at the top of the slope and let it roll down the slope into tin B. Only tin A was moving before they collided so only tin A had momentum.
When tin A hit tin B, they both roled on a short way but at half the speed at which tin A was going originally. This is because only tin A brought momentum into the collision and now it has to share the momentum with tin B. Bceuase they are identical tins, each should get half the momentum and thus be going at half the velocity. After the collision, there is still the same total momentum as there was before but it now shared outl. Keeping the amount of momentum the same before and after is called CONSERVATION OF MOMENTUM. (It doesn't last long because this rule of Physics only works until friction on the carpet acts on the tins)Then I set up two ramps at the same height to create a head on collision. Tin A is coming towards us and so we say it has POSITIVE momentum. Tin B is going away so we say it has NEGATIVE momentum. Momentum has a direction so we say that it is a vector.
Now let's say tin A has momentum +10 and tin B has momentum -10. The total momentum means adding them together. +10 + (-10) = 0. So if momentum is conserved, there will be the same total momentum after the collision: ZERO total momentum. What happened was that the tins stopped dead when they hit each other so it turned out to be true.
If we did this with tinsof different mass they would not stop dead because momentum = mass x velocity so one tin would have more momentum than the other. Try it.
Year 10 Cup cake cases experiment
Take one cup cake case and hold it up as high as you can. Time it as it falls to the ground. Do this 3 times to check that the result is REPEATABLE. It should fall at roughly a steady speed because it has a small weight (pull of gravity) and a large surface area so it is easy for the air resistance (drag) to become so large that it is the same size but opposite direction to the weight. When this happens, the resultant force is zero and there is no acceleration so it falls at a steady speed called the TERMINAL VELOCITY.
Now put a second cup cake case inside the first. Hold it up as high as you can and drop it, timing the fall. The weight has doubled but the area is still the same so the only way the air resistance can double to achieve zero resultant force and terminal velocity is by going much faster.Keep adding cup cake cases, stacked inside each other to increase the weight whilst keeping the area the same.
Here is my graph. Notice the small random errors shown by points not quite on the best fit line. This is our third falling forces experiment and the pattern is still the same on the graph. It is further evidence that the theory of weight, air resistance and terminal velocity is true. The findings of the first experiment have turned out to be REPRODUCIBLE - same independent variable, same dependent variable, same control variable but different situation and yet STILL THE SAME PATTERN.
Wednesday, 1 July 2020
Covid graph update - back to the original gradient
I have been taking the data on a Wednesday for the 7-day rolling average. I used this site to calculate the average for the last 7 days and got 118, exactly the same as last week. I have added it to my graph and got Excel to calculate the trendline. It is now back to almost exactly the same trendline as when I first calculated it 3 weeks ago.
The points are now further from the line but that is often the case if Physics experiments that plot a graph like this for discharging a capacitor. When the current is low and there are fewer significant figures, the uncertainties are higher and points can be further from the line. This explains why the R-squared value is lower this week.