YouTube Star ‘Rocks’ Math (Schwetzingen Newspaper)

“30kg of plastic has been found in a blue whale’s stomach: how much would that be if a person swallowed just as much proportional to their own bodyweight?” Tom Crawford from Oxford began his guest lecture at Hebel-Gymnasium with this question. The students calculated that you’d find six (empty) plastic shopping bags in a human stomach. The other results worked out over the course of the entertaining presentation were also very impressive.

Tom Crawford doesn’t just have rock music as a hobby, rather with his tattoos and piercings, he looks like a rockstar too – though his tattoos are all to do with maths: since for example, the decimal places of “e” (Euler’s number) wind around his arm, the number pi is also encoded in an infinite series. On his YouTube channel “Tom rocks maths”, he presents science in an entertaining way – sometimes even pieces of clothing fly off during stripteases: “I want to show that maths isn’t always just super serious but it can also be fun.”

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The mathematics lecturer is currently part of the Heidelberg Laureate Forum in Heidelberg. This is where the best maths and computer scientists in the world are meeting up with junior researchers and journalists. Crawford came to Schwetzingen at the invitation of maths teacher Birgit Schillinger. He brought along some exciting questions. The common theme was Tom’s favourite number, pi, which is used in so many formulas. How many ping pong balls are needed to lift the sunken Titanic off the ground? Which factors are involved when a footballer bends a ball so that it flies in an arc past the wall into the goal? When calculating the trajectory, several physical variables play a role. But how? Crawford studied the mathematics behind it. His doctoral thesis was on fluid mechanics: What path does a river take when it flows into the sea? The findings help us to understand sea pollution and possibly help to stop it.

At the end, the Hebelians made Platonic solids, of which, amazingly, there are only five. Strange? No, Tom explains this number by the sum of the angles at the corners – all very logical! Finally a student’s question, which example in mathematics has impressed Tom the most: “It is terrific how the wave characteristic of light follows from Maxwell’s equations, which deal with electricity and magnetism, with only the help of mathematics. Maths is just awesome!”

Birgit Schillinger

Thanks to Cameron Bunney for the translation.

The original article in Schwetzingen can be found here.

Reducing Ocean Pollution using Maths

80% of marine pollution comes from the land via rivers, and so by understanding where river water goes, we can focus our clean-up efforts on the most susceptible areas. Live interview with BBC Radio Oxford.

Come and watch me explain my research in full detail at New Scientist Live on Friday 11th October 2019.

My PhD Thesis

My PhD thesis on modelling the spread of river water in the ocean in its entirety – not for the faint hearted! Unless you are a researcher in fluid mechanics, I strongly recommend reading the summary articles here before tackling the beast below. If you have any questions/comments please do get in touch via the contact form.

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Nailing Science: The Maths of Rivers

Creating scientifically accurate nail art whilst discussing my research in fluid dynamics with Dr Becky Smethurst and Dr Michaela Livingston-Banks at the University of Oxford.

We recorded 1h30mins of footage, so this is the heavily edited version of our chat ranging from the fluid dynamics equations needed to describe the flow of water in a river, the Coriolis effect, the experimental set up replicating this, and how these experiments can help with the clean up of pollution.

How Plesiosaurs Ruled the Ocean using their Flippers

Plesiosaurs ruled the oceans during the time of the dinosaurs with specially adapted flippers that enabled them to swim faster and with greater efficiency than any other animal. Luke Muscutt studied the 4-flipper arrangement by conducting experiments at the University of Southampton to investigate exactly how it all worked…

With thanks to the UK Fluids Network and the Journal of Fluid Mechanics for supporting this video.

Size matters when it comes to speed

How fast should an animal be able to move? And why are the biggest animals, which pack more muscle, not the fastest? That’s what Yale scientist Walter Jetz was wondering, so he and his colleagues looked at hundreds of animal species and have come up with a new theory that successfully puts a speed limit on most species…

  • There is a theoretical maximum speed that is expected to increase with body size,  however, in order to actually get to any speed you need to first accelerate, and larger animals take much longer to do so – much like a truck accelerating to 60mph compared to a motorbike or car.
  • Large bodied animals simply do not have sufficient energy to reach their theoretical maximum speed.
  • The general distribution is a ‘hump-shape’ as shown in the plots below. Maximum speed increases with size until we reach a critical mass beyond which the maximum speed reached starts to decrease.

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  • Data for over 450 species were included in the study, across land, air and water.
  • The study provides insight into evolutionary trade-offs for different species as they evolve to increase their chances of survival.

You can listen to the full interview with the Naked Scientists here.

Image copyright Dawn Key

 

Glow in the dark corals

I went along to the Royal Society Summer Exhibition to meet coral expert Jorg Wiedenmann and to see his collection of glow in the dark corals…

  • Tropical corals live all over the world including the Great Barrier Reef, the Caribbean and Fiji.
  • The corals glow in a wide range of colours including various shades of green, yellow and red.
  • Corals are in fact animals and belong to the same species group as jellyfish and sea anemones.
  • Corals in a colony will extend their tentacles in unison to capture prey such as tiny crustaceans or little fish and then use stinging cells similar to jellyfish and sea anemones before feeding on them.
  • The sensitivity of corals to changes in their environment means that they are ideal for studying human impact on the climate.
  • Glowing pigments can be used as a fluorescent dye in biomedical research to understand how diseased cells work and to test new drugs.

 

You can listen to the full interview for the Naked Scientists here.

Spinning a Giant Fish Tank

Yes, you read that correctly. I really did spend a good chunk of the 4 years of my PhD spinning a giant fish tank. This isn’t just any old spinning fish tank though, as you may have guessed, it was specially designed to represent the real-world scenario of a river discharging into the ocean, but on a manageable scale in the lab. So what does such a setup look like? Well, below is a diagram of the tank, taken from my thesis (please excuse my crude drawing in Microsoft Word – it’s harder than you might think).

Let’s start with the tank itself. It’s made from acrylic (basically plastic) and is 1m x 1m with a depth of around 60cm, though it was only filled to 40cm with salt water. As you can see in the diagram, the tank is actually divided up into two sections by an internal barrier. The reason for this was to allow the source structure to be attached to the outside of the tank – I wasn’t allowed to drill holes into the actual tank despite all of my protests… It had to be attached in this way to allow the freshwater from the model river to flow into the main tank which contained the salt water in the model ocean.

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The freshwater is stored in the reservoir (a plastic box) attached to the top of the metal structure surrounding the whole setup. This is to provide stability once the whole thing starts rotating, and also I assume to prevent things from flying off and hitting me. The river water flows out of the reservoir down a pipe and enters into the source structure. The amount of water released is controlled by a flow meter and an electronic switch. Once in the source structure, the water begins to accumulate until it resembles a flowing river and then it is released into the ocean (saltwater ambient). The water continues to flow throughout an experiment, much like a real river.

This all happens of course whilst the whole thing is spinning on a giant turntable. Turntable is an appropriate name because it basically just looks like a giant set of DJ decks (with only one disc a metre across). The speed is controlled by a computer and it can go pretty fast, trust me. Before the electronic switch was installed to start and stop the flow of freshwater from the reservoir, I used to have to climb up a ladder and flick the switch manually as it went spinning past. This was fine for the low speeds, but once things started speeding up I couldn’t flick the switch without knocking the entire structure which disturbed all of the measurements I had made. The only answer was to basically climb onto the structure myself and hang off the side whilst it went spinning round at high speed. If anyone ever saw me doing that I’m pretty sure I would have been thrown out of the lab, but hey when science calls ‘you gotta do what you gotta do’.

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Now the source structure (shown in the diagram and picture above) was quite the piece of engineering… by which I mean an absolute nightmare to design. Most of the first year of my PhD was spent trying out different designs until finally we found one that gave a discharge that looked like an actual river. If the stream comes out too strong then it looks like a jet – think about squirting a hose in your garden. If it’s not strong enough then it’s just a point source – like a sponge slowly leaking out water. Neither of which represent a river. The trick was to feed the pipe carrying the freshwater into an l-shaped box filled with foam. The combination of the shape, plus the presence of the foam, meant that the box would become sufficiently filled with water before any of it exited into the ocean. It was key that the box filled up above the depth of the opening into the saltwater, so that the depth of the water when it left the source was known (and equal to the depth of the opening). We need to know this initial depth because the depth of the freshwater as it enters into the ocean is incredibly important in determining the properties of the current that forms, but that ladies and gentleman is another story for another day.

 

All of the articles explaining my PhD thesis can be found here.

How to build a river in the lab

My thesis is based on experiments. A weird thing for a mathematician to say you might think, but that’s the truth. It was always planned to be experimental in nature – it even says so in the title – and that’s because it isn’t practical to go to the nearest large scale river outflow (for my work that would be the Rhine in the Netherlands) and start trying to measure things. Fieldwork works well on a Geography trip: you put your wellies on and start splashing around in a stream, measuring the depth with a metre ruler and the speed of the stream by timing a little paper boat as it sails downstream… But things aren’t so easy when you’re talking about a river several kilometres wide and tens of metres deep. The bigger rivers are harder to measure, but the big rivers are precisely the ones that we need to look at, because they’re the only ones big enough to be affected by the earth’s rotation. But we’ll come to that. First up, how do we recreate a big river in the lab?

The trick is to scale things down, as you may have guessed, but there’s a little more to it than just building a scale model of a river. Those little wooden models of a city or building that architects use to help see how their plans will come to life are scale models of the real thing: they are built the same, just with all measurements at a ratio of 1:500 say of the real distances. For example, if a real-life football pitch is 100m in length and 75m wide, then for a 1:500 scale model it would be 20cm long and 15cm wide. A scale model is a good idea in principal, but when working with rivers that are 1km wide and 10m deep, once you scale it down to lab-size, your depth is about as thin as a piece of paper, which isn’t practical. We have to be a little cleverer as mathematicians and think about what properties of the river are the most important and then only include those in our lab model.

I’ll give you an example. Let’s suppose we are trying to work out how fast Usain Bolt travels when he runs the 100m. For ease of the numbers, we can say he runs 100m in 10.0 seconds (a slow day for Usain – he’d had a few too many chicken nuggets before the race). There are many other factors that will affect his speed:

  • The wind was blowing at a speed of 1m/s against him
  • It was raining
  • He was wearing a waterproof coat (he forgot to remove it)
  • His bodyweight was 2kg higher than normal (those damn chicken nuggets)
  • One of his shoes was missing a spike
  • The race was in Brazil

We know that all of these things will affect Usain’s speed, but which do we actually think are important enough to include them in our model? If we ignore them all then at a first guess, we can just use the speed = distance/time triangle from school which gives 100/10 = 10m/s. This would be a first order estimate using just two properties: time and distance. If we want to include more information and get a more accurate answer, then maybe we can include the wind speed: 1m/s against him means he must run at 11m/s to cover 100m in 10 seconds. This is an increase of 10% on our first estimate of his speed, and so probably quite important. Because of the direction of the wind the rain will act against him too, though probably by only a very small amount. The coat will increase the air resistance slowing him down, but again probably quite small.

The key point here is that there are many factors that will affect the speed of Usain Bolt as he’s running the 100m, but as mathematicians our job is to figure out which ones are the most important and to only consider those. If we tried to model every small effect things would get very complicated very quickly and we don’t want that (trust me I’ve tried). Simple is good – so long as you don’t ignore the important bits…

For Usain’s speed we can probably keep the distance, time and the wind speed and that’s about it. Even if we included everything else I doubt the value would change very much from 11m/s, certainly by less than 10% which is a nice acceptable error that we can live with. For scaling rivers down to work with them in the lab we have to do the same thing: pick the important parts of the problem and ignore the rest. The key thing is picking the right bits – which we’ll come onto next time.

 

All of the articles explaining my PhD thesis can be found here.

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