The Engineering Of The Falkirk Wheel

February 13, 2026 by Al Williams 4 Comments

We live in an age where engineering marvels are commonplace: airplanes crisscross the sky, skyscrapers grow like weeds, and spacecraft reach for the stars. But every so often, we see something unusual that makes us take a second look. The Falkirk Wheel is a great example, and, even better, it is functional art, as well.

The Wheel links two canals in Scotland. Before you click away, here’s the kicker: One canal is 35 meters higher than the other. Before 1933, the canals were connected with 11 locks. It took nearly a day to operate the locks to get a boat from one canal to the other. In the 1930s, there wasn’t enough traffic to maintain the locks, and they tore them out.

Fast Forward

In the 1990s, a team of architects led by [Tony Kettle] proposed building a wheel to transfer boats between the two canals. The original model was made from [Tony’s] daughter’s Lego bricks.

The idea is simple. Build a 35-meter wheel with two cassions, 180 degrees apart. Each cassion can hold 250,000 liters of water. To move a boat, you fill the caissons with 500 tonnes of water. Then you let a boat into one of them with its weight displacing an equal amount of water, so the caissons stay at the same weight.

Once you have a balanced system, you just spin the wheel to make a half turn. There are 10 motors that require 22.5 kilowatts, and each half turn consumes about 1.5 kilowatt-hours.

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Does This Electron Make Me Look Fat? Weighing An Electron

February 12, 2026 by Al Williams 5 Comments

[The Signal Path] shows us how to recreate a classic science experiment to measure the weight of an electron. Things are easier for us, because unlike [J. J. Thomson] in 1897, we have ready sources of electrons and measuring equipment. Check it out in the video below.

The main idea is to trap an electron using a magnetic field into a circular path. You can then compute the forces required to keep it in that circle, along with some other equations, and combine them. The result lets you compute the charge to mass ratio using parameters you can either control or measure, like the radius of the circular path and the electric field.

Helmholtz coils create the magnetic field, and a cold cathode tube provides the electrons. Honestly, the equipment looks a bit like something out of an old monster movie.

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Bash Via Transpiler

February 12, 2026 by Al Williams 9 Comments

It is no secret that we often use and abuse bash to write things that ought to be in a different language. But bash does have its attractions. In the modern world, it is practically everywhere. It can also be very expressive, but perhaps hard to read.

We’ve talked about Amber before, a language that is made to be easier to read and write, but transpiles to bash so it can run anywhere. The FOSDEM 2026 conference featured a paper by [Daniele Scasciafratte] that shows how to best use Amber. If you prefer slides to a video, you can read a copy of the presentation.

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PROFS: The Office Suite Of The 1980s

February 11, 2026 by Al Williams 10 Comments

Today, we take office software suites for granted. But in the 1970s, you were lucky to have a typewriter and access to a photocopier. But in the early 1980s, IBM rolled out PROFS — the Professional Office System — to try to revolutionize the office. It was an offshoot of an earlier internal system. The system would hardly qualify as an office suite today, but for the time it was very advanced.

The key component was an editor you could use to input notes and e-mail messages. PROFS also kept your calendar and could provide databases like phonebooks. There were several key features of PROFS that would make it hard to recognize as productivity software today. For one thing, IBM terminals were screen-oriented. The central computer would load a form into your terminal, which you could fill out. Then you’d press send to transmit it back to the mainframe. That makes text editing, for example, a very different proposition since you work on a screen of data at any one time. In addition, while you could coordinate calendars and send e-mail, you could only do that with certain people.

In general, PROFS connected everyone using your mainframe or, perhaps, a group of mainframes. In some cases, there might be gateways to other systems, but it wasn’t universal. However, it did have most of the major functions you’d expect from an e-mail system that was text-only, as you can see in the screenshot from a 1986 manual. PF keys, by the way, are what we would now call function keys.

The calendar was good, too. You could grant different users different access to your calendar. It was possible to just let people see when you were busy or mark events as confidential or personal.

You could actually operate PROFS using a command-line interface, and the PF keys were simply shorthand. That was a good thing, too. If you wanted to erase a file named Hackaday, for example, you had to type: ERASE Hackaday AUT$PROF.

Styles

PROFS messages were short and were essentially ephemeral chat messages. Of course, because of the block-mode terminals, you could only get messages after you sent something to the mainframe, or you were idle in a menu. A note was different. Notes were what we could call e-mail. They went into your inbox, and you could file them in “logs”, which were similar to folders.

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Forget Waldo. Where’s Luna 9?

February 11, 2026 by Al Williams 13 Comments

Luna 9 was the first spacecraft to soft-land on the moon. In 1966, the main spacecraft ejected a 99-kg lander module that used a landing bag to survive impact. The problem is, given the technology limitations of 1966, no one is exactly sure where it is now. But it looks like that’s about to change.

A model of the Luna 9 lander with petals deployed.

We know that the lander bounced a few times and came to rest somewhere in Oceanus Procellarum, in the area of the Reiner and Marius craters. The craft deployed four stabilizing petals and sent back dramatic panoramas of the lunar surface. The Soviets were not keen to share, but Western radio astronomers noticed the pictures were in the standard Radiofax format, so the world got a glimpse of the moon, and journalists speculated that the use of a standard might have been a deliberate choice of the designers to end run against the government’s unwillingness to share data.

Several scientists have been looking for the remains of the historic mission, but with limited success. But there are a few promising theories, and the Indian Chandrayaan-2 orbiter may soon confirm which theory is correct. Interestingly, Pravda published exact landing coordinates, but given the state of the art in 1966, those coordinates are unlikely to be completely correct. The Lunar Reconnaissance Orbiter couldn’t find it at that location. The leading candidates are within 5 to 25 km of the presumed site.

The Luna series had a number of firsts, including — probably — the distinction of being the first spacecraft stolen by a foreign government. Don’t worry, though. They returned it. Since the Russians didn’t talk much about plans or failures, you can wonder what they wanted to build but didn’t. There were plenty of unbuilt dreams on the American side.

Featured Art – 1:1 model of the Luna 9, Public Domain.

Pi Pico Learns Morse Code

February 10, 2026 by Al Williams 2 Comments

When [101 Things] didn’t want to copy Morse code, he decided to build a Pi Pico system to read it for him. On the face of it, this doesn’t seem particularly hard, until you look at the practical considerations. With perfectly timed dots and dashes, it would be trivial. But in real life, you get an audio signal. It has been mangled and mixed with noise and interference as it travels through the air. Then there’s the human on the other end who will rarely send at a constant speed with no errors.

Once you consider that, this becomes quite the project, indeed. The decoder captures audio via the Pi’s analog-to-digital converter. Then it resamples the input, applies an FFT, and converts the output via a complex classification pipeline that includes, among other things, Bayesian decoding. Part of the pipeline makes simple typo corrections. You can see the device do its thing in the video below.

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Living In The (LLM) Past

February 9, 2026 by Al Williams 23 Comments

In the early days of AI, a common example program was the hexapawn game. This extremely simplified version of a chess program learned to play with your help. When the computer made a bad move, you’d punish it. However, people quickly realized they could punish good moves to ensure they always won against the computer. Large language models (LLMs) seem to know “everything,” but everything is whatever happens to be on the Internet, seahorse emojis and all. That got [Hayk Grigorian] thinking, so he built TimeCapsule LLM to have AI with only historical data.

Sure, you could tell a modern chatbot to pretend it was in, say, 1875 London and answer accordingly. However, you have to remember that chatbots are statistical in nature, so they could easily slip in modern knowledge. Since TimeCapsule only knows data from 1875 and earlier, it will be happy to tell you that travel to the moon is impossible, for example. If you ask a traditional LLM to roleplay, it will often hint at things you know to be true, but would not have been known by anyone of that particular time period.

Chatting with ChatGPT and telling it that it was a person living in Glasgow in 1200 limited its knowledge somewhat. Yet it was also able to hint about North America and the existence of the atom. Granted, the Norse apparently found North America around the year 1000, and Democritus wrote about indivisible matter in the fifth century. But that knowledge would not have been widespread among common people in the year 1200. Training on period texts would surely give a better representation of a historical person.

The model uses texts from 1800 to 1875 published in London. In total, there is about 90 GB of text files in the training corpus. Is this practical? There is academic interest in recreating period-accurate models to study history. Some also see it as a way to track both biases of the period and contrast them with biases found in data today. Of course, unlike the Internet, surviving documents from the 1800s are less likely to have trivialities in them, so it isn’t clear just how accurate a model like this would be for that sort of purpose.

Instead of reading the news, LLMs can write it. Just remember that the statistical nature of LLMs makes them easy to manipulate during training, too.

Featured Art: Royal Courts of Justice in London about 1870, Public Domain