ChatGPT is an AI large language model (LLM) which specializes in conversation. While using it, [Gil Meiri] discovered that one way to create models in FreeCAD is with Python scripting, and ChatGPT could be encouraged to create a 3D model of a plane in FreeCAD by expressing the model as a script. The result is just a basic plane shape, and it certainly took a lot of guidance on [Gil]’s part to make it happen, but it’s not bad for a tool that can’t see what it is doing.
The first step was getting ChatGPT to create code for a 10 mm cube, and plug that in FreeCAD to see the results. After that basic workflow was shown to work, [Gil] asked it to create a simple airplane shape. The resulting code had objects for wing, fuselage, and tail, but that’s about all that could be said because the result was almost — but not quite — completely unlike a plane. Not an encouraging start, but at least the basic building blocks were there. Continue reading “ChatGPT Makes A 3D Model: The Secret Ingredient? Much Patience”→
It’s been a running battle in some quarters for years, whether analog sensor processing is better than digital. Proponents of digital are sometimes driven by lack of familiarity with analog circuitry, while analog die-hards point to delays and software crashes in microcontrollers. We’d probably toe the line that a mixture of the two skills is best, but [paul] has gone full-on for the analog side with his position and limit sensor for a remote telescope. The ‘scope had only one control wire carrying a digital signal, so how was he to get extra information down it? The solution was to overlay a DC voltage, and use a summing network composed of a series of op-amps to encode position and limit data as voltage.
In operation, the circuit is a straightforward DC summing amplifier of the type that op-amps were designed for and at which they excel. We’re not so sure it needs the high-precision resistors and the choice of op-amps seems the wrong way round with the AD8532’s high current output being better suited to driving the line than straightforward summing, but we can see it does the job. If you’re after a demonstration of a DC summing amplifier using an op-amp, here’s your project. Meanwhile if you’re curious about an op-amp inside the black box, take a look at one of the simplest integrated circuit op-amps ever made.
Although generally hydrogen is only mentioned within the context of transportation and energy storage, by far the most useful applications are found in industrial applications, including for the chemical industry, the manufacturing of steel, as well as that of methanol and fertilizer. This is illustrated by how today most of all hydrogen produced today is used for these industrial applications, as well as for applications such as cooling turbo generators, with demand for hydrogen in these applications rapidly increasing.
Currently virtually all hydrogen produced today comes from natural gas, via steam methane reformation (SMR), with potentially methane pyrolysis making natural gas-derived hydrogen a low-carbon source. The remainder of hydrogen comes from coal gasification and a small fraction from electrolysis of water. The hydrogen is often produced on-site, especially at industrial plants and thermal power plants. So aside from any decarbonization efforts, there are many uses for hydrogen which the public appears to be generally unaware of.
This leads us to the somewhat controversial hydrogen ladder.
There are a lot of things you can do with today’s powerful microcontrollers, but sometimes you really need a full embedded Linux setup. [Dylan Brophy] wanted to make it easier to add Linux to his own projects and designed the BeagleStamp.
Squeezed onto a 1″ square, the BeagleStamp puts the power of a PocketBeagle into an easy to solder module you can add to a project without all that tedious mucking about with individually soldering all the components of a tiny Linux computer every time. As a bonus, the 4 layer connections are constrained to the stamp as well, so you can use lower layer count boards in your project and have your Linux too.
The first run of boards was delivered with many of the pins unplated, but [Brophy] plans to work around it for the time being so he can spot any other bugs before the next board revision. Might we suggest a future version using RISC-V?
After Richard Branson delivered some inspiring words from his seat aboard SpaceShipTwo Unity, he unbuckled himself and started to float around the vehicle’s cabin along with three other Virgin Galactic employees. Reaching an apogee of 86 kilometers (53 miles), the passengers enjoyed four minutes of weightlessness during the July 2021 flight that was live-streamed over the Internet to an audience of millions. After years of delays, SpaceShipTwo had finally demonstrated it was capable of taking paying customers to the edge of space. As far as victories go — it was pretty impressive.
Yet despite the spectacle, weeks and months went by without an announcement about when commercial flights of the world’s first “spaceline” would finally begin. Now, nearly two years after Branson’s flight, Unity has flown again. Except instead of carrying the first group of customers, it performed the sort of un-powered test flight that Virgin Galactic hasn’t performed since 2017. Clearly, something didn’t go to plan back then.
Richard Branson aboard Unity
The company is being as tight-lipped as ever, saying only that this test flight was necessary to “evaluate the performance of the spaceship…following the modification period.” The exact nature of these modifications is unclear, but for some hints, we could look at the New Yorker article from September 2021. It alleged that, unwilling to derail Branson’s highly publicized flight, Unity’s pilots decided not to abort their ascent despite several warning lights in the cockpit alerting them that the vehicle’s trajectory was deviating from the norm. Virgin Galactic later denied their characterization of the event, but the fact remains that Unity did leave its designated airspace during the flight, and that the Federal Aviation Administration grounded the spacecraft until an investigation into the mishap could be completed. Continue reading “Virgin Galactic Cautiously Returns To Flight”→
When you’ve got a piece of interesting old aviation hardware on your desk, what do you do with it? If you’re not willing to relegate it to paperweight status, your only real choice is to tear it down to see what makes it tick. And if you’re lucky, you’ll be able to put it to work based on what you learned.
That’s what happened when [Glen Akins] came across a tachometer for a jet airplane, which he promptly turned into a unique CPU utilization gauge for his computer. Much of the write-up is concerned with probing the instrument’s innards to learn its secrets, although it was clear from the outset that his tachometer, from Kollsman Instruments, was electrically driven. [Glen]’s investigation revealed a 3-phase synchronous motor inside the tach. The motor drives a permanent magnet, which spins inside a copper cup attached to the needle on the tach’s face. Eddy currents induced in the cup by the spinning magnet create a torque that turns the needle against the force of a hairspring. Pretty simple — but how to put the instrument to work?
[Glen]’s solution was to build what amounts to a variable frequency drive (VFD). His power supply is based on techniques he used to explore aircraft synchros, which we covered a while back. The drive uses a trio of MCP4802 8-bit DACs to generate three phase-shifted sine waves via direct digital synthesis with an RP2040. The 3-phase signal drives the motor and spins the dial, with 84-Hz corresponding to full-scale deflection.
The video below shows the resulting CPU utilization gauge — which just queries for the current load level and sends it to the RP2040 over serial — in action. It’s not exactly responsive to rapid changes, but that’s to be expected from a mechanical system. And compared to exploring such a nice instrument, it really doesn’t matter.
An age-old vulnerability of physical keypads is visibly worn keys. For example, a number pad with digits clearly worn from repeated use provides an attacker with a clear starting point. The same concept can be applied to keyboards by using a thermal camera with the help of machine learning, but it also turns out that some types of keys and typing styles are harder to read than others.
Researchers at the University of Glasgow show how machine learning can pull details from thermal images like these quickly and effectively.
Touching a key with a fingertip imparts a slight amount of body heat, and that small amount of heat can be spotted by a thermal sensor. We’ve seen this basic approach used since at least 2005, and two things have changed since then: thermal cameras gotten much more common, and researchers discovered that by combining thermal readings with machine learning, it’s possible to eke out slight details too difficult or subtle to spot by human eye and judgement alone.
Here’s a link to the research and findings from the University of Glasgow, which shows how even a 16 symbol password can be attacked with an average accuracy of 55%. Shorter passwords are much easier to decipher, with the system attacking 6 and 8 symbol passwords with an accuracy between 92% and 80%, respectively. In the study, thermal readings were taken up to a full minute after the password was entered, but sooner readings result in higher accuracy.
A few things make things harder for the system. Fast typists spend less time touching keys, and therefore transfer less heat when they do, making things a little more challenging. Interestingly, the material of the keycaps plays a large role. ABS keycaps retain heat far more effectively than PBT (a material we often see in custom keyboard builds like this one.) It also turns out that the tiny amount of heat from LEDs in backlit keyboards runs effective interference when it comes to thermal readings.
Amusingly this kind of highly modern attack would be entirely useless against a scramblepad. Scramblepads are vintage devices that mix up which numbers go with which buttons each time the pad is used. Thermal imaging and machine learning would be able to tell which buttons were pressed and in what order, but that still wouldn’t help! A reminder that when it comes to security, tech does matter but fundamentals can matter more.
