TechyMagThings

Many of us of a certain age will have had their first true, good 3D video game experience with Super Mario 64. Unlike previous 3D games, the camera was an object controllable by the player, rather than a first-person-ony mode or one where the game tries to guess the best placement for the camera. We might take this mechanic for granted today, but 3D was a new technology at the time that took experimentation before settling on the norms we have today. From a programming perspective, 3D graphics can be a bit of a head-scratcher but [Gabriel] shows that perspective and the camera can be as simple as a few lines of math.

When starting out as a programmer, [Gabriel] used various tools that provided a camera somewhat automatically. But after reaching the limits of these types of frameworks, the next step is to learn how that works from scratch. It turns out that it’s a bit of matrix math, with values for foreground and background clipping planes as well as aspect, field of view, and position. This basically replicates a trapezoidal prism which can be thought of as a viewer looking at a scene from the perspective of a camera. To provide the depth effect, the X and Y coordinates are divided by the Z coordinate within this matrix system, making far-away objects smaller and generating the 3D effect.

On [Gabriel]’s site which explains this method, there are a few sliders in several examples that demonstrate how changing values of each of these variables changes the perspective and the object being displayed. For a math lesson it is very interactive and helps intuit these concepts. Cameras aside, the generation of 3D objects has its own unique set of math equations to learn about that are “equally” interesting.

Even if almost tragically impractical in a world where digital calculators are cheap as chips, mechanical calculators and their big mechanical computer brethren remain an absolute marvel of engineering. Using nothing but elements like simple gears their motion is used to calculate everything from a simple multiplication to the proper targeting instructions for an Iowa-class battleship’s guns.

This fascination, along with the mind-bendingly high prices for commercial digital calculators led [3D all Workshop] to spend 2 months on designing his own mechanical calculator. Fully FDM 3D-printed, of course.

In the video the design process and troubleshooting step are covered along with the workings of the mechanisms for both addition and multiplication. While this may seem simple, basically converting numbers of rotations into a final indicator position, aspects like carrying a digit and adding a multiplication feature to the mechanism require some proper engineering.

Of course, using FDM printing for tolerance-sensitive things like gears meant that a lot of time was spent redesigning aspects of the mechanism, going through about a hundred design iterations until it worked, with the help from a bit of lubrication.

Naturally this isn’t the first 3D-printed mechanical calculator, not to mention ones made from wood, but always it’s pretty cool to see one made from first fundamentals.

In the era before PCB shops would make almost any PCB imaginable, as well making many other manufacturing processes for prototypes available to hobbyists, there were several ways of making PCBs at home. Many of which involve harsh chemicals and were easy to mess up. Getting a single-layer PCB using the toner transfer method, for example, took a bit of practice (and a fume hood) to get right. [Bettina Neumryr] is working on a custom two-layer PCB, and has a new trick to get it to come out right despite the added complexity of the second layer.

The method starts out as a standard single-layer board in effect. Toner is ironed onto a copper board, in this case using a laminator, which allows the board to go into an acid bath which washes away all of the un-tonered copper. But with the second layer exposed, this would wash away the other side of the board completely. [Bettina] is using a new method here to protect that layer during the first bath: covering it in ink from a magic marker. With the first board etched, the ink and toner get washed off and the second layer is carefully lined up, put through the laminator, and then the opposite side gets covered in ink for the second acid bath.

After the process is complete and many layers of ink and toner are removed, [Bettina] is left with a PCB that’s ready to receive electronic components, if a little stained from all the ink. As to what this specific board is going to be used for, she’s kept that a bit cryptic as it’s the subject of a future video. Her builds usually revolve around designs from antique elecronics magazines, so it’s almost certainly something of that nature, and that’s also why this specific design couldn’t be just sent off to a board shop.

Although we often think that we got certain aspects of aerodynamics pretty much licked at this point, details like the optimal shape of a propeller remains hotly debated, both in- and outside of academia. This also includes wilder designs like toroidal propellers that even after more than a hundred years are still mostly just being evaluated. Recently [Neuronautics] took a shot at figuring out whether toroidal propellers even make sense.

In order to do this, first an efficiency baseline was established using a conventional and highly optimized propeller. After scanning it in to get its exact geometry and running it through a computational fluid dynamics (CFD) simulation, the software spat out a number of about 73%.

This left figuring out an optimized shape for the toroidal propeller to pit against it. While you can absolutely brute-force the seventeen shape parameters being considered here and test them in CFD, this would take insanely long. The hack here is to use multiple reference frame (MRF) to drastically speed up the selection process, though even then it still took two months. An example of using MRF with regular propellers is discussed  in a 2019 paper by [Randi Franzke] et al. in Energies.

Although MRF saves a lot of simulation time, you still end up with a lot of data that has to be analyzed for interesting patterns. For this [Neuronautics] trained a artificial neural network to automate filtering the many options for the most optimal ones, until converging onto a single design.

This G1401 design was the lucky winner, though with only a simulated 62.9% efficiency. Subsequently the one aspect that had been left unchanged was also iterated through, in the form of many different airfoil shapes until the final design appeared.

This design was then 3D printed in resin, which showed the first hurdle with the selection process, in that the printed versions were too thin and flexible to be usable as propellers. Cue many hours of manual tweaking of the design to make it actually printable.

Although the final design didn’t exceed 62% efficiency in a final test, the comment section to the video rightfully points out that the comparison was between a commercially made propeller and a DIY resin-printed one, which adds a whole other batch of variables. That said, it’s unlikely that there’d have been an obvious improvement either way, otherwise we’d already have seen toroidal propellers pop up everywhere on drones and aircraft.

We often see scientific breakthroughs in journals or other media that’s reported on as if it’s a revolutionary technology guaranteed to reshape human existence, only to never hear about it again. A more cynical reason for this phenomenon is a certain amount of clickbait or engagement farming, but the real culprit often tends to be the discovery of a process that can’t produce the new material or effect at a scale that makes sense for mass production. One of those are MXenes (“max-enes”), a two-dimensional material first produced over a decade ago, but new research into them has developed a much more efficient way of producing them.

Before this discovery, these materials were produced in a convoluted process involving the MXene precursor materials, combining them with an etchant, washing them off, and then repeatedly spinning them in a centrifuge to separate out unwanted byproducts. As one can imagine, this doesn’t produce material in an industrial quantity. But the new method uses a vapor deposition process which simplifies the precursor steps using less expensive materials, as well as skips the etching step. After that, the researchers have found that the MXenes can grow in a much more controlled way, allowing for greater production amounts and higher quality.

In the intervening years since their discovery and first synthesis MXenes have shown potential for wide-ranging applications, from battery production to antennas to water purification. Another interesting application is as a switchable Faraday cage, as we’ve covered in the past. Hopefully the slow plod of scientific discovery continues and we can start seeing more of these incremental gains improving our lives, even if we don’t get a sudden technological revolution from it.

The PICO-8 is what is known as a ‘fantasy console’– you can program it, and there are oodles of games, but it’s not actually the 8-bit console it pretends to be. It’s a virtual machine, one that can run on top of any modern OS. When [UncleStem] got into PICO-8, he decided that he liked the PICO-8’s portability, he wanted a different kind of portability– so he took the ‘fantasy’ out of ‘fantasy console’ with his GameBoy-esqe handheld build, the build/dev video of which is embedded below.

At its core, it’s a Raspberry Pi Zero2W. That’s rather overkill for an 8-bit virtual machine, but it’s what he had on hand, and it makes for an easy build. The real hero of the build is the 720 by 720 pixel IPS display that matches the PICO-8’s square aspect ratio and takes up most of the real estate on the handheld. Even better, it has HDMI in and sound support, so with some buttons and a battery the hardware is all there after [UncleStem] designs a handsome 3D printed case, and also has a go milling it out of aluminum before giving up and having a pro do it.

Since it’s so easy to do these days, everything lives on a custom PCB from his sponsor that gives the handheld good mechanical stability. He’s also using the full-colour silkscreen option to make a very pretty PCB. If that part of the project appeals, we’ve covered guides to PCB art before. He’s shared the PCB and everything else he can on a google drive, though note that the fantasy console itself is not open source, and would need purchased to finish the project.

Oddly enough, this is not the first handheld we’ve seen based on the PICO-8. That would be this project that uses a single-button camcorder form-factor. As unique as that is, this project has the benefit of working with the whole library of PICO-8 games.

It’s been more than a year since [Henrik Forstén] built the first iteration of his synthetic-aperture radar (SAR) imaging drone, and he’s certainly been productive in the meantime. Not only did he develop a much more powerful autofocus algorithm to clean up the radar images, but he also extended the software to create high-resolution interferometric images.

The main limitation of the original radar system was the GPS, which only had a resolution of about one meter; the autofocus algorithm owed much of its improved clarity to an improved estimation of the drone’s position. A simpler, though more expensive, solution was to add an RTK-capable GPS receiver. RTK (Real-Time Kinematic) receivers use a fixed ground station to constantly transmit a correction signal, letting them reach a couple centimeters of accuracy. Since the drone doesn’t actually need to know its position in real time, it can also use PPK (Post-Processing Kinematic) positioning, which compares recorded GPS signals after the flight to obtain similarly accurate positions.

[Henrik] also implemented a few other hardware improvements, including stabilizing the phase-locked loop used to generate the radar’s frequency sweep. The controller FPGA’s SD card interface had too low a bandwidth to record data in real time, so [Henrik] also implemented a simple, fast compression algorithm to speed that up. Most significantly, he also developed a program for interferometric imaging. The drone flies the same path twice at different altitudes; by comparing phase information from different passes, it’s possible to detect a target’s elevation. Normally, the radar program assumes constant elevation, making tall objects seem to lean toward the radar source; an interferogram, on the other hand, allowed [Henrik] to generate a detailed elevation map.

[Henrik] is no stranger to synthetic aperture radar; we’ve previously covered a bike-mounted iteration and a budget SAR system. If the concepts behind this are still a bit fuzzy, we’ve also covered a guide to making your own SAR setup.