While studying failure modes for quadcopters, and how to get them safely to the ground with less than a full quad of propellers, a group of researchers at the Institute for Dynamic Systems and Control at ETH Zurich came up with a great idea: a mode of flight that’s like the controlled spinning descent of a maple seed.
The Monospinner runs on the absolute minimum number of moving parts. Namely, one. Even a normal helicopter has a swash plate for adjustable blade pitch, and a tail rotor to keep it from spinning. Give up the idea that you want to keep it from spinning, and you can achieve controlled flight with a lot less. Well, one motor and a whole lot of math and simulation.
The Monospinner is carefully weighted so that it’s as stable as possible while spinning, but so far it’s unable to spin itself up from a standstill. In initial tests, they attached it to a pivot to help. The best part of the video (below) is when the researcher throws it, spinning, into the air and it eventually stabilizes. Very cool.
Continue reading “Your Quadcopter Has Three Propellers Too Many”
This significant discovery in nanotechnology could also be the first practical use of a Tesla coil in modern times that goes beyond fun and education. A self-funded research team at Rice University has found that unordered heaps of carbon nanotubes will self-assemble into conductive wires when exposed to the electric field of a strong Tesla coil. The related paper by lead author and graduate student [Lindsey R. Bornhoeft], introduces the phenomenon as “Teslaphoresis”. Continue reading “Teslaphoresis: Tesla Coil Causes Self-Assembly In Carbon Nanotubes”
Has this ever happened to you? You start out on a reverse-engineering project, start digging in, and then get stumped. Then you go looking on the Internet for help, and stumble across someone who’s already done exactly what you’re trying to do?
[Geekabit] wrote us with a version of this tale of woe. In his case, the protocol to be reversed was Atmel’s debugWire protocol for debugging on low-pin-count parts. There are a number of websites claiming it’s “secret” or whatever, but it actually looks like it’s just poorly documented. Anyway, [RikusW] seems to have captured all of the signals way back in 2011. Good job!
The best part of [geekabit]’s story is that he had created the Wikipedia page on debugWire himself to inspire collaboration on reverse-engineering the protocol, and someone linked in [RiskusW]’s work. When [geekabit] picked up the problem again a bit later, he did a bit of web research and found it solved — on the page that he started.
Maybe it’s not a tale of woe after all, but a tale of unintentional collaboration. Anyway, it serves as a reminder that if you’re interested in the destination more than the voyage of discovery, it never hurts to do your research beforehand. And now we all know about the low-level details of the debugWire protocol. Anyone written up a driver yet?
Thanks [geekabit] for the tip and the story! Image from ATmega32-AVR, which explains nicely how to use the Dragon in debugWire mode.
A lot of you use WiFi for your Internet of Things devices, but that pretty much rules out a battery-powered deployment because WiFi devices use a lot of juice. Until now. Researchers at the University of Washington have developed a passive WiFi implementation that uses only microwatts per device.
Working essentially like backscatter RFID tags do, each node has a WiFi antenna that can be switched to either reflect or absorb 2.4 GHz radiation. Your cell phone, or any other WiFi device, responds to this backscattered signal. All that’s missing is a nice steady signal to reflect.
A single, plugged-in unit provides this carrier wave for multiple WiFi sensor nodes. And here’s the very clever part of the research: to keep the carrier from overwhelming the tiny modulated signal that’s coming from the devices, the plugged-in unit transmits off the desired frequency and the battery-powered units modulate that at just the right difference frequency so that the resulting (mixed) frequency is in the desired WiFi band.
If you’re a radio freak, you’ll recognize the WiFi node’s action being just like a frequency mixer. That’s what the researchers (slightly mysteriously) refer to as the splitting of the analog transmission stage from the digital. The plugged-in unit transmits the carrier, and the low-power nodes do the mixing. It’s like a traditional radio transmitter, but distributed. Very cool.
There’s a bunch more details to making this system work with consumer WiFi, as you’d imagine. The powered stations are responsible for insuring that there’s no collision, for instance. All of these details are very nicely explained in this paper (PDF). If you’re interested in doing something similar, you absolutely need to give it a read. This idea will surely work at lower frequencies, and we’re trying to think of a reason to use this distributed transmitter idea for our own purposes.
And in case you think that all of this RFID stuff is “not a hack”, we’ll remind you that (near-field) RFID tags have been made with just an ATtiny or with discrete logic chips. The remotely-powered backscatter idea expands the universe of applications.
Thanks [Ivan] for the tip!
Continue reading “Passive WiFi On Microwatts”
The strength of object printed on filament-based 3D printers varies by the plastic used, the G-code used by the printer, the percent infill, and even the temperature the plastic was extruded at. Everything, it seems, has an effect on the strength of 3D printed parts, but does the color of filament have an effect on the stress and strain a plastic part it can withstand? [Joshua M. Pearce] set out to answer that question in one of his most recent papers.
The methods section of the paper is about what you would expect for someone investigating the strength of parts printed on a RepRap. A Lulzbot TAZ 4 was used, along with natural, white, black, silver, and blue 3mm PLA filament. All parts were printed at 190°C with a 60°C heated bed.
The printed parts demonstrated yet again that a RepRap can produce parts that are at least equal in material strength to those produced by a proprietary 3D printer. But what about a difference in the strength among different colors? While there wasn’t a significant variation in the Young’s modulus of parts printed in different colors, there was a significant variation of the crystallization of differently colored printed parts, with white PLA producing the largest percent crystallinity, followed by blue, grey, black, and finally natural PLA. This crystallinity of a printed part can affect the tensile properties of a printed part, but [Pearce] found the extrusion temperature also has a large effect on the percentage of crystallinity.
Quick. What’s the difference in conductivity between silver and copper? Today, that’s easy to find out. You just ask Google (maybe even out loud if you have a phone handy). But it wasn’t that long ago that you needed another option. Before the Internet age, a big part of being “that guy” (or gal) was knowing where to go to find things. You had to be a master of the library’s reference section, know what might be in an encyclopedia or an almanac.
However if you were a hardcore math, science, or engineering geek you probably had, at least, one edition of CRC handbooks. Today, we usually think of CRC as cyclic redundancy check, but back then it was the Chemical Rubber Company.
The Chemical Rubber Company dates back to 1903 when brothers Arthur, Leo, and Emanuel Friedman were selling rubber lab aprons in Cleveland, Ohio (Arthur, apparently, had been in a similar business from 1900). In 1913, the brothers offered a short (116-page) booklet called the Rubber Handbook free with the purchase of a dozen aprons.
Continue reading “Before Google There Was the Chemical Rubber Company”
We’ve seen ’em before: the charts and graphs in poorly photocopied ’80s datasheets, ancient research papers, or even our college prof’s chalkboard chicken scratch. Sadly, this marvelously plotted data is locked away in a poorly rendered png or textbook graphic. Fortunately, a team of programmers have come the rescue to give us the proper thieving tool to lift that data directly from the source itself, and that tool is Engauge.
Engauge is an open source software tool that enables to convert pictures of plots into the numerical representation of their data. While some of us might still be tracing graphs by hand, Engauge enables us to simply define reference points on the graph, and a clever image-processing algorithm extracts the curve for us automatically! Sure, there’s a little fine-tuning to determine what counts as data, but the net result is an all-in-one software tool that eats pictures and produces data–no intermediate steps required!
Engauge has been helping scientists and engineers preserve ancient data logs for years now, but it’s a tool that’s still fresh today when we’re recording from an analog o’scope or lifting those xs and ys off a textbook. In a world that’s increasingly digital, we’ve got the Engague developers to thank for arming us with the right tool for the job. All that said, If graph-thieving isn’t your thing, try spline-thieving to go from camera to CAD.
Engauge is a little lacking in the demo-video department, but we dug up a quickie on YouTube.
Thanks for the tip, [Jason]!
Continue reading “Engauge Makes Graph Thieving a Cinch”