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“Smart skin” can identify weaknesses in bridges and airplanes using laser scanner

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Recent research results have demonstrated that two-dimensional, on-demand mapping of the accumulated strain on metal structures will soon be a reality thanks to an engineered “smart skin” that’s only a fraction of the width of a human hair. By utilizing the unique properties of single-walled carbon nanotubes, a two-layer film airbrushed onto surfaces of bridges, pipelines, and airplanes, among others, can be scanned to reveal weaknesses in near real-time. As a bonus, the technology is barely visible even on a transparent surface, making it that much more flexible as an application.

Stress-inducing events, along with regular wear and tear, can deform structures and machines, affecting their safety and operability. Mechanical strain on structural surfaces provides information on the condition of the materials such as damage location and severity. Existing conventional sensors are only able to measure strain in one point along one axis, but with the smart skin technology, strain detection in any direction or location will be possible.

How “Smart Skin” Technology is Used

In 2002, researchers discovered that single-wall carbon nanotubes fluoresce, i.e., glow brightly when stimulated by a light source. Later, the fluorescence was further found to change color when stretched. This optical property was then considered in the context of metal structures that are subject to strain, specifically to apply the property as a diagnostic tool. To obtain the fluorescent data, researchers applied the smart skin to a testing surface, irradiated the area with a small laser scanner, and captured the resulting nanotube color emissions with an infrared spectrometer. Finally, two-dimensional maps of the accumulated strain were generated with the results.

Smart skin technology could be used to monitor the structural integrity in commercial jet engines. | Credit: CC0 via Pixabay, User: blickpixel

The primary researchers, Professors Satish Nagarajaiah and Bruce Weisman of Rice University in Texas, have published two scientific papers explaining the methods used for achieving this technology and the results of its proof-of-principle application. As described in the papers, aluminum bars with holes or notches in areas of potential stress were tested with the laser technique to demonstrate the full potential of their invention. The points measured were located 1 millimeter apart, but the researchers stated that the points could be located 20 times closer for even more accurate readings. Standard strain sensors have points located several millimeters apart.

What Are Carbon Nanotubes?

Carbon nanotubes (CNTs) are carbon molecules that have been structurally modified into cylinders, or rather, rolled up sheets of carbon atoms. There has been some evidence suggesting that CNTs can be formed via natural processes such as volcanic events. However, to really capitalize on their unique characteristics, production in a laboratory environment is much more efficient.

Several methods can be used for production, but the most widely used method for synthesizing CNTs is chemical vapor deposition (CVD). This process combines a catalyzing metal with a carbon-containing gas which are heated to approximately 1400 degrees Fahrenheit, triggering the carbon molecules to assemble and grow into nanotubes. The resulting formation resembles a forest or lawn grass, each trunk or blade averaging .43 nanometers in diameter. The length is dependent on variables such as the amount of time spent in the high heat environment.

An artistic depiction of a carbon nanotube. | Credit: AJC1 via Flickr, CC BY-SA 2.0

Besides surface analysis, carbon nanotubes have proven invaluable in many research and commercial arenas, their luminescence being only one of many properties that can improve and enable other technologies. Their mechanical tensile strength is 400 times that of steel while only having one sixth the density, making them very lightweight. CNTs also have highly conductive electrical and thermal properties, are extremely resistant to corrosion, and can be filled with other nanomaterials. All of these advantages open up their applications to include solar cells, sensors, drug delivery, electronic devices and shielding, lithium-ion batteries, body armor, and perhaps even a space elevator, assuming significant advances overcome its hurdles.

Next Steps

The nanotube-laced smart skin is ready for scaling up into real-world applications, but its chosen industry may take time to adopt given the general resistance to change in a field with long-standing existing technology. While awaiting embrace in the arena it was primarily designed for, the smart skin has other potential uses in engineering research applications. Bruce Weisman, also the discoverer of CNT fluorescence, anticipates its advantages being used for testing the design of small-scaled structures and engines prior to deployment. Niche applications like these may be the primary entry point into the market for some time to come. In the meantime, the researchers plan to continue developing their strain reader to capture simultaneous readings from large surfaces.

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Accidental computer geek, fascinated by most history and the multiplanetary future on its way. Quite keen on the democratization of space. | It's pronounced day-sha, but I answer to almost any variation thereof.

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Tesla briefly offered this Robotaxi part for your personal car

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Credit: @tpgoebel | X

Tesla briefly offered one Robotaxi part in its Parts Catalog for your personal car, only to remove it just a short time after it was first noticed.

Tesla’s Robotaxi camera washer apparatus was briefly available for purchase on the company’s Online Parts Catalog. The camera washer was first noticed on Model Y Robotaxi vehicles about six months ago in Austin.

First noticed by Not a Tesla App, the Camera Washer entries appeared for the new “Juniper” Model Y under a category called “Halo,” which has also now disappeared. Interestingly, Halo probably is related to Tesla’s internal “Project Halo,” which was a project that aimed to retrofit customer-owned Model Ys into functional Robotaxis.

This hardware addition would likely be required for the vehicle to operate as a Robotaxi, as the Camera Washer seems to be a non-negotiable part of the vision-based system Tesla utilizes for self-driving efforts.

However, this part has since been removed and is no longer visible on the EPC.

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Now the true question lingers: Why would Tesla add this Camera Washer to the Model Y parts catalog? Is it planning to make it available for owners to utilize on their own cars for personal use, or will it become a prerequisite for Robotaxi operation in customer-owned cars?

While discussing the upgrade options for Hardware 3 vehicles during the Q1 Earnings Call, Tesla CEO Elon Musk had said that the company could establish small, satellite shops that would upgrade cameras and self-driving computers. Perhaps this same strategy could be utilized for vehicles that want to be included in Robotaxi but do not have the correct hardware.

AI4 is currently represented as capable of unsupervised self-driving, and the same was said about HW3 at one point, only for Tesla to admit last quarter that it would, unfortunately, not be possible. Perhaps AI4 vehicles might need this camera washer as a prerequisite, just as HW3 cars will need that camera and computer upgrade.

This could be the first hint of that’s where we are headed.

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Tesla Robotaxi gets sweeping but polarizing change

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Credit: Tesla

Tesla has started rolling out a broader change to the ride experience for its Robotaxi fleet by silencing turn signals, but the change is certainly polarizing.

Tesla has generally made it clear that its purpose-built ride-hailing platform, Robotaxi, will cater to the rider in nearly every way possible. This includes having climate preferences, music, and other personal settings loaded up in the car as the rider enters.

But Tesla is taking it a step further by muting turn signal chimes altogether, a change that appears to be a way to make the ride more peaceful:

However, there are a handful of people who are not thrilled about this change. Turn signals are a conditioned part of the human mind for those who ride in a car regularly.

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Taking a turn without one feels strange and odd, and not hearing it click while activated could set off some alarms for riders, who might use the noise as confirmation that other drivers know of their intention to turn.

Turn signal noises are still audible in customer cars, so if you use FSD in your personal vehicle, you will still hear the turn signal.

The move is certainly one that is unique, but not one that separates it from other ride-sharing services. In a normal car, the clicking sound confirms to the driver that the blinker is active. In a fully driverless Robotaxi, that feedback serves no purpose for passengers, other than peace of mind.

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Tesla Full Self-Driving v14.3.6 review: a rare regression, but some bright spots

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Credit: Tesla

Tesla released Full Self-Driving version 14.3.6 last week, and after what was potentially one of the best FSD releases in v14.3.5, there has been a bit of a regression. While there are some bright spots, the changes made to v14.3.6 seem to have backtracked some behaviors.

Overall, it is hard to really complain about FSD in any sense; it has revolutionized how I travel literally anywhere. According to my self-driving app, the last time I went a day without using it was 59 days ago.

However, I think it’s also important to recognize when things are just plain bad with FSD. There are times it does truly mind-boggling things, and I’ll dive into those here. Additionally, I only had these issues on local roads, not on highways. Highway operation, generally, is always incredible other than the occasional complaint about speed or left lane camping.

With those things being said, my personal experience may not represent others’ experiences. A handful of people have said they have had a similar experience on v14.3.6, while others have said it is more than normal.

Turning Hesitancy, Inaccuracy

I’ve noticed more inaccuracy turning into multi-lane stretches of road than in any version I can remember. I’ve had at least three instances of FSD turning into a stretch of roadway that has two or more lanes, and not selecting a lane confidently as it has in past versions.

Instead, the car will drive over one of the dashed road lines, and the steering wheel will jerk back and forth before picking the lane. It should be said that it has always picked the correct lane when choosing based on the navigation, but it is still very indecisive. The steering wheel jerking is reminiscent of some of the later versions of v13.

I admit I really hate to see the steering wheel jerking come back. However, I think when Tesla releases v14.3.7, it won’t be present. When there are occurrences of it in FSD versions, it is usually resolved by the following release.

FSD Disregards Manual Turn Signals

This is my biggest bone to pick with FSD other than Navigation issues, but this one seems like it would be such an easy fix.

If Tesla is going to put the word “Supervised” on the end of “Full Self-Driving,” then when I tell the car to do something, it should do it. If I input an increase in speed by pressing the accelerator, the car will immediately respond. It does not disregard my input because it feels it is traveling at the right speed.

FSD should never disobey and turn off turn signals that the driver inputs. Trying to direct the car into the correct lane, I had initiated the left turn signal not once, not twice, but three times, with the car turning it off all three times and continuing in a lane that would end in just one block. The only solution at this point would be to zipper merge.

This goes back to the fact that self-driving’s biggest bottleneck might be rider preference. A zipper merge might have been more than reasonable, might have saved me time that I spent sitting through an additional light cycle, and might be something many drivers would do. I was in no hurry, I traditionally do not try to zipper merge because it feels inconsiderate, and lastly, the car should have just followed my input.

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This caused me to disengage and drive manually the rest of the way home. Sometimes I just do not need FSD to try to pass every car it can at intersections.

Bird Braking is a Thing of the Past

The big complaint with recent versions of Full Self-Driving has been what we’ve coined as “bird braking,” which is when the car will brake suddenly as a bird flies past.

There have been zero issues with this so far in v14.3.6, which is an excellent improvement.

FSD Might Already Be Taking Note of Driver Preferences

Another thing I have noticed over the past few days is that v14.3.6 seems to already be taking my preferences with navigation into account.

This is something that is supposed to be rolling out with the Summer Update, but I have a hunch it’s already present and might have been included in this v14.3.6 build. On Friday, FSD pulled into an entrance to a local convenience store that it had never attempted to go into before.

Typically, I manually pull into this entrance because it avoids heavy cross traffic at the main entrance. FSD has always chosen that congested main entrance.

Additionally, FSD has pulled into my assigned parking spot at my townhouse community on multiple occasions with this release. This is something that used to happen ocassionally, but not consistently.

It also navigated back to the same convenience store last night, drove through crazy cars scrambling to gas pumps, navigated out of the parking lot correctly, drove me home, and, once again, parked in my assigned spot.

As previously stated, this release just seems to have a few things that need to be brought to Tesla’s attention, and also to make others who use FSD aware of some things that I’ve experienced. I look forward to the next release that will remedy these issues, just as Tesla has always done in the past.

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