Plastics: Photopolymers For 3D Printing And Beyond

Chances are good that if you’ve done any 3D printing, it was of the standard fused deposition modeling variety. FDM is pretty simple stuff — get a bit of plastic filament hot enough, squeeze the molten goo out of a fine nozzle, control the position of the nozzle more or less precisely in three dimensions, and repeat for hours on end until your print is done. To the outsider it looks like magic, but to us it’s just another Saturday afternoon.

Resin printing is another thing altogether, and a lot closer to magic for most of us. The current crop of stereolithography printers just have a high-resolution LCD display between a UV light source and a build tank with a transparent bottom. Prints are built up layer by layer by flashing UV light patterns into the tank as a build plate slowly lifts it up from the resin, like some creature emerging from the primordial goo.

Of course it’s all just science, but if there is any magic in SLA printing, surely it’s in the resins used for it. Their nondescript brown plastic bottles and information-poor labels give little clue as to their ingredients, although their hydrocarbon reek and viscous, sticky texture are pretty good clues. Let’s take a look inside the resin bottle and find out what it is that makes the magic of SLA happen.

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Ground Effect Aerodynamics On An RC Car

Ground effect aerodynamics will return to Formula 1 in a big way in the 2022 season, hopefully washing away the bad taste left in fan’s mouths after the recent controversial season decider. [Engineering After Hours] has experimented with F1 aerodynamics on RC cars before, and decided that it was time to try and implement a proper ground-effect design himself.

The aim of ground effect aerodynamics is to create a constriction for airflow between the bottom of the car and the ground underneath. This constriction accelerates the flow beneath the car, and as per Bernoulli’s principle, causes a corresponding pressure drop, sucking the car down onto the track. Viscosity also plays a role; from the car’s perspective, the road beneath the vehicle is moving backwards at some speed, pulling on the fluid thanks to the boundary layer on the ground itself. This further helps increase the strength of the effect.

A vacuum-formed undertray complete with side skirts was installed on the RC car in order to generate ground effect downforce. A quick test with a leaf blower indicates the system works, and that the side skirts are a key component.

Lateral acceleration was significantly improved by around 20% in testing with the ground effects installed, though [Engineering After Hours] admits that without a wind tunnel, the results aren’t the most scientific. However, with the undertray being relatively lightweight, we suspect the aero elements are likely providing plenty of benefit without too much of a negative effect on acceleration or handling.

Check out some of the other aero experiments [Engineering After Hours] has undertaken, too. Video after the break. Continue reading “Ground Effect Aerodynamics On An RC Car”

Box with a hole. Camera and Raspberry Pi inside.

A Label Maker That Uses AI Really Poorly

[8BitsAndAByte] found herself obsessively labeling items around her house, and, like the rest of the world, wanted to see what simple, routine tasks could be made unnecessarily complicated by using AI. Instead of manually identifying objects using human intelligence, she thought it would be fun to offload that task to our AI overlords and the results are pretty amusing.

She constructed a cardboard enclosure that housed a Raspberry Pi 3B+, a Pi Camera Module V2, and a small thermal printer for making the labels. The enclosure included a hole for the camera and a button for taking the picture. The image taken by the Pi is analyzed by the DeepAI DenseCap API which, in theory, should create a label for each object detected within the image. Unfortunately, it doesn’t seem to do that very well and [8BitsAndAByte] is left with labels that don’t match any of the objects she took pictures of. In some cases it didn’t even get close, for example, the model thought an apple was a person’s head and a rotary dial phone was a cup. Go figure. It didn’t really seem to bother her though, and she got a pretty good laugh from the whole thing.

It appears the model detects all objects in the image, but only prints the label for the object it was most certain about. So maybe part of her problem is there were just too many objects in the background? If that were the case, you could probably improve the accuracy of the model by placing the object against a neutral background. That may confuse the AI a lot less and possibly give you better results. Or maybe try a different classifier altogether? Or don’t. Then you could just use it as a fun, gag project at your next get-together. That works too.

Cool project [8BitsAndAByte]! Hey, maybe this is a sign the world will still need some human intelligence after all. Who knows?

Continue reading “A Label Maker That Uses AI Really Poorly”