Centered around voxels, a number of which add up as values comprising a volume in 3D space, the research team has come up with a new concept and process that starts by controlling sound waves initially, but has the potential to go much further with incredible versatility, perhaps in retail, automotive, copyrighting, or even as far as the ocean. With acoustic filtering and tagging, the team led by Columbia Computer Science Professor Changxi Zheng is combining volume and 3D printing in a way most of us certainly never would have considered.
“In the past, people have explored computational design of specific products, like a certain type of muffler or a particular shape of trumpet,” says Zheng. “The general approach to manipulating sound waves has been to computationally design chamber shapes. Our algorithm enables new designs of noise mufflers, hearing aids, wind instruments, and more – we can now make them in any shape we want, even a 3D-printed toy hippopotamus that sounds like a trumpet.”
“We also have proposed a very intriguing new way to use acoustic filters: we can use our acoustic voxels as acoustic tags, unique to each piece we 3D print, and encode information in them. This is similar to QR codes or RFIDs, and opens the door to encoding product and copyright information in 3D printing.”
This is not the first time the team has dabbled in manipulating acoustics, as well as working to improve them—and it’s also not their first experience incorporating 3D printing and experiencing all of the resulting benefits therein. In 2015, we followed along as the researchers applied their computational technique in creating and 3D printing what they cleverly dubbed the zoolophone, a variation on the xylophone—and in that case, made with wooden keys in animal shapes. This was obviously a preliminary project in comparison to their latest, showing that they were becoming increasingly interested in sounds in relation to geometries, and manipulating them together.
The geometries grow significantly more complex and more varied as the researchers delve further into both acoustics and 3D technology.
“Using an efficient method of simulating the transmission matrix of an assembly built from these underlying primitives, our method is able to optimize both the arrangement and the parameters of the acoustic shape primitives in order to satisfy target acoustic properties of the filter,” state the researchers in their paper.
The team is making progress that could prove to be far-reaching, with items like car mufflers and musical wind instruments as examples of what could be substantially improved on.
“With 3D printers today, geometric complexity is no longer a barrier. Even complex shapes can be fabricated with very little effort,” Zheng notes. “So the question is: can we use complex shapes to improve acoustic properties of products?”
And while it’s certainly off the topic of manufacturing and copyrighting, it’s not too surprising to hear that their ambitions may travel as far as the sea too, incorporating control of ultrasonic waves.
“We are investigating some of the intriguing possibilities of ultrasonic manipulation, such as cloaking, where sound propagation can be distorted to hide objects from sound waves. This could lead to new designs of sonar systems or underwater communication systems. It’s an exciting area to explore.”
As the researchers point out, while one object may look the same on the outside, it could have a completely different acoustic build within, producing a varied sound. They tested the idea with an iPhone app created specifically for this project, recording the sounds and then identifying each object correctly. This could also have great implications for stamping original 3D printed artwork as well as figurines, looking toward the embedding of acoustic data—which may work surprising magic all around as everyone from the artist to the retailer feels the benefits. How else do you think this concept might be useful? Discuss further over in the Acoustic Filters & 3D Printing forum at 3DPB.com.
[Source: Columbia Engineering / Images: Columbia Computer Science]