This website uses cookies primarily for visitor analytics. Certain pages will ask you to fill in contact details to receive additional information. On these pages you have the option of having the site log your details for future visits. Indicating you want the site to remember your details will place a cookie on your device. To view our full cookie policy, please click here. You can also view it at any time by going to our Contact Us page.

Finding the strongest shapes with 3D printing

19 March 2013

Professor Henrich Jaeger's lab at the University of Chicago uses 3D printing to test complex qualities of shapes made via a computer.

Graduate student Marc Miskin manufactured granular materials of various shapes in a 3D printer to test their aggregate properties when jammed into a confined space (photo: Rob Kozloff)

Professor Heinrich Jaeger’s research group examines materials and phenomena that appear simple at the surface, but which reveal tremendous complexity upon close examination. One such phenomenon is 'jamming', in which aggregates of randomly placed particles, including spheres or more complicated shapes, or even molecules, transition from fluid-like to solid-like behaviour.
Jamming lends itself to soft robotics, in addition to other applications as explored in a workshop at the University of Chicago last October. In recent computer simulations and experiments, Jaeger and graduate student Marc Miskin investigate another aspect of jamming.

They analysed how the properties of a jammed material can be tuned by changing the shape of the constituent particles.

Miskin and Jaeger addressed a daunting question in their research: given a design goal for the jammed aggregate - for example, to have it as stiff or as soft as possible in response to an applied force - what particle shape will best produce the desired outcome?

For this complex optimisation problem, they faced an infinite variety of shapes to choose from. So Miskin employed a computer algorithm, referred to as an 'evolutionary optimisation' (see video clip) to answer this question.
The computer designed particles by starting from a random shape, and then iteratively altered its configuration, at each stage performing a series of simulations that tested how close the performance approximated the stated goal.

Once an optimal shape was identified, Miskin then manufactured a large number of copies with the lab’s 3D printer for testing in a vice-like squeezing apparatus to verify his algorithm’s predictions

Contact Details and Archive...

Print this page | E-mail this page

RS Components Condition Monitoring