032025_Veera_06
Portrait of Professor Veera Sundararaghavan.
Veera Sundararaghavan is leading a DARPA SURGE project to enable the lifetimes of 3D printed parts to be predicted, specifically metal parts produced through laser powder bed fusion, although in the images, they are working with a 3D printer that produces plastic parts.
The team is combining imaging and audio data that capture defects that arise during the manufacturing process with detailed computer modeling that can simulate how the part will perform over repeated stresses.
Ideally, people working in remote locations could fix broken machinery without sending away for parts that would take weeks to arrive, making parts locally on demand instead. Even though 3D printed parts are much more expensive than cold forged parts, avoiding downtime pays off in many cases. However, they also fail more quickly, so predicting part lifetimes is important to weigh the overall cost and prevent interrupted missions.
Veera Sundararaghavan is a Professor of Aerospace Engineering at the University of Michigan – Ann Arbor and the director of Multiscale Structural Simulations Laboratory. His research is on multi-length scale computational techniques for modelling and design of aerospace materials with a focus on microstructural mechanics (crystal plasticity, homogenization) and molecular simulation. He is particularly interested in new computational techniques that can revolutionize the way we compute in materials science: machine learning and quantum computing algorithms.
March 20, 2025.
Photo by Marcin Szczepanski/Lead Multimedia Producer, University of Michigan College of Engineering
032025_Veera_06
Portrait of Professor Veera Sundararaghavan.
Veera Sundararaghavan is leading a DARPA SURGE project to enable the lifetimes of 3D printed parts to be predicted, specifically metal parts produced through laser powder bed fusion, although in the images, they are working with a 3D printer that produces plastic parts.
The team is combining imaging and audio data that capture defects that arise during the manufacturing process with detailed computer modeling that can simulate how the part will perform over repeated stresses.
Ideally, people working in remote locations could fix broken machinery without sending away for parts that would take weeks to arrive, making parts locally on demand instead. Even though 3D printed parts are much more expensive than cold forged parts, avoiding downtime pays off in many cases. However, they also fail more quickly, so predicting part lifetimes is important to weigh the overall cost and prevent interrupted missions.
Veera Sundararaghavan is a Professor of Aerospace Engineering at the University of Michigan – Ann Arbor and the director of Multiscale Structural Simulations Laboratory. His research is on multi-length scale computational techniques for modelling and design of aerospace materials with a focus on microstructural mechanics (crystal plasticity, homogenization) and molecular simulation. He is particularly interested in new computational techniques that can revolutionize the way we compute in materials science: machine learning and quantum computing algorithms.
March 20, 2025.
Photo by Marcin Szczepanski/Lead Multimedia Producer, University of Michigan College of Engineering