Collin Foster to spend a study year at Lawrence Berkeley National lab

10/19/2021 Debra Levey Larson

Written by Debra Levey Larson

Collin Foster in aerospace lab
Collin Foster

Doctoral student Collin Foster was selected as one of just 65 graduate students to receive the U.S. Department of Energy Office of Science Graduate Student Research fellowship, a program that allows him to spend up to 12 months of his graduate studies in residence at Lawrence Berkeley National Laboratory.

“This is a particularly coveted fellowship because Collin will get a year of world-class training, as well as access to state-of-the-art facilities and resources,” said Francesco Panerai, Foster’s adviser in the Department of Aerospace Engineering at the University of Illinois Urbana-Champaign.

Foster will be at the Advanced Light Source at Lawrence Berkeley National Lab to conduct in-situ high temperature experiments on composite materials used in hypersonic flight.

DOE’s press release states this program “prepares graduate students to enter jobs of critical importance to the DOE mission and secures our national position at the forefront of discovery and innovation.”

“Understanding the nonlinear thermal response of thermal protection systems is critical to the development of multi-physics simulations for the hypersonic environment,” Foster said.

Providing some background, Foster said, “Ablative carbon- and silica-phenolic weaves are the primary technologies to withstand the dynamic chemical, mechanical, and thermal loadings experienced during reentry flight. An established tool for extracting these relevant geometries from the 3D anisotropic materials is x-ray micro-computed tomography, to resolve at sub-micron resolution. High thermal loading must be captured in place with micro-CT in order to accurately characterize material response for both the weave and resin phases.

“The relevant materials are subject to inert atmosphere thermal degradation for pyrolysis, and reactive flows in an oxygenated environment under continuous acquisition. The large quantities data captured will be segmented and reconstructed using state-of-the-art convolutional neural networks. Segmented regions are meshed for multi-physics simulations and evaluated for effective properties,” Foster said.

For a list of the 65 awardees, their institutions, host DOE laboratory/facility, and priority research areas of projects, visit the website.


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This story was published October 19, 2021.