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MSE Colloquium: Darren Pagan, Pennsylvania State University

All dates for this event occur in the past.

2040 Fontana Labs
140 W. 19th Ave
Columbus, OH 43210
United States

Dr. Darren Pagan

Assistant Professor, Materials Science and Engineering Department
Penn State University
 

New Opportunities for Inclusion of Constitutive Modeling in the Interpretation and Analysis of In-situ X-ray Diffraction Data


High-performance designs that utilize engineering alloys are driving a need to understand and predict deformation in-situ at the fine length scales in order to reduce weight, increase operating temperatures, and improve fatigue life. With brighter high-energy X-ray sources and more efficient detectors our ability to probe bulk microstructural and micromechanical response at these length scales in conditions mimicking processing and in-service is continuously improving. In fact, measurement capabilities have rapidly improved to the point that our ability to collect large amounts X-ray data has far outstripped our ability to effectively analyze it. A possible reason for this is that analysis techniques have grown around the paradigm of characterizing static material structure as opposed to evolving material response. Since its adoption as a material characterization technique, X-ray scattering has relied on combinations of scattering and structural material models to extract material-relevant quantities from the raw data. As X-ray techniques have become increasingly complex, the scattering half of the modeling efforts required for data interpretation have advanced continuously, while the material half of modeling efforts have progressed at much a slower pace.

photo of Darren Pagan, Penn State University Materials Science and Engineering

In my presentation, I will describe examples of how replacing static material structural models with thermomechanical constitutive modeling (both phenomenological and machine-learning driven) can build a much richer understanding of material evolution during complex thermomechanical processes and provide a means of more effective data analysis.

Bio

 

Darren Pagan is an assistant professor in the Materials Science and Engineering Department and is an associate of the Institute for Computational and Data Sciences at Penn State. He earned a B.S. degree in mechanical engineering from Columbia University in 2010 and his Ph.D. in mechanical engineering from Cornell University in 2016. Prior to joining Penn State, Darren Pagan was a staff scientist overseeing the structural materials and mechanics program at the Cornell High Energy Synchrotron Source (CHESS). At CHESS, he was responsible for the design, construction, and commissioning of the Structural Materials Beamline (SMB) and the Forming and Shaping Technology Beamline (FAST). Darren joined the faculty of the Department of Materials Science and Engineering at Penn State in 2020.
 

 

Zoom link

https://osu.zoom.us/j/94975564317?pwd=cHc2d05KNDdMdlJqcERuSTFyY1pBUT09

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