First-generation graduate Brittany Rodriguez advances manufacturing scie...
Joe Tuccillo, a human geography research scientist, leads the UrbanPop project that uses census data to create synthetic populations. Using a Python software suite called Likeness on ORNL’s high-performance computers, Tuccillo’s team generates a population with individual ‘agents’ designed to represent people that interact with other agents, facilities and services in a simulated neighborhood.
Two ORNL teams recently completed Cohort 18 of Energy I-Corps, an immersive two-month training program where the scientists define their technology’s value propositions, conduct stakeholder discovery interviews and develop viable market pathways.
Power companies and electric grid developers turn to simulation tools as they attempt to understand how modern equipment will be affected by rapidly unfolding events in a complex grid.
Researchers at the Department of Energy’s Oak Ridge National Laboratory and partner institutions have launched a project to develop an innovative suite of tools that will employ machine learning algorithms for more effective cybersecurity analysis of the U.S. power grid.
Brian Sanders is focused on impactful, multidisciplinary science at Oak Ridge National Laboratory, developing solutions for everything from improved imaging of plant-microbe interactions that influence ecosystem health to advancing new treatments for cancer and viral infections.
The contract will be awarded to develop the newest high-performance computing system at the Oak Ridge Leadership Computing Facility.
Brittany Rodriguez never imagined she would pursue a science career at a Department of Energy national laboratory. However, after some encouraging words from her mother, input from key mentors at the University of Texas Rio Grande Valley, or UTRGV, and a lot of hard work, Rodriguez landed at DOE’s Manufacturing Demonstration Facility, or MDF, at Oak Ridge National Laboratory.
The Department of Energy’s Oak Ridge National Laboratory has publicly released a new set of additive manufacturing data that industry and researchers can use to evaluate and improve the quality of 3D-printed components. The breadth of the datasets can significantly boost efforts to verify the quality of additively manufactured parts using only information gathered during printing, without requiring expensive and time-consuming post-production analysis.
ORNL hosted the Mid-South Regional Chapter of the American Society for Photogrammetry and Remote Sensing, or ASPRS. Participants spanning government, academia and industry engaged in talks, poster sessions, events and workshops to further scientific discovery in a field devoted to using pictures to understand changes to the earth’s inhabitants and landscape.
A newly established internship between ORNL and Maryville College is bringing cybersecurity careers to a local liberal arts college. The internship was established by a Maryville College alumni who recently joined ORNL.