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Researchers at Oak Ridge National Laboratory have developed a modeling method that uses machine learning to accurately simulate electric grid behavior while protecting proprietary equipment details. The approach overcomes a key barrier to accurate grid modeling, helping utilities plan for future demand and prevent blackouts.
The University of Oklahoma and Oak Ridge National Laboratory, the Department of Energy’s largest multi-program science and energy laboratory, have entered a strategic collaboration to establish a cutting-edge additive manufacturing center based in Norman, OK.
Inspired by a visit to ORNL’s Manufacturing Demonstration Facility, Jonaaron Jones launched a career in additive manufacturing that led to founding Volunteer Aerospace and now leading Beehive Industries’ external parts business. Through close collaboration with MDF, Jones has helped drive innovation in defense, aviation and energy, while growing high-tech jobs and strengthening the U.S. manufacturing base.
During his first visit to Oak Ridge National Laboratory, Energy Secretary Chris Wright compared the urgency of the Lab’s World War II beginnings to today’s global race to lead in artificial intelligence, calling for a “Manhattan Project 2.”
Melissa Cregger of the Department of Energy’s Oak Ridge National Laboratory has received the Presidential Early Career Award for Science and Engineers, or PECASE, the highest honor bestowed by the U.S. government on outstanding early-career scientists and engineers.
Researchers at Oak Ridge National Laboratory have developed a new automated testing capability for semiconductor devices, which is newly available to researchers and industry partners in the Grid Research Integration and Deployment Center.
P&G is using simulations on the ORNL Summit supercomputer to study how surfactants in cleaners cause eye irritation. By modeling the corneal epithelium, P&G aims to develop safer, concentrated cleaning products that meet performance and safety standards while supporting sustainability goals.
Phong Le is a computational hydrologist at ORNL who is putting his skills in hydrology, numerical modeling, machine learning and high-performance computing to work quantifying water-related risks for humans and the environment.
National lab collaboration enables faster, safer inspection of nuclear reactor components, materials
A research partnership between two Department of Energy national laboratories has accelerated inspection of additively manufactured nuclear components, and the effort is now expanding to inspect nuclear fuels.
During Hurricanes Helene and Milton, ORNL deployed drone teams and the Mapster platform to gather and share geospatial data, aiding recovery and damage assessments. ORNL's EAGLE-I platform tracked utility outages, helping prioritize recovery efforts. Drone data will train machine learning models for faster damage detection in future disasters.