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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.
In collaboration with the U.S. Department of Homeland Security’s Science and Technology Directorate, researchers at ORNL are evaluating technology to detect compounds emitted by pathogens and pests in agricultural products at the nation’s border.
Training nuclear safety experts to measure the unseen: ORNL’s course enhances nuclear accountability
Professionals from government and industry gathered at ORNL for the Nondestructive Assay Holdup Measurements Training Course for Nuclear Criticality Safety, a hands-on training in nondestructive assay, a technique for detecting and quantifying holdup without disturbing operations.
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.”
Working at nanoscale dimensions, billionths of a meter in size, a team of scientists led by ORNL revealed a new way to measure high-speed fluctuations in magnetic materials. Knowledge obtained by these new measurements could be used to advance technologies ranging from traditional computing to the emerging field of quantum computing.
Neus Domingo Marimon, leader of the Functional Atomic Force Microscopy group at the Center for Nanophase Materials Sciences of ORNL, has been elevated to senior member of the Institute of Electrical and Electronics 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.
Researchers at the Department of Energy’s Oak Ridge National Laboratory are using non-weather data from the nationwide weather radar network to understand how to track non-meteorological events moving through the air for better emergency response.
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.
A team of researchers at ORNL are using virtual reality to understand normal and abnormal human behavior in a given location – specifically, a nuclear reactor. As people move around their lives, they tend to do similar activities in the same