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1 - 10 of 164 Results
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.”

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.

Scientists designing the world’s first controlled nuclear fusion power plant, ITER, needed to solve the problem of runaway electrons, negatively charged particles in the soup of matter in the plasma within the tokamak, the magnetic bottle intended to contain the massive energy produced. Simulations performed on Summit, the 200-petaflop supercomputer at ORNL, could offer the first step toward a solution.

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.


Maximiliano Ferrari, a researcher in the Grid Systems Architecture group at the Department of Energy’s Oak Ridge National Laboratory, has been elevated to prestigious senior membership in the Institute of Electrical and Electronics Engineers.