Quantum precision reached in modeling molten salt behavior
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.
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.
Chad Parish, a senior researcher at ORNL, studies materials at the atomic level to improve nuclear reactors. His work focuses on fusion and fission energy, using microscopy and collaborating with experts to advance materials for extreme environments.
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.
The US focuses on nuclear nonproliferation, and ORNL plays a key role in this mission. The lab conducts advanced research in uranium science, materials analysis and nuclear forensics to detect illicit nuclear activities. Using cutting-edge tools and operational systems, ORNL supports global efforts to reduce nuclear threats by uncovering the history of nuclear materials and providing solutions for uranium removal.
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
The National Center for Computational Sciences, located at the Department of Energy’s Oak Ridge National Laboratory, made a strong showing at computing conferences this fall. Staff from across the center participated in numerous workshops and invited speaking engagements.
Researchers are using machine learning to provide a more complete picture of building geometries that include building height to within three meters of accuracy. This model not only provides building height for any building in the world, but it will also feed into LandScan and other large government datasets for planning and response.
FREDA is a new tool being developed at ORNL that will accelerate the design and testing of next-generation fusion devices. It is the first tool of its kind to combine plasma and engineering modeling capabilities and utilize high performance computing resources.
The Department of Energy’s Oak Ridge National Laboratory had a major presence at this year’s International Conference for High Performance Computing, Networking, Storage, and Analysis (SC24).