Quantum precision reached in modeling molten salt behavior
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.
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.
Scientists conducted a groundbreaking study on the genetic data of over half a million U.S. veterans, using tools from the Oak Ridge National Laboratory to analyze 2,068 traits from the Million Veteran Program.
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
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.
Scientists and land managers interested in accessing the first dataset of its kind on one of the most biologically diverse ecosystems in the world were given hands-on tutorials during a recent workshop by researchers supporting the ORNL Distributed Active Archive Center for Biogeochemical Dynamics.
Scientists at ORNL have developed a first-ever urban heat wave simulation that takes into account the compounding effects from building infrastructure. The method provides a more accurate picture of the impacts from excessive heat on at-risk
Scientists at the Department of Energy’s Oak Ridge National Laboratory recently demonstrated an autonomous robotic field monitoring, sampling and data-gathering system that could accelerate understanding of interactions among plants, soil and the environment.
In early November, ORNL hosted the International Atomic Energy Agency (IAEA) Interregional Workshop on Safety, Security and Safeguards by Design in Small Modular Reactors, which welcomed 76 attendees representing 15 countries, three U.S. national labs, domestic and international industry partners, as well as IAEA officers.