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The Consortium for Advanced Simulation of Light Water Reactors uses its Virtual Environment for Reactor Applications (VERA) software for the modeling and simulation of various nuclear reactors, such as the Westinghouse AP1000 pressurized water reactor.

The Department of Energy’s Oak Ridge National Laboratory is collaborating with industry on six new projects focused on advancing commercial nuclear energy technologies that offer potential improvements to current nuclear reactors and move new reactor designs closer to deployment.

The electromagnetic isotope separator system operates by vaporizing an element such as ruthenium into the gas phase, converting the molecules into an ion beam, and then channeling the beam through magnets to separate out the different isotopes.

A tiny vial of gray powder produced at the Department of Energy’s Oak Ridge National Laboratory is the backbone of a new experiment to study the intense magnetic fields created in nuclear collisions.

Oak Ridge National Laboratory’s Summit supercomputer was named No. 1 on the TOP500 List, a semiannual ranking of the world’s fastest computing systems. Credit: Carlos Jones/Oak Ridge National Laboratory, U.S. Dept. of Energy.

The US Department of Energy’s Oak Ridge National Laboratory is once again officially home to the fastest supercomputer in the world, according to the TOP500 List, a semiannual ranking of the world’s fastest computing systems.

Oak Ridge National Laboratory launches Summit supercomputer.

The U.S. Department of Energy’s Oak Ridge National Laboratory today unveiled Summit as the world’s most powerful and smartest scientific supercomputer.

ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system.

A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the