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Laminations such as these are compiled to form the core of modern electric vehicle motors. ORNL has developed a software toolkit to speed the development of new motor designs and to improve the accuracy of their real-world performance.

Oak Ridge National Laboratory scientists have created open source software that scales up analysis of motor designs to run on the fastest computers available, including those accessible to outside users at the Oak Ridge Leadership Computing Facility.

Researchers used machine learning methods on the ORNL Compute and Data Environment for Science, or CADES, to map vegetation communities in the Kougarok Watershed on the Seward Peninsula of Alaska. The colors denote different types of vegetation, such as w

A team of scientists led by Oak Ridge National Laboratory used machine learning methods to generate a high-resolution map of vegetation growing in the remote reaches of the Alaskan tundra.

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Scientists from the Critical Materials Institute used the Titan supercomputer and Eos computing cluster at ORNL to analyze designer molecules that could increase the yield of rare earth elements found in bastnaesite, an important mineral 

SmartTruck, a small business in Greenville, SC, recently completed its first detailed unsteady analysis using modeling and simulation at the OLCF and became the first company to request certification from the EPA through CFD. Image Credit: SmartTruck

Long-haul tractor trailers, often referred to as “18-wheelers,” transport everything from household goods to supermarket foodstuffs across the United States every year. According to the Bureau of Transportation Statistics, these trucks moved more than 10 billion tons of goods—70.6 ...

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Scientists at Oak Ridge National Laboratory have conducted a series of breakthrough experimental and computational studies that cast doubt on a 40-year-old theory describing how polymers in plastic materials behave during processing.

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