News Article, February 16, 2022 • Machine learning used to predict direction-dependent mechanical properties of metals A machine-learning algorithm developed at Sandia could provide auto manufacturing, aerospace and other industries a faster and more cost-efficient way to test bulk materials. The technique was published recently in the scientific journal Materials Science and Engineering: A. Production stoppages are...
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Sandia uncovers hidden factors that affect solar farms during severe weather
News Article, August 31, 2021 • Machine learning found farm age, cloud cover impact performance during a storm Sandia National Laboratories researchers combined large sets of real-world solar data and advanced machine learning to study the impacts of severe weather on U.S. solar farms, and sort out what factors affect energy generation. Their results were published...