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Male student wearing clear safety goggles peering through a 3D-printed item.

A group of high school graduates and community college students visited ORNL to meet staff and find out just what goes on at a DOE national laboratory. The Job Shadow Day was arranged by tnAchieves, a student support organization that works to increase higher educational opportunities for students across Tennessee through scholarships and mentorship. 
 

ORNL researchers modeled how hurricane cloud cover would affect solar energy generation as a storm followed 10 possible trajectories over the Caribbean and Southern U.S. Credit: Andy Sproles/ ORNL,U.S. Dept. of Energy

ORNL researchers modeled how hurricane cloud cover would affect solar energy generation as a storm followed 10 possible trajectories over the Caribbean and Southern U.S.

Sangkeun “Matt” Lee received the Best Poster Award at the Institute of Electrical and Electronics Engineers 24th International Conference on Information Reuse and Integration.

Lee's paper at the August conference in Bellevue, Washington, combined weather and power outage data for three states – Texas, Michigan and Hawaii –  and used a machine learning model to predict how extreme weather such as thunderstorms, floods and tornadoes would affect local power grids and to estimate the risk for outages. The paper relied on data from the National Weather Service and the U.S. Department of Energy’s Environment for Analysis of Geo-Located Energy Information, or EAGLE-I, database.