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An algorithm developed and field-tested by ORNL researchers uses machine learning to maintain homeowners’ preferred temperatures year-round while minimizing energy costs. Credit: ORNL, U.S. Dept. of Energy

Oak Ridge National Laboratory researchers designed and field-tested an algorithm that could help homeowners maintain comfortable temperatures year-round while minimizing utility costs.

Brian Damiano

Brian Damiano, head of the Centrifuge Engineering and Fabrication Section, has been elected fellow of the American Society of Mechanical Engineers.

Smart Neighborhood homes

To better determine the potential energy cost savings among connected homes, researchers at Oak Ridge National Laboratory developed a computer simulation to more accurately compare energy use on similar weather days.