The work by the team at PNNL takes a critical step in leveraging ML to accelerate advanced manufacturing R&D, specifically for manufacturing techniques without access to efficient, first-principles simulations.
Staff at PNNL recently completed a report highlighting commercial products enabled through projects funded by the Department of Energy’s Building Technologies Office.
The Simple Building Calculator, developed at PNNL, meets a need for a quick, interactive, and economic method to evaluate energy use—and potential savings from efficiency measures—in simple commercial buildings.
Scientists are pioneering approaches in the branch of artificial intelligence known as machine learning to design and train computer software programs that guide the development of new manufacturing processes.
PNNL’s Ján Drgoňa and Draguna Vrabie are part of an international team that authored a most-cited paper on Model Predictive Control, an approach for improving operations, energy efficiency, and comfort in buildings.
PNNL’s Reid Hart and Bing Liu have earned individual Champions of Energy Efficiency in Buildings awards from the American Council for an Energy-Efficient Economy.
PNNL's Tegan Emerson was invited to be one of two plenary speakers at the inaugural AIM 2022 congress. The Minerals, Metals & Materials Society organized AIM 2022 to connect materials and manufacturing researchers from around the world.
A new control system shows promise in making millions of homes contributors to improved power grid operations, reaping cost and environmental benefits.
