By combining computational modeling with experimental research, scientists identified a promising composition that reduces the need for a critical material in an alloy that can withstand extreme environments.
PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.
New methodological approach demonstrates how to assess the economic value, including non-traditional value streams, of converting non-powered dams to hydroelectric facilities.
Fish biologist Brenda Pracheil has been named chair of the Low Impact Hydropower Institute focused on reduction of impacts of hydropower dams on the environment.
Recognizing how innovation and clean technologies at the very edge of the grid can work together to transition the electricity system, PNNL takes a multidisciplinary approach to advancing and integrating renewable energy solutions.
Rotational Hammer Riveting, developed by PNNL, joins dissimilar materials quickly without preheating rivets. The friction-based riveting enables use of lightweight magnesium rivets and also works on aluminum and speeds manufacturing.
PNNL scientists developed a new, tiny battery and tag to track younger, smaller species, to evaluate behavior and estimate survival during downstream migration.
PNNL biologists have developed a more efficient way to estimate salmon survival through dams that uses solid science but saves over 42 percent of the cost.
Twelve energy-related technologies developed at PNNL have been selected for additional technology maturation funding to help move them from the laboratory and field tests to the marketplace.
PNNL's Sensor Fish were deployed at Ice Harbor Dam to collect data from a new turbine. The data indicates the design changes are making travel through the dam less arduous for fish.
