A modeling study shows that adding batteries to a dam could decrease the wear and tear on hydropower turbines and open up new opportunities for dam operators to earn revenue.
Researchers at PNNL share a research- and practitioner-informed approach to assess the threat landscape, elicit and integrate feedback into solutions, and ultimately share outcomes with the emergency response and public safety community.
Two new publications provide emergency response agencies with critical insights into commercially available unmanned ground vehicles used for hazardous materials response.
Zhiqun (Daniel) Deng, Lab Fellow at PNNL, has been named a fellow of the American Society of Mechanical Engineers, an honor that recognizes outstanding engineering achievements.
PNNL’s science and technology helps hydropower operators detect, prevent and recover from cyberattacks while protecting a source of electricity that enhances grid reliability and resilience.
A team from PNNL contributed several articles to the Domestic Preparedness Journal showcasing recent efforts to explore the emergency management and artificial intelligence research and development landscape.
Led by interns from multiple DOE programs, a newly expanded dataset allows researchers to use easy-to-obtain measurements to determine the elemental composition of a promising carbon storage mineral.
A team of researchers recently coordinated a series of international workshops aimed at enhancing chemical research security and fostering collaboration among scientists and academic researchers from both countries.
A new analysis shows how renewable energy sources like solar, wind and hydropower respond to climate patterns, and how utilities can use this data to save money and invest in energy storage.
Alicia Amerson's passion for science communication, expertise in marine mammal research, and experience in wildlife photography provide a robust foundation for her new role with the Clallam County Marine Resources Committee.
A new digital twin platform can help hydropower dam operators by providing accurate and predictive models of physical turbines that improve facilities and enhance reliability.
