The Data-Model Convergence (DMC) Initiative is a multidisciplinary effort to create the next generation of scientific computing capability through a software and hardware co-design methodology.
In January 2024, CESER—in partnership with GDO, NASEO, and PNNL—created a set of state energy security cohorts to support the coordination and technical development of state energy security planning, assessment, and mitigation.
The E-COMP Initiative is creating new capabilities that enable the optimized design and operation of energy systems subject to multiple objectives and with high levels of power electronics.
E4D is a 3D geophysical modeling and inversion program designed for subsurface imaging and monitoring using static and time-lapse electrical resistivity tomography (ERT), spectral induced polarization (SIP) and travel-time tomography data.
PNNL will partner with the U.S. Department of Transportation’s Volpe Center to explore ways to to achieve federal goals for developing electric transmission infrastructure in transportation rights-of-way (ROWs).
PNNL is a leader in the integration of aberration-corrected electron microscopy, in-situ techniques, and atom probe tomography to address challenges in nuclear materials, environmental remediation, energy storage, and national security.
PNNL’s ESMI is a Laboratory-funded research and development (R&D) program focused on transforming and accelerating materials development processes for next-generation energy storage technologies.
Fish reintroduction is the intentional establishment of a fish species in an area where it existed historically prior to hydropower development and other terrain changes to the species’ habitat.
The Flow Tradeoff Tool is a free, comprehensive software toolkit designed to evaluate trade-offs between hydropower energy production and environmental flows.
The Grid Storage Launchpad (GSL) is a national capability for energy storage research funded by the Department of Energy Office of Electricity and located on the Pacific Northwest National Laboratory (PNNL) campus in Richland, Washington
A new set of resources from PNNL helps guide dam owners and operators through response and recovery actions in the wake of cybersecurity or unusual incidents.
By improving the Weather Research and Forecasting (WRF)-Solar model, this project aims to reduce forecast errors, improve sub-grid scale variability estimates, and more accurately estimate forecast uncertainty.
