Projects

27 results found
Filtered by Computational Research, Federal Buildings, High-Performance Computing, National Security, Radiation Measurement, Renewable Energy, and Solar Energy

Best Practices

FEMP's operations and maintenance (O&M) resources offer federal agencies technology- and management-focused guidance to improve energy and water efficiency and ensure safer and more reliable operations.
PROGRAM

Electron Microscopy

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.
INITIATIVE

HydroPASSAGE

The HydroPASSAGE project addresses hydropower challenges, which include efforts to improve environmental performance of hydropower.

HydroWIRES

HydroWIRES initiative helps water stakeholders reap the full benefit of hydropower’s superpower: versatility
INITIATIVE

Improving Solar Forecasting

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.
PROGRAM

Lidar Buoy Program

PNNL administers two research buoys for the U.S. Department of Energy that allows collection of wind meteorological and oceanographic data off the nation's coasts.
INITIATIVE

m/q Initiative

PNNL is heavily engaged in the development and use of mass spectrometry technology across its science, energy, and security missions, from fundamental research through mature operational capabilities.
PROGRAM

National Security Training

PNNL designs, delivers, and manages training programs that enable partners worldwide to understand their individual or organizational roles and responsibilities, fulfill a job function, or strengthen a particular skill set.

PNNL @ NeurIPS 2020

PNNL data scientists and engineers will be presenting at NeurIPS, the Thirty Fourth Conference on Neural Information Processing Systems, and the co-located Women in Machine Learning workshop, WiML.