Projects

15 results found
Filtered by Environmental Performance of Hydropower, Graph and Data Analytics, Radiation Measurement, Solar Energy, Vehicle Energy Storage, Vehicle Technologies, and Visual Analytics
PROGRAM

Agile BioFoundry

PNNL evaluates bacterial, fungi, and algae strains as part of a four-step process to streamline and standardize biomanufacturing processing.
PROGRAM

Battery500 Consortium

PNNL is working with national laboratories and academia to provide electric vehicle manufacturers with batteries that are more reliable, high-performing, safe, and less expensive.

Dynamic Curbs in Urban Settings

A multi-institution research team led by PNNL is addressing curb usage management challenges in large urban areas by developing a city-scale dynamic curb use simulation tool and an open-source curb management platform. 
INITIATIVE

HydroPASSAGE

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

LightMAT Consortium

PNNL is leading a consortium that provides funding opportunities to the automotive industry for accelerating new lightweight technologies in on-highway vehicles.

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.
INITIATIVE

Virtual Reality for High-Impact Learning

PNNL creates immersive software experiences to meet a variety of challenges. One such challenge in science, technology, engineering, and mathematics (STEM) education is providing quality computer science education for all students.

Visual Sample Plan

Visual Sample Plan (VSP) is a software tool that supports the development of a defensible sampling plan based on statistical sampling theory and the statistical analysis of sample results to support confident decision making.