The next-generation ShAPE machine has arrived at PNNL, where it will help prove the mettle of the ShAPE extrusion technique. ShAPE 2 is designed to allow researchers to produce larger, more complex extrusions.
Researchers from PNNL have been assessing installation and use of electric heat pumps in an Alaskan community that relies on fuel oil for heat. The resulting information could advance electrification in cold rural areas across the nation.
The use of disciplines in pure mathematics can increase the reliability and explainability of machine learning models that “transcend human intuition,” according to PNNL scientists.
To overcome high-performance computing bottlenecks, a research team at PNNL proposed using graph theory, a mathematical field that explores relationships and connections between a number, or cluster, of points in a space.
Scientists are pioneering approaches in the branch of artificial intelligence known as machine learning to design and train computer software programs that guide the development of new manufacturing processes.
A new control system shows promise in making millions of homes contributors to improved power grid operations, reaping cost and environmental benefits.
Lighting control data are critical for optimizing the design and operation of future lighting systems for the benefit of occupants and energy efficiency.
PNNL researchers develop software that uses geographical data to build a free, open-source grid reference system to provide a precise system to locate structures.
New building energy codes could reduce utility bills by $138 billion and prevent 900 million metric tons of CO2 emissions coming from buildings. Now, they will be easier to adopt.