A team of researchers at PNNL is developing a new approach to explore the higher-dimensional shape of cyber systems to identify signatures of adversarial attacks.
In a study off the West Coast, researchers find that although seabirds generally soar underneath the height of possible future wind turbine blades, more work is being done to fully understand seabird flight behavior.
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.
Two renewable energy approaches—enhanced geothermal systems and floating offshore wind energy—get new focus as Energy Earthshot™ Research Centers at PNNL.
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.
PNNL researchers developed a new model to help power system operators and planners better evaluate how grid-forming, inverter-based resources could affect the system stability.
Two PNNL studies that describe the potential value of offshore wind off the Oregon Coast and distributed wind in Alaska were published in the journal Energies.
PNNL has paired one of its offshore wind research buoys with its ThermalTracker-3D technology to correlate avian activity with ocean and weather conditions off the California coast.
