Computational Science News

June 29, 2022

News Release: Scientists Look to the Sky in Effort To Mitigate Carbon Problem

A global research effort spearheaded by NREL has assessed two promising technologies to remove carbon dioxide from the atmosphere. While still in the early stages of development, direct air carbon capture and sequestration--together with other carbon dioxide removal strategies--are considered critical to achieving a net-zero greenhouse gas emissions economy.

May 26, 2022

Joint Institute for Strategic Energy Analysis Launches Green Computing Catalyzer

The third catalyzer in the JISEA Catalyzers initiative will explore algorithmic energy efficiency, in addition to ways to limit energy usage of computing and potential pathways to reuse, repair, or recycle hardware products and materials.

May 6, 2022

No Time, No Chips: No Problem for NREL

Amid global supply chain delays and semiconductor shortages, NREL researchers use creative problem-solving to deploy two high-performance computing solutions within one year.

April 29, 2022

Building Trust in AI To Ensure Equitable Solutions

Researchers at NREL are leading research to address bias in artificial intelligence and machine learning for clean energy innovation.

March 14, 2022

News Release: Scientists Show Large Impact of Controlling Humidity on Greenhouse Gas Emissions

Greenhouse gas emissions from air conditioners are expected to climb as economic growth drives efforts to control both temperature and humidity, according to an analysis by scientists from the National Renewable Energy Laboratory and Xerox PARC.

Jan. 11, 2022

NREL Scientists Dive Into Data in Search of Answers

In NREL's Insight Center, models come to life, illuminating pathways to a clean energy future.

Jan. 5, 2022

Python Opens Up New Applications for EnergyPlus Building Energy Simulation

Buildings account for more than 40% of U.S. energy use and 70% of U.S. electricity use. Reducing that consumption and "shaping" it to match renewable generation requires us to design and operate buildings to be more efficient, flexible, and responsive. To do that, we must be able to better predict and model building energy use.

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