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At least 1,459 records · Page 81

ML Clustering to Identify Natural Gas Pipeline Infrastructure Vulnerabilities

The network of more than 2.5 million miles of natural gas pipelines the U.S. are exposed to a range of vulnerabilities, ranging from extreme weather, to human behavior, and increasingly, to cyber threats. Advanced, data-driven analytics, including the use of machine learning and artificial intelligence, afford an opportunity to identify potential vulnerabilities, better understand risks, and help mitigate vulnerabilities in the network. At NETL, machine learning is being used to explore pipeline vulnerabilities and identify significant clusters of failure events, including failures due to weather, human behavior, and materials. These findings are being used to support the development of new technologies, including sensors, but can also be used to evaluate and inform mitigation strategies to reduce risks and vulnerabilities throughout the network.

Bauer, Jennifer↗

Grant Support for the United States-Extreme Light Infrastructure Joint Dialogue Meeting

This Brightest Light Initiative (BLI) Workshop Report captures the important research ideas and recommendations for enabling that work developed by over 100 leading scientists at a community-initiated workshop held March 27-29, 2019 in Washington, DC. Workshop attendees developed an understanding of key opportunities, as well as gaps in current technologies and capabilities, for science enabled by the highest-intensity lasers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗