Method and system for analyzing gas leak based on machine learning

Patent · 24 July 2018

OSTI ID:1464218

Smith, Clinton J.; Saha, Bhaskar; Beck, Victor A.; Schwartz, David E.

Embodiments of the present invention provide a system for estimating a location of a gas leak, based on machine learning from forward gas concentration data provided by an analog or scale model including a gas source. The system improves significantly over previous systems by providing high quality, physically accurate forward modeling data inexpensively. During operation, the system configures an aerosol source at a first location to emit a gaseous aerosol. The system then configures a laser source to illuminate the aerosol with a laser sheet. The system may then obtain an image of a reflection of the laser sheet from the aerosol. The system may then analyze the image to quantify a three-dimensional concentration distribution of the aerosol. The system may then estimate, based on solving an inverse problem and an observed second gas concentration, a second location of a second gas source.

• Research Organization: Palo Alto Research Center Incorporated, Palo Alto, CA (United States)
• Sponsoring Organization: USDOE Advanced Research Projects Agency - Energy (ARPA-E)
• DOE Contract Number: AR0000542
• Assignee: Palo Alto Research Center Incorporated (Palo Alto, CA)
• Patent Number(s): 10,031,040
• Application Number: 15/472,018
• OSTI ID: 1464218
• Country of Publication: United States
• Language: English

Related Subjects

03 NATURAL GAS
97 MATHEMATICS AND COMPUTING