Quantifying greenhouse gas methane emissions from simulated plumes: A hybrid computational fluid dynamics (CFD) and image-based approach

Simple item page
dc.contributor.authorMansoori, Ghazal
dc.contributor.supervisorDarcie, Thomas Edward
dc.contributor.supervisorSmith, Levi
dc.date.accessioned2025-12-02T21:36:55Z
dc.date.available2025-12-02T21:36:55Z
dc.date.issued2025
dc.degree.departmentDepartment of Electrical and Computer Engineering
dc.degree.levelMaster of Applied Science MASc
dc.description.abstractGiven methane’s role as a potent greenhouse gas with a significantly higher short term global warming potential than carbon dioxide, its accurate quantification is critical for early detection and mitigation. This thesis presents a simulation-driven framework for quantifying greenhouse gas methane leak rates using image-based projections derived from computational fluid dynamics (CFD). Methane emissions with field-representative leak rates were modeled in open-air environments using three dimensional (3D) simulations under varying wind and leak source conditions. The resulting volumetric data were transformed to mimic the output of remote optical sensing systems, enabling leak rate estimation via a MATLAB-based algorithm grounded in the principles of mass conservation. This approach offers a practical foundation for remote methane quantification, with potential applications in sensor validation, environmental monitoring, and climate action strategies focused on emission reductions.
dc.description.scholarlevelGraduate
dc.identifier.urihttps://hdl.handle.net/1828/22935
dc.languageEnglisheng
dc.language.isoen
dc.rightsAvailable to the World Wide Web
dc.subjectGas leak quantification
dc.subjectGreenhouse gas methane emissions
dc.subjectComputational fluid dynamics (CFD)
dc.subjectSimulation
dc.titleQuantifying greenhouse gas methane emissions from simulated plumes: A hybrid computational fluid dynamics (CFD) and image-based approach
dc.typeThesis

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Mansoori_Ghazal_MASc_2025.pdf
Size:
5.77 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.62 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Electronic Theses and Dissertations (ETD)
 
University of Victoria Libraries

We acknowledge and respect the Lək̓ʷəŋən (Songhees and Esquimalt) Peoples on whose territory the university stands, and the Lək̓ʷəŋən and W̱SÁNEĆ Peoples whose historical relationships with the land continue to this day.