Computationally efficient quantification of unknown fugitive emissions sources
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Fugitive emissions or unintentional losses of gas (e.g. leaks) are a significant source of greenhouse gases within the oil and gas sector. Previous work has demonstrated the potential of a scalar transport adjoint method for using sparse sensor data to locate and quantify multiple simultaneous unknown fugitive emission sources within a bluff-body dominated facility environment. This paper builds directly on that work and demonstrates the significant computational time reductions that can be achieved by modifying this approach to use a database of pre-computed retro-tracers (PRT). The computational cost, as well as estimated source emission rates and locations, were compared for both an open field release and multiple releases in a bluff-body dominated domain when using the PRT method versus the concurrent gas transport computations from previous work. For the open-field release, given the same wind input there were no significant differences in results of the two approaches. For the bluff-body dominated multiple source case (a domain representative of an actual gas plant), using simplified wind fields for the PRT database generation allowed major sources to be successfully located. The emission rates were computed within −75% to −32% of their actual value. When the wind direction coverage was increased to 110° from ∼60°, the emission rate computations improved to within approximately −30% to −25%. The total computational cost for both methods was of a similar order of magnitude when including the initial database generation for the PRT method, but non-reusable computational time was reduced by a factor of 200–600 times making the PRT method feasible on a standard desktop computer once the database is generated. This is a noteworthy achievement as it raises the possibility of continuous or near-continuous characterization of unknown fugitive emissions sources within
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it