Large Scale Test Apparatus to Test External Leak Detection Technologies
Bibliographic record
Abstract
When it comes to evaluating traditional computational leak detection technologies pipeline operators have a suite of simulated testing methods available. In the last several years however External Leak Detection Technologies have become more mature and potentially could provide operators with another layer of leak detection with more sensitivity than seen in traditional methods. The challenge with these technologies is in the evaluation of their sensitivity, reliability, and robustness. ENBRIDGE INC (Enbridge) and C-FER Technologies 1999 Inc. (C-FER) begun a comprehensive study to assess the state-of-the-art external, continuously distributed sensors for leak detection in early 2012. Initially, a technology review was undertaken to identify commercial, off-the-shelf technologies with the potential to detect small leaks of oil from buried pipelines. From this literature review, four technologies were identified; Distributed Temperature Sensing (DTS), Distributed Acoustic Sensing (DAS), Vapor Sensing Tubes (VST), and Hydrocarbon Sensing Cables (HSC). All four methods require proprietary materials and technology, which have had limited independent testing efforts to date. To evaluate these four leak detection methods and their vendors in an objective way, Enbridge and C-FER initiated the design and construction of a large-scale External Leak Detection Experimental Research apparatus (ELDER) that can accommodate a full-size segment of pipeline within a trench, at the same scale used in pipeline construction in North America. An instrumented pipe segment is buried in the trench with sensing cables laid alongside. The apparatus generates leaks with controlled variables including rate, pressure and temperature, and at various locations to accurately represent pipeline leaks. This paper summarizes the literature review on the four selected leak detection technologies that were identified as candidates for large-scale evaluation. The discussion will also include features of the ELDER apparatus, and re-engineered pipeline construction techniques that were required to accurately represent a full-scale pipeline trench within a laboratory environment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".