Development of a Tunable Diode Laser Absorption Spectroscopy Mass-Flux Sensor for Quantifying Hydrocarbon Storage Tank Venting
Bibliographic record
Abstract
Fixed-roof liquid hydrocarbon storage tanks are a recognized source of volatile organic compounds and greenhouse gases.However, current emissions estimates suffer from a lack of reliable models due to poor in situ validation.This work presents the development and characterization of an intrinsically safe, low velocity mass-flux sensor for monitoring storage tank venting.The sensor is based on tunable diode laser absorption spectroscopy (TDLAS) with wavelength modulation.Similar sensors have been successfully used to measure high velocity flows, such as shock propagation and scramjet combustor exhaust.The oxygen within the vapour space of fixed-roof storage tanks is targeted in the near-IR as the absorption species.Sensor design, optimum operational parameters, and indoor characterization results are presented.An oxygen concentration precision of greater than 0.11% absolute was achieved over the tested range of 2.5 to 21% O2.For measurements at 21% O2, a velocity standard deviation of 0.24 m/s for 30-s average measurements was achieved, which could be improved to 0.07 m/s with a 10-minute interval drift correction.However, the velocity measurement accuracy was poor at lower O2 concentrations, restricting the mass flux capability of the current system.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".