Critical Shear Stress Estimates of Sunken Alberta Bitumen
Bibliographic record
Abstract
As observed in several recent spills (e.g., DBL-152, TX; Enbridge-Kalamazoo, MI), under certain circumstances, released oil can sink to the bottom of a water body. Once on the bottom, the oil can move or remobilize into the water column. The National Oceanic and Atmospheric Administration’s (NOAA) Office of Response and Restoration (ORR) uses mathematical models to predict the trajectory of spilled oil. The critical shear stress (CSS) for an oil is used to predict the movement of sunken oil along and off the bottom. The CSS has only been measured for one oil (Hibernian crude). The Coastal Response Research Center (CRRC) at the University of New Hampshire (UNH) has an annular flume equipped with a velocity profiler that can be used to estimate CSS by measuring the instantaneous, three-dimensional water current velocities at which sunken oils undergo movement and erosion of visible oil droplets occur. The CSS of sunken Alberta bitumen was determined by progressively increasing current velocities until deformation, movement and erosion of the stranded oil was observed. Tests were conducted in freshwater at water temperatures of 5, 15 and 25°C. At temperatures ≥ 18.5 ± 1.9 °C, mass erosion of visible droplets was observed in current velocities greater than 20 cm/s (0.39 knots.), corresponding to a CSS of 1.9 Pa. No erosion was observed at temperatures < 18.5 ± 1.9 °C in current velocities up to 100 cm/s (2.25 knots). Understanding the transport and fate of sunken oil is an important prerequisite for recovery of non-buoyant oils. Unfortunately, details regarding environmental conditions and physical properties of crude oil are limited. Spill trajectory modelers make a “best guess” of the expected conditions needed to erode and resuspend oil from the bottom. CSS data are needed for a range of oils. This thesis research estimated CSS for an Alberta bitumen, providing modelers information to predict the behavior of sunken Alberta bitumen.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".