Large‐eddy simulation and low‐order modeling of sediment‐oxygen uptake in a transitional oscillatory flow
Bibliographic record
Abstract
We have tested a dissolved oxygen (DO) transport model based on large‐eddy simulation (LES) of a transitional oscillatory flow observed in the bottom boundary layer of Lake Alpnach, Switzerland. The transition from a quasi‐laminar to a fully turbulent state makes this flow difficult to study with a Reynolds‐averaged Navier‐Stokes equation (RANSE) model. By resolving the full range of governing transport processes, LES provides a reliable prediction of the sediment‐oxygen uptake (SOU). The model biogeochemical and flow parameters have been calibrated against DO and velocity measurements from published in situ data at the earliest phase available in the cycle. The fully developed flow thus obtained is used as an initial condition for the imposed oscillatory forcing. Numerical predictions show that transport in the outer layer is in equilibrium with the main current throughout most of the cycle and that nonequilibrium effects are limited to the diffusive sublayer response to the external forcing. During flow deceleration, the concentration boundary layer slowly expands as turbulence decays; later, during re‐transition, mixing is restored by rapid and intense turbulent production events enhancing the SOU with a well‐defined time lag. An algebraic model for the SOU is proposed for eventual inclusion in RANSE biogeochemical management‐type models developed based on parameterizations used in turbulent mass transfer and with the support of published numerical data and the present simulation. The only input parameters required are the sediment oxidation rate, bulk temperature and DO concentration, and friction velocity.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".