An estimate of the axial dispersion during flow through a compressible wood‐chip bed
Bibliographic record
Abstract
Abstract In this work, we present a methodology to characterise the axial dispersion of a solute during steady‐flow through a compressible bed of wood chips under mechanical load. We use a non‐invasive imaging technique, namely electrical resistance tomography (ERT), to visualise the uniaxial displacement of a salt solution. Here we demonstrate that under two limiting cases the porosity of the porous bed varies slowly in the flow‐direction and to the lowest order can be considered a constant. This simplified the optimisation routine we used to match the experimental data to the numerical results of the advection–diffusion equation. Using this, a methodology to estimate the axial dispersion is given by a minimisation scheme. In the experimental portion of the work we measure the axial dispersion of a bed of hemlock wood chips at three different kappa numbers κ , and compacted to three different compaction pressures p c . We find that the dispersion D e in the axial direction varies as a function of the porosity ε , according to $D_{{\rm e}} = a\varepsilon {}^{b} $ , where a = 7.2 × 10 −4 m 2 /s and b = −3.8 for hemlock wood chips. © 2011 Canadian Society for Chemical Engineering
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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 | 0.000 |
| 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 | 0.000 | 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".