Coupled Temperature and Transport Effects on Biofilm Growth Using the Thermal Lattice Boltzmann Method
Bibliographic record
Abstract
In this study, we developed an integrated cellular automata and thermal lattice Boltzmann model to investigate the effects of different temperatures and velocities in a microbioreactor. Compared with previous studies this model accounted for the direct effects of transient temperature on biofilm growth and indirect effects caused by changes of properties. In addition, the algorithms on variations in solid boundary conditions, detachment and extra mass transport have been improved. Results showed that temperature affected both the maximum biofilm concentration and growth speed. Roughly a 10-75% increase in biofilm concentration was observed, while in some cases the time needed to reach maximum concentration decreased from 30 days to 5 days. Despite of geometrical symmetry, changes in the upper inlet characteristics were more effective on biofilm growth. This demonstrates the capability of the present model to simulate biofilm behaviour in the microbioreactor and its potential industrial and clinical applications.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".