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Coupled Temperature and Transport Effects on Biofilm Growth Using the Thermal Lattice Boltzmann Method

2020· preprint· en· W3040986381 on OpenAlexaff
Mojtaba Aghajani Delavar, Junye Wang

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicLattice Boltzmann Simulation Studies
Canadian institutionsAthabasca University
Fundersnot available
KeywordsBiofilmCellular automatonLattice Boltzmann methodsThermalMaterials scienceMass transportBoltzmann constantMechanicsExponential growthChemistryThermodynamicsBiological systemPhysicsMathematicsBiologyEngineering physicsBacteria

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.279
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2020
Admission routes1
Has abstractyes

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