Coupled Flow Modelling for a Geothermally Facilitated Bioreactor
Bibliographic record
Abstract
Abandoned mines across the world leak contaminated waters into precious water resources, threatening human populations and natural environments alike. The primary demand from the industry for addressing the contamination is a passive system that utilizes locally available and cheap material, with little energy or maintenance requirement. Passive treatment systems can operate in remote regions, using diverse, inexpensive, and locally available material with low waste production, but are subject to ambient conditions and are often space intensive. The geothermal gradient available at abandoned mines is a viable heat energy source that can provide advantageous temperature conditions for established remediation techniques, namely bioremediation.Currently, the primary models used for testing new passive designs are either largely empirically based, or limit the scope of modelling parameters, making it difficult to incorporate innovative design aspects into the existing modelling framework. The following paper presents a model, based on kinetic parameters from a column experiment, which couples mechanics, thermodynamics, hydrodynamics, and microbial kinetics. The modelling results show the effect of an imposed temperature gradient on the permeability and microbially driven reactions of a bioreactor. The model reflects evolving thermal and mass transfer in the multiphase system. The addition of geothermal energy to a bioreactor is shown to improve long-term permeability, enhance reactions and precipitation kinetics, and decrease the necessary spatial expanse of designed bioreactor systems.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".