Optimizing Water Disinfection: A CFD Study on Microorganisms Collision against a Triply Periodic Minimal Surface
Bibliographic record
Abstract
Currently, point-of-use (POU) disinfection technologies have a significant impact addressing the control of microbial pathogens in water.Among the physical factors related to microbial filtration/inactivation, the rate of particles collision with the disinfecting surface is crucial to guarantee satisfactory efficiency.Through a Computational Fluid Dynamics (CFD) model run in Ansys CFX software, this study assesses the collision dynamics of particles configured according to E. coli cells' parameters against an infill mesh, designed to be manufactured as a metallic disinfectant.The mesh, created using Python coding due to its complexity, is based on the Triply Periodic Minimal Surface (TPMS) shape of the Schwarz P, providing a large surface area to volume ratio, with a geometry that allows high permeability.The efficiency of filtration was studied through analysis and comparison of different infill configurations, while also considering the pressure drop introduced by them, which is fundamental in the process' energy consumption.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".