Transport and clogging of microplastic particles in porous media: Microscale experiments and statistical analysis
Bibliographic record
Abstract
In recent years, the migration and distribution of microplastics (MPs) in the natural environment have garnered worldwide attention. However, little is known about the transport and intercept of MPs in infiltration systems. In infiltration systems, MPs could affect the flow through porous media, leading to complex flow and removal dynamics in various engineering applications. This will threaten the ecosystem and human health due to the characteristics of MPs. In this study, a two-dimensional porous media flow cell was developed to visualize the transport and intercept of microplastic particles in porous media. Statistical data on pore characteristics were gathered by tracking changes in pore clogging state under different particle concentrations and flow rates. It was found that the size ratio dt/dp was the critical factor influencing pore throat clogging probability. Pore throats were categorized into persistent-clogging, occasional-clogging, and non-clogging based on their clogging probability at different dt/dp. Additionally, the parameter dt/dpU that distinguished the occasional-clogging zone from the non-clogging zone decreased with increasing particle concentration. The clogging probability in the occasional-clogging zone was influenced by dt/dp, particle flux, and flow velocity in the pore throat. Furthermore, two distinct clogging mechanisms, independent and dependent clogging, were observed, determined by the states of neighboring pores. These findings have implications for assessing the interception performance of MPs in filtration systems. The results enhance our understanding of MPs transport and interception dynamics in porous media and contribute to the optimization of filtration system design and operation.
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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) | 0.000 | 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".