Triaxial drained behaviour of disposable face mask fibre reinforced sand
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The widespread usage of disposable face masks (DFM) during the COVID-19 pandemic has exacerbated waste management challenges, prompting an investigation into their potential reuse as a soil reinforcement material. Previous researchers have investigated the effect of mask fibres on pavement subbases and the environmental problems caused by these fibres. This study examines the mechanical properties of sandy soil enhanced with shredded and layered DFM under triaxial testing conditions, focusing on key parameters like shear resistance, elastic modulus, stress-strain characteristics, axial resistance, failure envelope, and brittleness index. Results show that adding DFM significantly improves soil cohesion, friction angle, shear strength, and peak deviatoric stress, especially at higher fibre contents and relative densities. However, increased DFM fibre content was associated with reduced elastic modulus, which stabilised in specimens with layered DFM, suggesting complex interactions between DFM content and soil mechanics. Concerns include potential void formation leading to asymmetric settlement and environmental issues on non-biodegradable fibre integration in soil. These findings highlight the need for meticulous mixture preparation, large-scale studies, and environmental assessments to evaluate the impact of using DFM in soil reinforcement, particularly for road construction and slope stabilisation. This research provides crucial insights into the potential of DFM for soil reinforcement.
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.
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 it