Effectiveness of EPS Bead Size and Cement Proportions on the Strength and Deformation of Light-Weighted Soil
Bibliographic record
Abstract
The current study investigates the deformation and strength of Light-Weighted Soil (LWS) comprised of silt, Expanded Polystyrene (EPS) beads, cement, and water. The EPS bead sizes employed in this study are 4, 5, and 6mm in diameter with densities of 0.011, 0.009, and 0.006g/cm3 and cement concentrations of 10% and 15%. The effects of different EPS bead sizes and cement proportions on the mechanical properties (strength and deformation) of LWS are evaluated by Unconfined Compression Strength (UCS) tests. The findings show that the EPS bead sizes significantly impact the strength and deformations of the LWS. The smaller the EPS bead size, the higher the observed strength, but, on the other hand, bigger EPS bead sizes have lower strength and higher ductility. It was also revealed that the strength of LSW is entirely dependent on the cement concentration. High cement content in the LWS has more strength and brittleness, but it is more prone to deformation. The cost can be decreased by increasing the EPS bead size, and thus the prescription of mixed soil can be enhanced. The use of EPS beads with a diameter of 4-6mm is recommended in the construction process, especially in backfill for retaining walls. Each EPS bead size provides advantages in different context, depending on engineering applications and field conditions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".