Effect of Retarders and Dispersing Agents on the Performance of Cement-Bentonite Cut off Wall
Bibliographic record
Abstract
Singapore is a densely populated country and land reclamation has played an important part in relieving the continuous demand of land space.The empoldering method is considered an attractive alternate over traditional land reclamation method due to the reduced dependency on sand (which is a scarce material) and hence, a more sustainable method to increase land area.One of the key features in a polder is the seepage cut-off wall.The seepage cut-off wall consists of Cement-Bentonite (CB) mix which has sufficiently low permeability and enough strength but not be too brittle such that cracks appear.Typically, the construction of a panel of the seepage cut-off wall takes around 12-18 hours depending on the depth of the wall.Therefore, it is critical to delay the hydration reaction long enough, so that the CB mix remains workable/flowable during the construction of the seepage cut-off wall.Hence retarders or dispersing agents are used to delay the chemical reaction, thereby maintaining the workability of the mix.The retarders or dispersing agent should not alter the hydration and cementitious properties of cement.The main objective of the paper is to evaluate the effect of different retarders on two important parameters of the CB mix: unconfined compressive strength and permeability.Four chemicals are considered for the current study, wherein two chemicals are retarders, and two are retarders but with dispersing properties as well.The results showed that the CB mixes with dispersing agents have higher strength and lower permeability than CB sample with retarders.
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.
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) | 0.001 | 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) | 0.001 | 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".