Case Study: Construction and <i>In Situ</i> Hydraulic Conductivity Evaluation of a Deep Soil-Cement-Bentonite Cutoff Wall
Bibliographic record
Abstract
This paper presents a case study of a deep soil-cement-bentonite (SCB) slurry trench cutoff wall constructed outside of Smithland, KY, in 2010. Installed to a maximum depth of 56 m, this cutoff wall is the deepest known seepage barrier installed using continuous trenching. The wall was installed around the perimeter of a deep excavation to reduce long-term dewatering costs associated with construction of a hydroelectric power plant adjacent to the Ohio River. After wall construction, a dewatering system was installed inside the area enclosed by the wall to facilitate the deep excavation. Preconstruction design and construction details are presented along with the results of a post-construction assessment of the hydraulic conductivity (k) of the wall. Steady-state groundwater flow measurements from the dewatering system coupled with information on the wall thickness and water levels inside and outside of the wall were used to obtain a large-scale estimate of the in situk of the wall. The in situk was compared with laboratory k values measured for specimens prepared from grab samples of the as-mixed SCB backfill. Comparisons also were made to the target (design)k and the expected field mixed backfill k established during a preconstruction bench-scale study. The comparisons revealed that the in situk is approximately one order of magnitude less than the design k and approximately equal to the average laboratory k measured from grab samples and the expected k from the results of the bench-scale study.
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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 | 0.001 | 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".