Boone Dam Test Grout Program: Objectives, Engineering Design, and Observations
Bibliographic record
Abstract
On October 20, 2014 a sinkhole appeared near the downstream toe area of the earthfill embankment at Boone Dam, followed by turbid seepage discharge into the tailrace. These events initiated a large-scale, multi-faceted response by the Tennessee Valley Authority (TVA) and its engineering partners. Seepage issues were determined to be related to internal erosion and loss of soils within the karst foundation. Evaluation of grouting techniques for short-term and long-term mitigation were considered. Many questions had to be considered: 1) What are the objectives to be addressed by grouting? 2) What grouting techniques are viable to satisfy the objectives in a karst environment with significant clay infilling? 3) What are the uncertainties, risks, and benefits of grouting at Boone Dam? 4) How can these uncertainties, risks, and benefits be evaluated? A test grouting program (i.e., field study) was designed and executed to evaluate the potential for low mobility grouting (LMG) techniques for treatment of the soil-infilled karst. Multiple test areas were designed, each with specific objectives, hole layouts, grouting techniques, instrumentation, and engineering evaluation factors. The program was designed to allow field adjustments to be made by the engineering team based on observed performance and long-term mitigation strategies. The study demonstrated that the behavior of LMG is dependent on the slump of the mix, grain size distribution of the aggregate, and the presence or absence of fly ash. The study also demonstrated that displacement grouting (using LMG) within the epikarst (transition zone between soil and karstic limestone) may result in significant and sometimes unanticipated piezometric and ground responses.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".