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Record W2332990047 · doi:10.1061/9780784412350.0102

Composite Cut-Off Walls for Existing Dams: Theory and Practice

2012· article· en· W2332990047 on OpenAlexaff
Donald A. Bruce, Trent L. Dreese, Mark Harris, Douglas M. Heenan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGrouting, Rheology, and Soil Mechanics
Canadian institutionsPCL Construction (Canada)Aurora College
Fundersnot available
KeywordsDiaphragm (acoustics)DrillingGeotechnical engineeringComposite numberSlurryStructural engineeringGeologyResidualPermeability (electromagnetism)Finite element methodEngineeringMaterials scienceComputer scienceMechanical engineeringComposite material

Abstract

fetched live from OpenAlex

During the last 10 years, the theory and practice of composite cut-off walls has been developed in the United States. The theory is that, prior to the construction of a remedial concrete diaphragm wall through a dam and into its foundation rock, the whole alignment is systematically grouted to a verified residual permeability. The grouting is conducted in two rows, and the wall is then built between them. This approach has the following advantages: 1. The drilling and grouting constitutes an extremely intense site investigation, as well as being a ground treatment in "clean" fissure conditions. Thus, the depth and extent of the diaphragm wall can be logically determined, i.e., it will be installed only where potentially erodible material has been found in the rock mass. Since the cost of drilling and grouting is a fraction of the cost of a diaphragm wall, the overall project costs are minimized. 2. The alignment of the diaphragm wall is pretreated, so that potentially catastrophic, sudden slurry losses are prevented from occurring. 3. By conducting the drilling and grouting into the clean fissured rock mass below and beyond the concrete diaphragm to an engineered target, the effective extent of the concrete cut-off is significantly and cost-effectively increased. Guidance is provided on the design and construction of the grouted element of the composite wall structure.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.894
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.296
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2012
Admission routes1
Has abstractyes

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