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Record W2323590070 · doi:10.1061/40970(309)81

Strength and Permeability of a Deep Soil Bentonite Slurry Wall

2008· article· en· W2323590070 on OpenAlexaff
Christopher R. Ryan, Charles A. Spaulding

Bibliographic record

VenueGeoCongress 2008 · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsKensington Health
Fundersnot available
KeywordsGeotechnical engineeringSlurryPenetrometerGeologyPermeability (electromagnetism)CompactionPiezometerTrenchBentoniteGroundwaterMaterials scienceSoil waterComposite materialSoil scienceAquifer

Abstract

fetched live from OpenAlex

In 2006, a Soil Bentonite (SB) slurry wall was constructed at a brownfield redevelopment of a former steel mill site in Mayfield, NSW Australia. At this site, the slurry wall is designed to block groundwater flow that might contribute to the contamination of an adjacent waterway, the Hunter River. The wall was approximately 1500 m long and up to 49 m deep, constituting an apparent depth record for walls of this type. As a part of the construction QC, there was an extensive amount of testing done, including an unusual amount of in situ strength testing using both a static cone penetrometer and field vane shear measurements. These latter measurements offer a unique opportunity to determine the strength gain of SB backfill material. Results show a moderate stiffening of the SB material after it has been in the trench. This is consistent with field observations which show that, while SB backfill is placed in a semi-fluid condition, after some weeks it can be excavated with a vertical face. Results also show that the wall does not achieve a full static state of stress over its full depth. Rather, as the material "sets", arching occurs, in effect holding some of the weight of the backfill on the sides of the trench. Extensive permeability testing of field-mixed SB backfill samples also provides a basis for design of future walls. In an earlier design mix program, a good correlation between percentage of fines and reduced permeability was established. It is clear that the fines content must be at a certain minimum to achieve stability in the backfill and to permit the blending of a low permeability backfill mix. Data are also presented showing the effects of permeation over an unusually long test period with contaminated groundwater.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.212
Teacher spread0.202 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations13
Published2008
Admission routes1
Has abstractyes

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