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Record W6987306532

Slope stability evaluation of an old earth fill dam founded on glaciolacustrine clays

2016· dissertation· en· W6987306532 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2016
Typedissertation
Languageen
FieldEngineering
TopicDam Engineering and Safety
Canadian institutionsnot available
Fundersnot available
KeywordsConsolidation (business)Shear strength (soil)Oedometer testSlope stabilityDirect shear testPenetration testShear (geology)Earth (classical element)Earth materials
DOInot available

Abstract

fetched live from OpenAlex

A number of earth dams in Canada are founded on and constructed with glaciolacustrine clay deposits. This type of soil can have stability issues particularly in aging dams. Environmental loading such as wetting-drying and freezing-thawing produce fissures and can cause degradation in shear strength with time. This thesis provides an opportunity to assess the stability of an aging earth fill dam. The author’s research focused on a typical earth fill dam in Ontario. A comprehensive field investigation was conducted. Cone Penetration Test (CPTu) was carried out to determine the in-situ strength of the local materials. Shelby tubes with diameter of 102 mm and 76 mm were used to retrieve soil samples from the clay foundation, clay core and placed clay blanket. Structural and mineralogical components of the clay were examined by means of Scanning Electron Microscopy (SEM) and X-Ray Diffraction (XRD) test, respectively. A series of laboratory tests such as consolidated-undrained compression tests, direct shear tests, and 1D consolidation tests were carried out to determine the strength and the deformation parameters. Finally, seepage and stress-deformation modelling as well as slope stability analysis were performed to assess the stability of the earth fill dam.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.865
Threshold uncertainty score1.000

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 head0.022
GPT teacher head0.216
Teacher spread0.194 · 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.

Study designObservational
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

Citations0
Published2016
Admission routes1
Has abstractyes

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