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Record W2620047387 · doi:10.1139/cgj-2016-0248

Flume-scale experiments on suffusion at bottom of cutoff wall in sandy gravel alluvium

2017· article· en· W2620047387 on OpenAlexvenueno aff
Yulong Luo, Min Nie, Ming Xiao

Bibliographic record

VenueCanadian Geotechnical Journal · 2017
Typearticle
Languageen
FieldEngineering
TopicDam Engineering and Safety
Canadian institutionsnot available
FundersPriority Academic Program Development of Jiangsu Higher Education InstitutionsHohai UniversityNational Natural Science Foundation of China
KeywordsFlumeGeotechnical engineeringAlluviumGeologyPore water pressureLateral earth pressureCutoffHydraulic conductivityFlow (mathematics)GeomorphologySoil waterMechanicsSoil science

Abstract

fetched live from OpenAlex

This paper presents a series of flume-scale experiments to investigate suffusion at the bottom of a cutoff wall in an internally unstable sandy gravel alluvium. The initiation, progression, and potential failure of suffusion and the interactive effects of geomechanical and hydraulic conditions with the evolution of suffusion were investigated in this particular application. Temporal and spatial development of pore pressure, earth pressure, and settlement demonstrated suffusion was a multi-phase (involving pore water, fine and coarse fractions) and multi-field (involving seepage, seepage-induced fine-fraction variation, and stress–deformation) coupling phenomenon. Suffusion initiated at the downstream side of the tip of the cutoff wall and then generally progressed backward to the upstream side. The monitored earth pressure provided an evidence of the heterogeneous stress distribution in internally unstable soil. Two linear empirical formulas for average hydraulic gradients at the initiation of suffusion and at blowout were derived based on the flume-scale model experiments.

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 score0.002
Threshold uncertainty score0.005

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.012
GPT teacher head0.225
Teacher spread0.213 · 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

Citations35
Published2017
Admission routes1
Has abstractyes

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