MétaCan
Menu
← Back to cohort
Record W2606744455 · doi:10.11159/icgre17.157

Load-deformation Analysis of a Pile in Expansive Soil upon Infiltration

2017· article· en· W2606744455 on OpenAlexafffundvenueabout
Yunlong Liu, Sai K. Vanapalli, Amina W. BA

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship CouncilUniversity of Ottawa
KeywordsExpansive clayPileInfiltration (HVAC)Geotechnical engineeringExpansiveDeformation (meteorology)GeologySoil scienceMaterials scienceSoil waterComposite materialCompressive strength

Abstract

fetched live from OpenAlex

Piles are widely used as foundations in regions with expansive soil deposits to safely carry loads from the superstructure to the soil without undergoing unacceptable deformations.These foundations are typically designed assuming that that the soil is in a state of saturated condition extending conventional soil mechanics principles.However, the soil surrounding the pile in expansive soils is typically in an unsaturated state.Due to this reason, the mechanical behaviour of the pile is significantly influenced by matric suction.In this paper, the pile load transfer model proposed by Zhang and Zhang (2012) is modified by taking account of the influence of matric suction on the pile-soil interface shear strength for estimating the load-deformation behaviour.In addition, an algorithm is developed for estimating the load-deformation analysis of a single pile in expansive soils, taking account of infiltration conditions.An example problem is presented for highlighting the influence of infiltration on the load settlement behavior of a single pile in Regina clay, which is a typical expansive soil from Canada.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.021

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.005
GPT teacher head0.184
Teacher spread0.179 · 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

Citations2
Published2017
Admission routes4
Has abstractyes

Explore more

Same venueProceedings of the World Congress on Civil, Structural, and Environmental Engineering→Same topicGeotechnical Engineering and Soil Mechanics→French-language works237,207→