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Record W2912086578 · doi:10.1139/cgj-2018-0590

Evaluation of peak side resistance for rock socketed shafts in weak sedimentary rock from an extensive database of published field load tests: a limit state approach

2019· article· en· W2912086578 on OpenAlexvenueno aff
Pouyan Asem, Paolo Gardoni

Bibliographic record

VenueCanadian Geotechnical Journal · 2019
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsnot available
FundersUniversity of Illinois at Urbana-Champaign
KeywordsSiltstoneGeotechnical engineeringOil shaleLoad testingLimit state designGeologyModulusSedimentary rockMaterials scienceComposite materialStructural engineeringEngineering

Abstract

fetched live from OpenAlex

This paper presents analyses of the measured peak side resistance of rock sockets constructed in weak claystone, shale, limestone, siltstone, and sandstone. The peak side resistance is obtained from in situ axial load tests on drilled shafts, anchors, and plugs. The parameters that affect the development of peak side resistance are determined using in situ load test data. It is found that peak side resistance increases with the unconfined compressive strength and deformation modulus of the weak rock, and decreases with the increase in length of the shear surface along the rock socket sidewalls. The increase in socket diameter also slightly decreases the peak side resistance. Additionally, it is found that the initial normal stresses do not significantly affect the measured peak side resistance in the in situ load tests. The in situ load test data are used to develop an empirical design equation for determination of the peak side resistance. The proposed model for peak side resistance and the reliability analysis are used to determine the corresponding resistance factors for use in the load and resistance factor design framework for assessment of the strength limit state.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.023
GPT teacher head0.252
Teacher spread0.228 · 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 designSimulation or modeling
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

Citations17
Published2019
Admission routes1
Has abstractyes

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