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Record W4390766209 · doi:10.1111/ffe.14229

Influence of pore water pressure on concrete creep and a creep model considering the effect of cohesion and internal friction angle

2024· article· en· W4390766209 on OpenAlexaff
Wenbo Liu, Shuguang Zhang

Bibliographic record

VenueFatigue & Fracture of Engineering Materials & Structures · 2024
Typearticle
Languageen
FieldEngineering
TopicConcrete Properties and Behavior
Canadian institutionsGeomechanica (Canada)
FundersNatural Science Foundation of Guangxi ProvinceNational Natural Science Foundation of China
KeywordsCreepCohesion (chemistry)Materials scienceFriction angleViscoplasticityInternal pressureGeotechnical engineeringComposite materialMechanicsStructural engineeringConstitutive equationGeologyFinite element methodEngineering

Abstract

fetched live from OpenAlex

Abstract A new nonlinear viscoplastic body considering cohesion and internal friction coefficient versus time is proposed by considering cohesion and internal friction angle. A new creep model for concrete considering cohesion and internal friction angle is obtained by interlocking it with the conventional model. The results show that the creep model can properly reflect the creep development of soft‐cut concrete at the pile head by comparing the creep model with the three‐dimensional creep test data trends under various levels of loading. The model can well describe the whole process of creep deformation and also better compensate for the shortcomings of the traditional creep model that cannot describe the characteristics of accelerated creep deformation.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.006
GPT teacher head0.209
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 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

Citations5
Published2024
Admission routes1
Has abstractyes

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