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Record W6884772171 · doi:10.12438/cst.2023-1084

Study on symmetric creep model based on creep curves and parametric sensitivity analysis

2024· article· en· W6884772171 on OpenAlexaff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2024
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsGeomechanica (Canada)
Fundersnot available
KeywordsCreepParametric statisticsDeformation (meteorology)Oil shaleCurve fittingRock mass classificationSensitivity (control systems)Acceleration

Abstract

fetched live from OpenAlex

In order to obtain the creep characteristics of the surrounding rock of the Dianzhong water diversion tunnel and to study the long-term stability of the surrounding rock of the tunnel, a fully automated triaxial developed by Wuhan Institute of Geotechnics, Chinese Academy of Sciences, is used to carry out the uniaxial creep test of green mud shale. The axial creep curve and isochronous stress-strain curve of green mud shale are obtained. And the long-term strength value of green mud shale is determined based on the characteristics of isochronous stress-strain curve. Based on the classical creep curve characteristics and a large number of experimental creep curves, it is found that the equations describing the attenuation creep curve can be treated by symmetry. Therefore, it is assumed that the acceleration curve and the decay creep curve are symmetric about the midpoint of the stable creep curve. An accelerated creep model based on the symmetry of the creep curve is obtained. And a set of methods to determine the parameters of the creep model is proposed based on the characteristics of the creep test curve. Finally, the parameters introduced into the accelerated creep model for sensitivity analysis. The parameters introduced into the model have a clear physical meaning. The results show that with the increasing axial stress, the instantaneous strain value and creep deformation value of the rock are also increasing, and the instantaneous strain of the rock under the first stage load accounts for the largest ratio of the total creep deformation. The established creep model can not only well describe the attenuation creep and stable creep deformation law of green mud shale, it also better make up for the defects of the Nishihara model that cannot describe the accelerated creep. The agreement between the model curve and the test curve is much higher than that between the model and the test curve, and the correlation coefficients between the model curve and the test curve under different stresses are all above 0.90. Meanwhile, the validation of different types of test curves and model curves also shows that the model can be applied to the prediction of creep curves of different types of rocks. Finally, the value of parameter j is introduced to control the deformation rate and the time to enter accelerated creep. The value of parameter k controls the creep time and the creep rate in the accelerated stage.

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)0.001
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.216
GPT teacher head0.499
Teacher spread0.283 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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