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Record W4388429871 · doi:10.2991/978-94-6463-258-3_28

On the Creep Analysis of Rock Masses by Using a Viscoelastoplastic Model

2023· book-chapter· en· W4388429871 on OpenAlex
Amir Arsalan Jameei, A.R. Azami, S. Moallemi, Khang Dang, Thamer Yacoub

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAtlantis highlights in engineering/Atlantis Highlights in Engineering · 2023
Typebook-chapter
Languageen
FieldEngineering
TopicGeotechnical and Geomechanical Engineering
Canadian institutionsRocscience (Canada)
Fundersnot available
KeywordsCreepGeologyGeotechnical engineeringMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Creep in rock masses is typically described as the gradual deformation that occurs when loads are applied for long durations at varying temperatures.This process, which may result from chemical reactions in susceptible environments, leads to instabilities and catastrophic strength degradation in the rock masses.An example of a susceptible environment is crystalline and sedimentary host rocks or rock salts in deep geological repositories.Such environments are subject to the long-term transfer of radionuclides at high temperatures.This research is focused on the study of creep in several numerical examples under different loading conditions.The simulations are conducted using finite element analysis of viscoelastic and viscoelastoplastic materials.The former uses the known Waste Isolation Pilot Plant (WIPP) model, and the latter incorporates a newly proposed viscoelastoplastic model that integrates the WIPP and Mohr-Coulomb (MC) models.Results are verified with available closed-form and numerical solutions.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
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 score0.927
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0040.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0020.002
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 head0.012
GPT teacher head0.197
Teacher spread0.185 · 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