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Record W2370286448

Analysis of numerical simulation methods for excavation failure zone of deep underground opening in hard rocks with high geostress

2012· article· en· W2370286448 on OpenAlexaboutno aff
Cheng Wu, Ping Zhang

Bibliographic record

VenueShuiwen dizhi gongcheng dizhi · 2012
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsExcavationGeotechnical engineeringConstitutive equationGeologyBrittlenessCohesion (chemistry)Stress fieldStress (linguistics)Stress pathFailure mode and effects analysisMining engineeringEngineeringStructural engineeringFinite element methodMaterials sciencePetrology
DOInot available

Abstract

fetched live from OpenAlex

With the construction of deep underground openings,the formation of excavation failure zone and its prediction have become a focus of rock mechanics in deep underground excavation both in China and abroad.Based on the analysis of mechanical properties of hard rocks during their failure process,the conventional continuum models and the cohesion weakening-friction strengthening(CWFS)model were compared.Numerical analysis of a circular test tunnel in a Mine-by Experiment at the URL in Canada was carried out by using FLAC with elastic-perfectly plastic,elastic brittle,strain softening and CWFS constitutive models,respectively.The results of comparison of stress distribution,principal stress values at key points and plastic region among different models show that CWFS model can simulate the stress transfer and stress concentration to a deep area,which is the real situation when stress-induced failure occurs;the stress distribution calculated from CWFS model is much closer to that when the excavation failure zone is deleted.Compared to other models,the extent and depth of excavation failure zone calculated by CWFS are larger and they are in agreement with the field measurements.Finally,the CWFS model was used to investigate the failure zone in another case,the Kobbskaret road tunnel in Norway.The depth and extent of the excavation failure zone were predicted rather well and it again proves the rationality of using CWFS model in predicting the excavation failure zone of hard rocks in deep tunnels.

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)0.000
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: none
Teacher disagreement score0.513
Threshold uncertainty score0.866

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.301
Teacher spread0.278 · 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

Citations0
Published2012
Admission routes1
Has abstractyes

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