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Record W4406757977 · doi:10.11159/ijci.2025.001

Finite Element Investigation on the Response of Tunnel Rock-Supports in Zones Subjected To Squeezing Occurrence

2025· article· en· W4406757977 on OpenAlexvenueno aff
Gianluca Di Bella, Giulio Antonucci, Gennaro Scognamiglio

Bibliographic record

VenueInternational Journal of Civil Infrastructure · 2025
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsFinite element methodGeologyGeotechnical engineeringElement (criminal law)Structural engineeringForensic engineeringEngineeringLawPolitical science

Abstract

fetched live from OpenAlex

The minimization in the travel time for people and good is a fundamental factor in the economic progress of any nation.Achieving this objective can be realized through tunnelling, which often involves digging at significant depths.When tunnelling at high depths, the rock masses, especially if they are weak, can generate significant stress, so leading to substantial deformation during excavation operations.These large deformations around the tunnel frequently exceed the capacity of standard rock support systems, making it challenging to maintain the tunnel's stability and safety during construction.The current study deals with Finite Element analysis to investigate the stress-strain behaviour of the rock support of a deep tunnel under squeezing conditions.The rock support performances are evaluated and compared considering several fracturing conditions by means of a wide GSI range at simulating a decrease of the rock mass properties due to the proximity of tectonized zones.Different rock mass types are also studied with variations of mi parameter and uniaxial compressive strength.The performances of the rock supportssliding or stiff ribs -are evaluated and compared in terms of stresses and strain acting on.

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)0.000
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: Empirical
Teacher disagreement score0.397
Threshold uncertainty score0.329

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.011
GPT teacher head0.242
Teacher spread0.231 · 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
Published2025
Admission routes1
Has abstractyes

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