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Record W4221100768 · doi:10.1016/j.jrmge.2022.02.003

Experimental and numerical investigation into the non-explosive excavation of tunnels

2022· article· en· W4221100768 on OpenAlexaff
Quan Zhang, Zhigang Tao, Chun Yang, Shan Guo, Manchao He, Chongyuan Zhang, Huiya Niu, Chao Wang, Shen Wang

Bibliographic record

VenueJournal of Rock Mechanics and Geotechnical Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsMcGill University
FundersJiangsu Provincial Department of Education
KeywordsExplosive materialExcavationQuantum tunnellingRock blastingGeotechnical engineeringSection (typography)Computer simulationGangueMining engineeringGeologyEngineeringStructural engineeringMaterials scienceComputer scienceSimulationMetallurgyChemistry

Abstract

fetched live from OpenAlex

The use of explosives is restricted on some important holidays, and the handling of unexploded charge is very dangerous. Therefore, an innovative non-explosive technology called instantaneous expansion (IE) was developed for tunneling. IE, whose components are derived from solid wastes such as coal gangue and straw conduces to realizing the reuse of waste. Moreover, its cost is lower than explosives. Blind guns of IE are easy to treat with water. The IE tunneling method is classified into two categories, i.e. IE with a single fracture (IESF) and IE with multiple fractures (IEMF), which are used to form the tunnel cross-section directionally cross-section and to fragment the rocks inside the cross-section, respectively. In this study, the principle of IE tunneling was elaborated first. Then, tunneling experiments and numerical simulations were performed on IE, conventional blasting (CB) and shaped charge blasting (SCB) in comparison. The experimental and numerical results show that IE achieved the best performance of directional rock breaking and corresponded to the most minor excavation-induced damage zone of the surrounding rock. Besides, the tunnel cross-section created by IE was flat and smooth. Comparing IE with CB and SCB, the over/under-excavation area decreased by 64% and 17%, and the excavation-induced damage zone fell by 26% and 11%, respectively. The range of the loose circle is reduced, which is conducive to improving the long-term stability of the roadway. The research provides a safe and economical tunneling method with excellent application prospects.

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: none
Teacher disagreement score0.581
Threshold uncertainty score0.419

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 head0.009
GPT teacher head0.201
Teacher spread0.192 · 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

Citations27
Published2022
Admission routes1
Has abstractyes

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