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Record W4309000717 · doi:10.46873/2300-3960.1366

Numerical modelling of destress blasting – A state-of-the-art review

2022· review· en· W4309000717 on OpenAlex
Shuting Miao, Petr Koníček, Peng‐Zhi Pan, Hani S. Mitri

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

VenueJournal of Sustainable Mining · 2022
Typereview
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsMcGill University
FundersInstitute of Rock and Soil Mechanics, Chinese Academy of SciencesState Key Laboratory of Geomechanics and Geotechnical EngineeringChinese Academy of SciencesNational Natural Science Foundation of China
KeywordsRock blastingRock mass classificationGeotechnical engineeringStiffnessEngineeringMining engineeringExplosive materialStructural engineeringComputer simulationFracture (geology)Simulation

Abstract

fetched live from OpenAlex

As a proactive mine safety measure against the occurrence of rockburst, destress blasting has been applied to numerous mining conditions to precondition highly stressed rock mass to mitigate the risk of rockburst occurrence in deep mines as well as in deep underground constructions. However, the application of destress blasting mostly depends on engineering experience, while its mechanism and efficiency have not been well understood. Rapid advances in computer technology have made numerical simulation an economical and effective method to study the rock blasting effect. Enormous research efforts have been made to numerically investigate the blasting fracture mechanism, optimize blasting design, and assess the efficiency of destress blasting. This review focuses on the state-of-the-art progress in numerical modelling associated with destress blasting over the last two decades. Some commonly used modelling approaches for destressing blasting are compared and reviewed. Currently, two different ways of modelling based on static and dynamic modes are typically used to study the effect of blasting. In the static method, destress blasting is simulated by modifying the rock mass’s stiffness and strength properties to obtain the post-blast stress state in the destressed zone. The dynamic modelling technique focuses on the dynamic fracture process of coals and rock masses, during which the predetermination of the damage induced by blasting is not necessary. Moreover, the extent of damage zones around the blast hole can be precisely estimated in the dynamic modelling method by considering time-varying blast pressure and strain rate dependency on the strength of rock mass but at the cost of increased computation and complexity. Besides, different destress blasting modelling methods, generally classified into continuum-based, discrete-based, and coupled methods, are compared and reviewed. The fracture mechanism of blasting in the rock mass is revealed, and the destressing efficiency of the existing destress blasting design is assessed and compared with classical results. The factors that may affect the efficiency of destress blasting are summarized. Finally, the difficulties and challenges associated with the numerical modelling of destress blasting are highlighted briefly.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.795
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.052
GPT teacher head0.272
Teacher spread0.220 · 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