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Record W2886800692 · doi:10.11159/mmme18.2

Destress Blasting – From Theory to Practice

2018· article· en· W2886800692 on OpenAlex
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.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicForest Biomass Utilization and Management
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRock blastingComputer scienceGeologyMining engineering

Abstract

fetched live from OpenAlex

One of the most common methods that are practiced today for controlling violent rock failures in underground mines is destress blasting. One aspect of this method involves drilling and blasting areas that are stiff and highly stressed such as pillars, mining fronts and shaft sinking floors, to help dissipate high stress and energy accumulation, thus rendering a safer mining environment. Another aspect of the method relies on large scale blasting of one or more slots or panels near the active mining area to create a stress shadow around it and help reduce the stress and energy concentration. While the merits of the destress blasting method are conceptually well appreciated by many mines, its efficient implementation in the field has been hampered by the diversity of available information, the scarcity of well-documented destressing programs, as well as the absence of a dedicated design/analysis method. This has made the destress blasting method more like an art than an engineering science. This paper reviews the background theory, benefits, constitutive modelling, and practice of destress blasting. Current research on the evaluation of the destress blasting efficiency is discussed, and future research directions are highlighted.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.689

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 head0.005
GPT teacher head0.203
Teacher spread0.198 · 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