MétaCan
Menu
Back to cohort

Monitoring of rock stress change using instrumented rebar rock bolts

2021· article· en· W3197444911 on OpenAlexaff
Wilfried Maï, Mateusz Janiszewski, Lauri Uotinen, Rajiv S. Mishra, Mikael Rinne

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2021
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsFirst Quantum Minerals (Canada)
FundersBusiness FinlandAalto-Yliopisto
KeywordsRock mass classificationRock boltGeotechnical engineeringGeologyRebarStress (linguistics)Strain gaugeExcavationMining engineeringEngineeringStructural engineering

Abstract

fetched live from OpenAlex

Abstract Rock stress is causing unwanted deformations of deep underground spaces. Large deformations increase the risk of failure. The underground excavation causes rock stress changes in the surrounding rock mass, and the resulting deformations can be measured. In this paper, we present a method to monitor stress changes in the rock mass using rebar rock bolts instrumented with strain gauges to track the stress within the bolt. Next to that, we describe in-situ testing of this method using heating-induced stress in a natural underground environment. The heating experiment aims to create stress changes using rope heaters inserted into the rock mass and located symmetrically around a single instrumented rock bolt. The heat flux induced to the rock mass leads to volume expansion. The restricted thermal expansion causes an increase in the internal rock stress conditions. These conditions create a strain that can be measured and back-calculated as the rock stress change. The instrumented rock bolt and testing setup were installed in the Underground Research Laboratory located in a granitic rock below the Aalto University campus. The single bolt experiment demonstrates how instrumented rock bolts could monitor the changes in the rock mass stress state. The system can be used as a part of a real-time rock stress monitoring system in mining and rock engineering projects. The final part of the paper describes how this monitoring system can positively affect geotechnical risk management and increase the overall safety of underground construction.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.552

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 communication0.0000.001
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 head0.028
GPT teacher head0.210
Teacher spread0.182 · 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 designBench or experimental
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

Citations3
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueIOP Conference Series Earth and Environmental ScienceSame topicRock Mechanics and ModelingFrench-language works237,207