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Record W201101669 · doi:10.2172/840690

Impact of Drill and Blast Excavation on Repository Performance Confirmation

2000· report· en· W201101669 on OpenAlexaboutno aff
RJ Keller, N Francis, J.E. Houseworth, Nick Kramer

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsExcavationDrillGeotechnical engineeringMining engineeringGeologyFracture (geology)Explosive materialRock blastingRock mass classificationFlow (mathematics)EngineeringStructural engineeringMechanical engineeringMechanics

Abstract

fetched live from OpenAlex

There has been considerable work accomplished internationally examining the effects of drill and blast excavation on rock masses surrounding emplacement openings of proposed nuclear waste repositories. However, there has been limited discussion tying the previous work to performance confirmation models such as those proposed for Yucca Mountain, Nevada. This paper addresses a possible approach to joining the available information on drill and blast excavation and performance confirmation. The method for coupling rock damage data from drill and blast models to performance assessment models for fracture flow requires a correlation representing the functional relationship between the peak particle velocity (PPV) vibration levels and the potential properties that govern water flow rates in the host rock. Fracture aperture and frequency are the rock properties which may be most influenced by drill and blast induced vibration. If it can be shown (using an appropriate blasting model simulation) that the effect of blasting is far removed from the waste package in an emplacement drift, then disturbance to the host rock induced in the process of drill and blast excavation may be reasonably ignored in performance assessment calculations. This paper proposes that the CANMET (Canada Center for Mineral and Energy Technology) Criterion, based on properties that determine rock strength, may be used to define a minimum PPV. This PPV can be used to delineate the extent of blast induced damage. Initial applications have demonstrated that blasting models can successfully be coupled with this criterion to predict blast damage surrounding underground openings. The Exploratory Studies Facility at Yucca Mountain has used a blasting model to generate meaningful estimates of near-field vibration levels and damage envelopes correlating to data collected from pre-existing studies conducted. Further work is underway to expand this application over a statistical distribution of geologic parameters, encompassing all the rock types that will be encountered for the proposed repository site at Yucca Mountain. This paper suggests that, based on predicted and verified vibration levels from blasting a distance equal to four standard deviations is unlikely to affect properties that govern water flow in the host rock. The authors propose this predicted distance and verification of vibration levels may be applied to the excavation of repository subsurface openings that may be most efficiently excavated by drill and blast methods with a reasonable assurance of safety.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.017
GPT teacher head0.243
Teacher spread0.226 · 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 source (direct Gemma or distilled Codex), 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
Published2000
Admission routes1
Has abstractyes

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