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Record W2734410916 · doi:10.1201/9781003078944-7

Seven years of in situ stress measurements at the URL An overview

2020· book-chapter· en· W2734410916 on OpenAlexaffabout
C. Derek Martin, R.S. Read, Péter Lang

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsAtomic Energy (Canada)
Fundersnot available
KeywordsIn situComputer scienceGeographyMeteorology

Abstract

fetched live from OpenAlex

In 1982, Atomic Energy of Canada Limited (AECL) carried out the first in situ stress measurements at the proposed site for the Underground Research Laboratory (URL). These hydraulic fracturing measurements were taken between the 12- and 540-m depth in the general area of the proposed access shaft to the URL. The URL shaft was constructed in two stages. Stage 1 (upper shaft) was excavated from the surface to a depth of 255 m between 1983 March and 1985 April. This stage was excavated as a nominal 2.8- by 4.9-m-rectangular shaft by the traditional drill and blast benching method. Stage 2 (lower shaft) was excavated as a 4.6-m-diameter circular shaft using a full-face drill and blast technique. Since 1985, an extensive in situ stress research program has been ongoing to characterize the in situ stress state around the URL access shaft and the main development level at 240-m depth, and to address some of the commonly asked questions about in situ stress results: 1) Are in situ stresses dependent on the scale of the measurement technique? 2) What is the influence of geological features on the results? 3) Is residual stress a major component of the stress results? 4) Will different measurement techniques provide the same results? and 5) How can the stress data be presented in a useful form to the design engineer? To date, some of the above concerns have been investigated using overcoring (USBM, CSIR, and SSPB), hydraulic fracturing, under-excavation, microseismic monitoring and observations (shaft-wall failure and core discing), and our results are published or in press. This paper is a summary of our findings to date.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.954
Threshold uncertainty score0.710

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 head0.042
GPT teacher head0.231
Teacher spread0.189 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations22
Published2020
Admission routes2
Has abstractyes

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