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Record W2623982546 · doi:10.1139/cgj-2017-0043

Nondestructive health monitoring of soil nails using electromagnetic waves

2017· article· en· W2623982546 on OpenAlexvenueno aff
Jung-Doung Yu, Ki‐Hong Kim, Jong‐Sub Lee

Bibliographic record

VenueCanadian Geotechnical Journal · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsnot available
Fundersnot available
KeywordsSoil nailingSteel barGeotechnical engineeringNail (fastener)Bar (unit)Nondestructive testingGeologyMaterials scienceStructural engineeringEngineering

Abstract

fetched live from OpenAlex

The installed length and grouted length of a soil nail should be evaluated to prevent construction disasters and landslides. The objective of this study is the development and application of a nondestructive method for evaluating the installed length and grouted length of soil nails using electromagnetic waves. Experiments are conducted on steel bars, partially grouted steel bars, fully grouted steel bars, and soil nails. Electromagnetic waves are generated and detected by a time-domain reflectometer. The experimental results show that the respective round-trip travel times increase with an increase in the length of the steel bar, grouted steel bar, and soil nail. The velocities are greatest and lowest for steel bars and soil nails installed in soil, respectively. For partially grouted steel bars, multiple reflections are detected at the interface between the nongrouted sections and grouted sections. The velocity decreases with an increase in the grouted ratio of the soil nail. This study demonstrates that electromagnetic waves can be effectively applied for the evaluation of the installed length and grouted length of the soil nail for health monitoring.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.363
Threshold uncertainty score0.872

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 studies0.0010.000
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 head0.017
GPT teacher head0.255
Teacher spread0.237 · 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 designObservational
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

Citations12
Published2017
Admission routes1
Has abstractyes

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