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Record W2995797899 · doi:10.1002/essoar.10501397.1

Experimental Monitoring of Crack Closing and Sliding with Nonlinear Wave Interactions

2019· preprint· en· W2995797899 on OpenAlexaff
Alison Malcolm, Lauren Hayes, Kamal Moravej, Stephen Butt

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicGeophysics and Sensor Technology
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsNonlinear systemAnisotropyOrientation (vector space)Closing (real estate)MicrostructureMechanicsMaterials scienceGeologyOpticsPhysicsGeometryComposite materialMathematics

Abstract

fetched live from OpenAlex

It is now well-established that earthquakes change the seismic velocity of the near surface. There is certainly some understanding of what mechanisms are responsible for these changes, but there remain many questions. Here we attempt to answer the question of the relative importance of different connection mechanisms between cracks and how these change with applied load. To study this, we first perform nonlinear wave-mixing experiments in two sandstone samples at a variety of applied uniaxial stresses. The two samples differ in the relative orientation of their microstructures. We find that although the samples show velocity anisotropy we do not see aligned structures in scanning electron microscope images. By measuring the changes in velocities with applied stress we find that most cracks close during our experiments independent of crack orientation. By contrast, we find that the nonlinear wave interactions vary strongly with applied load and with crack orientation. We analyze these differences and relate them to an emerging model of nonlinear wave interactions with microstructures.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.244
Teacher spread0.223 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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