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Record W2069272856 · doi:10.1029/2001jb001460

Undrained poroelastic response of sandstones to deviatoric stress change

2002· article· en· W2069272856 on OpenAlexaboutno aff
D. A. Lockner, Sergei Stanchits

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsnot available
Fundersnot available
KeywordsPoromechanicsPore water pressureStress (linguistics)Effective stressGeologyDilatantGeotechnical engineeringDeformation (meteorology)PorosityMaterials sciencePorous medium

Abstract

fetched live from OpenAlex

Deformation of porous crustal rock through diagenesis, tectonic loading, or other processes can change pore volume and affect fluid pressure. The largest stress‐induced pore pressure changes occur when fluid is trapped in pores in an “undrained” condition. We have measured the undrained poroelastic response of two sandstones to changes in mean and deviatoric stress. Pore pressure was found to respond to mean stress σ m in the usual manner: Δ p = B Δσ m ( B ranging from 0.4 to 0.7), nearly independent of the ambient deviatoric stress state. However, variations in deviatoric stress (σ d = (σ 1 − σ 3 )/2) at constant mean stress were also found to induce a reversible (elastic) pore pressure response to stress levels up to and exceeding 80% failure stress (i.e., Δ p = = const.). The coefficient η became more negative with increasing deviatoric stress level in sandstone and Ottawa sand samples. That is, η represents a dilatant response where increased deviatoric stress causes a decrease in pore pressure. The poroelastic response to deviatoric stress is explained in terms of anisotropic matrix stiffening due to closure of crack‐like pore space or flattening of grain contacts at high ambient stress levels and can be important in calculations of earthquake stress transfer.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.080
GPT teacher head0.312
Teacher spread0.232 · 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.

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

Citations110
Published2002
Admission routes1
Has abstractyes

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