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Record W4408445380 · doi:10.5194/egusphere-egu25-1946

Elasticity control through overburden and adsorption competition in porous media

2025· preprint· en· W4408445380 on OpenAlexaff
Rui Wu, Hongpu Kang, Fuqiang Gao, Bing Q. Li, Kerry Leith, Qinghua Lei, Gennady Y. Gor, Paul Antony Selvadurai, Xiangyuan Peng, Shuangyong Dong, Y. Li

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicDam Engineering and Safety
Canadian institutionsWestern University
Fundersnot available
KeywordsOverburdenPorous mediumElasticity (physics)AdsorptionPorosityMaterials scienceGeotechnical engineeringComposite materialGeologyChemistry

Abstract

fetched live from OpenAlex

Adsorption-induced deformation is common in porous rocks, but its role in stressed porous rocks remains unclear. These changes in elasticity have critical implications for geological stability, particularly in regions experiencing alternating droughts and wet conditions. This study investigates elastic deformation in fine-grained sandstone under cyclic loading over 34 days, with humidity increased to near dew point. Adsorption-induced weakening decreases from over 40% to less than 10% as overburden pressure rises from 1 MPa to levels below crack initiation. Similar trends are observed in fine-grained granite. A multi-scale model combining contact mechanics and nanopore adsorption explains these results, highlighting stress competition between adsorption effects and overburden pressure. Adsorption weakening becomes negligible beyond burial depths of 200 meters in sandstone and 700 meters in granite. These findings improve understanding of near-surface geological hazards, such as exfoliation, landslides, and cliff failure, under extreme climatic events. 

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.768
Threshold uncertainty score0.999

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 integrity0.0000.001
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 head0.007
GPT teacher head0.206
Teacher spread0.199 · 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 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
Published2025
Admission routes1
Has abstractyes

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