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Record W2055041382 · doi:10.5539/esr.v1n2p23

Liquefaction Potential Variations Influenced by Building Constructions

2012· article· en· W2055041382 on OpenAlexvenueno aff
Behnam Rahrou Khatibi, Mehdi Hosseinzadeh Sutubadi, Gholam Moradi

Bibliographic record

VenueEarth Science Research · 2012
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsLiquefactionPore water pressureGeotechnical engineeringEffective stressSoil liquefactionShear (geology)GeologyShear stressConstitutive equationOverburden pressureAccelerationStress (linguistics)Environmental scienceEngineeringMaterials scienceStructural engineeringComposite materialFinite element method

Abstract

fetched live from OpenAlex

In this paper, a sand deposit with liquefaction potential was simulated in FLAC using Finn constitutive model. Equivalent loads of 5, 10, 15 and 20-story buildings were applied to the deposit. As a cyclic loading, acceleration time history of Bam earthquake was used. To examine pore water pressure variations in the soil mass during the earthquake loading, parameter ru (pore water pressure ration, which equals pore water pressure increment divided by the initial mean effective stress in the soil mass) was defined for the software by a Fish function. Static analyses show that by increasing the applied loading due to building construction, the values of effective and shear stress increase and it generally can be a factor to influence liquefaction potential. Furthermore, dynamic analyses show that there is a shallow longitudinal area beneath 15 and 20-story buildings in which liquefaction potential increases due to high confining effective stress.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.311
Teacher spread0.291 · 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 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

Citations6
Published2012
Admission routes1
Has abstractyes

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