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Record W4390690955 · doi:10.1139/cgj-2023-0294

Vertical seismic response of end-bearing piles in nearly saturated soil

2024· article· en· W4390690955 on OpenAlexvenueno aff
Changjie Zheng, Jingquan Yang, George Kouretzis, Xuanming Ding

Bibliographic record

VenueCanadian Geotechnical Journal · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCoastal and Marine Dynamics
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsGeotechnical engineeringDegree of saturationBiot numberPilePoromechanicsSaturation (graph theory)GeologyPore water pressureBearing capacitySoil waterPorous mediumPorositySoil scienceMechanics

Abstract

fetched live from OpenAlex

This paper presents a study on the effect of the degree of saturation of the foundation soil on the vertical seismic response of end-bearing piles subjected to P-waves. The research focuses on nearly saturated soil, where the air phase is not continuous and air bubbles are dissolved in the pore water, and thus can be treated as two-phase material. The response of the two-phase soil–pile system is quantified by means of a rigorous coupled hydromechanical model, which is based on Biot’s theory for poroelastic media and treats the air bubbles–pore water mixture as a homogeneous fluid obeying Boyle’s law. Numerical results are used to illustrate the influence of the degree of saturation of the soil layer on the seismic strong motion transferred to the pile head, i.e., the capacity of piles to filter seismic wave energy. This work bridges the gap between single-phase and two-phase saturated soil models, which predict profoundly different pile head displacements at incident wave frequencies of practical interest, and elucidates the mechanisms that lead to these differences.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

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 integrity0.0000.000
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 head0.009
GPT teacher head0.200
Teacher spread0.191 · 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 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

Citations4
Published2024
Admission routes1
Has abstractyes

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Same venueCanadian Geotechnical JournalSame topicCoastal and Marine DynamicsFrench-language works237,207