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Record W4406087701 · doi:10.3390/app15010457

Consideration of Rocking Wind Turbine Foundations on Undrained Clay with an Efficient Constitutive Model

2025· article· en· W4406087701 on OpenAlexafffund
Behrouz Badrkhani Ajaei, M. Hesham El Naggar

Bibliographic record

VenueApplied Sciences · 2025
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGeotechnical engineeringTurbineCritical state soil mechanicsConstitutive equationGeologyEngineeringStructural engineeringMechanical engineeringFinite element method

Abstract

fetched live from OpenAlex

The concept of rocking foundations has been successfully tested and promoted for building and bridge foundations. In this paper, the applicability of rocking foundations to wind turbines is investigated, specifically for wind turbines constructed on undrained clay. An efficient form of von Mises constitutive model with non-linear kinematic hardening is integrated with the ABAQUS finite element software by a computer code and validated against experimental data. A cohesive contact of foundation–soil with limited tension is applied to simulate suction stresses at the foundation bottom–soil interface, which better represented the rocking foundation behavior. The obtained finite element results demonstrate that by allowing minimal foundation uplift under operational loads, an existing foundation can be used to support loads from a larger wind turbine than it is designed for. Allowing such uplifts corresponds to a rocking foundation design that is demonstrated in this paper to be safe and functional for a wind turbine under both operational and extreme conditions.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

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 science0.0010.000
Research integrity0.0010.000
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 head0.016
GPT teacher head0.241
Teacher spread0.225 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

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