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Record W4391592405 · doi:10.3390/civileng5010009

Finite Element Model of Concrete-Filled, Fiber-Reinforced Polymer Tubes for Small-Scale Wind Turbine Towers

2024· article· en· W4391592405 on OpenAlexaff
Yikai Gong, Martin Noël

Bibliographic record

VenueCivilEng · 2024
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTurbineFinite element methodMaterials scienceStructural engineeringScale (ratio)FiberScale modelComposite materialEngineeringMechanical engineeringAerospace engineeringPhysics

Abstract

fetched live from OpenAlex

The finite element method was used to study the feasibility of concrete-filled, fiber-reinforced polymer tubes (CFFTs) for small-scale wind turbine towers in remote areas. Although CFFTs have been successfully employed for a variety of structural applications, their use for wind turbine towers is novel and has yet to be investigated in detail. The objective of the study was to identify, for the first time, the most important parameters for design and compare the behavior of CFFT towers versus conventional steel and concrete towers. The model was first validated using experimental results reported in the literature followed by a series of parametric studies to evaluate the importance of several key parameters. In the first phase, the effect of different geometric properties (taper and concrete filling ratio) and reinforcement configurations (FRP laminate configuration, steel reinforcement ratio, and prestressing level) were investigated for cantilever tower models with concentrated lateral loads. A 10 m high CFFT wind turbine tower model was subsequently modeled and studied under different loading configurations. The influence of the height-to-diameter (h/D) ratio on cantilever CFFT models was also studied and a conservative preliminary design that can be refined for specific turbine systems and wind conditions was adopted using the h/D ratio. The CFFT tower model was compared to concrete and steel tubular models with similar geometry to study the advantages of CFFT towers and showed that CFFTs can be an efficient alternative.

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 categoriesMeta-epidemiology (narrow)
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 score0.150
Threshold uncertainty score1.000

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 integrity0.0000.000
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 head0.017
GPT teacher head0.228
Teacher spread0.211 · 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 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
Published2024
Admission routes1
Has abstractyes

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