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Record W4303575404 · doi:10.1007/s00419-022-02277-0

Exact series solutions of composite beams with rotationally restrained boundary conditions: static analysis

2022· article· en· W4303575404 on OpenAlexaff
Yuan Zhang, Lei Zhang, Sigong Zhang

Bibliographic record

VenueArchive of Applied Mechanics · 2022
Typearticle
Languageen
FieldEngineering
TopicComposite Structure Analysis and Optimization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBoundary value problemDeflection (physics)Composite numberSlip (aerodynamics)Series (stratigraphy)Structural engineeringExact solutions in general relativityBoundary (topology)Mathematical analysisMathematicsEngineeringPhysicsClassical mechanicsGeologyAlgorithm

Abstract

fetched live from OpenAlex

Abstract The structural performance of composite beams is sensitive to load distribution as well as actual boundary conditions. Although the composite beam theory has been solidly established and exact solutions have been readily developed for various loading and boundary conditions, almost all of them are limited to classical boundary conditions (free, pinned and clamped) and there has been little discussion about the actual support conditions in real structures. The general representation of actual boundary conditions can be defined as rotationally restrained edges. In this research, an analytical model with exact series-type solutions was developed for composite beams with rotationally restrained edges. The model and displacement solutions were validated by other analytical methods and numerical results. The influence of rotational and end-slip restraints was investigated. It was found that the deflection and interface slip of composite beams are highly affected by both restraints introduced by the actual boundary conditions. The current model can be used as a benchmark for future design methods considering the realistic boundary conditions of composite beams.

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: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.004
GPT teacher head0.189
Teacher spread0.184 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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