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Record W4414934996 · doi:10.1080/15397734.2025.2563683

Refined three-variable theory for the bending response of multidirectional functionally graded nanobeams

2025· article· en· W4414934996 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMechanics Based Design of Structures and Machines · 2025
Typearticle
Languageen
FieldEngineering
TopicComposite Structure Analysis and Optimization
Canadian institutionsArtificial Intelligence in Medicine (Canada)
FundersJazan University
KeywordsBendingFunctionally graded materialTimoshenko beam theoryVibrationWork (physics)Finite element methodBuckling

Abstract

fetched live from OpenAlex

A new and improved shear deformation theory, featuring three variables and a built-in correction factor, is introduced to study the bending behavior of two-directional functionally graded (FG) beams. The displacement field is developed using the foundational ideas of Euler–Bernoulli beam theory (EBT). This work explores two types of coated FG nanobeams: hardcore (HC) and softcore (SC). Three patterns of material distribution are analyzed: a bidirectional setup, a unidirectional transverse layout, and a unidirectional axial design. To capture small-scale effects, the strain gradient nonlocal elasticity theory is applied. The governing equilibrium equations for the nanobeams are established through the principle of total potential energy. A sophisticated solution method, utilizing Galerkin’s approach, is used to effectively handle different boundary conditions. The FG beam is represented as resting on an elastic foundation, characterized by the Winkler, Pasternak, and Kerr models. This study offers a thorough assessment of how these elements together affect the critical buckling loads of nanobeams.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Methods · Consensus signal: none
Teacher disagreement score0.934
Threshold uncertainty score0.401

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.007
GPT teacher head0.213
Teacher spread0.205 · 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