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Record W4210725095 · doi:10.1139/tcsme-2020-0111

Modeling the effect of the inclination angle on the dynamic response of a biaxially pre-stressed plate

2022· article· en· W4210725095 on OpenAlexvenueno aff
Ahmet Daşdemir

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicComposite Structure Analysis and Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsDimensionless quantityFinite element methodVibrationMaterials scienceStructural engineeringMechanicsStress (linguistics)Elasticity (physics)Aspect ratio (aeronautics)Material propertiesComposite materialEngineeringPhysics

Abstract

fetched live from OpenAlex

In this study, I report on an investigation of the forced vibrations procured by an arbitrary angled time-harmonic loading from a plate based on a rigid foundation. The study was formulated according to the three-dimensional linearized theory of elasticity for solids under initial stress (TLTESIS). It was assumed throughout the investigation that there is a rigid clamped state between the system and the rigid ground; further, it was assumed that the plate was exposed to biaxially static initial stresses. Given this, a mathematical model was developed, and then solved using a three-dimensional finite element method (3D-FEM). Presented are numerical investigations that illustrate the influence of changes in the inclination of the force, as well as other important factors such as dimensionless frequency parameters, on the dynamic behavior of the system. In particular, the results indicate that the effect the initial stresses have on the dynamic stress distribution character increases with the aspect ratio but decreases with the thickness ratio.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.313
Threshold uncertainty score0.279

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.004
GPT teacher head0.188
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 teacher head, 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicComposite Structure Analysis and OptimizationFrench-language works237,207