MétaCan
Menu
Back to cohort
Record W4396723827 · doi:10.21203/rs.3.rs-3998430/v1

A semi-analytical and numerical approach for solving 2-D and 6-D nonlinear and complex functionally graded tubular systems

2024· preprint· en· W4396723827 on OpenAlexaff
Liming Dai, Kamran Foroutan

Bibliographic record

VenueResearch Square · 2024
Typepreprint
Languageen
FieldEngineering
TopicComposite Structure Analysis and Optimization
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsNonlinear systemApplied mathematicsMathematicsComputer scienceMathematical analysisPhysics

Abstract

fetched live from OpenAlex

<title>Abstract</title> This study delves into nonlinear vibratory responses of functionally graded (FG) tubes subjected to transverse loads, considering material properties that vary with temperature. A refined beam model established for the tubes satisfies the stress boundary conditions on inner and outer surfaces of the tubes. The nonlinear vibration equations for these functionally graded tubes are meticulously derived with employment of the Zhang–Fu high-order shear deformation beam model, the von Kármán equation, and Hamilton’s principle. The proposed approach is applied to address externally excited nonlinear FG tube systems, encompassing both the 2 degrees of freedom (DOF) single-mode systems and 6 DOF multi-mode systems. Utilizing Galerkin’s method, the resulting discretized nonlinear governing equations allow for the analyses of single and multi-mode tubular system behavior. In solving for the tubular system, an approach implementing the P-T method is managed to be implemented, which yields a continuous semi-analytical solution throughout the entire time domain considered. The approach also demonstrates the advances on the development of a genuinely new computational method with broad impact. In comparison to the widely used Runge-Kutta (R-K) method, the proposed approach demonstrates superior efficiency, accuracy, and reliability, especially for highly nonlinear and complex systems like the FG tubular systems.

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: none
Teacher disagreement score0.791
Threshold uncertainty score0.917

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 communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.048
GPT teacher head0.328
Teacher spread0.280 · 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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueResearch SquareSame topicComposite Structure Analysis and OptimizationFrench-language works237,207