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Record W1986140074 · doi:10.1142/s0219455403000860

Analysis of Toroidal Shells Using the Differential Quadrature Method

2003· article· en· W1986140074 on OpenAlexaff
D. Redekop, T. Muhammad

Bibliographic record

VenueInternational Journal of Structural Stability and Dynamics · 2003
Typearticle
Languageen
FieldEngineering
TopicComposite Structure Analysis and Optimization
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsStaticsToroidFinite element methodQuadrature (astronomy)VibrationBucklingParametric statisticsStructural engineeringDifferential (mechanical device)Nyström methodNumerical analysisNumerical integrationComputer scienceMathematicsMathematical analysisEngineeringPhysicsClassical mechanicsAcousticsBoundary value problemElectronic engineering

Abstract

fetched live from OpenAlex

In new applications of toroidal shells it is often necessary to solve problems of statics, response, vibration, and buckling. While the finite element method can serve as the main means of analysis it is desirable to have available a second, complementary, method that can be used for verification, parametric studies, and specialized analyses. In this paper the use of the new differential quadrature method in such a complimentary role is investigated. Problems involving the statics, response, vibration, and buckling of toroidal shells are analyzed. Numerical results obtained are compared with finite element calculations. Finally conclusions are drawn concerning the agreement between the methods, and the usefulness of the new method for specialized studies.

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)0.001
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.001
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 head0.007
GPT teacher head0.257
Teacher spread0.250 · 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

Citations6
Published2003
Admission routes1
Has abstractyes

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Same venueInternational Journal of Structural Stability and DynamicsSame topicComposite Structure Analysis and OptimizationFrench-language works237,207