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Record W1982008535 · doi:10.1115/1.4027212

Mode Count and Modal Density of Isotropic Circular Cylindrical Shells Using a Modified Wavenumber Space Integration Method

2014· article· en· W1982008535 on OpenAlexaff
Mohammad Hossein Farshidianfar, Anooshiravan Farshidianfar, Mahdi Mazloom Moghadam

Bibliographic record

VenueJournal of vibration and acoustics · 2014
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Phenomena Research
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsWavenumberModalIsotropyMode (computer interface)Boundary value problemPhysicsMathematical analysisSpace (punctuation)MathematicsOpticsMaterials science

Abstract

fetched live from OpenAlex

A new method based on the wavenumber space integration algorithm is proposed in order to obtain mode count and modal density of circular cylindrical shells. Instead of the simplified equation of motion, the exact equation is applied in mode count calculations. Modal plots are changed significantly in the k-space when using the exact equation. Mode repetition in cylindrical shells is represented by additional mode count curves in the k-space. On the other hand, a novel technique is presented in order to implement boundary condition effects in mode count and modal density calculations. Integrating these two significant corrections, a modified wavenumber space integration (MWSI) method is developed. Mode count and modal densities of three shells with different geometrical and acoustical properties are obtained using the MWSI method and conventional WSI. Results are verified using the exact mode count calculations. Moreover, effects of geometrical properties are studied on mode count plots in the k-space. Modal densities are obtained for cylindrical shells of different lengths, radii, and thicknesses. Finally, modal densities of cylindrical shells are compared to flat plates of the same size and boundary condition. Interesting results are obtained which will contribute in calculation of acoustic radiation efficiency and sound transmission in cylindrical shells.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.506
Threshold uncertainty score0.373

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.020
GPT teacher head0.283
Teacher spread0.263 · 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

Citations6
Published2014
Admission routes1
Has abstractyes

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