Analysis of a barrel-stave flextensional transducer using MAVART and ATILA finite element codes
Bibliographic record
Abstract
A small barrel-stave flextensional transducer, designed and tested at Defence Research and Development Canada -Atlantic (DRDC Atlantic), is a candidate source for underwater coastal surveillance and acoustic communications applications.This high-power transducer (in excess of 190 dB re 1 |aPa @ 1 m) has an outside diameter, length and mass of 5.7 cm, 12.7 cm, and 1.1 kg, respectively.The measured fundamental flexural resonance frequency was 1.8 kHz with a transmitting voltage response of 118 dB re 1 |aPa/V @ 1m and an omnidirectional radiation pattern.Two computer models were developed for this transducer using finite element codes MAVART™ (Model to Analyze the Vibrations and Acoustic Radiation of Transducers) and ATILA (Analysis of Transducers by Integration of Laplace equations).Comparisons are made between the calibration measurements and the model predictions.[2Summer student supported in part by Sensor Technology Limited.]s o m m a i r eUn petit transducteur flextensionnel à douves, conçu et mis à l 'essai à Recherche et développement pour la défense Canada -Atlantique (RDDC Atlantique), est une source possible pour des applications de surveillance côtière sous-marine et de communications acoustiques.Ce transducteur de grande puissance (supérieure à 190 dB, rapportée à 1 DPa à 1 m) a un diamètre extérieur de 5,7 cm, une longueur de 12,7 cm et une masse de 1,1 kg.La fréquence fondamentale de résonance en flexion mesurée était de 1,8 kHz avec une réponse en tension d'émission de 118 dB, rapportée à 1 DPa/V à 1 m, et un diagramme de rayonnement omnidirectionnel.Deux modèles informatisés ont été élaborés pour ce transducteur à l 'aide des codes à éléments finis MAVART™ (modèle pour analyser les vibrations et le rayonnement acoustique de transducteurs) et ATILA (analyse de transducteurs par intégration d'équations de Laplace).Des comparaisons sont effectuées entre les mesures d 'étalonnage et les prédictions à partir des modèles.[2Stagiaire d 'été rémunéré en partie par Sensor Technology Limited.]
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".