TRACEO3D Ray Tracing Model for Underwater Noise Predictions - Inria - Institut national de recherche en sciences et technologies du numérique
Communication Dans Un Congrès Année : 2017

TRACEO3D Ray Tracing Model for Underwater Noise Predictions

Rogério M. Calazan
  • Fonction : Auteur
  • PersonId : 1022221
Orlando C. Rodríguez
  • Fonction : Auteur
  • PersonId : 1022222

Résumé

Shipping noise is the main source of underwater noise raising concern among environmental protection organizations and the scientific community. Monitoring of noise generated by shipping traffic is a difficult challenge within the context of smart systems and solutions based on acoustic modeling are being progressively adopted to overcome it. A module of sound propagation stands as a key point for the development of a smart monitoring system since it can be used for the calculation of acoustic pressure, which can be combined with estimates of the source pressure level to produce noise predictions. This paper addresses the usage of the TRACEO3D model for application in such systems; the model validity is addressed through comparisons with results from an analytical solution and from a scale tank experiment. The comparisons show that the model is able to predict accurately the reference data, while a full-field model (normal mode-based, but adiabatic) is only accurate till a certain degree. The results show that TRACEO3D is robust enough to be used efficiently for predictions of sound propagation, to be included as a part of a smart system for underwater noise predictions.
Fichier principal
Vignette du fichier
448071_1_En_17_Chapter.pdf (467.67 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01629581 , version 1 (06-11-2017)

Licence

Identifiants

Citer

Rogério M. Calazan, Orlando C. Rodríguez. TRACEO3D Ray Tracing Model for Underwater Noise Predictions. 8th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), May 2017, Costa de Caparica, Portugal. pp.183-190, ⟨10.1007/978-3-319-56077-9_17⟩. ⟨hal-01629581⟩
119 Consultations
174 Téléchargements

Altmetric

Partager

More