Experimental validation of models for prediction of marine pile driving sound

Various models for the underwater noise radiation due to marine pile driving are being developed worldwide, to predict the sound exposure of marine life during pile driving activities. However, experimental validation of these models is scarce, especially for larger distances. Recently, TNO has been...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:The Journal of the Acoustical Society of America 2017-05, Vol.141 (5), p.3992-3992
Hauptverfasser: Müller, Roel A., Nijhof, Marten, Binnerts, Bas, de Jong, Christ A., Ainslie, Michael A., Jansen, Erwin
Format: Artikel
Sprache:eng
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Various models for the underwater noise radiation due to marine pile driving are being developed worldwide, to predict the sound exposure of marine life during pile driving activities. However, experimental validation of these models is scarce, especially for larger distances. Recently, TNO has been provided with data from underwater noise measurements up to 65 km from the piling location, gathered during the construction of two wind farms in the Dutch North Sea. These measurement data have been compared with different modeling approaches, in which the sound source is either formulated as an equivalent point source, or as a axially symmetric finite element model of the pile including the surrounding water and sediment. Propagation over larger distances, with varying bathymetry, is modeled efficiently by either an incoherent adiabatic normal mode sum or a flux integral approach. Differences between simulation and measurement data are discussed in terms of sound exposure level and spectral content, which leads to more insight into the mechanisms of sound radiation and propagation that are relevant during marine piling activities. An overview is given of the merits, shortcomings, and possibilities for improvement of the models.
ISSN:0001-4966
1520-8524
DOI:10.1121/1.4989140