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  4. Prediction of underwater sound due to pile driving for offshore wind farms - A challenge for numerical simulation
 
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Prediction of underwater sound due to pile driving for offshore wind farms - A challenge for numerical simulation

Publikationstyp
Conference Paper
Date Issued
2012-08
Sprache
English
Author(s)
Lippert, Stephan  
Lippert, Tristan  
Estorff, Otto von  
Milatz, Marius  orcid-logo
Reimann, Katja  
Institut
Geotechnik und Baubetrieb B-5  
TORE-URI
http://hdl.handle.net/11420/12422
Volume
10
Start Page
7939
End Page
7950
Citation
41st International Congress and Exposition on Noise Control Engineering (INTER-NOISE 2012)
Contribution to Conference
41st International Congress and Exposition on Noise Control Engineering, INTER-NOISE 2012  
Scopus ID
2-s2.0-84883572117
Offshore wind energy farms have become an important addition to onshore parks. Major advantages are better wind conditions and the separation to human living space. A crucial drawback, however, is the possible negative impact on marine wildlife during the construction of the commonly-used pile foundations. In particular, marine mammals can be affected by high sound pressure levels in the water caused by pile driving. Different concepts to reduce underwater sound emission, e.g. bubble curtains or cofferdams, already exist. Due to the immense cost of offshore tests, it seems to be advisable to predict and optimize the efficiency of sound damping measures by numerical simulation. The current contribution gives an overview of possible modeling strategies and their limitations. General difficulties arise due to the huge system size and the complex interaction of pile, soil, and surrounding water. Especially, the prediction of the underwater sound levels at a distance of several kilometers from the pile for frequencies in the kHz range is very demanding. Based on a preliminary study it is shown that numerical simulation is suitable for such problems. Additionally, first results of a research project are presented that aims at the further development of the models and a validation by offshore tests.
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