Research Ambient Noise DIrectionality (RANDI) 3.1 Physics Description.

Breeding, J. Ernest; Pflug, Lisa A.; Bradley, Marshall; Walrod, Melanie H.

doi:10.21236/ada316034

Cited by 36 publications

(23 citation statements)

References 9 publications

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“…and are additional length correction which can be found from Breeding et al (1996). This is an empirical model based on a large number of measurements, which is also used by worldwide noise models such as RANDI (Breeding, et al, 1996).…”

Section: Shipping Datamentioning

confidence: 99%

“…This is an empirical model based on a large number of measurements, which is also used by worldwide noise models such as RANDI (Breeding, et al, 1996). Given that the predominant bandwidth for shipping noise ranges from 10Hz to 1000Hz (although it does extend into the higher frequencies at least up to 40kHz (Viers et al, 2016)), the modelled narrow band spectrum from equation (1) was integrated into standard 1/3 octave central frequency spectrum between 10 1000Hz, giving the representative source level (SL) of the ship noise in 1/3 octave band.…”

Section: Shipping Datamentioning

confidence: 99%

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Shipping noise in a dynamic sea: a case study of grey seals in the Celtic Sea

Chen

Shapiro

Bennett

et al. 2017

Marine Pollution Bulletin

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Shipping noise is a threat to marine wildlife. Grey seals are benthic foragers, and thus experience acoustic noise throughout the water column, which makes them a good model species for a case study of the potential impacts of shipping noise. We used ship track data from the Celtic Sea, seal track data and a coupled ocean-acoustic modelling system to assess the noise exposure of grey seals along their tracks. It was found that the animals experience step changes in sound levels up to~20dB at a frequency of 125Hz, and~10dB on average over 10 1000Hz when they dive through the thermocline, particularly during summer. Our results showed large seasonal differences in the noise level experienced by the seals. These results reveal the actual noise exposure by the animals and could help in marine spatial planning.

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Section: Shipping Datamentioning

confidence: 99%

Section: Shipping Datamentioning

confidence: 99%

Shipping noise in a dynamic sea: a case study of grey seals in the Celtic Sea

Chen

Shapiro

Bennett

et al. 2017

Marine Pollution Bulletin

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“…5 pav. Laivų generuojamo triukšmo bei greičio priklausomybė, apskaičiuota taikant Breeding et al (1996) algoritmą Fig. 5.…”

Section: Rezultatai Ir Jų Analizėunclassified

“…Atliekant povandeninio triukšmo modeliavimą buvo pasitelktas plačiai taikomas laivų triukšmo lygių spektrinis algoritmas Breeding et al (1996), leidžiantis prognozuoti laivų triukšmo lygius. Šis algoritmas buvo parinktas atsižvelgiant į duomenų prieinamumą duomenų bazėse bei jo sudėtingumą.…”

Section: Išvadosunclassified

Underwater Noise Modeling in Lithuanian Area of the Baltic Sea

Bagočius

Narščius

2017

Science - Future of Lithuania

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2017 © Straipsnio autoriai. Leidėjas VGTU leidykla "Technika". Šis straipsnis yra atvirosios prieigos straipsnis, turintis Kūrybinių bendrijų (Creative Commons) licenciją (CC BY-NC 4.0), kuri leidžia neribotą straipsnio ar jo dalių panaudą su privaloma sąlyga nurodyti autorių ir pirminį šaltinį. Straipsnis ar jo dalys negali būti naudojami komerciniams tikslams. MOKSLAS -LIETUVOS ATEITIS SCIENCE -FUTURE OF LITHUANIA

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“…Application of the standard thus usually concerns single ship measurements (Arveson and Vendittis, 2000;De Robertis et al, 2013). Several models describing URN have been proposed (Breeding et al, 1996;Wittekind, 2014;Audoly and Rizzuto, 2015;Brooker and Humphrey, 2015), using combinations of ship parameters to derive frequency dependent equivalent (omni-directional) point source representations of the noise radiating ship.…”

Section: Introductionmentioning

confidence: 99%

Estimates of Source Spectra of Ships from Long Term Recordings in the Baltic Sea

et al. 2017

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Estimates of the noise source spectra of ships based on long term measurements in the Baltic sea are presented. The measurement data were obtained by a hydrophone deployed near a major shipping lane south of the island Öland. Data from over 2,000 close-by passages were recorded during a 3 month period from October to December 2014. For each passage, ship-to-hydrophone transmission loss (TL) spectra were computed by sound propagation modeling using 1. bathymetry data from the Baltic Sea Bathymetry Database (BSBD), 2. sound speed profiles from the HIROMB oceanographic model, 3. seabed parameters obtained by acoustic inversion of data from a calibrated source, and 4. AIS data providing information on each ship's position.These TL spectra were then subtracted from the received noise spectra to estimate the free field source level (SL) spectra for each passage. The SL were compared to predictions by some existing models of noise emission from ships. Input parameters to the models, including e.g., ship length, width, speed, displacement, and engine mass, were obtained from AIS (Automatic Identification System) data and the STEAM database of the Finnish Metereological Institute (FMI).

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Research Ambient Noise DIrectionality (RANDI) 3.1 Physics Description.

Cited by 36 publications

References 9 publications

Shipping noise in a dynamic sea: a case study of grey seals in the Celtic Sea

Shipping noise in a dynamic sea: a case study of grey seals in the Celtic Sea

Underwater Noise Modeling in Lithuanian Area of the Baltic Sea

Estimates of Source Spectra of Ships from Long Term Recordings in the Baltic Sea

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