Underwater Radiated Noise Measurements on a Chemical Tanker Measurements at Sea- Trials Compared to Model-Scale Tests and CFD Jan Hallander, Da-Qing Li and Torbjörn Johansson SSPA Sweden AB Gothenburg, Sweden www.sspa.se
Acknowledgement The present work has been realized within the scope of AQUO, a collaborative research project supported by the European Union 7th Framework Programme through Grant Agreement N 314227. www.aquo.eu
Introduction The goal of the EU-funded AQUO project was to provide policy makers with practical guidelines to mitigate underwater noise footprint due to shipping in order to prevent adverse consequences to marine life. Three levels of characterization of the ocean shipping noise footprint: This presentation will focus on the prediction of and measurements of ships as noise sources
Introduction Underwater Radiated Noise (URN) is of growing environmental concern due to potential adverse effects on marine fauna Shipping noise is a strong contributor to the underwater noise levels in the band from 10 Hz to 1000 Hz The main sources are propeller, main engine and auxiliary engines EC Marin Strategy Framework Directive, descriptor 11: input of energy, including underwater noise, should be at levels that are not harmful to the environment IMO (MEPC 2014) Guidelines for the reduction of underwater noise from commercial shipping to address adverse impacts on marine life
Requirements and validation Classification Society Rules DNV GL: Silent Class Notation, 2010 BV Rule Note: Underwater Radiated Noise, 2014 Standards for measurements at sea ANSI/ASA (deep water) ISO/DPAS 17208-1 (proposal 2011) AQUO project proposal (shallow water) Port of Vancouver, Canada, 2017: Reduced fee for ships that fulfil classification society rules on URN
Prediction of URN by model scale tests and CFD Validation by full scale measurements There is a need to predict the URN from ships before they are built to assess if the design will fulfill the requirements Semi-empirical models (based on measurement data and calculations) Model-scale measurements Numerical calculations There is a need to validate that a ship fulfills the URN requirements at sea trials This presentation shows the results of full-scale measurements performed compared to predictions of propeller noise based on model-scale measurements in the SSPA cavitation tunnel and predictions using Computational Fluid Dynamics (CFD).
Measurement object M/T Olympus Oil and chemical tanker (DNV ICE-1A) Length 116 m Design draft 8,1 m 7515 GT Main engine 4 320 kw @ 600 rpm Gearbox 1:5 3 x aux engines @ 1800 rpm One four-bladed propeller, D=4,8m, Controllable Pitch
Full scale measurements: Trial area
Full scale measurements 50 m
Model scale measurements Noise Pressure pulses Photo and video documentation
CFD Multi-phase Delayed Detached Eddy Simulation (DDES) Ffowcs-Williams Hawkings (FWH) acoustic analogy Numerical Scheme: Multiphase mixture flow incompressible solver Pressure and velocity solved in a coupled manner Bounded 2 nd order central difference for convection terms in momentum equations QUICK scheme in other transport equations Propeller rotation handled by sliding mesh technique Bounded 2 nd order implicit scheme for time-derivative Time-step is 6.94x10-4 [s] at full scale 47 million grid cells at full scale
Loading Conditions for comparison LC1 LC2 LC5 LC6 P/D 0.87 0.87 0.521 0.521 Draft Design Ballast Design Ballast Condition NCR power ( 14 kn) NCR power ( 15 kn) 11 kn, nominal rpm 11 kn, nominal rpm Engine shaft power 3.67 3.67 1.94 1.75
Results: Cavitation observations LC2, model scale LC2, full scale 10 20 30 40 50 60 Suction side sheet cavitation (x=0.9 to tip), tip vortex cavitation with some oscillations and bursting
Results: Cavitation observations LC6, model scale LC6, full scale 10 20 30 40 50 60 No suction side sheet cavitation, thin tip vortex cavitation, face side leading edge vortex
Results: Cavitation observations LC6, model scale, face side 40 60 Face side leading edge vortex 70 90
Results: Cavitation observations Cavitation pattern at full scale, video image vs. DDES
Results: URN LC1, full scale vs. model scale LC5, full scale vs. model scale 200 190 180 M/T Olympus, LC1 FS mean FS envelope MS SSPA 200 190 180 M/T Olympus, LC5 FS mean FS envelope MS SSPA L ps (f) [db re 1 Pa 2 /Hz @ 1 m] 170 160 150 140 130 120 L ps (f) [db re 1 Pa 2 /Hz @ 1 m] 170 160 150 140 130 120 110 110 100 10 1 10 2 10 3 f s [Hz] 100 10 1 10 2 10 3 f s [Hz]
Results: URN full scale vs. model scale LC1, source identification 5 Hz to 100 Hz
Results: URN full scale vs. model scale LC5, source identification 5 Hz to 100 Hz
Results: URN full scale vs. CFD CFD predicts higher a BPF TL loss in FS probably underestimated Fairly good 3 rd to 5 th BPF CFD under predicts TVC noise, DDES underresolved the tip vortex Broadband noise 110 200 Hz fairly good
Conclusions With appropriate post-processing and source identification, the full scale data is very useful for validation against requirements, characterizing the noise signature and for benchmarking predictions by model testing and computational methods. Noise sources on M/T Olympus are mainly propeller-related, but there are some strong tones from engine revolutions and ignition. Overall the URN estimated from model tests have a good correlation with the character of noise spectra in full scale. For DDES-FWH method, the results are more intricate. The TVC (Tip vortex Cavitation) is captured in the simulation but its strength and extension are less than that observed in the sea trial. Due to this, the simulation under-predicts the noise level in the frequency range where the TVC is expected to have an important contribution. Limited in frequency by time and space resolution. Very demanding in terms of CPU.
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