Underwater noise propagation models and its application in renewable energy parks: WaveRoller Case Study

In the light of global warming, large-scale transition to renewable power sources is a worldwide challenge, playing wind power a significant role. Sea wave energy is being increasingly regarded in many countries as a major and promising resource but, like all forms of energy conversion, it will inevitably have an impact on the marine environment. WaveRoller, a Wave Energy Conversion Device, is installed in front of Almagreira beach, on the west coast of Portugal. The purpose of this thesis is to study and quantify the underwater radiated noise from this device using an underwater acoustic model in order to estimate potential effects it may have in the marine environment. The model used to run the data will be MIKE Zero – Underwater Acoustic Simulator by DHI . In the study site only cetacean species are expected to occur. Results showed that behavioural responses might be expected for low and mid-frequency cetaceans if they swim close to the device. Also, the device shouldn’t be installed in an area in which a population of cetaceans exists in a 28m ray. For these individuals, injury can be assumed if SEL (Sound Exposure Level) is higher than 215 dB re 1μPa2.s, for non-pulse sounds. Results showed the calculated maximum SEL of the Waveroller sound is 150 dB re 1μPa2.s and therefore no injury is expected. MIKE Zero – Underwater Acoustic Simulator is a powerful tool to test any device that produces underwater noise and offers the possibility to create Surface Sound maps of results by using MIKEXYZ Converter tool

Measured and modeled acoustic propagation underneath the rough Arctic sea-ice

Author Posting. © Acoustical Society of America, 2017. This article is posted here by permission of Acoustical Society of America for personal use, not for redistribution. The definitive version was published in Journal of the Acoustical Society of America 142 (2017): 1619-1633, doi:10.1121/1.5003786.A characteristic surface duct beneath the sea-ice in the Marginal Ice Zone causes acoustic waves to be trapped and continuously interact with the sea-ice. The reflectivity of the sea-ice depends on the thickness, the elastic properties, and its roughness. This work focuses on the influence of sea-ice roughness on long-range acoustic propagation, and on how well the arrival structure can be predicted by the full wave integration model OASES. In 2013, acoustic signals centered at 900 Hz were transmitted every hour for three days between ice-tethered buoys in a drifting network in the Fram Strait. The experiment was set up to study the signal stability in the surface channel below the sea-ice. Oceanographic profiles were collected during the experiment, while a statistical description of the rough sea-ice was established based on historical ice-draft measurements. This environmental description is used as input to the range independent version of OASES. The model simulations correspond fairly well with the observations, despite that a flat bathymetry is used and the sea-ice roughness cannot be fully approximated by the statistical representation used in OASES. Longrange transmissions around 900 Hz are found to be more sensitive to the sea-ice roughness than the elastic parameters.The fieldwork was performed under funding from the Research Council of Norway through the UNDER-ICE (Grant No. 226373) project and ENGIE E&P Norway providing additional support. The data analysis, modeling and preparation of the publication has been carried out under funding from the Office of Naval Research (Global) (Grant No. N62909-14-1-NO33) and UNDER ICE (Grant No. 226373) projects. The U.S. Office of Naval Research provided partial support for this work under Grant No. N000141210176 to the Woods Hole Oceanographic Institution

Hydroacoustic Channel Emulator - HACE

Kongsberg Maritime wanted a channel emulator for testing their hydroacoustic equipment before deploying it at sea. The benefits of such a system are that it detects problems in an earlier phase of development, thus conveniently reducing the number of expensive sea trials necessary. This master thesis describes how a channel emulator with hydroacoustic properties can be made. The emulator will replace the transducers and water with a computer simulating the acoustics, an audio interface and voltage attenuation. Our approach has been to develop a stable and user-friendly channel emulator with a basis in acoustic wave theory. The hydroacoustic channel emulator, HACE, includes acoustic simulation models where the user is allowed to change acoustic parameters and place the positions of transducers for both point-to-point and network communication. This thesis has focused on advanced acoustic models such as Doppler spread, surface scatter, varying seabed and surface in 3D, sound speed profile with ray tracing, and network communication, together with the fundamental models such as, propagation loss and delay, and reflections. In order to meet the requirements of this master s thesis, with respect to latency and jitter, a good programming platform is important. MATLAB was chosen due to the huge library of built-in-functions, especially with respect to digital signal processing. To control the system a user interface was created with the focus on simplicity, where the interface allows the user to control the system and adjust parameters. The real-time requirement for the system was a latency with a maximum of 100 ms. Since the latency is dependent on both software and hardware, and varies from setup to setup, a calibration function was developed to ensure the best performance for each individual system. HACE has full control over the system latency and exploits it when adding the propagation delay. The minimum latency was measured as 34.2 ms, which resulted in a minimum distance between two nodes using a sound speed of 1500 m/s, being 51.3 meters. For the system to model other distances correctly, this latency must be taken into account when adding propagation delay. Ideally, zero latency would have been preferred so that all distances could be simulated. Two tests were performed to determine the performance of the total system, one that compared the real world impulse response with the simulated impulse response, and secondly to verify the propagation delay in HACE against the measured distance from APOS. The results showed that the simulated ranges corresponded well with the ranges measured in APOS, with an offset of around 20 cm throughout all the results. Impulse response measurements were performed at a sea trial in Horten (Breiangen) measuring at horizontal ranges from 0 to 3000 meters between two nodes. Results from the sea trial compared with those of HACE showed very good similarities between the two, with time deviations between the first and second arrival being from 0 - 3 ms (0 to 15 %), where the largest deviations were found at the shortest ranges

Adapting Deep Learning for Underwater Acoustic Communication Channel Modeling

The recent emerging applications of novel underwater systems lead to increasing demand for underwater acoustic (UWA) communication and networking techniques. However, due to the challenging UWA channel characteristics, conventional wireless techniques are rarely applicable to UWA communication and networking. The cognitive and software-defined communication and networking are considered promising architecture of a novel UWA system design. As an essential component of a cognitive communication system, the modeling and prediction of the UWA channel impulse response (CIR) with deep generative models are studied in this work. Firstly, an underwater acoustic communication and networking testbed is developed for conducting various simulations and field experiments. The proposed test-bed also demonstrated the capabilities of developing and testing SDN protocols for a UWA network in both simulation and field experiments. Secondly, due to the lack of appropriate UWA CIR data sets for deep learning, a series of field UWA channel experiments have been conducted across a shallow freshwater river. Abundant UWA CIR data under various weather conditions have been collected and studied. The environmental factors that significantly affect the UWA channel state, including the solar radiation rate, the air temperature, the ice cover, the precipitation rate, etc., are analyzed in the case studies. The obtained UWA CIR data set with significant correlations to weather conditions can benefit future deep-learning research on UWA channels. Thirdly, a Wasserstein conditional generative adversarial network (WCGAN) is proposed to model the observed UWA CIR distribution. A power-weighted Jensen–Shannon divergence (JSD) is proposed to measure the similarity between the generated distribution and the experimental observations. The CIR samples generated by the WCGAN model show a lower power-weighted JSD than conventional estimated stochastic distributions. Finally, a modified conditional generative adversarial network (CGAN) model is proposed for predicting the UWA CIR distribution in the 15-minute range near future. This prediction model takes a sequence of historical and forecast weather information with a recent CIR observation as the conditional input. The generated CIR sample predictions also show a lower power-weighted JSD than conventional estimated stochastic distributions

Modelling, Simulation and Data Analysis in Acoustical Problems

Modelling and simulation in acoustics is currently gaining importance. In fact, with the development and improvement of innovative computational techniques and with the growing need for predictive models, an impressive boost has been observed in several research and application areas, such as noise control, indoor acoustics, and industrial applications. This led us to the proposal of a special issue about “Modelling, Simulation and Data Analysis in Acoustical Problems”, as we believe in the importance of these topics in modern acoustics’ studies. In total, 81 papers were submitted and 33 of them were published, with an acceptance rate of 37.5%. According to the number of papers submitted, it can be affirmed that this is a trending topic in the scientific and academic community and this special issue will try to provide a future reference for the research that will be developed in coming years