Learning underwater ocean acoustics: computational modelling, experiments, and development of AI/ML-based models

Date(s)
Thursday 28th November 2024 (15:00-16:00)
Contact
Event Convenor Contact: Martin.Richter@nottingham.ac.uk
Description
Speaker's Name: Wrik Mallik
Speaker's Affiliation: University of Glasgow
Speaker's Research Theme(s): Applied Mathematics,Computational statistics and machine learning
Abstract:
Underwater radiated noise from shipping activities and offshore wind turbine construction/operation adversely affects the echolocation marine mammals. Noise levels in various regions of the North Sea, Arctic Ocean, and Atlantic Ocean off the coast of British Isles have almost doubled over the last decade due to various marine activities and can only be expected to increase with further increase of marine trade and offshore wind turbine construction, if left unchecked. Thus, there is an urgent need to develop accurate underwater noise source characterization and prediction capability of underwater radiated noise to regulate marine pile driving practices. To analyse various interesting underwater ocean acoustic phenomena like broadband noise scattering, attenuation, and coupled fluid-acoustic interaction I have adopted both high-fidelity computational modelling and creative experiments. Finally, to develop a unifying model of underwater ocean acoustic propagation, a data-driven model is also being developed to complement the computational modelling and experiments as a toolbox with fast prediction capability of far-field noise radiation. Such a data-driven driven model is agnostic to the source of the data and is developed via state-of-the-art AI/ML architectures.

Venue: online (Teams)
Online Conference Link: https://teams.microsoft.com/l/meetup-join/19%3ameeting_MjcwY2JkY2EtNzQzZS00ZGFhLWJmNjQtNmNiNmMzODEwZTgz%40thread.v2/0?context=%7b%22Tid%22%3a%2267bda7ee-fd80-41ef-ac91-358418290a1e%22%2c%22Oid%22%3a%22ac9aefe7-3e46-4f97-97c8-d17f8aef5d78%22%7d

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