In the Cooperative Research Ships (CRS) Data Driven working group, participants worked on several problem cases in ship hydrodynamics using data driven methods. The problem cases included significant event detection, performance prediction, whipping assessment and rudder control.

In this webinar we will summarize these projects and highlight the main results and conclusions. The results of the Data Driven working group motivated us to continue our research in the CRS Fusion working group, where we aim to fuse domain knowledge and data driven approaches to tackle various challenges in ship hydrodynamics.

CRS SHARE Webinar ‘Data Driven’ on Thursday 28 April 2022, 14.00 – 16.30 CET

Programme

• Scientific Machine Learning for Ship Hydromechanics – Gabriel D. Weymouth, University of Southampton
• Can machine learning identify the conditions leading to significant green water impact events? – Tormod Landet, DNV
• Ship performance prediction using machine learning –  Thomas Scholcz, MARIN & Nico van den Heuvel, DAMEN & Eivind Ruth, DNV
• Machine learning for fast assessment of whipping nonlinearities – Alexandru Andoniu, Bureau Veritas
• Rudder control with Reinforcement Learning – Bülent Düz, MARIN

Register here: https://us06web.zoom.us/webinar/register/WN_3CBNg8HhQEaI1eMtehpQAQ