Thu, 29 December, 2022
GATERS partners meet in person for their joint SC & GA meetings in conjunction with the 4th International AYOCOL 2022 colloquium on 13-16 Dec 2022 in Istanbul
The GATERS project partners had their 1st “in-person/online” Steering Committee and General Assembly joint meetings at their partner, Istanbul Technical University (ITU)’s Campus, on 13-14th of December in conjunction with the 4th of the international AYOCOL Colloquium series on: “Ship Design & Optimisation and Energy Efficient Devices for Fuel Economy”, on 15-16 December 2022.
These combined events gave the project partners the opportunity for preparatory meetings for upcoming sea trials and mingling. In particular, to visit the manufacturer partner GURDESAN’s site and the DOGRUYOL shipyard in Yalova to review the ongoing manufacturing tasks and the drydocking site where the target vessel MV ERGE will be retrofitted in the new year (below pictures).
The Steering Committee and the General Assembly meetings took place at the Faculty of Naval Architecture and Ocean Engineering of ITU on the 13th and 14th of December with a warm welcome reception by the Dean, Prof Emin Korkut. The meetings were ended by the GATERS partners’ visit to the ITU’s Hydrodynamic Testing facilities at the Ata Nutku Towing Tank and the newly commissioned large cavitation tunnel ITUCAT (below pictures).
The partners also participated in AYOCOL 2022 colloquium and contributed by presenting five papers entitled and shown in the below pictures: https://www.ayocol.itu.edu.tr/
(1) Experimental Powering Performance Analysis of M/V ERGE in Calm Water and Waves presented by Dr B. Aktas (UoS);
(2) Investigation of Gate Rudder Blade Design for Ship Powering Using the Design of Experiment (DoE) Method, presented by AY Gurkan (UoS);
(3) On the Full-Scale Powering Extrapolation of Ships with Gate Rudder System (GRS) by C Celik (ITU);
(4) The Performance Prediction and Energy Saving Evaluation for the Retrofit of a Gate Rudder System on a General Cargo Vessel using CFD Procedures by Dr K Mizzi (NAS);
(5) Data-Driven Fuel Consumption Rate Estimation by Using Deep Learning by Serhan Gokcay (Hidroteknik)