CFD Modelling of Air Lubrication Systems in Ships
CFD Modelling of Air Lubrication Systems in Ships Roya Shademani1, Tommi Mikkola1, Teemu Manderbacka1, Sasan Tavakoli2, Heikki Remes11Department of Mechanical engineering, Aalto University 2 University of Melbourne, AustraliaRoya.shademani@aalto.fi Presented at the 26th Numerical Towing Tank Symposium (NuTTS) – Duisburg, Germany Maritime transportation dominates global trade, with oceangoing ships, including container vessels, bulk carriers, and […]
Status and future trends of electrification-based solutions for efficiency-oriented ship retrofitting
STATUS AND FUTURE TRENDS OF ELECTRIFICATION-BASED SOLUTIONS FOR EFFICIENCY-ORIENTED SHIP RETROFITTING Maria Carmela Di Piazza, Marcello Pucci, Alessandro Iafrati (Institute of Marine Engineering-National Research Council) Presented at IEEE SARS ITEC Europe – November 2024 ABSTRACT The development of retrofitting solutions to increase the fuel efficiency and environmental sustainability of vessels is a hot topic. […]
OPTIMIZATION OF AN AIR LUBRICATION SYSTEM FOR GEOMETRY & TOPOLOGY
OPTIMIZATION OF AN AIR LUBRICATION SYSTEM FOR GEOMETRY & TOPOLOGY Hannes Renzsch (FRIENDSHIP SYSTEMS)Andrew Spiteri, Eduardo Blanco-Davis (LJMU)Milad Armin (ENKI Marine)Alex Routledge (Armada Technologies) Presented at 16th Symposium on High-Performance Marine Vehicles – “Technologies for the Ship of the Future”, Germany ABSTRACT This paper presents the challenges of developing and optimizing a second-generation Passive […]
AI MODEL FOR THE PREDICTION OF SHIP MOTIONS AND FUEL CONSUMPTION OF A KAMSARMAX BULK CARRIER
AI MODEL FOR THE PREDICTION OF SHIP MOTIONS AND FUEL CONSUMPTION OF A KAMSARMAX BULK CARRIER Mingyang Zhang a, Pentti Kujala b, Spyros Hirdaris c, Nikolaos Tsoulakos d a Department of Mechanical Engineering, Marine Technology Group, Aalto University, Espoo, Finlandb School of Engineering, Aalto University, Espoo, FinlandTallinn University of Technology, Estonian Maritime Academy, Tallinn, Estonia c American Bureau of Shipping, Global Ship […]
COMPARISON & EVALUATION OF LEARNING CAPABILITIES OF DEEP LEARNING METHODS FOR PREDICTING SHIP MOTIONS
COMPARISON & EVALUATION OF LEARNING CAPABILITIES OF DEEP LEARNING METHODS FOR PREDICTING SHIP MOTIONS Mingyang Zhang a, Cong Liu a, Pentti Kujala b, Spyros Hirdaris c a Department of Mechanical Engineering, Marine Technology Group, Aalto University, Espoo, Finlandb School of Engineering, Aalto University, Espoo, FinlandTallinn University of Technology, Estonian Maritime Academy, Tallinn, Estonia c American Bureau of Shipping, Global Ship Systems Centre, […]
AI-BASED SURROGATE MODELS FOR THE PREDICTION OF SHIP FUEL CONSUMPTION
AI-BASED SURROGATE MODELS FOR THE PREDICTION OF SHIP FUEL CONSUMPTION Mingyang Zhang a, Pentti Kujala b, Spyros Hirdaris c, Nikolaos Tsoulakos d a Department of Mechanical Engineering, Marine Technology Group, Aalto University, Espoo, Finlandb School of Engineering, Aalto University, Espoo, FinlandTallinn University of Technology, Estonian Maritime Academy, Tallinn, Estonia c American Bureau of Shipping, Global Ship Systems Centre, Athens, Greeced Laskaridis […]
RETROFIT SOLUTIONS TO ACHIEVE 55% GHG REDUCTION BY 2030
RETROFIT SOLUTIONS TO ACHIEVE 55% GHG REDUCTION BY 2030 Andrew Spiteri (LJMU)Vasilios Zagkas & Reuben D’Souza, SimFWD This article about the RETROFIT55 project featured in the April edition of The Naval Architect Magazine – April 2024 ABSTRACT The RETROFIT55 project aims to address the urgent need for decarbonization in the maritime industry by […]
Existing technologies and scientific advancements to decarbonize shipping by retrofitting
EXISTING TECHNOLOGIES AND SCIENTIFIC ADVANCEMENTS TO DECARBONIZE SHIPPING BY RETROFITTING Aleksander A. Kondratenko a,b , Mingyang Zhang c, Sasan Tavakoli d , Elias Altarriba e,f, Spyros Hirdaris g a Department of Space, Earth and Environment, Chalmers University of Technology, Gothenburg, Swedenb Faculty of Industrial Technology, Technical University of Sofia, Sofia, Bulgariac Department of Mechanical Engineering, […]
HULL AND PROPELLER BIOFOULING ASSESSMENT
ASSESSMENT OF HULL AND PROPELLER DEGRADATION DUE TO BIOFOULING USING TREE-BASED MODELS Nikos Themelis, School of Naval Architecture and Marine Engineering (NTUA)Vasilios Zagkas & George Nikolaidis, SimFWD ABSTRACT A hull and propeller biofouling assessment framework is presented and demonstrated using a bulk carrier as a case study corresponding to an operational period of two […]
DEEP LEARNING METHOD FOR PREDICTION OF SHIP FUEL CONSUMPTION
DEEP LEARNING METHOD FOR PREDICTION OF SHIP FUEL CONSUMPTION Mingyang Zhang, Pentti Kujala, Spyros Hirdaris, Aalto University, FinlandNikolaos Tsoulakos, Laskaridis Shipping Co. Ltd ABSTRACT In recent years, the European Commission and the International Maritime Organization (IMO) implemented various operational measures and policies to reduce ship fuel consumption and related emissions. The effectiveness of […]
