A review on ship motions and quiescent periods prediction models

The prediction of ship motions and quiescent periods, is of paramount importance for the maritime industry. The capability to predict these events sufficiently in advance has the potential to improve the safety and efficiency of several marine operations, such as landing and take-off on aircraft carriers, transfer of cargo, and mating...

Numerical methods for monitoring and evaluating the biofouling state and effects on vessels’ hull and propeller performance: A review

Monitoring and evaluating the biofouling state and its effects on the vessel's hull and propeller performance is a crucial problem that attracts the attention of both academy and industry. Effective and reliable tools to address this would allow a timely cleaning procedure able to trade off costs, efficiency, and environmental impacts. In...

Data science and advanced analytics for shipping energy systems

The purpose of this chapter is to provide an overview of the state-of-the-art and future perspectives of Data Science and Advanced Analytics for Shipping Energy Systems. Specifically, we will start by listing the different static and dynamic data sources and knowledge base available in this particular context. Then we will review the Data...

Artificial Intelligence-based short-term forecasting of vessel performance parameters

Deterministic models based on the laws of physics, as well as data-driven models, are often used to assess the current state of vessels and their systems, as well as predict their future behaviour. Predictive maintenance methodologies (i.e., Condition Based Maintenance) and advanced control strategies (i.e., Model Predictive Control) are...

Physical and Data-Driven Models Hybridisation for Modelling the Dynamic State of a Four-Stroke Marine Diesel Engine

Accurate, reliable, and computationally inexpensive models of the dynamic state of combustion engines are a fundamental tool to investigate new engine designs, develop optimal control strategies, and monitor their performance. The use of those models would allow to improve the engine cost-efficiency trade-off, operational robustness, and...

Computationally aware estimation of ultimate strength reduction of stiffened panels caused by welding residual stress: From finite element to data-driven methods

Ultimate limit state (ULS) assessment examines the maximum load-carrying capacity of structures considering inelastic buckling failure. Contrary to the traditional allowable stress principle which is mainly based on experiences, the ULS assessment focuses on explicitly evaluating the structural safety margin and thus enables a consistent...

Digital twins of the mooring line tension for floating offshore wind turbines to improve monitoring, lifespan, and safety

The number of installed floating offshore wind turbines (FOWTs) has doubled since 2017, quadrupling the total installed capacity, and is expected to increase significantly over the next decade. Consequently, there is a growing consideration towards the main challenges for FOWT projects: monitoring the system’s integrity, extending the...

Digital Twin of the Mooring Line Tension for Floating Offshore Wind Turbines

The number of installed Floating Offshore Wind Turbines (FOWTs) has doubled since 2017, quadrupling the total installed capacity, and is expected to increase significantly over the next decade. Consequently, there is a growing consideration towards the main challenges for FOWT projects: monitoring the system's integrity, extending the...

Ship diesel engine performance modelling with combined physical and machine learning approach

Condition Based Maintenance on diesel engines can help to reduce maintenance load and better plan maintenance activities in order to support ships with reduced or no crew. Diesel engine performance models are required to predict engine performance parameters in order to identify emerging failures early on and to establish trends in...