Computationally Aware Surrogate Models for the Hydrodynamic Response Characterization of Floating Spar-Type Offshore Wind Turbine

Due to increasing environmental concerns and global energy demand, the development of Floating Offshore Wind Turbines (FOWTs) is on the rise. FOWTs offer a promising solution to expand wind farm deployment into deeper waters with abundant wind resources. However, their harsh operating conditions and lower maturity level compared to fixed...

Floating offshore wind turbine mooring line sections health status nowcasting: From supervised shallow to weakly supervised deep learning

The global installed capacity of floating offshore wind turbines is projected to increase by at least 100 times over the next decades. Station-keeping of floating offshore renewable energy devices is achieved through the use of mooring systems. Mooring systems are exposed to a variety of environmental and operational conditions that cause...

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...

Surrogate models to unlock the optimal design of stiffened panels accounting for ultimate strength reduction due to welding residual stress

In this paper, for the first time, a three-step approach for the optimal design of stiffened panels accounting for the ultimate limit state due to welding residual stress is developed. First, authors rely on state-of-the-art analytical approaches coupled with recently data-driven nonlinear finite element methods surrogates characterized by...

Machine learning-based identification of vulnerability factors for masonry buildings in aggregate: The historicalcentre of casentino hit by the 2009 l'aquila earthquake

Seismic events in Italy and worldwide have highlighted the high vulnerability of unreinforced masonry (URM) structures in small historical centres. A key feature of these settlements is to be mostly composed of buildings in aggregate, i.e., interconnected by a more or less structurally effective connection. The seismic assessment of such...

Physically plausible propeller noise prediction via recursive corrections leveraging prior knowledge and experimental data

For propeller-driven vessels, cavitation is the most dominant noise source producing both structure-borne and radiated noise impacting wildlife, passenger comfort, and underwater warfare. Physically plausible and accurate predictions of the underwater radiated noise at design stage, i.e., for previously untested geometries and operating...

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...

Artificial Intelligence Based Short-Term Motions Forecasting for Autonomous Marine Vehicles Control

The development of fast and accurate intelligent vessel control systems is a necessary milestone on the path toward operating autonomous marine vehicles effectively in harsh environments and complex mission settings. One of the main problems of existing control systems is the disparity between the forecasted behaviour and how the vessel actually...

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...

Computational prediction of underwater radiated noise of cavitating marine propellers: On the accuracy of semi-empirical models

The potential impact of underwater radiated noise from maritime operations on marine fauna has become an important issue. The most dominant noise source on a propeller-driven vessel is propeller cavitation, producing both structure-borne and radiated noise, with a broad spectrum that covers a wide range of frequencies. To ensure acceptable...

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...

Hybrid Modelling Approach of a Four-stroke Medium Speed Diesel Engine

Diesel engines will remain a fundamental component of propulsion systems due to their maturity, reliability, and power density. Building Digital Twins of the propulsion system is one feasible solution to pursue the optimal propulsions system operation, estimating system states and efficiency. This work will investigate a modelling approach that...

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...

Physical, data-driven and hybrid approaches to model engine exhaust gas temperatures in operational conditions

Fast diesel engine models for real-time prediction in dynamic conditions are required to predict engine performance parameters, to identify emerging failures early on and to establish trends in performance reduction. In order to address these issues, two main alternatives exist: one is to exploit the physical knowledge of the problem, 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...