Digital Twins have much attention in the shipping industry, attempting to support all phases of a vessel’s life cycle. With several tools appearing in Digital Twin software suites, high-quality manoeuvring and performance prediction remain cornerstones. Propulsion efficiency is in focus while in service. Simulator-based training is in focus to ensure safety of manoeuvring in confined waters and harbours. Prediction of ships’ velocity and turn rate are essential for correct look and feel during training, but phenomena like dynamic inflow to propellers, bank and shallow water effects limit simulators’ accuracy, and master mariners often comment that simulations could be in better agreement with actual behaviours of their vessel. This paper focuses on digital twin enhancements to better match reality. Using data logged during in-service operation, we first consider a system identification perspective, employing a first-principles model structure. Showing that a complete firstprinciples model is not identifiable under the excitation met in service, we employ a Recurrent Neural Network to predict deviations between measured velocities and the model output. The outcome is a hybrid of a first-principles model with a machine learning generic approximator add-on. The paper demonstrates significant improvements in prediction accuracy of both in-harbour manoeuvring and shallow water passage conditions.
The increasing focus on energy efficient operation of vessels can be seen in both legislation and research. This paper focuses attention on the human factor influencing energy efficiency and explores the conditions for improving energy efficiency in working vessels taking situational awareness (SA) theory into consideration.
The study builds on two cases: an offshore supply vessel for the oil & gas industry and an installation vessel for wind turbines. The study used qualitative methods based on 49 interviews with seafarers and onshore employees from the vessels and shipping companies.
The study has identified that the energy efficiency of a ship is mainly influenced by legislation and the praxis formed on board. The results showed that the theory on SA is very a useful tool in explaining the factors affecting the energy efficiency of a vessel and the praxis.
The study has shown that obtaining a more energy efficient operation is complex and depends not only on the officer on board the ship. The improvement of energy efficiency is possible, but there is a need to understand the complexity of the issue and to involve both the crew and the entire system around the ship, and to obtain a shared perspective of energy efficient operation. Furthermore, in order to improve energy efficiency in shipping companies, there is a need to support the seafarers in gaining more skills for operating the ship more energy efficiently; to do this the right way there is a need to create an understanding of the system by the authorities, ship owners and charterers.
The widespread use of software-intensive cyber systems in critical infrastructures such as ships (CyberShips) has brought huge benefits, yet it has also opened new avenues for cyber attacks to potentially disrupt operations. Cyber risk assessment plays a vital role in identifying cyber threats and vulnerabilities that can be exploited to compromise cyber systems. Understanding the nature of cyber threats and their potential risks and impact is essential to improve the security and resilience of cyber systems, and to build systems that are secure by design and better prepared to detect and mitigate cyber attacks. A number of methodologies have been proposed to carry out these analyses. This paper evaluates and compares the application of three risk assessment methodologies: system theoretic process analysis (STPA-Sec), STRIDE and CORAS for identifying threats and vulnerabilities in a CyberShip system. We specifically selected these three methodologies because they identify threats not only at the component level, but also threats or hazards caused due to the interaction between components, resulting in sets of threats identified with each methodology and relevant differences. Moreover, STPA-Sec, which is a variant of the STPA, is widely used for safety and security analysis of cyber physical systems (CPS); CORAS offers a framework to perform cyber risk assessment in a top-down approach that aligns with STPA-Sec; and STRIDE (Spoofing, Tampering, Repudiation,Information disclosure, Denial of Service, Elevation of Privilege) considers threat at the component level as well as during the interaction that is similar to STPA-Sec. As a result of this analysis, this paper highlights the pros and cons of these methodologies, illustrates areas of special applicability, and suggests that their complementary use as threats identified through STRIDE can be used as an input to CORAS and STPA-Sec to make these methods more structured.
Ship collision and grounding events constitute a major hazard for ship operations, and ship collision risk analyses have to be carried out for installations such as offshore structures for extraction of hydrocarbons, offshore wind farms, and bridges spanning waterways. This book provides assessment procedures for ship collision and grounding analysis and includes probabilistic methods for collision and grounding risk assessment, estimation of the energy released during collisions, and prediction of the extent of damage on the involved structures.
The main feature of the book is that it encapsulates reliable and fast analysis methods for collision and grounding assessment and the methods have been extensively validated with experimental and numerical results. In addition, all the described analysis methods include realistic calculation examples so as to provide confidence in their use to eventually conduct the required assessment according to the rules and design codes. The book is intended as a handbook for professionals and researchers in the industry dealing with design and analysis of ships and offshore structures. The book can also be used as a text book for postgraduate courses orientated towards the design and analysis of ship and offshore structures.
Closed-form expressions to estimate the energy absorption and damage extent for severe ship collision damages were initially developed in 1999 [1, 2], and further validated with experimental data in 2016 [3]. To gain further confidence for applications within design using the proposed analytical procedure, it is evident that more detailed and comprehensive comparisons and validations with experiments and numerical simulations are necessary. The purpose of the present paper is to use the analytical approach and finite element analyses to study in depth model-scale and full-scale collision tests so that to further quantify key calculation parameters and to verify the capability and accuracy of the proposed analytical method. In total 18 experimental tests and one full-scale collision accident are evaluated. The 18 experimental energy absorption-penetration and collision force-penetration curves, and the associated finite element simulations, are compared with results obtained from the analytical calculations. It can be concluded that the analytical method gives consistently good agreement with all experiments analysed here. Finally, an application of the analytical method is demonstrated by an example where speed restrictions are determined in a port to avoid LNG cargo leakage in an event of an LNG carrier being struck by another ship.
The severe slugging flow is always challenging in oil & gas production, especially for the current offshore based production. The slugging flow can cause a lot of potential problems, such as those relevant to production safety, fatigue as well as capability. As one typical phenomenon in multi-phase flow dynamics, the slug can be avoided or eliminated by proper facility design and control of operational conditions. Based on a testing facility which can emulate a pipeline-riser or a gas-lifted production well in a scaled-down manner, this paper experimentally studies the correlations of key operational parameters with severe slugging flows. These correlations are reflected through an obtained stable surface in the parameter space, which is a natural extension of the bifurcation plot. The maximal production opportunity without compromising the stability is also studied. Relevant studies have already showed that the capability, performance and efficiency of anti-slug control can be dramatically improved if these stable surfaces can be experimentally determined beforehand.
In this paper we extend the state-of-the-art stochastic programming models for the Maritime Fleet Renewal Problem (MFRP) to explicitly limit the risk of insolvency due to negative cash flows when making maritime shipping investments. This is achieved by modeling the payment of ships in a number of periodical installments rather than in a lump sum paid upfront, representing more closely the actual cash flows for a shipping company. Based on this, we propose two alternative risk control measures, where the first imposes that the cash flow in each time period is always higher than a desired threshold, while the second limits the Conditional Value-at-Risk. We test the two models on realistic test instances based on data from a shipping company. The computational study demonstrates how the two models can be used to assess the trade-offs between risk of insolvency and expected profits in the MFRP.
Background: Seafarers are at an increased risk of developing cardiovascular diseases (CVDs), potentially due to a stressful working environment and behavioral risk factors. To develop better prevention strategies, it is important to elucidate the extent of this risk. Therefore, we conducted a systematic literature review on CVD in seafarers. Method: We conducted systematic searches in five databases. All studies investigating CVDs among occupational seafarers, published in articles or conference papers, were eligible for inclusion. The identified records were screened and reviewed by two independent researchers, who also evaluated the methodological quality of the included studies. Results: Three thousand nine hundred and seventeen records qualified for screening, and 55 were eligible for inclusion. Most of the studies were observational, including cohort, frequency, incidence or prevalence studies, and review of case records. Around half were assessed at risk of biased findings. Participants in the studies were primarily from North America or the European continent and work onboard transportation vessels. Many studies investigated CVDs as a cause of death, focusing on conditions such as CVD, ischemic heart disease, and myocardial infarction. Frequency of CVD conditions varied but indicate that seafarers face a greater risk compared to the reference populations or control groups. Environmental factors were mainly investigated as risk factors. Conclusion: Our results indicate a higher risk of CVDs among seafarers compared to reference or control groups. However, due to the variable quality of the evidence, well-designed studies are needed to establish the causes of cardiovascular mortality and morbidity in seafarers and to investigate behavioral aspects of cardiovascular risk.
An efficient extreme ship response prediction approach in a given short-term sea state is devised in the paper. The present approach employs an active learning reliability method, named as the active learning Kriging + Markov Chain Monte Carlo (AK-MCMC), to predict the exceedance probability of extreme ship response. Apart from that, the Karhunen-Loève (KL) expansion of stochastic ocean wave is adopted to reduce the number of stochastic variables and to expedite the AK-MCMC computations. Weakly and strongly nonlinear vertical bending moments (VBMs) in a container ship, where the former only accounts for the nonlinearities in the hydrostatic and Froude-Krylov forces, while the latter also accounts for the nonlinearities in the radiation and diffraction forces together with slamming and hydroelastic effects, are studied to demonstrate the efficiency and accuracy of the present approach. The nonlinear strip theory is used for time domain VBM computations. Validation and comparison against the crude Monte Carlo Simulation (MCS) and the First Order Reliability Method (FORM) are made. The present approach demonstrates superior efficiency and accuracy compared to FORM. Moreover, methods for estimating the Mean-out-crossing rate of VBM based on reliability indices derived from the present approach are proposed and are validated against long-time numerical simulations.
This follow up paper concerns relational contracts in the maritime industry from a legal, game theoretical, and strategic perspective. The paper discusses the purpose of a relational contract, the specific legal characteristics in a relational contract, and draw up economic explanations of the relations among the clauses in relational contract. Strategy and game theory are used to explain the output of negotiations and explain how to behave if to obtain joint utility in a contractual relationship in the maritime industry.