Study on lockage safety of LNG-fueled ships based on FSA

Lv, Pengfei; Zhuang, Yuan; Deng, Jian; Su, Wei

doi:10.1371/journal.pone.0174448

Cited by 10 publications

(3 citation statements)

References 12 publications

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“…Jeong et al investigated the potential risk of LNG fueling and, for two typical LNG-fueled ships, evaluated the extent of indicative safety exclusion zones for the LNG fueling station, using the integrated quantitative risk assessment software [15]. From the perspective of risk potential in the LNG fuel, the application of safety assessment [16] in the shipbuilding industry originated in the late 1980s and began to change the traditional post-accident ship accident research model with reference to some pre-control methods used in the nuclear industry [17]. The emergence of ship damage has prompted the shipping industry to become more aware of the importance of research and application of ship safety assessments.…”

Section: Literature Reviewmentioning

confidence: 99%

Dynamics Simulation for Process Risk Evolution on the Bunker Operation of an LNG-fueled Vessel with Catastrophe Mathematical Models

Xuan

et al. 2019

JMSE

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Liquefied nature gas (LNG) is a green energy. LNG-fueled vessels are extremely complex engineering systems. In view of the inherent hazardous properties of LNG fuel, LNG fueling is not only an important part, but it is also full of high risks in the operation of LNG-fueled vessels (LNGFVs). Therefore, it is necessary to study the risk factors, and the intrinsic relationship among them between the LNG and the vessel, and to simulate the system dynamics in the process of LNGFV operation. During the process of fueling of LNGFV, at every moment the vessel interacts with the energy and information of the surrounding environment. First, the impact of the three interactions of the fueling operation process, ship factors, and environmental factors were analyzed on the risk of fueling operation, and a complete node system was proposed as to the complex system dynamics mode. Second, by analyzing the boundary conditions of the system, the relationship of factors was established via the tools of system dynamics (SD). Based on the catastrophe theory (CA), the dynamics model for the fueling of LNG is set up to study the system’s risk mutation phenomenon. Third, combined with the simulation results of the case analysis, the risk evolution mode of the LNGFV during the fueling process was obtained, and constructive opinions were put forward for improving the safe fueling of the LNGFV. Application examples show that formal description of risk emergence and transition is a prerequisite for the quantitative analysis of the risk evolution mode. In order to prevent accidents, the coupling synchronization of risk emergence should be weakened, and meanwhile risk control should be implemented.

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Section: Literature Reviewmentioning

confidence: 99%

Dynamics Simulation for Process Risk Evolution on the Bunker Operation of an LNG-fueled Vessel with Catastrophe Mathematical Models

Xuan

et al. 2019

JMSE

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“…Furthermore, some ports have built or plan to build two or more LNG berths to accommodate more LNG ships. On the other hand, the navigation safety of LNG ships, along with that of other ships including those carrying crude oil, LPG, and various chemicals, are among the top concerns of the Maritime Safety Administrations (MSA) because these materials are highly hazardous due to their flammable, highly polluting, or explosive properties [7,8]. In particular, LNG ships are typically big and carry large volumes of dangerous gas.…”

Section: Introductionmentioning

confidence: 99%

A Simulation Model of the Influence of LNG Ships on Traffic Efficiency at Tianjin Port

Li,

Tian,

Meng

et al. 2024

JMSE

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Tianjin Port is one of the largest ports in northern China. Liquefied natural gas (LNG) ships are one of the most special ship types, and their navigation safety and efficiency has become the top concern of the port authority. There are two LNG berths at the port, and the annual arrivals, which reach more than 100, increasingly influence other ships. The objective of this study is to evaluate the influence of LNG ships on other ships in a quantitative way. To realize this, a simulation system is established by analyzing the factors affecting waterway transit efficiency. The software Arena is adopted to simulate the arrival and departure of the ships at Tianjin Port and to simulate how the average waiting time and the average queue length in the port area are affected by the LNG ships. A traffic system for the two ship types is formulated, and the mutual influences between them are expressed by the inbound and outbound waterway states. The simulations are performed under both existing and new ship traffic regulations. Cases in which the number of LNG ships gradually increases are simulated comprehensively. The simulation model as well as the results can serve as a good reference for the local port authority in the formulation of traffic regulations.

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“…The consequence was that the difficulty and gradient instability of training would increase, and the conclusion of the diversified training data with the big data of sports medicine. Lv P [17], a Chinese scholar, has proposed a deep network algorithm, which can realize hundreds of levels of training structure, removes the whole connection level and integrates all functions into one module, so that it can achieve faster data. Speed of transmission; American scholar [18]- [20] has constructed ''Sports Medical Data Record'' based on convolution neural network, which can help improve the theory of clinical diagnosis of sports.…”

Section: Introductionmentioning

confidence: 99%

Research and Analysis of Sport Medical Data Processing Algorithms Based on Deep Learning and Internet of Things

Pang

2019

IEEE Access

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With the development of computer and information technology, more and more data and image information are generated in medical field. Sports medicine, as an important branch of medical cause, is responsible for ensuring national sports safety and rehabilitation after injury. How to use a large number of sports medical data and cases to accurately analyze and mine useful data and information has become an important research direction of sports medical data processing and mining. This paper will focus on the information mining and analysis of large sports medical data, focusing on the loss of training mode and the accuracy of convolution algorithm. In order to achieve effective prediction and risk assessment of sports medicine-related diseases, this paper starts with the improved convolutional neural network deep learning algorithm, and adopts the resampling algorithm with self-adjusting function, supplemented by tensor convolution self-coding algorithm. Ural network model assists multi-dimensional data analysis of sports medicine. Finally, in order to build an intelligent medical data platform for sports medicine, this paper innovatively proposes a cloud-based hardware-in-the-loop simulation model. Experiments show that this method provides reference and technical support for the realization of a real cloud-based fusion system. INDEX TERMS Sport medicine, improved deep learning algorithm, sport medicine big data, tensor convolution self-coding deep learning algorithm, cloud-end fusion hardware-in-the-loop simulation model.

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Study on lockage safety of LNG-fueled ships based on FSA

Cited by 10 publications

References 12 publications

Dynamics Simulation for Process Risk Evolution on the Bunker Operation of an LNG-fueled Vessel with Catastrophe Mathematical Models

Dynamics Simulation for Process Risk Evolution on the Bunker Operation of an LNG-fueled Vessel with Catastrophe Mathematical Models

A Simulation Model of the Influence of LNG Ships on Traffic Efficiency at Tianjin Port

Research and Analysis of Sport Medical Data Processing Algorithms Based on Deep Learning and Internet of Things

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