Analysis of the operational energy efficiency for inland river ships

Sun, Xiaomin; Yan, Xinping; Wu, Bing; Song, Xin

doi:10.1016/j.trd.2013.03.002

Cited by 73 publications

(37 citation statements)

References 3 publications

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“…Some scholars discussed the influence of environmental factors from the perspective of ship energy efficiency optimization. Sun et al calculated and analyzed the EEOI (Energy Efficiency Operation Index) of an inland container ship under both calm water and real navigation conditions; the results demonstrate that the environmental factors and sailing speed have a great impact on the fuel consumption of inland ships [26]. Wang et al analyzed the relationship between the sailing speed, navigation environment, and ship fuel consumption in the Yangtze River based on a ship's energy efficiency model.…”

Section: Literature Reviewmentioning

confidence: 99%

Effect of Seasonal Flow Field on Inland Ship Emission Assessment: A Case Study of Ferry

et al. 2020

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The purpose of this paper is to evaluate the effect of the seasonal flow field on inland ship emissions and to improve calculation accuracy. Firstly, the flow field model is built through numerical simulation to correct the sailing speed of the ship from the Automatic Identification System (AIS) information in real-time. Then, an optimal emission estimation model for inland ships considering flow field factors is proposed. Finally, the effectiveness of the optimization model is demonstrated by a case study, and the influence of the seasonal flow field on emission calculation is analyzed. It indicates that the calculation results of the model considering the influence of the flow field are more accurate. Without considering the flow field, the results of emission calculations are often underestimated, especially in summer, which shows the importance of incorporating the flow field factors into the calculation of inland ship emissions.

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Section: Literature Reviewmentioning

confidence: 99%

Effect of Seasonal Flow Field on Inland Ship Emission Assessment: A Case Study of Ferry

et al. 2020

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“…Literature sources Ship type Weng and Yang (2015), Heij and Knapp (2012), Cariou, Mejia, andWolff (2008), Balmat et al (2011), Li, Yin, and Fan (2014), Hull type Balmat et al (2009) Ship age , Balmat et al (2009), Zhang et al (2013), Li, Yin, and Fan (2014), Wu et al (2015) Ship flag or registry , Balmat et al (2009), Li, Yin, and Fan (2014) Gross tonnage Zhang et al (2013), , Balmat et al (2009), Hansen, Jepsen, and Hermansen (2012), Li, Yin, and Fan (2014), Knapp, Bijwaard, and Heij (2011) Ship speed Balmat et al ( 2011), Talley, Yip, and Jin (2012) Ship defects Hänninen and Kujala (2014), Knapp, Bijwaard, and Heij (2011) Loading Guedes Soares and Teixeira (2001), Akyuz and Celik (2014) Crew Akhtar and Utne (2014), Mullai and Paulsson (2011), Yang et al (2013), Hänninen and Kujala (2012), Weng and Yang (2015), Prabhu Gaonkar, Xie, and Fu (2013) Location Weng and Yang (2015), Mullai and Paulsson (2011), Sun et al (2013) Rain, fog Mullai and Paulsson (2011), Balmat et al (2009), Weng and Yang (2015) Visibility Balmat et al (2009), Zhang et al (2013) Wind Zhang et al (2013), Heij et al (2013) Season , Zhang et al (2013),…”

Section: Variablementioning

confidence: 99%

Bayesian network modelling and analysis of accident severity in waterborne transportation: A case study in China

Wang

Yang

2018

Reliability Engineering & System Safety

149

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The rapid development of the shipping industry requires the use of large vessels carrying highvolume cargoes. Accidents incurred by these vessels can lead to a heavy loss of life and damage to the environment and property. As a leading country in international trade, China has developed its waterway transport systems, including inland waterways and coastal shipping, in the past decades. A few catastrophic shipping accidents have occurred during this period. This paper aims to develop a new risk analysis approach based on Bayesian networks (BNs) to enable the analysis of accident severity in waterborne transportation. Although the risk data are derived from accidents that occurred in China's waters, the risk factors influencing accident severity and the risk modelling methodology are generic and capable of generating useful insights on waterway risk analysis in a broad sense. To develop the BN-based risk model, waterway accident data are first collected from all accident investigation reports by China's Maritime Safety Administration (MSA) from 1979 to 2015. Based on the derived quantitative data, we identify the factors related to the severity of waterway accidents and use them as nodes of the risk model. Second, based on a receiver operating characteristic (ROC) curve, an augmented naïve BN (ABN) model is selected through a comparative study with a naïve BN (NBN) model to analyse the key risk factors influencing waterway accident severity. The results show that the key factors influencing waterway safety include the type and location of the accident and the type and age of the ship. Moreover, a novel scenario analysis is conducted to predict accident severity in various situations by combining different states (e.g., high risk) of the key factors to generate useful insights for accident prevention. More specifically, the findings can aid transport authorities, ship owners and other stakeholders in improving waterborne transportation safety under uncertainty.

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“…Researchers [8]- [11] in various countries have done significant research on reducing the emission of CO2. Through the calculation and analysis, Sun [12] et al found that the navigation environment can significantly affect the energy efficiency of inland ships. Chang [13] found that the best deceleration is a dynamic process and mainly depends on charter rates and fuel prices.…”

Section: Introductionmentioning

confidence: 99%

A New Numerical Modelling Method for System Energy Efficiency Calculation

Song¹,

Yuan²,

Zhang³

et al. 2018

ElAEE

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This paper focuses on greenhouse gas emissions of new energy ships by investigating energy efficiency of the ships using solar photovoltaic system. According to the operating characteristics of the diesel generator set, a novel energy efficiency model of the generator diesel engine was established, where the solar photovoltaic system was included to analyze the model energy efficiency. In order to evaluate the feasibility and availability of the proposed model, experimental data acquired from the solar photovoltaic system testing, in a real-world large ro-ro ship, was collected and compared with the model output. The fuel consumption with and without the use of the solar photovoltaic system was used to analyze the ship's energy efficiency. The comparison results demonstrate that the proposed energy efficiency model for marine generator diesel engines with solar photovoltaic system is able to represent the ship's efficiency level, with an estimation error of 3.43 %.

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Analysis of the operational energy efficiency for inland river ships

Cited by 73 publications

References 3 publications

Effect of Seasonal Flow Field on Inland Ship Emission Assessment: A Case Study of Ferry

Effect of Seasonal Flow Field on Inland Ship Emission Assessment: A Case Study of Ferry

Bayesian network modelling and analysis of accident severity in waterborne transportation: A case study in China

A New Numerical Modelling Method for System Energy Efficiency Calculation

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