基于HHM-RFRM的船舶航行风险评估方法研究
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摘要
船舶航行风险是由各种风险因素交互作用产生。综合HHM-RFRM理论,构建船舶航行多维风险情景危险度测度模型,以风险因素耦合视角探讨船舶航行风险管理问题。在船舶航行多维风险情景危险度测度模型中结合贝叶斯定理,对船舶航行风险情景进行了定性与定量化过滤、评级。最后以大连港某从事商务活动的货船为例,验证了所提出方法的可行性。传统的风险评估方法只能评估单个风险因素对系统的影响,此评估方法克服了这一局限性,为船舶航行风险管理提供新的视角。
With the development of the shipping market,domestic and international shipping accidents occur frequently which make the ship navigation risk management issues become increasingly prominent.The effective evaluation and comprehensive risk identification of the ship navigation can provide the scientific basis for the dynamic management and safe dispatching for the maritime departments and ship enterprises,and guarantee the safety of people's lives and property in the process of ship navigation.Previous scholars' researches are based on the construction of single risk factor index system for risk management focusing on the impact of individual risk factors on the overall systemic risk.However,the risk of ship navigation is generated by the interaction of various risk factors,and a single risk model can't fully explain the source of the risk.In view of this background,a multidimensional risk measurement model based on the ideas and methodologies of Hierarchical Holographic Modeling(HHM)and Risk Filtering,Ranking and Management Framework(RFRM)is built.In this paper,the method of HHM-RFRM is improved from the following three aspects:First,in terms of scenario recognition,the concept of multidimensional risk factors is presented,supposing that Vnmrepresents a risk scenario consisting of mrisk factors and is numberedn.Vnm is called the m-dimensional risk scenario,and Nkrepresents the risk factor in the risk scenario Vnm.Second,in terms of risk qualitative assessment,the characteristics of each risk factor are qualitatively analyzed to help the decision maker to quantify the risk factors and overall risk of navigation from its ability to defeat the ship's navigational system,aiming at the complex characteristic of ship navigation risk.According to the theory of Matalas and Fiering,the characteristics of each risk factor can be further evaluated to provide the reference standard for quantitative assessment by reflecting its ability to defeat the system protection ability including three defensive features of resilience,robustness,and redundancy.Third,in terms of quantitative risk assessment,the degree of the risk scenario is quantitatively calculated from two dimensions of probability and consequence,introducing the multidimensional risk measurement model combined with Bayesian theorem.The assessment of multiple risk factors including environment,software,hardware,and management is integrated.The risk source of the interaction of the key risk factors can be reflected.In this paper,the HHM framework of ship navigation risk is constructed based on the analysis of the risk factors of ship navigation.Afterwards,the concept of multidimensional risk scenario is proposed,and each risk scenario is identified by HHM.Further,the RFRM method is combined with the Bayesian theorem to filter and grade the ship navigation risk situation qualitatively and quantitatively.Finally,the feasibility of the proposed method is verified by taking the cargo ship dealing with the commercial activities in Dalian Port as an example.A new perspective for the ship navigation risk management is provided in this paper.
With the development of the shipping market,domestic and international shipping accidents occur frequently which make the ship navigation risk management issues become increasingly prominent.The effective evaluation and comprehensive risk identification of the ship navigation can provide the scientific basis for the dynamic management and safe dispatching for the maritime departments and ship enterprises,and guarantee the safety of people's lives and property in the process of ship navigation.Previous scholars' researches are based on the construction of single risk factor index system for risk management focusing on the impact of individual risk factors on the overall systemic risk.However,the risk of ship navigation is generated by the interaction of various risk factors,and a single risk model can't fully explain the source of the risk.In view of this background,a multidimensional risk measurement model based on the ideas and methodologies of Hierarchical Holographic Modeling(HHM)and Risk Filtering,Ranking and Management Framework(RFRM)is built.In this paper,the method of HHM-RFRM is improved from the following three aspects:First,in terms of scenario recognition,the concept of multidimensional risk factors is presented,supposing that Vnmrepresents a risk scenario consisting of mrisk factors and is numberedn.Vnm is called the m-dimensional risk scenario,and Nkrepresents the risk factor in the risk scenario Vnm.Second,in terms of risk qualitative assessment,the characteristics of each risk factor are qualitatively analyzed to help the decision maker to quantify the risk factors and overall risk of navigation from its ability to defeat the ship's navigational system,aiming at the complex characteristic of ship navigation risk.According to the theory of Matalas and Fiering,the characteristics of each risk factor can be further evaluated to provide the reference standard for quantitative assessment by reflecting its ability to defeat the system protection ability including three defensive features of resilience,robustness,and redundancy.Third,in terms of quantitative risk assessment,the degree of the risk scenario is quantitatively calculated from two dimensions of probability and consequence,introducing the multidimensional risk measurement model combined with Bayesian theorem.The assessment of multiple risk factors including environment,software,hardware,and management is integrated.The risk source of the interaction of the key risk factors can be reflected.In this paper,the HHM framework of ship navigation risk is constructed based on the analysis of the risk factors of ship navigation.Afterwards,the concept of multidimensional risk scenario is proposed,and each risk scenario is identified by HHM.Further,the RFRM method is combined with the Bayesian theorem to filter and grade the ship navigation risk situation qualitatively and quantitatively.Finally,the feasibility of the proposed method is verified by taking the cargo ship dealing with the commercial activities in Dalian Port as an example.A new perspective for the ship navigation risk management is provided in this paper.
引文
[1]Kim H,Haugen S,Utne I B.Assessment of accident theories for major accidents focusing on the MV SEWOLdisaster:Similarities,differences,and discussion for a combined approach[J].Safety Science,2016,82(2):410-420.
[2]Kim T E,Nazir S,Overgard K I.A STAMP-based causal analysis of the Korean Sewol ferry accident[J].Safety Science,2016,83(3):93-101.
[3]谢新连,桑惠云,杨秋平,等.中国进口原油运输船队规划案例[J].系统工程理论与实践,2013,06:1543-1549.
[4]刘铁民.低概率重大事故风险与定量风险评价[J].安全与环境学报,2004,4(2):89-91.
[5]许金华,孙德强,范英,等.基于FTA仿真的三高气田事故风险概率[J].系统工程理论与实践,2012,32(4):877-884.
[6]姜艳萍,樊治平,苏明明.应急决策方案的动态调整方法研究[J].中国管理科学,2011,19(5):104-108.
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[8]Heinrich H W.Industrial accident prevention:A scientific approach[M].New York:McGraw-Hill Book,1959.
[9]Gibson J J,The contribution of experimental psychology to the formulation of the problem of safety:A brief for basic research[A].Behavioral approaches to accident research[C].New York:Association for the Aid of Crippled Children,1961:77-89.
[10]Haddon W J.Energy damage and the 10countermeasure strategies[J].Trauma,1973,13:321-331.
[11]Huntington H P,Daniel R,Hartsig A,et al.Vessels,risks,and rules:Planning for safe shipping in Bering Strait[J].Marine Policy,2014,1(1):119-127.
[12]Goerlandt F,Montewka J.A framework for risk analysis of maritime transportation systems:A case study for oil spill from tankers in a ship-ship collision[J].Safety Science,2015,76:42-66.
[13]Balmat J F,Lafont F,Maifret R,et al.Maritime risk assessment(MARISA),a fuzzy approach to define an individual ship risk factor[J].Ocean Engineering,2009,36(15-16):1278-1286.
[14]Montewka J,Ehlers S,Goerlandt F,et al.A framework for risk assessment for maritime transportation systems-A case study for open sea collisions involving RoPax vessels[J].Reliability Engineering&System Safety,2014,124(1):142-157.
[15]Berle O,Asbjrnslett B E,Rice J B.Formal vulnerability assessment of a maritime transportation system[J].Reliability Engineering&System Safety,2011,96(6):696-705.
[16]刘大刚,郑中义,吴兆麟.大风浪中航行船舶风险体系分析[J].交通运输工程学报,2004,4(2):100-102.
[17]张敏,张玲.基于失效情景的应急设施选址评估指标体系与模型[J].中国管理科学,2016,24(11):129-136.
[18]张明红,佘廉,耿波.基于情景的结构化突发事件相似度研究[J].中国管理科学,2017,25(1):151-159.
[19]Kaplan S,Haimes Y Y,Garrick B J.Fitting hierarchical holographic modeling into the theory of scenario structuring and a resulting refinement of the quantitative definition of risk[J].Risk Analysis,2001,21(5),807-815.
[20]Haimes Y Y.风险建模、评估和管理[M].西安:西安交通大学出版社,2007.
[21]Matalas N C,Fiering M B.Water-resource systems planning[C]//National Academy of Sciences,Study in Geophsics:climate,climatic change and water supply.Washington DC:National Academy Press,1977:99-110.
[22]樊运晓,卢明,李智,等.基于危险属性的事故致因理论综述[J].中国安全科学学报,2014,24(11):139-145.
[23]陈天平,郑连清,张新源.HHM在信息系统风险识别中的应用[J].中国安全生产科学技术,2008,06:98-100.
[24]中华人民共和国海事局.内河船舶安全检查指南[M].大连:大连海事大学出版社,2009.
[2]Kim T E,Nazir S,Overgard K I.A STAMP-based causal analysis of the Korean Sewol ferry accident[J].Safety Science,2016,83(3):93-101.
[3]谢新连,桑惠云,杨秋平,等.中国进口原油运输船队规划案例[J].系统工程理论与实践,2013,06:1543-1549.
[4]刘铁民.低概率重大事故风险与定量风险评价[J].安全与环境学报,2004,4(2):89-91.
[5]许金华,孙德强,范英,等.基于FTA仿真的三高气田事故风险概率[J].系统工程理论与实践,2012,32(4):877-884.
[6]姜艳萍,樊治平,苏明明.应急决策方案的动态调整方法研究[J].中国管理科学,2011,19(5):104-108.
[7]Heinrich H W.Industrial accident prevention.New York:McGraw-Hill,1931.
[8]Heinrich H W.Industrial accident prevention:A scientific approach[M].New York:McGraw-Hill Book,1959.
[9]Gibson J J,The contribution of experimental psychology to the formulation of the problem of safety:A brief for basic research[A].Behavioral approaches to accident research[C].New York:Association for the Aid of Crippled Children,1961:77-89.
[10]Haddon W J.Energy damage and the 10countermeasure strategies[J].Trauma,1973,13:321-331.
[11]Huntington H P,Daniel R,Hartsig A,et al.Vessels,risks,and rules:Planning for safe shipping in Bering Strait[J].Marine Policy,2014,1(1):119-127.
[12]Goerlandt F,Montewka J.A framework for risk analysis of maritime transportation systems:A case study for oil spill from tankers in a ship-ship collision[J].Safety Science,2015,76:42-66.
[13]Balmat J F,Lafont F,Maifret R,et al.Maritime risk assessment(MARISA),a fuzzy approach to define an individual ship risk factor[J].Ocean Engineering,2009,36(15-16):1278-1286.
[14]Montewka J,Ehlers S,Goerlandt F,et al.A framework for risk assessment for maritime transportation systems-A case study for open sea collisions involving RoPax vessels[J].Reliability Engineering&System Safety,2014,124(1):142-157.
[15]Berle O,Asbjrnslett B E,Rice J B.Formal vulnerability assessment of a maritime transportation system[J].Reliability Engineering&System Safety,2011,96(6):696-705.
[16]刘大刚,郑中义,吴兆麟.大风浪中航行船舶风险体系分析[J].交通运输工程学报,2004,4(2):100-102.
[17]张敏,张玲.基于失效情景的应急设施选址评估指标体系与模型[J].中国管理科学,2016,24(11):129-136.
[18]张明红,佘廉,耿波.基于情景的结构化突发事件相似度研究[J].中国管理科学,2017,25(1):151-159.
[19]Kaplan S,Haimes Y Y,Garrick B J.Fitting hierarchical holographic modeling into the theory of scenario structuring and a resulting refinement of the quantitative definition of risk[J].Risk Analysis,2001,21(5),807-815.
[20]Haimes Y Y.风险建模、评估和管理[M].西安:西安交通大学出版社,2007.
[21]Matalas N C,Fiering M B.Water-resource systems planning[C]//National Academy of Sciences,Study in Geophsics:climate,climatic change and water supply.Washington DC:National Academy Press,1977:99-110.
[22]樊运晓,卢明,李智,等.基于危险属性的事故致因理论综述[J].中国安全科学学报,2014,24(11):139-145.
[23]陈天平,郑连清,张新源.HHM在信息系统风险识别中的应用[J].中国安全生产科学技术,2008,06:98-100.
[24]中华人民共和国海事局.内河船舶安全检查指南[M].大连:大连海事大学出版社,2009.
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