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Formulation of a Model for Ship Transit Risk
... FMECA is advance FMEA where critically of failure is quantitatively account for reliability and maintainability of the system. Analysis of FMCEA should provide answer to system description, possible failure and mode of failure, cause of failure effect of failure, severity of consequence and reliability data, specify assessment method for detection status and mitigation of unwanted effects towards reduction and elimination ((Kite 1996, Ahvejarhi, 2001& Emi, 1997 Where: E= Failure consequence probability of failure mode i , L = occurrence likelyhood of failure mode i, Number of failure mode of the item which fall under particular severity class, T=Duration of application of mission place. ...
... The models intended for use are highly dependent on appropriately selected databases that accurately represent the local situation and the effectiveness of the models, however, will reflect any data limitations. Therefore creative procedures are required to develop the requisite data and relationships, the model by using expert judgments, worldwide data and data from other areas (e.g., the North Sea), making assumptions about the similarity of operations in the concerned area elsewhere, and making assumptions about how behaviour in one aspect of operations (e.g., company management quality) and/or one parameter (e.g., loss of crew time) correlates with another area (e.g., operations safety) (Kite, 1996). ...
... Collision accident scenarios carry heavy consequence, thus its occurrence is infrequence. Complete risk and reliability modelling require frequency estimation, consequence quantification, uncertainties and cost benefit analysis of the holistic system [1,2]. Like the frequency and consequence analysis, collision cost data are hard to come by, however, whatever little data that is available should be made meaningful as much as possible through available tools especially system based predictive tools required for decision support system necessary mitigation decision for sustainable and reliable waterways. ...
Inland water transportation project is considered today as one of the mitigation option available for humanity to curb carbon footage. Collision in inland water transportation represents the biggest treat to inland water transportation; its occurrence is very infrequent but has grave consequence that makes its avoidance a very imperative factor. The nature of the threat of collision can be worrisome, as they can lead to loss of life, damage to environment, disruption of operation, injuries, instantaneous and point form release of harmful substance to water, air and soil and long time ecological impact. However, the development of complex system like inland water transportation and collision avoidance system also needs to meet economic sustainability for decision requirement related to collision avoidane. This makes analysing and quantifying occurrence scenarios, consequence of accident very imperative for reliable and sustainable design for exercise of technocrat stewardship of safety and safeguard of environmental. This paper discusses the cost benefit analysis for risk control option required for operational, societal and technological change decision for sustainable inland water transportation system. The paper presents the result of predictive cost for collision aversion aversion for in River Langat waterways development.
... Therefore, combination of stochastic, statistical, reliability and probabilistic together with hybrid employment of goal based, formal safety assessment methods and fuzzy multi criteria network method that use historical data of waterways, vessel environmental and traffic data could yield efficient, sustainable and reliable design product for complex and dynamic systems. The general hypothesis behind assessing physical risk model of ship in waterways is that the probability of an accident on a particular transit depends on a set of risk variables which required to be analyzed for necessary conclusion of prospective reliable design [10]. Risk and reliability modeling involves hazard identification, risk screening, broadly focused, narrowly focused and detailed Analysis, Table 2 shows iterative method that can be incorporated for various needs and stages of the process. ...
The maritime and offshore industry has made use of the ocean in a very responsible way, the challenged posed by environmental concern in the coastline is evolving new technology and new ways for technological development. In an age so dire to find alternative and sensitive ways to mitigate challenge of global warming, climate changes and its associated impact, maritime and offshore activities is loaded with requirement to build new sustainable and reliable technology for deep sea operation in order to fulfil alternative mitigation options for climate change, decline of coastline resources and enthophication. Expanding deep sea operation require development of technology related to dynamic position, mobile berthing facilities, collision aversion, impact of new environment, wave, wind on marine structure, supply vessel operation and fact that coastal water transportation attracts low probability and high consequence accidents. This makes reliability requirements for the design and operability for safety and environmental protection very necessary. This paper discusses process work in risk, hazard and reliability based design and safe and efficient operability deep water operation waters. This includes a system based approach that covers proactive risk as well as holistic multi criteria assessment of required variables to deduce mitigation options and decision support for preventive, protective and control measures of risk of hazard for deep water marine offshore operation.
... Collision accident scenarios carry heavy consequence, thus its occurrence is infrequence. Complete risk and reliability modelling require frequency estimation, consequence quantification, uncertainties and cost benefit analysis of the holistic system [1,2]. Like the frequency and consequence analysis, collision cost data are hard to come by, however, whatever little data that is available should be made meaningful as much as possible through available tools especially system based predictive tools required for decision support system necessary mitigation decision for sustainable and reliable waterways. ...
... Therefore, combination of stochastic, statistical, reliability and probabilistic together with hybrid employment of goal based, formal safety assessment methods and fuzzy multi criteria network method that use historical data of waterways, vessel environmental and traffic data could yield efficient, sustainable and reliable design product for complex and dynamic systems. The general hypothesis behind assessing physical risk model of ship in waterways is that the probability of an accident on a particular transit depends on a set of risk variables which required to be analyzed for necessary conclusion of prospective reliable design [10]. Risk and reliability modeling involves hazard identification, risk screening, broadly focused, narrowly focused and detailed Analysis, Table 2 shows iterative method that can be incorporated for various needs and stages of the process. ...
... Collision accident scenarios carry heavy consequence, thus its occurrence is infrequence. Complete risk and reliability modelling require frequency estimation, consequence quantification, uncertainties and cost benefit analysis of the holistic system [1,2]. Like the frequency and consequence analysis, collision cost data are hard to come by, however, whatever little data that is available should be made meaningful as much as possible through available tools especially system based predictive tools required for decision support system necessary mitigation decision for sustainable and reliable waterways. ...
nland water transportation project is considered today as one of the mitigation option available for humanity to curb carbon footage. Collision in inland water transportation represents the biggest treat to inland water transportation; its occurrence is very infrequent but has grave consequence that makes its avoidance a very imperative factor. The nature of the threat of collision can be worrisome, as they can lead to loss of life, damage to environment, disruption of operation, injuries, instantaneous and point form release of harmful substance to water, air and soil and long time ecological impact. However, the development of complex system like inland water transportation and collision avoidance system also needs to meet economic sustainability for decision requirement related to collision avoidane. This makes analysing and quantifying occurrence scenarios, consequence of accident very imperative for reliable and sustainable design for exercise of technocrat stewardship of safety and safeguard of environmental. This paper discusses the cost benefit analysis for risk control option required for operational, societal and technological change decision for sustainable inland water transportation system. The paper presents the result of predictive cost for collision aversion aversion for in River Langat waterways development.
... The USCG has used a classical statistical analysis of nationwide accident data to prioritize federal spending to improve port infrastructures [13, 14]. More recently, researchers have used probabilistic risk assessment (PRA) [15] in the maritime domain [16, 17, 18, 19, 20, 21, 22, 23] by examining risk in the context of maritime transportation systems [9]. In a maritime transportation system (MTS), traffic patterns change over time in a complex manner. ...
A proposal has been made to the California legislature to dramatically increase the frequency and coverage of ferry service in the San Francisco Bay area. A major question in the approval process is the effect of this expansion on the level of congestion on the waterway and the effect this will have on the safety of vessels in the area. A simulation model was created to estimate the number of vessel interactions in the current system and their increases caused by three alternative expansion plans. The output of the simulation model is a geographic profile showing the frequency of vessel interactions across the study area, thus representing the level of congestion under each alternative. Comparing these geographic interaction profiles to a similar one generated for the current ferry service in the San Francisco Bay allows evaluation of the increase in exposure of ferries to adverse conditions, such as, for example, the interaction of high-speed ferries in restricted visibility conditions. This analysis has been submitted to the legislature as part of the overall assessment of the proposal and will be used in the expansion decision.
... Over the years, various safety implementation measures have been developed to prevent and mitigate the damage caused by maritime accidents, such as the recent sinking of the Prestige off the Spanish Galician coast and the grounding of the Exxon-Valdez in the Prince William Sound. Probabilistic Risk Assessment (PRA) is a relatively new method developed to quantify maritime risk and estimate the effect of such safety measures (Hara and Nakamura 1995;Roeleven et al. 1995;Kite-Powell 1996;Slob 1998;Fowler and Sorgard 2000;Trbojevic and Carr 2000;Wang 2000;Guedes Soares andTeixeira 2001). PateCornell (1996)provides a step-wise approach to characterize uncertainty in probabilistic risk analysis. ...
Recent studies in the assessment of risk in maritime transportation systems have used simulation-based probabilistic techniques. Amongst them are the San Francisco Bay (SFB) Ferry exposure assessment in 2002, the Washington State Ferry (WFS) Risk Assessment in 1998 and the Prince William Sound (PWS) Risk Assessment in 1996. Representing uncertainty in such simulation models is fundamental to quantifying system risk. This paper illustrates the representation of uncertainty in simulation using Bayesian techniques to model input and output uncertainty. These uncertainty representations describe system randomness as well as lack of knowledge about the system. The study of the impact of proposed ferry service expansions in San Francisco Bay is used as a case study to demonstrate the Bayesian simulation technique. Such characterization of uncertainty in simulation-based analysis provides the user with a greater level of information enabling improved decision making.
... (9,10) More recently, quantitative risk assessment (QRA) has been introduced in the assessment of risk in the maritime domain. (11)(12)(13)(14)(15)(16)(17)(18) Paté-Cornell (1) defines six levels of treatment of uncertainty in risk analysis: (0) identification of hazards; (1) worst-case analysis; (2) plausible upper bound analysis; (3) best estimates; (4) probability and risk analysis; and (5) display of risk uncertainties. On this scale, the early work in maritime risk assessment could be classified as Level 3, providing best estimates of accident risk, while the later work using QRA can be classified as Level 4. None of the work has considered epistemic uncertainty or the dynamic nature of the aleatory uncertainty. ...
Recent work in the assessment of risk in maritime transportation systems has used simulation-based probabilistic risk assessment techniques. In the Prince William Sound and Washington State Ferries risk assessments, the studies' recommendations were backed up by estimates of their impact made using such techniques and all recommendations were implemented. However, the level of uncertainty about these estimates was not available, leaving the decisionmakers unsure whether the evidence was sufficient to assess specific risks and benefits. The first step toward assessing the impact of uncertainty in maritime risk assessments is to model the uncertainty in the simulation models used. In this article, a study of the impact of proposed ferry service expansions in San Francisco Bay is used as a case study to demonstrate the use of Bayesian simulation techniques to propagate uncertainty throughout the analysis. The conclusions drawn in the original study are shown, in this case, to be robust to the inherent uncertainties. The main intellectual merit of this work is the development of Bayesian simulation technique to model uncertainty in the assessment of maritime risk. However, Bayesian simulations have been implemented only as theoretical demonstrations. Their use in a large, complex system may be considered state of the art in the field of computational sciences.
... Early work concentrated on assessing the safety of individual vessels or marine structures, such as nuclear powered vessels (Pravda & Lightner, 1966), vessels transporting liquefied natural gas (Stiehl, 1977) and offshore oil and gas platforms (Paté-Cornell, 1990). More recently, Probabilistic Risk Assessment (Bedford and Cooke, 2002) has been introduced in the assessment of risk in the maritime domain (Roeleven et al., 1995; Kite-Powell, 1996; Slob, 1998; Fowler and Sorgard, 2000; Trbojevic and Carr, 2000; Wang, 2000; Guedes Soares and Teixeira, 2001). The Prince William Sound (PWS) Risk Assessment (Merrick et al., 2000Merrick et al., , 2002), Washington State Ferries (WSF) Risk Assessment (van Dorp et al. (2001) and an exposure assessment for ferries in San Francisco Bay (Merrick et al., 2003) are three examples of successful risk studies in this domain, combining system simulation with probabilistic risk assessment techniques. ...
Several major risk studies have been performed in recent years in the maritime transportation domain. These studies have had significant impact on management practices in the industry. The first, the Prince William Sound risk assessment, was reviewed by the National Research Council and found to be promising but incomplete, as the uncertainty in its results was not assessed. The difficulty in assessing this uncertainty is the different techniques that need to be used to model risk in this dynamic and data-scarce application area. In previous articles, we have developed the two pieces of methodology necessary to assess uncertainty in maritime risk assessment, a Bayesian simulation of the occurrence of situations with accident potential and a Bayesian multivariate regression analysis of the relationship between factors describing these situations and expert judgments of accident risk. In this article, we combine the methods to perform a full-scale assessment of risk and uncertainty for two case studies. The first is an assessment of the effects of proposed ferry service expansions in San Francisco Bay. The second is an assessment of risk for the Washington State Ferries, the largest ferry system in the United States.
... Over the years, various safety implementation measures have been developed to prevent and mitigate the damage caused by maritime accidents, such as the recent sinking of the Prestige off the Spanish Galician coast and the grounding of the Exxon-Valdez in the Prince William Sound. Probabilistic Risk Assessment (PRA) is a relatively new method developed to quantify maritime risk and estimate the effect of such safety measures (Hara and Nakamura 1995;Roeleven et al. 1995;Kite-Powell 1996;Slob 1998;Fowler and Sorgard 2000;Trbojevic and Carr 2000;Wang 2000;Guedes Soares andTeixeira 2001). PateCornell (1996)provides a step-wise approach to characterize uncertainty in probabilistic risk analysis. ...
Recent studies in the assessment of risk in maritime transportation systems have used simulation-based probabilistic techniques. Amongst them are the San Francisco Bay (SFB) Ferry exposure assessment in 2002, the Washington State Ferry (WFS) Risk Assessment in 1998 and the Prince William Sound (PWS) Risk Assessment in 1996. Representing uncertainty in such simulation models is fundamental to quantifying system risk. This paper illustrates the representation of uncertainty in simulation using Bayesian techniques to model input and output uncertainty. These uncertainty representations describe system randomness as well as lack of knowledge about the system. The study of the impact of proposed ferry service expansions in San Francisco Bay is used as a case study to demonstrate the Bayesian simulation technique. Such characterization of uncertainty in simulation-based analysis provides the user with a greater level of information enabling improved decision making.
This paper presents an argument for using more probabilistic safety assessment in the maritime transportation system. Currently, risk analysis takes place in a largely decentralized fashion and only a handful of quantitative risk analyses have been conducted. However, as the risk-informed system of managing maritime transportation matures, it is probable that more data will be collected and quantitative analyses will be conducted more often. An optimization perspective is presented to identify potential avenues of research in the maritime domain.
Several major risk studies have been performed in recent years in the maritime transportation domain. These studies have had significant impact on management practices in the industry. The first, the Prince William Sound risk assessment, was reviewed by the National Research Council and found to be promising but incomplete, as the uncertainty in its results was not assessed. The difficulty in assessing this uncertainty is the different techniques that need to be used to model risk in this dynamic and data-scarce application area. In previous articles, we have developed the two pieces of methodology necessary to assess uncertainty in maritime risk assessment, a Bayesian simulation of the occurrence of situations with accident potential and a Bayesian multivariate regression analysis of the relationship between factors describing these situations and expert judgments of accident risk. In this article, we combine the methods to perform a full-scale assessment of risk and uncertainty for two case studies. The first is an assessment of the effects of proposed ferry service expansions in San Francisco Bay. The second is an assessment of risk for the Washington State Ferries, the largest ferry system in the United States.
After the grounding of the Exxon Valdez and its subsequent oil spill, all parties with interests in Prince William Sound (PWS) were eager to prevent another major pollution event. While they implemented several measures to reduce the risk of an oil spill, the stakeholders disagreed about the effectiveness of these measures and the potential effectiveness of further proposed measures. They formed a steering committee to represent all the major stakeholders in the oil industry, in the government, in local industry, and among the local citizens. The steering committee hired a consultant team, which created a detailed model of the PWS system, inte- grating system simulation, data analysis, and expert judgment. The model was capable of assessing the current risk of accidents involving oil tankers operating in the PWS and of evaluating measures aimed at reducing this risk. The risk model showed that actions taken prior to the study had reduced the risk of oil spill by 75 percent, and it identified measures estimated to reduce the accident frequency by an additional 68 percent, including improving the safety-management systems of the oil companies and stationing an enhanced-capability tug, called the Gulf Service, at Hinchinbrook Entrance. In all, various stakeholders made multi- million dollar investments to reduce the risk of further oil spills based on the results of the risk assessment. (Decision analysis: risk. Industries: petroleum, transportation. Reliability: system safety.)
Collisions are studied as the main risks of floating production, storage and offloading (FPSO) offloading operations in this paper. The large application of FPSO in offshore industry has highlighted the safety issues during offloading operation. Firstly, the research progress about offshore collisions and the related risk analysis methods are studied. Secondly, a compact analysis of collisions and near miss cases is done in order to identify the risk factors associated with the collisions. The results are illustrated using fault tree analysis method. Finally, qualitative analyses of collisions are discussed regarding excessive surge and horizontal oscillation based on the feature of FPSO operations in China seas. The status of FPSO with diverse relative positions is studied and the corresponding risk control measures are presented. The works herein are instructive for the operation process during FPSO offloading.
Is it safer for New Orleans river gambling boats to be underway than to be dockside? Is oil transportation risk reduced by
lowering wind restrictions from 45 to 35 knots at Hinchinbrook Entrance for laden oil tankers departing Valdez, Alaska? Should
the International Safety Management (ISM) code be implemented fleet-wide for the Washington State Ferries in Seattle, or does
it make more sense to invest in additional life craft? Can ferry service in San Francisco Bay be expanded in a safe manner
to relieve high way congestion? These risk management questions were raised in a series of projects spanning a time frame
of more than 10 years. They were addressed using a risk management analysis methodology developed over these years by a consortium
of universities. In this paper we shall briefly review this methodology which integrates simulation of Maritime Transportation
Systems (MTS) with incident/accident data collection, expert judgment elicitation and a consequence model. We shall describe
recent advances with respect to this methodology in more detail. These improvements were made in the context of a two-year
oil transportation risk study conducted from 2006–2008 in the Puget Sound and surrounding waters. An application of this methodology
shall be presented comparing the risk reduction effectiveness analysis of a one-way zone, an escorting and a double hull requirement
in the same context.
ABSTRACT The ability of tug escort vessels to save oil-laden tankers that become,disabled in Prince William Sound, Alaska, is tested using a simulation of the drift path of the tankers. Tug escort schemes are intended to save ,tankers that have lost steering or propulsion ,by attaching ,a line ,and either holding the tanker from running aground until a repair can be made or towing the tanker to port. The ability of an ,escort tug to save ,disabled tankers depends ,on its position at the time of the accident, the location, speed and direction of the tanker at the time of the failure and the wind and current conditions that changed ,dynamically ,during a save ,attempt. To accurately test the save capability of a proposed escort scheme, a simulation of the Prince William Sound is created that models dynamic,changes in environmental conditions and thus the movement,of the tanker. The
The Strait of Istanbul, the narrow waterway separating Europe from Asia, holds a strategic importance in maritime transportation as it links the Black Sea to the Mediterranean. It is considered as one of the world's most congested and difficult-to-navigate waterways. Over 55,000 transit vessels pass through the Strait annually, roughly 20% of which carry dangerous cargo. In this study, we have analyzed safety risks pertaining to transit vessel maritime traffic in the Strait of Istanbul and proposed ways to mitigate them. Safety risk analysis was performed by incorporating a probabilistic accident risk model into the simulation model. A mathematical risk model was developed based on probabilistic arguments regarding instigators, situations, accidents, consequences, and historical data, as well as subject-matter expert opinions. Scenario analysis was carried out to study the behavior of the accident risks, with respect to changes in the surrounding geographical, meteorological, and traffic conditions. Our numerical investigations suggested some significant policy indications. Local traffic density and pilotage turned out to be two main factors affecting the risks at the Strait of Istanbul. Results further indicate that scheduling changes to allow more vessels into the Strait will increase risks to extreme levels. Conversely, scheduling policy changes that are opted to reduce risks may cause major increases in average vessel waiting times. This in turn signifies that the current operations at the Strait of Istanbul have reached a critical level beyond which both risks and vessel delays are unacceptable.
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