A Maritime Oil Spill Risk Assessment Model

2001 ◽  
Vol 2001 (1) ◽  
pp. 235-240 ◽  
Author(s):  
Lalit Yudhbir ◽  
Eleftherios Iakovou

ABSTRACT Mantime oil transportation decision-making models that integrate with oil spill risk assessment methodologies are scarce. Recently, first time quantitative efforts have been developed for the maritime transportation of petroleum products. However, there still exists a serious gap in the literature concerning risk assessment models that provide a rather significant input to any maritime oil transportation model, namely the estimation and assignment of risk costs to the links of such a network. The authors first present a critical review of oil spill risk assessment efforts found in the literature and then the development of a novel oil spill risk assessment model. The goal of this risk assessment methodology is twofold: first, to determine and assign risk costs to the links of a maritime transportation network, and second, to provide insights into contributors that lead to spills. Such insights may further lead to guidelines for the prevention of future incidents leading to spills. A federal regulatory agency (such as the U.S. Coast Guard) and/or a commercial shipper may use the identification of the dominant contributors to oil spills to evaluate the merits of alternative regulatory and shipping policies that could lead to improved safety performance of the marine system. The authors finally exhibit the usage of the proposed methodology on a real case scenario.

2014 ◽  
Vol 13 (3) ◽  
pp. 415-420 ◽  
Author(s):  
Yan Lu ◽  
Jia Wang ◽  
Wenpu Wei ◽  
Yong Yang ◽  
Wei An

1979 ◽  
Vol 1979 (1) ◽  
pp. 37-43
Author(s):  
Halûk Özkaynak ◽  
Brian L. Murphy ◽  
Joel J. Watson

ABSTRACT The tanker oil spill risk assessment model (TRAM) allows a user to investigate the way in which oil spill probabilities, and amounts spilled, vary with such factors as fleet composition, navigational aids, or particular properties of the route. Such a comparison of alternatives is generally required for an environmental impact statement. TRAM operates through multiplication of a series of matrices: P, Q, R, and S. The rows and columns of all matrices are parameterized by accident type (such as collision or grounding) and location (such as at a pier, or in a harbor). The probability of an accident (P) and of a spill following an accident (Q) are based on world tanker fleet data. The matrix S expresses the conditional probability that if there is a spill, the vessel will be a total loss. This enables catastrophic spills in which spill size can be related to vessel size to be distinguished from minor spills in which vessel size is generally not a factor. The matrix R contains most of the unique features of the model. It accounts for vessel and route-specific features that reasonably may be expected to alter the world tanker fleet data. Examples are given from the literature for the elements of R corresponding to: fleet composition (domestic/foreign carrier); navigation aids such as vessel traffic system; vessel age, and construction (double hull, inerting system, segregated ballast, etc.); and various features of the tanker route, such as channel width and traffic density, based on Macduff's causation probability formalism. The practical usage of the model is demonstrated by applying it to a hypothetical project involving tanker oil transportation. The extension of this analysis technique to other forms of risk analysis studies (including operations other than oil transport) is also discussed.


2018 ◽  
Vol 135 ◽  
pp. 1117-1127 ◽  
Author(s):  
Ehsan Arzaghi ◽  
Rouzbeh Abbassi ◽  
Vikram Garaniya ◽  
Jonathan Binns ◽  
Faisal Khan

2014 ◽  
Vol 2014 (1) ◽  
pp. 299545 ◽  
Author(s):  
Yan Lyu ◽  
Yong Yang ◽  
Wenpu Wei ◽  
Wei An

With the greatly development in offshore gas and oil activity in China, the potential risk of oil spill attract more public attentions. In order to effectively limit the spilling incidence and bring it under control, it is necessary to establish a risk assessment model for offshore petroleum activity and prepare the oil spill response resource in an effective way. In this paper, a quantified risk assessment model, including the spill probability and consequence assessment, was developed using fuzzy comprehensive method. The spill probability assessment was established with view of the operative manual and statistic leakage/damage data of different kinds of offshore petroleum facilities and operation; the consequence assessment was proposed to several factors including the spilling volume, property of spilled oil, spilling location and the elements of spilling detection and controlling capability of operator. Based on the result from risk assessment, we can identify the comprehensive spill risk level (low, ALARP, high) and make a decision whether the response resource allocated to the site could be enough. The multiply oil spill response devices and facilities, especially the oil recovery vessel, were largely used in China and will be expand in future.


2016 ◽  
Vol 144 (16) ◽  
pp. 3400-3411
Author(s):  
D. C. DOVER ◽  
E. M. KIRWIN ◽  
N. HERNANDEZ-CERON ◽  
K. A. NELSON

SUMMARYThe Pandemic Risk Assessment Model (PRAM) is a mathematical model developed to analyse two pandemic influenza control measures available to public health: antiviral treatment and immunization. PRAM is parameterized using surveillance data from Alberta, Canada during pandemic H1N1. Age structure and risk level are incorporated in the compartmental, deterministic model through a contact matrix. The model characterizes pandemic influenza scenarios by transmissibility and severity properties. Simulating a worst-case scenario similar to the 1918 pandemic with immediate stockpile release, antiviral demand is 20·3% of the population. With concurrent, effective and timely immunization strategies, antiviral demand would be significantly less. PRAM will be useful in informing policy decisions such as the size of the Alberta antiviral stockpile and can contribute to other pandemic influenza planning activities and scenario analyses.


2010 ◽  
Vol 151 (34) ◽  
pp. 1365-1374 ◽  
Author(s):  
Marianna Dávid ◽  
Hajna Losonczy ◽  
Miklós Udvardy ◽  
Zoltán Boda ◽  
György Blaskó ◽  
...  

A kórházban kezelt sebészeti és belgyógyászati betegekben jelentős a vénásthromboembolia-rizikó. Profilaxis nélkül, a műtét típusától függően, a sebészeti beavatkozások kapcsán a betegek 15–60%-ában alakul ki mélyvénás trombózis vagy tüdőembólia, és az utóbbi ma is vezető kórházi halálok. Bár a vénás thromboemboliát leggyakrabban a közelmúltban végzett műtéttel vagy traumával hozzák kapcsolatba, a szimptómás thromboemboliás események 50–70%-a és a fatális tüdőembóliák 70–80%-a nem a sebészeti betegekben alakul ki. Nemzetközi és hazai felmérések alapján a nagy kockázattal rendelkező sebészeti betegek többsége megkapja a szükséges trombózisprofilaxist. Azonban profilaxis nélkül marad a rizikóval rendelkező belgyógyászati betegek jelentős része, a konszenzuson alapuló nemzetközi és hazai irányelvi ajánlások ellenére. A belgyógyászati betegek körében növelni kell a profilaxisban részesülők arányát és el kell érni, hogy trombózisrizikó esetén a betegek megkapják a hatásos megelőzést. A beteg trombóziskockázatának felmérése fontos eszköze a vénás thromboembolia által veszélyeztetett betegek felderítésének, megkönnyíti a döntést a profilaxis elrendeléséről és javítja az irányelvi ajánlások betartását. A trombózisveszély megállapításakor, ha nem ellenjavallt, profilaxist kell alkalmazni. „A thromboemboliák kockázatának csökkentése és kezelése” című, 4. magyar antithromboticus irányelv felhívja a figyelmet a vénástrombózis-rizikó felmérésének szükségességére, és elsőként tartalmazza a kórházban fekvő belgyógyászati és sebészeti betegek kockázati kérdőívét. Ismertetjük a kockázatbecslő kérdőíveket és áttekintjük a kérdőívekben szereplő rizikófaktorokra vonatkozó bizonyítékokon alapuló adatokat.


Author(s):  
C.K. Lakshminarayan ◽  
S. Pabbisetty ◽  
O. Adams ◽  
F. Pires ◽  
M. Thomas ◽  
...  

Abstract This paper deals with the basic concepts of Signature Analysis and the application of statistical models for its implementation. It develops a scheme for computing sample sizes when the failures are random. It also introduces statistical models that comprehend correlations among failures that fail due to the same failure mechanism. The idea of correlation is important because semiconductor chips are processed in batches. Also any risk assessment model should comprehend correlations over time. The statistical models developed will provide the required sample sizes for the Failure Analysis lab to state "We are A% confident that B% of future parts will fail due to the same signature." The paper provides tables and graphs for the evaluation of such a risk assessment. The implementation of Signature Analysis will achieve the dual objective of improved customer satisfaction and reduced cycle time. This paper will also highlight it's applicability as well as the essential elements that need to be in place for it to be effective. Different examples have been illustrated of how the concept is being used by Failure Analysis Operations (FA) and Customer Quality and Reliability Engineering groups.


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