RISK ANALYSIS OF OFFSHORE TRANSPORTATION ACCIDENT IN ARCTIC WATERS

2021 ◽  
Vol 159 (A3) ◽  
Author(s):  
R Abbassi ◽  
F Khan ◽  
N Khakzad ◽  
B Veitch ◽  
S Ehlers
Keyword(s):  
Monte Carlo ◽  
Risk Analysis ◽  
Historical Data ◽  
Fault Trees ◽  
Northern Sea Route ◽  
Accident Scenarios ◽  
Oil Tanker ◽  
Harsh Conditions ◽  
Monte Carlo Framework ◽  
Transportation Accident

A methodology for risk analysis applicable to shipping in arctic waters is introduced. This methodology uses the Bowtie relationship to represent an accident causes and consequences. It is further used to quantify the probability of a ship accident and also the related accident consequences during navigation in arctic waters. Detailed fault trees for three possible ship accident scenarios in arctic transits are developed and represented as bowties. Factors related to cold and harsh conditions and their effects on grounding, foundering, and collision are considered as part of this study. To illustrate the application of the methodology, it is applied to a case of an oil-tanker navigating on the Northern Sea Route (NSR). The methodology is implemented in a Markov Chain Monte Carlo framework to assess the uncertainties arisen from historical data and expert judgments involved in the risk analysis.

Risk Analysis of Offshore Transportation Accident in Arctic Waters

2017 ◽  
Vol Vol 159 (A3) ◽  
Author(s):  
R Abbassi ◽  
F Khan ◽  
N Khakzad ◽  
B Veitch ◽  
S Ehlers
Keyword(s):  
Monte Carlo ◽  
Risk Analysis ◽  
Historical Data ◽  
Fault Trees ◽  
Northern Sea Route ◽  
Accident Scenarios ◽  
Oil Tanker ◽  
Harsh Conditions ◽  
Monte Carlo Framework ◽  
Transportation Accident

A methodology for risk analysis applicable to shipping in arctic waters is introduced. This methodology uses the Bowtie relationship to represent an accident causes and consequences. It is further used to quantify the probability of a ship accident and also the related accident consequences during navigation in arctic waters. Detailed fault trees for three possible ship accident scenarios in arctic transits are developed and represented as bowties. Factors related to cold and harsh conditions and their effects on grounding, foundering, and collision are considered as part of this study. To illustrate the application of the methodology, it is applied to a case of an oil-tanker navigating on the Northern Sea Route (NSR). The methodology is implemented in a Markov Chain Monte Carlo framework to assess the uncertainties arisen from historical data and expert judgments involved in the risk analysis.

Preventing Accidental Spills: Risk Analysis and the Discharge Permitting Process

1994 ◽  
Vol 29 (3) ◽  
pp. 189-197 ◽  
Author(s):  
Frans A. N. van Baardwijk
Keyword(s):  
Risk Analysis ◽  
Surface Waters ◽  
Legal Framework ◽  
Sewage Water ◽  
Correction Factors ◽  
Analysis Method ◽  
Sewage Water Treatment ◽  
Accident Scenarios ◽  
Contaminating Substances ◽  
Permitting Process

The contribution of accidental discharges to the total emission of contaminating substances in surface waters is relatively increasing, as regular discharges are reduced. In The Netherlands a program has been started to develop a quantitative risk analysis method to be used within the discharge permitting process. The methodology takes into account the type of activities and related accident scenarios in terms of failure frequencies and source sizes, correction factors according to specific circumstances, as well as the nature of the receiving system (types of surface waters, but also public sewage water treatment plants). The methodology will provide an indication of the risk reduction needed in terms of reducing the frequency and/or the volume of possible spills. The method itself, the use of it within the legal framework and the relation with the EC-Directives are discussed.

Coarse-grained modeling of the nucleation of polycyclic aromatic hydrocarbons into soot precursors

2019 ◽  
Vol 21 (9) ◽  
pp. 5123-5132 ◽  
Author(s):  
J. Hernández-Rojas ◽  
F. Calvo
Keyword(s):  
Monte Carlo ◽  
Polycyclic Aromatic Hydrocarbons ◽  
Aromatic Hydrocarbons ◽  
Physical Growth ◽  
Coarse Grained ◽  
Soot Precursors ◽  
Polycyclic Aromatic ◽  
Hydrocarbon Molecules ◽  
A Minor ◽  
Monte Carlo Framework

The aggregation and physical growth of polycyclic aromatic hydrocarbon molecules was simulated using a coarse-grained potential and a stochastic Monte Carlo framework. In agreement with earlier studies, homomolecular nucleation of pyrene, coronene and circumcoronene is found to be limited at temperatures in the 500–1000 K range. Heteromolecular nucleation is found to occur with a minor spontaneous segregation toward pure and equi concentrations.

scholarly journals Analisis Risiko Finansial Dengan Metode Simulasi Monte Carlo (Studi Kasus: Pt. Phase Delta Control)

2016 ◽  
Vol 8 (1) ◽  
pp. 62
Author(s):  
Atikah Aghdhi Pratiwi ◽  
Rosa Rilantiana
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Historical Data ◽  
Uncertain Variable ◽  
Random Numbers ◽  
Selling Price ◽  
Sales Volume ◽  
Simulation Research ◽  
Cost Of Production ◽  
A Company

AbstractBasically, the purpose of a company is make a profit and enrich the owners of the company. This is manifested by development and achievement of good performance, both in financial and operational perspective. But in reality, not all of companies can achieve good performance. One of them is because exposure of risk. This could threaten achievement of the objectives and existence of the company. Therefore, companies need to have an idea related to possible condition and financial projection in future periods that are affected by risk. One of the possible method is Monte Carlo Simulation. Research will be conducted at PT. Phase Delta Control with historical data related to production/sales volume, cost of production and selling price. Historical data will be used as Monte Carlo Simulation with random numbers that describe probability of each risk variables describing reality. The main result is estimated profitability of PT. Phase Delta Control in given period. Profit estimation will be uncertain variable due to some uncertainty

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