scholarly journals Development of comprehensive fire and explosion risk assessment on coal reclaim tunnel using Monte Carlo simulation and risk matrix method

2021 ◽  
Author(s):  
Nuhindro Priagung Widodo ◽  
Dimas Agung Permadi ◽  
Ahmad Ihsan ◽  
Ginting Jalu Kusuma
Keyword(s):  
Risk Assessment ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Matrix Method ◽  
Risk Matrix ◽  
Fire And Explosion ◽  
Explosion Risk

scholarly journals Development of Fire and Explosion Risk Assessment on Coal Reclaim Tunnel Using Monte Carlo Simulation and Risk Matrix Method

2021 ◽  
Author(s):  
Nuhindro Priagung Widodo ◽  
Dimas Agung Permadi ◽  
Ahmad Ihsan ◽  
Ginting Jalu Kusuma
Keyword(s):  
Risk Assessment ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Risk Group ◽  
Distribution Model ◽  
Risk Matrix ◽  
Moderate Risk ◽  
Controllable Factors ◽  
Fire And Explosion ◽  
Explosion Risk

The comprehensive fire and explosion risk assessment has been studied for Coal Reclaim Tunnel (CRT) facility by applying the Monte Carlo simulation method. In this research, the fire and explosion risk of two existing CRT, namely model A and model B, have been assessed. A set of 30 data for each factor has been used to define the statistical distribution model, sourced from historical data, field measurement, and laboratory experiments. Based on the simulation, CRT model A has a 100% extreme risk group, while model B has two risk groups, high risk=81.73% and moderate risk=18.27%, classified as a not acceptable risk. Several preventive actions were set to reduce the probability and severity level as low as reasonably possible, especially for the controllable factors. Furthermore, the probability and severity levels were re-adjusted by the Monte Carlo simulation. The result shows that both the CRT model have been grouped into a 100% moderate-risk group. For optimal prevention against explosion risk, a sensitivity analysis has been carried out to find the most influential factors for the fire and explosion risk in CRT. Through this research, a method for risk matrix assessment related to the fire and explosion in the CRT facility has been developed.

scholarly journals Economic analysis and risk assessment of biomass gasification CHP systems of different sizes through Monte Carlo simulation

2021 ◽  
Vol 7 ◽  
pp. 1954-1961
Author(s):  
Andrea Colantoni ◽  
Mauro Villarini ◽  
Danilo Monarca ◽  
Maurizio Carlini ◽  
Enrico Maria Mosconi ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Economic Analysis ◽  
Biomass Gasification

scholarly journals Fault Risk Assessment of Underwater Vehicle Steering System Based on Virtual Prototyping and Monte Carlo Simulation

2016 ◽  
Vol 23 (3) ◽  
pp. 97-105
Author(s):  
Deyu He ◽  
Niaoqing Hu ◽  
Lei Hu ◽  
Ling Chen ◽  
YiPing Guo ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Fault Injection ◽  
Fault Simulation ◽  
Virtual Prototyping ◽  
Underwater Vehicle ◽  
Steering System ◽  
Assessment Method ◽  
Risk Indicator

Abstract Assessing the risks of steering system faults in underwater vehicles is a human-machine-environment (HME) systematic safety field that studies faults in the steering system itself, the driver’s human reliability (HR) and various environmental conditions. This paper proposed a fault risk assessment method for an underwater vehicle steering system based on virtual prototyping and Monte Carlo simulation. A virtual steering system prototype was established and validated to rectify a lack of historic fault data. Fault injection and simulation were conducted to acquire fault simulation data. A Monte Carlo simulation was adopted that integrated randomness due to the human operator and environment. Randomness and uncertainty of the human, machine and environment were integrated in the method to obtain a probabilistic risk indicator. To verify the proposed method, a case of stuck rudder fault (SRF) risk assessment was studied. This method may provide a novel solution for fault risk assessment of a vehicle or other general HME system.

Risk assessment of construction projects using Monte Carlo simulation

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abroon Qazi ◽  
Mecit Can Emre Simsekler
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Risk Attitude ◽  
High Impact ◽  
Risk Exposure ◽  
Risk Matrix ◽  
Content Type ◽  
Simulation Based ◽  
Project Risks ◽  
Low Probability

PurposeThis paper aims to develop a process for prioritizing project risks that integrates the decision-maker's risk attitude, uncertainty about risks both in terms of the associated probability and impact ratings, and correlations across risk assessments.Design/methodology/approachThis paper adopts a Monte Carlo Simulation-based approach to capture the uncertainty associated with project risks. Risks are prioritized based on their relative expected utility values. The proposed process is operationalized through a real application in the construction industry.FindingsThe proposed process helped in identifying low-probability, high-impact risks that were overlooked in the conventional risk matrix-based prioritization scheme. While considering the expected risk exposure of individual risks, none of the risks were located in the high-risk exposure zone; however, the proposed Monte Carlo Simulation-based approach revealed risks with a high probability of occurrence in the high-risk exposure zone. Using the expected utility-based approach alone in prioritizing risks may lead to ignoring few critical risks, which can only be captured through a rigorous simulation-based approach.Originality/valueMonte Carlo Simulation has been used to aggregate the risk matrix-based data and disaggregate and map the resulting risk profiles with underlying distributions. The proposed process supported risk prioritization based on the decision-maker's risk attitude and identified low-probability, high-impact risks and high-probability, high-impact risks.

Monte Carlo Simulation Model for Predicting Salmonella Contamination of Chicken Liver as a Function of Serving Size for Use in Quantitative Microbial Risk Assessment

2021 ◽  
Author(s):  
Thomas Oscar
Keyword(s):  
Risk Assessment ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Simulation Model ◽  
Chicken Liver ◽  
Quantitative Microbial Risk Assessment ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Serving Size ◽  
Monte Carlo Simulation Model

The first step in quantitative microbial risk assessment (QMRA) is to determine distribution of pathogen contamination among servings of the food at some point in the farm-to-table chain. In the present study, distribution of Salmonella contamination among servings of chicken liver for use in QMRA was determined at meal preparation. A combination of five methods: 1) whole sample enrichment; 2) quantitative polymerase chain reaction; 3) cultural isolation; 4) serotyping; and 5) Monte Carlo simulation were used to determine Salmonella prevalence (P), number (N), and serotype for different serving sizes. In addition, epidemiological data were used to convert serotype data to virulence (V) values for use in QMRA. A Monte Carlo simulation model based in Excel and simulated with @Risk predicted Salmonella P, N, serotype, and V as a function of serving size from one (58 g) to eight (464 g) chicken livers. Salmonella P of chicken livers was 72.5% (58/80) per 58 g. Four serotypes were isolated from chicken livers: 1) Infantis (P = 28%, V = 4.5); 2) Enteritidis (P = 15%, V = 5); 3) Typhimirium (P = 15%, V = 4.8); and 4) Kentucky (P = 15%, V = 0.8). Median Salmonella N was 1.76 log per 58 g (range: 0 to 4.67 log/58 g) and was not affected ( P > 0.05) by serotype. The model predicted a non-linear increase ( P ≤ 0.05) of Salmonella P from 72.5% per 58 g to 100% per 464 g, minimum N from 0 log per 58 g to 1.28 log per 464 g, and median N from 1.76 log per 58 g to 3.22 log per 464 g. Regardless of serving size, predicted maximum N was 4.74 log, mean V was 3.9, and total N was 6.65 log per lot (10,000 chicken livers). The data acquired and model developed in this study fill an important data and modeling gap in QMRA for Salmonella and chicken liver.

A Weighted Monte Carlo Simulation Approach to Risk Assessment of Information Security Management System

2015 ◽  
Vol 11 (4) ◽  
pp. 63-78 ◽  
Author(s):  
Seyed Mojtaba Hosseini Bamakan ◽  
Mohammad Dehghanimohammadabadi
Keyword(s):  
Risk Assessment ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Information Security ◽  
Risk Analysis ◽  
Management System ◽  
Security Management ◽  
International Standards ◽  
Information Security Management ◽  
Information Security Management System

In recent decades, information has become a critical asset to various organizations, hence identifying and preventing the loss of information are becoming competitive advantages for firms. Many international standards have been developed to help organizations to maintain their competitiveness by applying risk assessment and information security management system and keep risk level as low as possible. This study aims to propose a new quantitative risk analysis and assessment methodology which is based on AHP and Monte Carlo simulation. In this method, AHP is used to create favorable weights for Confidentiality, Integrity and Availability (CIA) as security characteristic of any information asset. To deal with the uncertain nature of vulnerabilities and threats, Monte Carlo simulation is utilized to handle the stochastic nature of risk assessment by taking into account multiple judges' opinions. The proposed methodology is suitable for organizations that require risk analysis to implement ISO/IEC 27001 standard.

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