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.

scholarly journals Construction Diversion Risk Assessment for Hydropower Development on Sediment-Rich Rivers

Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 938
Author(s):  
Zida Song ◽  
Quan Liu ◽  
Zhigen Hu ◽  
Chunsheng Zhang ◽  
Jinming Ren ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Assessment Method ◽  
Energy Potential ◽  
Hydropower Development ◽  
Development Environment ◽  
Construction Diversion ◽  
The World ◽  
Overtopping Probability

Hydropower is an important renewable energy, and Construction Diversion Risk (CDR) should be highlighted and assessed during hydropower development. Since sediment-rich rivers are widely existing around the world and have great hydro-energy potential, assessing CDR for hydropower development on sediment-rich rivers in terms of engineering feasibility is of significance. This paper proposes a CDR assessment method for the sediment-rich hydropower development environment. The method is concise and practical, reflects diversion uncertainties and correlation, and mainly adopts the Gumbel–Hougaard Copula and the Monte Carlo Simulation. Through simulating flood evolution and sediment impact during diversion, the method can assess CDR basing on the cofferdam overtopping probability. Case results show that the proposed method can achieve CDR assessment on a sediment-rich river and highlights sediment impact on the diversion risk. Through results discussion, the risk feature of construction diversion on sediment-rich rivers is revealed, that sediment impact causes the dynamic and yearly-risen CDR. Hence, our conclusions are: (1) the proposed method is feasible, effective and has industrial potential, and (2) a diversion scheme on sediment-rich rivers is suggested that adopts the design with high or yearly-heightening cofferdams, based on the advanced CDR assessment to cope with the risk features of sediment-rich diversion environments.

scholarly journals Debris Flow Risk Assessment Method Based on Combination Weight of Probability Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Li Li ◽  
Shi Xin Zhang ◽  
Shao Hong Li ◽  
Yue Qiang ◽  
Zhou Zheng ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Debris Flow ◽  
Specific Weight ◽  
Assessment Method ◽  
Entropy Method ◽  
Equal Weight ◽  
Uniform Random Variable ◽  
New Approach

Risk assessment of debris flow is conducted by multicriteria decisions. Based on the shortcomings of the existing methods in determining the weight of assessment factors, this paper proposes a new approach to conduct a risk assessment of debris flow. This new approach regards the weight of factors as a uniform random variable, whose bounds could be determined by the equal weight method, maximal deviation method, and entropy method. The results of this new approach are obtained by Monte Carlo simulation. According to the risk of 72 debris flows collected in Beichuan, Sichuan, China, this new approach proves convergent. It is suggested that the minimum sample amount of Monte Carlo simulation should be 63095. The result also demonstrates that sorted results with different weights of factors vary a lot, so it is not convincing to sort samples with a specific weight.

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

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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