FPGA-based Monte Carlo simulation for fault tree analysis

2004 ◽  
Vol 44 (6) ◽  
pp. 1017-1028 ◽  
Author(s):  
Alireza Ejlali ◽  
Seyed Ghassem Miremadi
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Tree Analysis

A Comparison of Probabilistic-Monte Carlo and Fuzzy-Monte Carlo Simulation Approaches for Dynamic Fault Tree: Case of Renewable Power Systems

2020 ◽  
Author(s):  
Jafar Asghari ◽  
Mohammad Pourgol Mohammad
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Power Systems ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Tree Analysis ◽  
Renewable Energy Systems ◽  
Renewable Power ◽  
Dynamic Fault Tree ◽  
Different Types

Abstract Conventional Fault Tree Analysis (FTA) suffers from a variety of shortcomings which must be considered in critical analysis. The main disadvantage of FTA is its inability to model the dynamic failure behaviors of the components. Accordingly, Dynamic Fault Tree Analysis (DFTA) has been proposed to overcome such limitation. In this study, first, Monte Carlo simulation (MSC) approach is used to handle internal calculations of dynamic gates. The second main weakness of common FTA is about handling the different types of uncertainties. Hence, in the second step of this study, a combined of fuzzy numbers and MCS has been proposed to overcome the limitation of FTA in dealing with uncertainties. The main purpose of this paper is a comparative study on differences between MCS and Fuzzy-Monte Carlo simulation (FMCS) approaches for solving DFTA of a typical mechanical system. From available literatures, our proposed approaches have been demonstrated on different renewable energy systems, as case studies, and results are discussed. A comparison between MCS and FMCS shows that the results of FMCS method are reasonable and more realistic. Finally, in the last section, conclusions and some of the future wok are proposed.

scholarly journals FAULT TREE ANALYSIS OF FLY-OUTS IN METAL LATHE MACHINE OPERATIONS

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
AKINYEMI OLASUNKANMI ORIOLA ◽  
GIWA SOLOMON OLANREWAJU ◽  
ADEYEMI HEZEKIAH OLUWOLE ◽  
AKINTAN ADESHINAAYOMI LAWAL ◽  
MEBUDE OLADAPO
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Boolean Algebra ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Tree Analysis ◽  
Before And After ◽  
Safety Interventions ◽  
Lathe Machine ◽  
Safety Intervention

The most probable accident in lathe machining has been identified to be fly-outs. This study aim at determining the causal factors leading to fly-out accidents during lathe machining operations and subsequently determine the probability of occurrence of fly-out accident. Fault tree analysis (FTA) was used to identify risk factors. Boolean algebra equations were used to analyse the probability of fault occurrence. Monte Carlo simulation was carried out using OpenFTA software and the output of 1000 iterations was compared with the output of Boolean algebra. Safety intervention alternatives were evaluated by comparative analysis of before and after implementation of safety measures. Twenty four (24) minimum cut sets comprising of 21 basic events and 3 undeveloped events were identified. The top event has probability of 0.748 signifying high likelihood for fly-out. Monte Carlo simulation gave lower and upper bounds probabilities of 0.725 and 0.773, respectively. The event of the chuck key not pulled out of the chuck before machining begins was however noted to have the highest contribution to the occurrence of fly-out accident. The result of safety intervention alternatives revealed that the probability of fly-out becomes 0.192 with a safety benefit of N27, 800 after the first tier implementation. Other tiers of safety interventions will see the probability of fly-out go further down. By this, safety engineer has a scale for effectiveness of respective safety intervention programmes. Key words: fly-out, accident, safety, intervention, lathe, machine, operation

scholarly journals Using Probabilistic Fault Tree Analysis and Monte Carlo Simulation to Examine the Likelihood of Risks Associated with Ballasted Railway Drainage Failure

2021 ◽  
pp. 036119812098231
Author(s):  
Kristianto Usman ◽  
Michael Peter Nicholas Burrow ◽  
Gurmel Singh Ghataora ◽  
Manu Sasidharan
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Asset Management ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Railway Track ◽  
Mitigation Measures ◽  
Rational Approach ◽  
Railway Network ◽  
Tree Analysis

Inadequate track drainage can lead to a variety of issues, including flooding, accelerated track degradation, and progressive or sudden failure of railway track, slope, or embankment. These can result in unplanned track maintenance, additional passenger travel costs, and damage to third party property. However, railway drainage asset management is challenging because it involves the consideration of large interconnected assets, limited maintenance budgets, and unknown failure probabilities. To address this issue, this paper introduces a risk-informed approach for railway drainage asset management that uses fault tree analysis to identify the factors that contribute to railway drainage flood risk and quantifies the likelihood of the occurrence of these factors using Monte Carlo simulation. This rational approach enables drainage asset managers to evaluate easily the factors that affect the likelihood of railway track drainage failure, thereby facilitating the prioritization of appropriate mitigation measures and in so doing improve the allocation of scarce maintenance resources. The analysis identified 46 basic and 49 intermediate contributing factors associated with drainage failure of ballasted railway track (undesired event). The usefulness of the approach is demonstrated for three sites on the UK railway network, namely, Ardsley Tunnel, Clay Cross Tunnel, and Draycott. The analysis shows that the Clay Cross Tunnel had the highest probability of drainage failure and should be prioritized for maintenance over the other two sites. The maintenance required should focus on blockages because of vegetation overgrowth or debris accumulation.

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