Predicting reliability has a significant role in history of industrial engineering and today a wide range of reliability analysis methods are available for different types of systems. Fault tree analysis (FTA) is a widely used reliability assessment technique which represents the failure logic of a system. Although FTA has been improved during last decades, conventional FTA still 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 some of those limitations. Various methodologies have been developed for quantitative analysis of DFTA; however most of them require complicated analytical procedure (e.g. algebraic approach) or a significant calculation time for an accurate analysis. In this study, first, Probabilistic-Monte Carlo simulation (PMSC) approach is examined to handle internal calculations of dynamic gates. In the process of solving dynamic gates, generating random numbers by using Monte Carlo simulation approach, reduces calculation time and simplifies analytical procedure. The second main weakness of common FTA is about handling the uncertainties, allowing the use of linguistic variables, and integrating human error in failure logic model. Hence, in the second step of this study, a combined fuzzy logic and Monte Carlo technique  has been proposed to overcome the limitation of FTA in dealing with uncertainties. Using fuzzy numbers in DFTA can reduce the uncertainty of the results which is generated by the MCS approach. Our technique shows significanr improvement on the accuracy and reducing of the top event occurrence likelihood.

The main purpose of this paper is a comparative study on differences between probabilistic -Monte Carlo and Fuzzy-Monte Carlo simulation approaches for solving repairable DFTA of a typical mechanical system. The role of green energy systems in generating electric power is growing rapidly. Due to existing of multiple uncertainty sources in renewable energy production, the reliability analysis of such systems is affected by uncertainties. For this reason and also to compare the proposed techniques practically, from available literatures, our proposed approaches have been demonstrated on different renewable energy systems, as case studies, and results are discussed. A comparison between PMCS and FMCS shows that there are pros and cons in utilization of each techique. Finally, in the last section, conclusions and some of the future wok are proposed. Some recommnedations were made on the utilizations of each technique.


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

Division / Sponsors: 
Aerospace, Bioengineering, Applied Mechanics, Design Engineering Division, Advanced Energy Systems, Manufacturing Engineering Division, Noise Control and Acoustics, Nondestructive Evaluation, Diagnosis, and Prognosis (NDPD), Nuclear Engineering Division, Process Industries Division, Fluids Engineering, Heat Transfer, Materials, Microelectromechanical Systems, Safety Engineering and Risk Analysis, Computers & Information in Engineering


Paper Proceedings: https://asmedigitalcollection.asme.org/IMECE/IMECE2020/volume/84478

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