Fuzzy probability based fault tree analysis to propagate and quantify epistemic uncertainty

Purba, Julwan Hendry; Tjahyani, D.T. Sony; Ekariansyah, Andi Sofrany; Tjahjono, Hendro

doi:10.1016/j.anucene.2015.08.002

Cited by 56 publications

(41 citation statements)

References 38 publications

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“…The purpose of this stage is to generate the vector M B , as shown in Equation (12). M B is the result of the multiplication of Q n in Equation (3) with the expert weights, W, as shown in Equation (1) [24].…”

Section: Basic Event Final Membership Function Generationmentioning

confidence: 99%

Safety Analysis Technique for System with Limited Data: Case Study of the Multipurpose Research Reactor in Indonesia

et al. 2020

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Fault tree analysis (FTA) is frequently applied to deductively evaluate the safety systems of complex engineering systems such as chemical industries or nuclear facilities. To perform this analysis, generic data are commonly used due to the limitation of historical failure data of the system being evaluated. However, generic data have a degree of uncertainty and hence cannot represent the system's actual performance. In addition, generic data are not applicable to older components due to the aging process, which obviously degrades the reliability of those components. To deal with this limitation, another safety analysis method, called fuzzy fault tree analysis (FFTA), has been proposed. The purpose of this study is to apply FFTA to evaluate the performance of the primary cooling systems of G.A. Siwabessy Multipurpose Reactor (RSG-GAS). RSG-GAS is a research reactor, which belongs to the National Nuclear Energy Agency of Indonesia (BATAN). Expert justifications were used to evaluate the failure occurrences of basic events in the primary cooling system of the RSG-GAS through questionnaires. The assessment by experts is in the form of qualitative data, which are then converted into quantitative data by applying FFTA. Then, the top event probability generated from FFTA was applied to calculate the event probability using event tree analysis (ETA). It was obtained that the highest event probability was 4.304 × 10 −8 /year. Since it complies with The International Atomic Energy Agency (IAEA) specified core damage frequency (CDF) limit, i.e., not greater than 10 −5 /year of reactor operation, the reactor is safe to operate.

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Section: Basic Event Final Membership Function Generationmentioning

confidence: 99%

Safety Analysis Technique for System with Limited Data: Case Study of the Multipurpose Research Reactor in Indonesia

et al. 2020

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“…Fuzzy-based approaches are often the method of choice for handling of uncertainties, which includes the analysis of soft factors (Helton, Johnson, Oberkampf, & Sallaberry, 2010;Purba, Sony Tjahyani, Ekariansyah, & Tjahjono, 2015;Unwin, 1986). As a result of this, the use of fuzzy logic for risk analysis is common in various domains such as nuclear power plants (Rastogi & Gabbar, 2013), construction (Gürcanli & Müngen, 2009), and medical fields (Lee & Wang, 2011).…”

Section: Fuzzy Set Theorymentioning

confidence: 99%

Fuzzy System Dynamics Risk Analysis (FuSDRA) of Autonomous Underwater Vehicle Operations in the Antarctic

et al. 2019

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With the maturing of autonomous technology and better accessibility, there has been a growing interest in the use of autonomous underwater vehicles (AUVs). The deployment of AUVs for under-ice marine science research in the Antarctic is one such example. However, a higher risk of AUV loss is present during such endeavors due to the extreme operating environment. To control the risk of loss, existing risk analyses approaches tend to focus more on the AUV's technical aspects and neglect the role of soft factors, such as organizational and human influences. In addition, the dynamic and complex interrelationships of risk variables are also often overlooked due to uncertainties and challenges in quantification. To overcome these shortfalls, a hybrid fuzzy system dynamics risk analysis (FuSDRA) is proposed. In the FuSDRA framework, system dynamics models the interrelationships between risk variables from different dimensions and considers the time-dependent nature of risk while fuzzy logic accounts for uncertainties. To demonstrate its application, an example based on an actual Antarctic AUV program is presented. Focusing on funding and experience of the AUV team, simulation of the FuSDRA risk model shows a declining risk of loss from 0.293 in the early years of the Antarctic AUV program, reaching a minimum of 0.206 before increasing again in later years. Risk control policy recommendations were then derived from the analysis. The example demonstrated how FuSDRA can be applied to inform funding and risk management strategies, or broader application both within the AUV domain and on other complex technological systems.

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“…Fuzzy logic can copy the judgment of the uncertainty concept and the way of reasoning thinking of the human brain by using fuzzy sets and fuzzy rules [45,46]. Meanwhile, the model considers the inherent uncertainty of ecological variables and enables expressing nonlinear relations between ecological variables in a transparent way [47,48].…”

Section: Fuzzy Logic-based Habitat Modelingmentioning

confidence: 99%

Analysis of an Ecological Flow Regime during the Ctenopharyngodon Idella Spawning Period Based on Reservoir Operations

Qin

Pei

et al. 2019

Water

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The study of fish habitats is important for us to better understand the impact of reservoir construction on river ecosystems. Many habitat models have been developed in the past few decades. In this study, a fuzzy logic-based habitat model, which couples fuzzy inference system, two-dimensional laterally averaged hydrodynamic model, and two-dimensional shallow water hydrodynamic model, is proposed to identify the baseline condition of suitable habitat for fish spawning activities. The proposed model considers the reservoir and the downstream river channel, and explores the comprehensive effects of water temperature, velocity, and water depth on habitat suitability. A real-world case that considers the Ctenopharyngodon idella in the Xuanwei Reservoir of Qingshui River is studied to investigate the effect of in- and outflow of reservoir on fish habitat and the best integrative management measure of the model. There were 64 simulations with different reservoir in- and outflows employed to calculate the weighted usable area and hydraulic habitat suitability. The experimental results show that the ecological flow for Ctenopharyngodon idella spawning can satisfy the basic demand when the reservoir inflow is greater than 60 m3/s and the reservoir outflow is greater than 100 m3/s. The habitat ecological suitability is the best when the reservoir outflow is 120 m3/s. A more reasonable and reliable ecological flow range can be obtained based on the habitat model in this paper, which provides the best scenario for water resources planning and management in the Qingshui River Basin.

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Fuzzy probability based fault tree analysis to propagate and quantify epistemic uncertainty

Cited by 56 publications

References 38 publications

Safety Analysis Technique for System with Limited Data: Case Study of the Multipurpose Research Reactor in Indonesia

Safety Analysis Technique for System with Limited Data: Case Study of the Multipurpose Research Reactor in Indonesia

Fuzzy System Dynamics Risk Analysis (FuSDRA) of Autonomous Underwater Vehicle Operations in the Antarctic

Analysis of an Ecological Flow Regime during the Ctenopharyngodon Idella Spawning Period Based on Reservoir Operations

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