Reliability Study of the AP1000 Passive Safety System by Fuzzy Approach

Purba, Julwan Hendry; Tjahyani, D.T. Sony

doi:10.17146/aij.2014.271

Cited by 6 publications

(5 citation statements)

References 21 publications

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“…Two aspects of originalities of this study are (1) an introduction of fuzzy probabilities into fault tree analysis to describe the occurrence likelihoods of basic events, intermediate events and the top event; and (2) a substitution of Boolean algebra by fuzzy combination rules to quantify fault trees. This study is the further development of our previous studies in [15,19].…”

Section: Introduction mentioning

confidence: 64%

“…This number of experts has been properly implemeted in nuclear power plant safety assessment involving experts [15,19]. Those seven selected experts are then asked to qualitatively characterize the occurrence likelihoods of those 26 basic events.…”

Section: { }mentioning

confidence: 99%

“…To overcome this limitation, Purba and Sony Tjahyani [15] have utilized experts to qualitatively justify basic event reliability characteristics of the AP1000 safety systems. Due to imperfect knowledge or incomplete information, epistemic uncertainties are always involved in experts judgements [16].…”

Section: Introduction mentioning

confidence: 99%

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A Fuzzy Probability Algorithm for Evaluating the AP1000 Long Term Cooling System to Mitigate Large Break LOCA

Purba

2016

Atom Indo.

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Components of nuclear power plants do not always have historical failure data to probabilistically evaluate their reliability characteristics. To overcome this drawback, an alternative approach has been proposed by involving experts to qualitatively justify basic event likelihood occurences. However, expert judgments always involve epistemic uncertainty and this uncertainty needs to be quantified. Existing fault tree analysis quantifies uncertainty using Monte Carlo simulation, which is based on probability distributions. Since expert judgments are not described in probability distributions, Monte Carlo simulation is not appropriate for evaluating epistemic uncertainty. Therefore, a new approach needs to be developed to overcome this limitation. This study proposes a fuzzy probability algorithm to evaluate epistemic uncertainties in fault tree analysis. In the proposed algorithm, fuzzy probabilities are used to represent epistemic uncertainties of basic events, intermediate events, and the top event. To propagate and quantify epistemic uncertainty in fault tree analysis, a fuzzy multiplication rule and a fuzzy complementation rule are applied to substitute the AND Boolean and OR Boolean gates, respectively. To see the feasibility and applicability of the proposed algorithm, a case-based experiment on uncertainty evaluation of the AP1000 long term cooling system to mitigate the large break loss of coolant accident is discussed. The result shows that the best estimate probability to describe the failure of AP1000 long term cooling system generated by the proposed algorithmis 3.15×10-11 , which is very closed to the reference value of 1.11×10-11. This result confirms that the proposed algorithm offers a good alternative approach to quantify uncertainties in probabilistic safety assessment by fault tree analysis.

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Section: Introduction mentioning

confidence: 64%

Section: { }mentioning

confidence: 99%

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A Fuzzy Probability Algorithm for Evaluating the AP1000 Long Term Cooling System to Mitigate Large Break LOCA

Purba

2016

Atom Indo.

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“…FPFTA digunakan ketika data kegagalan kejadian dasar tidak tersedia. Sementara itu, analisis pohon kegagalan konvensional digunakan ketika kejadian dasar dari pohon kegagalan memiliki data keandalan (Purba, 2014b;Purba & Sony Tjahyani, 2014b;Purba dkk., 2015Purba dkk., , 2017Purba dkk., , 2022.…”

Section: A Analisis Pohon Kegagalan Berbasis Probabilitasunclassified

Analisis Keselamatan PLTN Berbasis Probabilitas Fuzzy

Purba¹

2023

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Teknologi PLTN dan teknologi sistem keselamatannya senantiasa berkembang seiring dengan perkembangan ilmu pengetahuan dan teknologi. Meskipun keandalan sistem keselamatan PLTN semakin baik, menihilkan kecelakaan dan risiko tetap tidak mungkin. Oleh karena itu, yang menjadi fokus peningkatan keandalan sistem keselamatan PLTN adalah memperkecil probabilitas kecelakaan dan menurunkan konsekuensi kecelakaan hingga tingkat risiko yang dapat diterima. Untuk dapat memperkirakan besarnya peluang terjadinya kecelakaan dan tingkat risiko dari pengoperasian PLTN maka perlu dilakukan analisis keselamatan probabilistik. Analisis keselamatan probabilistik konvensional memerlukan ketersediaan data kegagalan komponen. Tentunya PLTN yang masih dalam tahap disain atau yang belum pernah beroperasi tidak akan memiliki data kegagalan yang diperlukan. Kondisi ini menyebabkan penggunaan data generik menjadi tak terhindarkan. Hasil analisis dengan menggunakan data generik ini tentu saja tidak akan menggambarkan kondisi nyata dari sistem yang sedang dievaluasi, sehingga kurang tepat dijadikan sebagai bahan pertimbangan untuk meningkatkan keandalan sistem keselamatan. Oleh karena itu dikembangkanlah metode analisis keselamatan PLTN berbasis probabilitas fuzzy untuk mengevaluasi kinerja sistem keselamatan PLTN ketika data kegagalan komponen tidak tersedia. Metode baru ini memanfaatkan keilmuan, pengetahuan dan pengalaman yang dimiliki oleh pakar yang terlibat dalam mendisain dan mengembangkan reaktor tersebut. Metode analisis keselamatan probabilistik berbasis probabilitas fuzzy ini memiliki tiga fitur analisis yaitu analisis pohon kegagalan berbasis probabilitas fuzzy, analisis kritikalitas berbasis probabilitas fuzzy, dan analisis pohon kejadian berbasis probabilitas fuzzy. Untuk memudahkan pengguna, metode yang dikembangkan ini juga dilengkapi dengan perangkat lunak Intelligent Probabilistic Safety Assessment (IntelPSA). Metode analisis ini tentu saja akan memberikan kontribusi saintifik pada pengembangan teknologi keselamatan PLTN. Kontribusi saintifik yang pertama adalah FPPSA dapat menjadi komplemen untuk analisis keselamatan probabilistik konvensional ketika PLTN yang akan dievaluasi tidak memiliki data kegagalan komponen. Kontribusi saintifik yang kedua adalah konsep berpikir yang ditanamkan pada metode baru ini dapat menjadi acuan bagi para peneliti dalam mengembangkan metode analisis baru dengan penggunaan data kualitatif melalui justifikasi pakar berdasarkan keilmuan, pengetahuan dan pengalaman yang dimiliki ketika data kuantitatif tidak tersedia. Untuk aplikasi praktis, para pembuat kebijakan terkait dengan pembangunan dan pengoperasian PLTN pertama di Indonesia dapat mempertimbangkan untuk menggunakan perangkat lunak IntelPSA sebagai alat bantu untuk mengevaluasi keandalan sistem keselamatan PLTN yang dipilih sehingga pakar yang memahami teknologi dan sistem kerja dari reaktor nuklir yang akan dibangun dapat melakukan justifikasi secara kualitatif.

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“…Furthermore, Hadavi [2] developed accident scenarios and evaluated the performance of safety related systems of a typical WWER-1000 nuclear reactor also using FTA. FTA was also applied to evaluate the reliability of the Indian Prototype Fast Breeder Reactor [3], the failure probability of the containment spray injection system [4] and the reactor protection system [5] of a typical PWR, and the reliability of the AP1000 passive safety systems [6][7][8][9].…”

Section: Introduction mentioning

confidence: 99%

The Implementation of Importance Measure Approaches for Criticality Analysis in Fault Tree Analysis: A Review

Purba

Deswandri

2018

Jurnal Pengembangan Energi Nuklir

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THE IMPLEMENTATION OF IMPORTANCE MEASURE APPROACHES FOR CRITICALITY ANALYSIS IN FAULT TREE ANALYSIS: A REVIEW.Fault tree analysis (FTA) has been widely applied in nuclear power plant (NPP) probabilistic safety assessment to evaluate the reliability of a safety system. In FTA, criticality analysis is performed to identify the weakest paths in the system designs and components. For this purpose, an importance measure approach can be applied. Risk managers can apply information obtained from this analysis to improve safety by implementing risk reduction measure into the new design or build a more innovative design. Various importance measure approaches have been developed and proposed for criticality analysis in FTA. Each important measure approach offers specific purposes and advantages but has limitations. Therefore, it is necessary to understand characteristics of each approach in order to select the most appropriate approach to reach the purpose of the study. The objective of this study is to review the current implementations of importance measure approaches to rank individual basic events and/or minimal cut sets regarding their contributions to the unreliability or unavailability of NPP safety systems. This study classified importance measure approaches into two groups, i.e. probability–based importance measure approaches and fuzzy–based importance measure approaches. This study concluded that clear understanding of the purpose of the study, the type of reliability data at hands, and the uncertainty in the calculation need to be considered prior to the selection of the appropriate importance measure approach to the study of interest.

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Reliability Study of the AP1000 Passive Safety System by Fuzzy Approach

Cited by 6 publications

References 21 publications

A Fuzzy Probability Algorithm for Evaluating the AP1000 Long Term Cooling System to Mitigate Large Break LOCA

A Fuzzy Probability Algorithm for Evaluating the AP1000 Long Term Cooling System to Mitigate Large Break LOCA

Analisis Keselamatan PLTN Berbasis Probabilitas Fuzzy

The Implementation of Importance Measure Approaches for Criticality Analysis in Fault Tree Analysis: A Review

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