Assessing the Proliferation Resistance of Nuclear Fuel Cycle Systems Using a Fuzzy Logic-Based Barrier Method

Li, Jun; Yim, Man‐Sung; McNelis, David

doi:10.13182/nt08-a3957

Cited by 5 publications

(5 citation statements)

References 7 publications

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“…It adopts the similar procedures of the TOPS methodology and divides NFC into several steps and then uses the corresponding barriers to evaluate the PR performance of each NFC step. Nevertheless, FLB uses more barrier effectiveness levels (15 levels: ineffective minus I−, ineffective I, ineffective plus I+, low minus L−, low L, low plus L+, medium minus M−, medium M, medium plus M+, high minus H−, high H, high plus H+, very high minus VH−, very high VH, very high plus VH +), and employs a fuzzy logic model to quantify barrier effectiveness, which finally leads to a quantitative PR assessment 96 . Figure 6 shows the flow chart of the methodology.…”

Section: Non‐proliferation Assessment Methodologiesmentioning

confidence: 99%

“…The absolute value of each barrier is obtained from the available data of NFC, and is then normalized to a value in the range of 0‐1 according to the corresponding level partitions. Barrier effectiveness functions are thereafter used to calculate the fuzzy number of each barrier, aiming to capture the imprecise/uncertain nature of the available data/assessment,

\overset{A_{i}}{true} = ({}, x ∣ u_{\overset{false~}{A_{i}}} ((), x), i = 1, 2, \dots, N)

where

\overset{A_{i}}{true}

is the fuzzy number indicating barrier effectiveness of barrier i (11 barriers covering material and technical aspects are applied), x is the relative PR of barrier i with its value in the range of [0, 1],

u_{\overset{false~}{A_{i}}} ((), x)

is the membership function of x representing how much degree x belongs to barrier effectiveness level

\overset{A}{true}

(15 levels) and can be calculated by using any one of fuzzy number shapes, such as a triangle shape with or without overlap, or a Gaussian shape 96 …”

Section: Non‐proliferation Assessment Methodologiesmentioning

confidence: 99%

“…Together with the weight factor ( W ) at each NFC step, the fuzzy number function and relative PR of an NFC system can finally be obtained by 96

u_{{\overset{S}{true}}_{s}} ((), x_{{\overset{false~}{S}}_{s}}) = \frac{\sum_{j = 1}^{M} W ((), j) u_{\overset{false~}{S_{j}}} ((), x_{{\overset{false~}{S}}_{j}})}{\sum_{j = 1}^{M} W ((), j)}, normalF ((), \overset{false~}{u}) = \frac{\int x u_{\overset{false~}{u}} ((), x) italicdx}{\int u_{\overset{false~}{u}} ((), x) italicdx}

…”

Section: Non‐proliferation Assessment Methodologiesmentioning

confidence: 99%

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Nuclear non‐proliferation review and improving proliferation resistance assessment in the future

et al. 2020

Int J Energy Res

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Summary An increasing number of countries have taken nuclear energy as a preferred approach in response to the environment deterioration and energy supply deficit. The rapid expansion of nuclear technologies, however, would pose a great challenge to nuclear non‐proliferation, especially for the Generation IV nuclear reactor systems, which significantly differ from current nuclear fuel systems. This paper gives an overview of non‐proliferation research activities worldwide and outlines the existing problems, especially in non‐proliferation assessment. Because of numerous processes and various types of variables involved in nuclear fuel cycles (NFC), it is difficult to obtain a quantitative and objective assessment on non‐proliferation. In addition, the influences imposed by national nuclear policy on non‐proliferation have been rarely studied because of their large uncertainties, which may not precisely reflect the real non‐proliferation status in a specific country. In view of the above issues, we put forward an assessment framework by considering impact factors of national nuclear policy and by employing multi‐mathematical models to address some of the issues including subjectivity and uncertainties in the current assessment methodologies.

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Section: Non‐proliferation Assessment Methodologiesmentioning

confidence: 99%

\overset{A_{i}}{true} = ({}, x ∣ u_{\overset{false~}{A_{i}}} ((), x), i = 1, 2, \dots, N)

where

\overset{A_{i}}{true}

u_{\overset{false~}{A_{i}}} ((), x)

is the membership function of x representing how much degree x belongs to barrier effectiveness level

\overset{A}{true}

(15 levels) and can be calculated by using any one of fuzzy number shapes, such as a triangle shape with or without overlap, or a Gaussian shape 96 …”

Section: Non‐proliferation Assessment Methodologiesmentioning

confidence: 99%

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Nuclear non‐proliferation review and improving proliferation resistance assessment in the future

et al. 2020

Int J Energy Res

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“…Table 2 represents the 12 linguistic values used for measuring Japan's energy security in this study. Membership functions can be described in several manners such as triangle, trapezoid, or Gaussian distribution, but as it has been reported that the difference of shape of membership function can hardly influence the final result [24], the triangular membership function is adopted in this study. Table 3.…”

Section: Quantitative Analysis Of Japan's Energy Security Before and mentioning

confidence: 99%

“…The methodology for the quantification is based on the studies of nuclear fuel cycle proliferation resistance evaluation by using fuzzy logic [24,25] and will be described briefly as follows.…”

Section: Quantitative Analysis Of Japan's Energy Security Before and mentioning

confidence: 99%

Quantitative Analysis of Japan’s Energy Security Based on Fuzzy Logic: Impact Assessment of Fukushima Accident

Yamanishi¹,

Takahashi²,

Unesaki³

2017

Journal of Energy

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The Fukushima accident of March 2011 had great political, economic, and social impacts on Japan and marked a very important turning point in Japan's energy policy. As the accident has also greatly exposed the vulnerability of Japan's energy security, it is crucial to clarify the path that Japan should take to maintain and secure its energy security in case of any possible future outbreak that may threaten its energy security. For this purpose, we conducted a comprehensive and structural analysis of Japan's energy security based on APERC's 4As framework and by using fuzzy logic and the Fuzzy-DEMATEL method to quantitatively understand the performance of Japan's energy security and how the Fukushima accident had impacted the performance. Our results demonstrate that Japan's energy security has clearly degraded after experiencing Fukushima accident. In addition, the results of the structural analysis by the Fuzzy-DEMATEL method show that the most salient dimension in the 4As framework for improving Japan's energy security is the "Availability" dimension, and for this purpose nuclear energy and renewables play very important roles in securing the future energy security in Japan; this is consistent with the current energy policy measures announced in the Strategic Energy Plan of 2014.

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Comparison of proliferation resistance among natural uranium, thorium–uranium, and thorium–plutonium fuels used in CANada Deuterium Uranium in deep geological repository by combining multiattribute utility analysis with transport model

Nagasaki¹,

Wang²,

Buijs³

2018

Nuclear Engineering and Technology

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Assessing the Proliferation Resistance of Nuclear Fuel Cycle Systems Using a Fuzzy Logic-Based Barrier Method

Cited by 5 publications

References 7 publications

Nuclear non‐proliferation review and improving proliferation resistance assessment in the future

Nuclear non‐proliferation review and improving proliferation resistance assessment in the future

Quantitative Analysis of Japan’s Energy Security Based on Fuzzy Logic: Impact Assessment of Fukushima Accident

Comparison of proliferation resistance among natural uranium, thorium–uranium, and thorium–plutonium fuels used in CANada Deuterium Uranium in deep geological repository by combining multiattribute utility analysis with transport model

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