scholarly journals Timed Fault Tree Models of the China Yongwen Railway Accident

Author(s):  
Yu Lu ◽  
Zhaoguang Peng ◽  
Alice Miller ◽  
Tingdi Zhao ◽  
Chris Johnson
Keyword(s):  
2021 ◽  
Author(s):  
Jaden C. Miller ◽  
Spencer C. Ercanbrack ◽  
Chad L. Pope

Abstract This paper addresses the use of a new nuclear power plant performance risk analysis tool. The new tool is called Versatile Economic Risk Tool (VERT). VERT couples Idaho National Laboratory’s SAPHIRE and RAVEN software packages. SAPHIRE is traditionally used for performing probabilistic risk assessment and RAVEN is a multi-purpose uncertainty quantification, regression analysis, probabilistic risk assessment, data analysis and model optimization software framework. Using fault tree models, degradation models, reliability data, and economic information, VERT can assess relative system performance risks as a function of time. Risk can be quantified in megawatt hours (MWh) which can be converted to dollars. To demonstrate the value of VERT, generic pressurized water reactor and boiling water reactor fault tree models were developed along with time dependent reliability data to investigate the plant systems, structures, and components that impacted performance from the year 1980 to 2020. The results confirm the overall notion that US nuclear power plant industry operational performance has been improving since 1980. More importantly, the results identify equipment that negatively or positively impact performance. Thus, using VERT, individual plant operators can target systems, structures, and components that merit greater attention from a performance perspective.


2017 ◽  
Vol 14 (9) ◽  
pp. 517-522 ◽  
Author(s):  
Tszhim J. Leung ◽  
Jason H. Rife ◽  
Peter Seiler ◽  
Raghu Venkataraman

2015 ◽  
Vol 29 (29) ◽  
pp. 1550203
Author(s):  
Huanqing Cui ◽  
Li Cai ◽  
Sen Wang ◽  
Xiaoqiang Liu ◽  
Xiaokuo Yang

Probabilistic transfer matrix (PTM) is a widely used model in the reliability research of circuits. However, PTM model cannot reflect the impact of input signals on reliability, so it does not completely conform to the mechanism of the novel field-coupled nanoelectronic device which is called quantum-dot cellular automata (QCA). It is difficult to get accurate results when PTM model is used to analyze the reliability of QCA circuits. To solve this problem, we present the fault tree models of QCA fundamental devices according to different input signals. After that, the binary decision diagram (BDD) is used to quantitatively investigate the reliability of two QCA XOR gates depending on the presented models. By employing the fault tree models, the impact of input signals on reliability can be identified clearly and the crucial components of a circuit can be found out precisely based on the importance values (IVs) of components. So this method is contributive to the construction of reliable QCA circuits.


2021 ◽  
Author(s):  
Yassmeen Elderhalli ◽  
Nahla El-Araby ◽  
Osman Hasan ◽  
Axel Jantsch ◽  
Sofiene Tahar

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