Bayesian analysis method on processing reliability data of high flux engineering test reactor

2020 ◽  
Vol 199 ◽  
pp. 106912 ◽  
Author(s):  
Hui Bao ◽  
Yun Guo ◽  
Hang Zhang ◽  
Changhong Peng ◽  
Jianchao Lu
2021 ◽  
Author(s):  
Tri Tam Le

I give some benefits of the Bayesian analysis method from my personal experience in psychological research.


Author(s):  
Xuan Huang ◽  
Pingchuan Shen ◽  
Shuai Liu ◽  
Jian Liu ◽  
Xiaozhou Jiang ◽  
...  

Abstract High flux reactor is an important engineering test reactor, which can be used in irradiation research of materials, chemistry, isotopes, medicine and other fields. In the high flux reactor coolant system, there are a large number of nuclear pipes and the layout is complex. The optimization of seismic analysis method for reactor coolant system is an important part in the design process to ensure the nuclear pipes meet the design specifications. The traditional single point response spectrum method needs to envelope the response spectrum of different floors as the analysis input. This method is difficult to give the reasonable seismic load to the numerous nuclear pipes and it will increase the design cost and the difficulty of safety analysis about nuclear pipe. In this paper, an optimized seismic analysis method of reactor coolant system is proposed. By using the multi-point response spectrum method, the optimization of different excitation loading modes for different constrained support points is realized. The analysis results show that the multi-point response spectrum method can solve the problem that different support points are located at different elevation floors in the reactor coolant system, which makes the calculation results more accurate and reasonable. Compared with the traditional method, it can make the design more efficient and practical.


Author(s):  
Jinlin Liu ◽  
Wanhong Wang ◽  
Changhong Peng ◽  
Yun Guo

PSA is found to be a valuable tool for improving the safety and reliability of nuclear reactors due to intense involvement of human interactions in an experimental facility. It may also be advantageously applied to research reactors under design and construction. This paper demonstrates the study and result of a Level 1 internal initiating event PSA under the power operation mode to the High Flux Engineering Test Reactor (HFETR) which is under design and construction. The occurrence frequency of core damage which may potentially arise in HFETR is evaluated by using RiskSpectrum software, and event trees have been used to study the response of the installation to various initiating events whereas fault trees have been used in the modeling of safety system failures. Calculation results show that core damage frequency for HFETR research reactor is 5.28E−07 per year, and initiating events which have a significant contribution to CDF are loss of coolant water and loss of offsite power.


Universe ◽  
2019 ◽  
Vol 5 (2) ◽  
pp. 61 ◽  
Author(s):  
Alexander Ayriyan ◽  
David Alvarez-Castillo ◽  
David Blaschke ◽  
Hovik Grigorian

We develop a Bayesian analysis method for selecting the most probable equation of state under a set of constraints from compact star physics, which now include the tidal deformability from GW170817. We apply this method for the first time to a two-parameter family of hybrid equations of state that is based on realistic models for the hadronic phase (KVORcut02) and the quark matter phase (SFM α ) which produce a third family of hybrid stars in the mass–radius diagram. One parameter ( α ) characterizes the screening of the string tension in the string-flip model of quark matter while the other ( Δ P ) belongs to the mixed phase construction that mimics the thermodynamics of pasta phases and includes the Maxwell construction as a limiting case for Δ P = 0 . We present the corresponding results for compact star properties like mass, radius and tidal deformabilities and use empirical data for them in the newly developed Bayesian analysis method to obtain the probabilities for the model parameters within their considered range.


2020 ◽  
Author(s):  
Carlo Graziani

AbstractWe describe a simplified Bayesian analysis of vaccine trial data, in which a reparametrization of the Poisson likelihood leads to a factorization in which the protective vaccine efficacy VES and the nuisance parameter appear in different factors. As a consequence the posterior density acquires a factorized form, and marginalization over the nuisance parameter is trivial. Estimates of VES accordingly become a matter of simple manipulations of one-dimensional posterior probability densities. We demonstrate the method using the publically-released data on the efficacy of three vaccines agains SARS-CoV-2: the final Phase III data from the Pfizer/BioNTech and Moderna mRNA vaccines and the interim data released for the Sputnik V adenovirus-based vaccine.


1985 ◽  
Vol 15 ◽  
pp. 313-321 ◽  
Author(s):  
Zhang Mingchang ◽  
Zhao Yiyu ◽  
Shen Degui
Keyword(s):  

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