A Statistical Model for Prediction of Fuel Element Failure Using the Markov Process and Entropy Minimax Principles

1991 ◽  
Vol 93 (2) ◽  
pp. 195-205 ◽  
Author(s):  
Kie-Yong Choi ◽  
Young-Ku Yoon ◽  
Soon-Heung Chang
Keyword(s):  
Markov Process ◽  
Fuel Element ◽  
Statistical Model ◽  
Element Failure

Thermal-hydraulics analysis during fuel element failure in an operating PWR

2015 ◽  
Vol 85 ◽  
pp. 694-700 ◽  
Author(s):  
Wenzhen Chen ◽  
Lei Yang ◽  
Hongguang Xiao ◽  
Zhiyun Chen
Keyword(s):  
Fuel Element ◽  
Thermal Hydraulics ◽  
Element Failure

γ-Ray spectral analysis method for real-time detection of fuel element failure

2019 ◽  
Vol 133 ◽  
pp. 221-226 ◽  
Author(s):  
Guoxiu Qin ◽  
Qimin Wang ◽  
Youning Xu ◽  
Xilin Chen ◽  
Fan Li ◽  
...  
Keyword(s):  
Spectral Analysis ◽  
Fuel Element ◽  
Real Time ◽  
Analysis Method ◽  
Spectral Analysis Method ◽  
Element Failure ◽  
Γ Ray ◽  
Real Time Detection

Explicit solution of an optimal stopping problem: the burn-in of conditionally exponential components

1997 ◽  
Vol 34 (1) ◽  
pp. 267-282 ◽  
Author(s):  
C. Costantini ◽  
F. Spizzichino
Keyword(s):  
Markov Process ◽  
Statistical Model ◽  
Optimal Stopping ◽  
Continuous Time ◽  
Explicit Solution ◽  
Prior Distribution ◽  
Unknown Parameter ◽  
Two Dimensional ◽  
Optimal Stopping Problem ◽  
Optimal Duration

We consider the problem of the optimal duration of a burn-in experiment for n identical units with conditionally exponential life-times of unknown parameter Λ. The problem is formulated as an optimal stopping problem for a suitably defined two-dimensional continuous-time Markov process. By exploiting monotonicity properties of the statistical model and of the costs we prove that the optimal stopping region is monotone (according to an appropriate definition) and derive a set of equations that uniquely determine it and that can be easily solved recursively. The optimal stopping region varies monotonically with the costs. For the class of problems corresponding to a prior distribution on Λ of type gamma it is shown how the optimal stopping region varies with respect to the prior distribution and with respect to n.

Explicit solution of an optimal stopping problem: the burn-in of conditionally exponential components

1997 ◽  
Vol 34 (01) ◽  
pp. 267-282
Author(s):  
C. Costantini ◽  
F. Spizzichino
Keyword(s):  
Markov Process ◽  
Statistical Model ◽  
Optimal Stopping ◽  
Continuous Time ◽  
Explicit Solution ◽  
Prior Distribution ◽  
Unknown Parameter ◽  
Two Dimensional ◽  
Optimal Stopping Problem ◽  
Optimal Duration

We consider the problem of the optimal duration of a burn-in experiment for n identical units with conditionally exponential life-times of unknown parameter Λ. The problem is formulated as an optimal stopping problem for a suitably defined two-dimensional continuous-time Markov process. By exploiting monotonicity properties of the statistical model and of the costs we prove that the optimal stopping region is monotone (according to an appropriate definition) and derive a set of equations that uniquely determine it and that can be easily solved recursively. The optimal stopping region varies monotonically with the costs. For the class of problems corresponding to a prior distribution on Λ of type gamma it is shown how the optimal stopping region varies with respect to the prior distribution and with respect to n.

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