Probability evaluation of localized failure

2014 ◽  
pp. 1197-1201
Author(s):  
D _yd_ba ◽  
A Ró_a_ski ◽  
M Sobótka
Keyword(s):  
Probability Evaluation ◽  
Localized Failure

PROBABILITY EVALUATION OF TSUNAMI HEIGHT ALONG THE COAST OF TOKUSHIMA PREFECTURE USING RANDOM PHASE MODEL

2020 ◽  
Vol 76 (2) ◽  
pp. I_367-I_372
Author(s):  
Tomohiro YASUDA ◽  
Haruki TANAKA ◽  
Kohei SHIGETA ◽  
Junichi TANIGUCHI ◽  
Toshikazu KITANO
Keyword(s):  
Random Phase ◽  
Phase Model ◽  
Tsunami Height ◽  
Probability Evaluation

Break probability evaluation for a weld in piping of the water-cooled ceramic breeder blanket for CFETR

2019 ◽  
Vol 147 ◽  
pp. 111236
Author(s):  
Qingzhu Liang ◽  
Yun Guo ◽  
Changhong Peng ◽  
Dianle Wang ◽  
Jianchao Lu
Keyword(s):  
Probability Evaluation

scholarly journals STATISTICAL PROBABILITY EVALUATION OF OPERATING ITS

Transport ◽  
2010 ◽  
Vol 25 (2) ◽  
pp. 163-170 ◽  
Author(s):  
Adolfas Baublys ◽  
Aldona Jarašūnienė
Keyword(s):  
Analytical Description ◽  
Statistical Information ◽  
Transport Systems ◽  
Statistical Probability ◽  
Intelligent Transport ◽  
Loop Detectors ◽  
Probability Evaluation ◽  
Control Technologies ◽  
And Control

Intelligent Transport Systems (ITS) work with information and control technologies providing the core of ITS functions. Some of these technologies like loop detectors are well known to transportation professionals. However, there are a number of less familiar technologies and system concepts that are keys to ITS functions. Although information and control technologies act as a technical core of ITS, human factors also remain vitally important and potentially very complex issues. The process of operating ITS is influenced by a number of random factors. Along with an assessment of dependence upon separate random factors, the classification of those in the whole hierarchical structure of operating ITS is presented. Statistical information on operating ITS is renewed and replenished in the course of time. With the growth of information amounts, the costs of storing them also increase. Therefore, the article presents relevant algorithms for obtaining required statistical assessments with the least statistical information. It is deduced that while modelling the process of operating ITS, an analytical description of random factors applying non‐parametric assessment is suitable.

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