A predictive model for polyethylene cable insulation degradation in combined thermal and radiation environments

2018 ◽  
Vol 158 ◽  
pp. 119-123 ◽  
Author(s):  
Anna Vykydalová ◽  
Tibor Dubaj ◽  
Zuzana Cibulková ◽  
Gabriela Mizerová ◽  
Michal Zavadil
2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Xuan Wang

Cables in power generation and delivery are under high thermal stress cycles. Such high temperature can lead to cable insulation degradation, which will reduce the projected lifetime. Existing methods mainly focus on cable fault detection or insulation degradation mechanism. There is no existing tools for diagnosing the insulation degradation level and predicting the remaining useful life of the cable. The goal of my Ph.D. research is to develop reflectometry and data based approaches to monitor the health status of cables. The research will be conducted in three steps: (1) development of reflectometry based method to monitor the cable insulation degradation; (2) feature extraction and cable insulation degradation dynamic modeling based on the accelerated aging test data; (3) development of risksenstive particle filtering based fault diagnosis and prognosis algorithms for cable degradation; and (4) verification and validation the proposed solution with new experiment data and comparison with existing approaches.


Author(s):  
Yuan-Shang Chang ◽  
Ali Mosleh

Possible degradation of cable insulations exposed to radiation and heat is a safety and operational concern for nuclear power plants, particularly in the context of a license extension for the operation beyond original 40-year design life. Ethylene propylene rubber and silicone rubber are two major materials for the cable insulation. Degradation decreases the elongation at break of the insulation, which may lead to the exposure of the metal core in the cable, causing potential safety issues. This article proposes a mechanistic predictive model for the elongation at break as a function of time, temperature, and radiation dose rate. In the proposed model, the elongation at break curve is divided into an incubation section and a drop-off section with two parameters. In contrast to traditional deterministic approaches, this model projects the expected lifespan of cable insulation in the form of a probability distribution. The article also provides a validation of the model behavior using published experimental data.


2019 ◽  
Vol 13 (3) ◽  
pp. 363-369 ◽  
Author(s):  
Anan Zhang ◽  
Chunlin Gao ◽  
Wei Yang ◽  
Zhitong Zhou ◽  
Qian Li

1992 ◽  
Vol 14 (1) ◽  
pp. 24-28 ◽  
Author(s):  
K. Anandakumaran ◽  
D. J. Stonkus

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