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A predictive model for polyethylene cable insulation degradation in combined thermal and radiation environments
Reliable prediction of material service lifetime is important for ensuring safe operation in safety-critical systems such as nuclear facilities. Materials in these environments degrade due to several simultaneous effects, most important stressors are heat and radiation. In this work, samples of medi...
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Published in: | Polymer degradation and stability 2018-12, Vol.158, p.119-123 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Reliable prediction of material service lifetime is important for ensuring safe operation in safety-critical systems such as nuclear facilities. Materials in these environments degrade due to several simultaneous effects, most important stressors are heat and radiation. In this work, samples of medium density polyethylene cable insulation were subjected to thermal (110 °C) and γ-radiation stress (500 Gy h−1); a combined thermal and radiation test (85 °C and 4.5 Gy h−1) was also performed. Stability of cable insulation was studied by differential scanning calorimetry and isoconversional kinetic analysis employing a non-Arrhenian temperature function was carried out. From the dependence of residual stability on the degradation dose a predictive model for the cable service life was developed based on the thermal and radiation stress tests; the model validity was verified using the combined stress test results. The model assumes a first-order exponential decay of the residual stability with degradation dose. It allows to predict the degree of insulation damage in wide range of environmental conditions as both temperature and radiation dose effects are considered and radiation dose rate effect is also taken into account.
•Stability of PE insulation after thermal, radiation and combined ageing was determined.•Residual stability of the cable insulation after an artificial ageing was calculated.•A predictive model for degradation in combined environment was developed.•The model enables to predict service life for any given temperature and dose rate conditions. |
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ISSN: | 0141-3910 1873-2321 |
DOI: | 10.1016/j.polymdegradstab.2018.11.002 |