A best-estimate assessment model was established to predict the entire life time of the material due to crack development and propagation in aggressive environment. Stress corrosion cracking (SCC) growth rate was modeled to investigate the influence of corrosion environment on SCC. Uncertainties with respect to material parameters, aggressive medium and mechanical loadings were taken into account. In addition, mean value estimation method (MVM) and monte carlo simulation method (MCS) were used to solve the established theoretical model. The studies demonstrated that the results obtained by using MVM reached agreement to those by using MCS. And the life time of the material due to the crack development and propagation in the aggressive environment was accurately predicted.
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ASME Turbo Expo 2012: Turbine Technical Conference and Exposition
June 11–15, 2012
Copenhagen, Denmark
Conference Sponsors:
- International Gas Turbine Institute
ISBN:
978-0-7918-4473-1
PROCEEDINGS PAPER
A Model to Predict the Stress Corrosion Cracking Growth Rate of the Metallic Materials
Guang Chen Jiao,
Guang Chen Jiao
Shanghai Jiao Tong University, Shanghai, China
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Gang Chen,
Gang Chen
Shanghai Electric Power Generation Equipment Co., Ltd. Shanghai Turbine Plant, Shanghai, China
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Wei Zhe Wang
Wei Zhe Wang
Shanghai Jiao Tong University, Shanghai, China
Search for other works by this author on:
Guang Chen Jiao
Shanghai Jiao Tong University, Shanghai, China
Gang Chen
Shanghai Electric Power Generation Equipment Co., Ltd. Shanghai Turbine Plant, Shanghai, China
Wei Zhe Wang
Shanghai Jiao Tong University, Shanghai, China
Paper No:
GT2012-69134, pp. 273-275; 3 pages
Published Online:
July 9, 2013
Citation
Jiao, GC, Chen, G, & Wang, WZ. "A Model to Predict the Stress Corrosion Cracking Growth Rate of the Metallic Materials." Proceedings of the ASME Turbo Expo 2012: Turbine Technical Conference and Exposition. Volume 7: Structures and Dynamics, Parts A and B. Copenhagen, Denmark. June 11–15, 2012. pp. 273-275. ASME. https://doi.org/10.1115/GT2012-69134
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