Weibull and Bootstrap-Based Data-Analytics Framework for Fatigue Life Prognosis of the Pressurized Water Nuclear Reactor Component Under Harsh Reactor Coolant Environment
- Pusan National Univ., Busan (South Korea)
- Argonne National Lab. (ANL), Lemont, IL (United States)
In general, the fatigue life of a safety critical pressure component is estimated using best-fit fatigue life curves (S-N curves). These curves are estimated based on underlying in-air condition fatigue test data. The best-fitting approach requires a large safety factor to accommodate the uncertainty associated with large scatter in fatigue test data. In addition to this safety factor, reactor component fatigue life prognostics requires an additional correction factor that in general is also estimated deterministically. This additional factor known as the environmental correction factor Fen is to cater the effect of the harsh coolant environment that severely reduces the life of these components. The deterministic Fen factor may also lead to further conservative estimation of fatigue life leading to unnecessary early retirement of costly reactor components. To address the above-mentioned issues, we propose a data-analytics framework which uses Weibull and Bootstrap probabilistic modeling techniques for explicitly quantifying the uncertainty/scatter associated with fatigue life rather than estimating the lives based on a best-fit based deterministic approach. We assume the proposed probabilistic approach would provide the first hand information for assessing the maximum and minimum effects of pressurized water reactor water on the reactor component. In the discussed approach, in addition to the probabilistic fatigue curves, we suggest using a probabilistic environment correction factor Fen. Here, we assume the probabilistic fatigue curve and Fen would capture the S-N data scatter associated with the bulk effect of material grades, surface finish, strain rate, etc. on the material/component fatigue life.
- Research Organization:
- Argonne National Laboratory (ANL), Argonne, IL (United States)
- Sponsoring Organization:
- National Research Foundation of Korea (NRF); Korea Institute of Energy Technology Evaluation and Planning (KETEP); USDOE Office of Nuclear Energy (NE), Nuclear Reactor Technologies (NE-7). Light Water Reactor Sustainability Program
- Grant/Contract Number:
- AC02-06CH11357
- OSTI ID:
- 1579939
- Journal Information:
- Journal of Nondestructive Evaluation, Diagnostics and Prognostics of Engineering Systems, Vol. 3, Issue 1; ISSN 2572-3901
- Publisher:
- ASMECopyright Statement
- Country of Publication:
- United States
- Language:
- English
Similar Records
Statistical analysis of S—N type environmental fatigue data of Ni-base alloy welds using weibull distribution
Environmentally Assisted Fatigue in Light Water Reactor Environment
Related Subjects
pressurized water reactor
environmental fatigue
probabilistic life estimation
Weibull distribution
maximum likelihood estimation
Bootstrap method
data analytics
predictive modeling
probabilistic prognostics
reliability modeling
failure analysis
harsh or extreme environments
materials testing
mechanical engineering
service life prediction
structural engineering