Material degradation analysis and maintenance decisions based on material condition monitoring during in-service inspections

Technical Report · Fri Mar 01 00:00:00 EST 1996

DOI:https://doi.org/10.2172/380364· OSTI ID:380364

Yacout, A M; Orechwa, Y

The degradation of the material in critical components is shown to be an effective measure which can be used to compute the risk adjusted economic penalty associated with different maintenance decisions. The approach of estimating the probability, with confidence interval, of the time that a prescribed degradation level is exceeded is shown to be practical, as demonstrated in the analysis of irradiated fuel cladding. The methodology for the estimation of the probability is predicated on the existence of a parsimonious and robust mixed-effects model of the evolution of the degradation. This model, in general, relates measured surrogates of the degradation level to computed or measured variables, which characterize the environment during the operating history of the component. We propose and demonstrate the efficacy of using an artificial neural network, constructed via a genetic supervisor, as an aid in developing the requisite mixed-effects model and testing its continued validity as new data are obtained.

• Research Organization: Argonne National Lab. (ANL), Argonne, IL (United States)
• Sponsoring Organization: USDOE, Washington, DC (United States)
• DOE Contract Number: W-31109-ENG-38
• OSTI ID: 380364
• Report Number(s): ANL-FRA-1996-2; ON: DE97000493; TRN: 96:028442
• Resource Relation: Other Information: PBD: Mar 1996
• Country of Publication: United States
• Language: English

Related Subjects

22 NUCLEAR REACTOR TECHNOLOGY
20 FOSSIL-FUELED POWER PLANTS
99 MATHEMATICS
COMPUTERS
INFORMATION SCIENCE
MANAGEMENT
LAW
MISCELLANEOUS
EQUIPMENT
FAILURES
MATERIALS
MAINTENANCE
DECISION MAKING
COST
REACTOR COMPONENTS
MONITORING
PROBABILITY
NEURAL NETWORKS
POWER PLANTS
SERVICE LIFE
ECONOMICS
REPAIR
CLADDING
FUEL PINS