(A) statistical prediction model for fuel elements failure using markov process and entropy minimax principles = 마르코프 프로세스와 엔트로피 최소 최대 원리를 이용한 핵연료 파손예측을 위한 통계적 모델

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A new approach of statistical model for prediction of fuel element failure is developed to take into account the effects of overall operating history and damaging environmental conditions. It is accomplished by the application of dynamic reliability function and entropy minimax principles. the degradation of material properties of fuel cladding is mainly caused by the combined effects of accumulated dynamic stresses, neutron irradiation, and chemical and stress corrosion at operating temperatures. Since the degradation of material properties due to these effects can be considered as a Markov process, a dynamic reliability function is derived based on the Markov process. It is utilized to describe the effects on fuel elements failure of damaging environmental conditions and overall operating history. Four damage parameters, namely dynamic stress, the magnitude of power increase from the preceding power level and with ramp rate, and fatigue cycles are used to build this statistical prediction model. The dynamic reliability function and damage parameters are used to obtain effective damage parameters. The entropy maximization principle is applied to generate probability density function of effective damage parameters. The entropy minimization principle is applied to determine weighting factors for combination of the failure probabilities of the respective failure modes. In this way, the effects of operating history and damaging environmental conditions and damage sequence are more fully take into account in model.
Advisors
Yoon, Young-KuChang, Soon-Heung윤용구장순흥
Description
한국과학기술원 : 핵공학과,
Publisher
한국과학기술원
Issue Date
1991
Identifier
61808/325007 / 000855411
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 핵공학과, 1991.2, [ x, 58 p. ]

Keywords

엔트로피 최소 최대 원리.

URI
http://hdl.handle.net/10203/48805
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=61808&flag=dissertation
Appears in Collection
NE-Theses_Ph.D.(박사논문)
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