Monte Carlo Sensitivity and Uncertainty Analysis with Continuous-Energy Covariance Data
2017 · Nuclear Science and Engineering
저자
Dong Hyuk Lee, 심형진 (Hyung Jin Shim), Chang Hyo Kim
연구주제
Nuclear reactor physics and engineering · Nuclear and radioactivity studies
NTIS 과학기술표준분류
에너지/자원만에너지·환경·원자력 확장
지원 과제·AI 키워드로 잡을 근거가 없어 분류하지 않았다.
AI 연구 키워드·방법
continuous energy covariance data 핵자료 불확도
키워드 (OpenAlex)
Monte Carlo sensitivity analysis uncertainty analysis evaluated nuclear data libraries nuclear data uncertainty
초록
The continuous-energy Monte Carlo (MC) sensitivity and uncertainty (S/U) analysis conducted using the multigroup covariance matrices has a theoretical pitfall in that it is inconsistent with the principle of continuous-energy MC neutronics calculations because the use of the multigroup covariance matrices means treating covariance data as multigroup variables rather than continuous-energy variables. As a way to get around this deficiency and perform the MC S/U analysis on the theoretically consistent principle, this paper presents a new continuous-energy MC S/U formulation which directly utilizes the continuous-energy covariance data in the evaluated nuclear data libraries instead of the multigroup covariance matrices produced by nuclear data processing codes. The validity of the new MC S/U formulation is examined in terms of the input-nuclear-data-induced k uncertainty of the Godiva cri…
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교수 1
연구주제 1
Nuclear reactor physics and engineering