کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8176782 | 1526383 | 2014 | 5 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Challenges and solutions for random sampling of parameters with extremely large uncertainties and analysis of the 232Th resonance covariances
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
فیزیک و نجوم
ابزار دقیق
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Challenges and solutions for random sampling of parameters with extremely large uncertainties and analysis of the 232Th resonance covariances Challenges and solutions for random sampling of parameters with extremely large uncertainties and analysis of the 232Th resonance covariances](/preview/png/8176782.png)
چکیده انگلیسی
Covariance data in the existing evaluated nuclear data libraries often include large relative uncertainties and mathematical inconsistencies, which arise especially in combination with random sampling. The 232Th evaluation from the ENDF/B-VII.1 library has been taken as an example. Possible solutions for mathematically impossible correlation matrices with negative eigenvalues and too low correlation coefficients between inherently positive parameters with large relative uncertainties are proposed. Convergence of the random sampling for lognormal distribution with extremely high relative standard deviations is slow by nature. Using weighted sampling, single parameters or a limited number of correlated parameters with large uncertainties can be sampled. Efficient sampling of a large number of correlated parameters with extremely large relative uncertainties remains unsolved.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment - Volume 743, 11 April 2014, Pages 39-43
Journal: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment - Volume 743, 11 April 2014, Pages 39-43
نویسندگان
Gašper Žerovnik, Andrej Trkov, Luiz C. Leal,