کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
804094 1467868 2015 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Global response sensitivity analysis using probability distance measures and generalization of Sobol's analysis
ترجمه فارسی عنوان
تجزیه و تحلیل حساسیت پاسخ جهانی با استفاده از احتمالات اندازه گیری فاصله و تعمیم تجزیه و تحلیل سوبول
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی مکانیک
چکیده انگلیسی


• Development of global response sensitivity analysis procedures when input variables are dependent and non-Gaussian distributed, based on L2L2 norm and Hellinger distance.
• Examining the relation between Sobol's and L2L2 norm based analyses and demonstration that L2L2 norm based analysis is a generalization of the Sobol analysis.

The study introduces two new alternatives for global response sensitivity analysis based on the application of the L2L2-norm and Hellinger's metric for measuring distance between two probabilistic models. Both the procedures are shown to be capable of treating dependent non-Gaussian random variable models for the input variables. The sensitivity indices obtained based on the L2L2-norm involve second order moments of the response, and, when applied for the case of independent and identically distributed sequence of input random variables, it is shown to be related to the classical Sobol's response sensitivity indices. The analysis based on Hellinger's metric addresses variability across entire range or segments of the response probability density function. The measure is shown to be conceptually a more satisfying alternative to the Kullback–Leibler divergence based analysis which has been reported in the existing literature. Other issues addressed in the study cover Monte Carlo simulation based methods for computing the sensitivity indices and sensitivity analysis with respect to grouped variables. Illustrative examples consist of studies on global sensitivity analysis of natural frequencies of a random multi-degree of freedom system, response of a nonlinear frame, and safety margin associated with a nonlinear performance function.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Probabilistic Engineering Mechanics - Volume 41, July 2015, Pages 21–33
نویسندگان
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