A New Importance Measure for Sensitivity Analysis

LIU, Qiao; Homma, Tetsuya

doi:10.3327/jnst.47.53

Cited by 5 publications

(7 citation statements)

References 29 publications

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“…Several global sensitivity measures have been proposed [12][13][14][15][16][17]. Among them, the first-order sensitivity index [14] and the total-order sensitivity index [15] are popularly used.…”

Section: Global Sensitivity Analysis Methodsmentioning

confidence: 99%

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Sensitivity analysis of a passive decay heat removal system under a post-loss of coolant accident condition

Homma

2012

Journal of Nuclear Science and Technology

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Passive safety features are now of interest to the design of future generation reactors because of their peculiar characteristics of simplicity, reduction of human interaction, and avoidance of failures of active components. However, the large uncertainty associated with the responses of passive systems might not be ignored. Therefore, it is necessary to identify the uncertain inputs that have the important impact on the uncertainty of the system performance. In this study, two global sensitivity measures, the first-order sensitivity index and the total-order sensitivity index, are applied to a natural circulation decay heat removal system of a gas-cooled fast reactor for identifying the important system inputs. It is found that the uncertainty in the system pressure contributes the most to the uncertainty in the system outputs. In addition, the cooler (the heat exchanger of the emergency cooling system) wall temperature, the Nusselt number in the mixed convection regime, and the friction factor in the mixed convection flow regime also have small impact on the uncertainty of the system outputs.

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Section: Global Sensitivity Analysis Methodsmentioning

confidence: 99%

“…If the distributions of the model outputs are highly skewed, variance will not be suitable to represent uncertainty. In this case, other sensitivity indices, such as the indicator proposed by Liu and Homma [17], might be suitable.…”

Section: Uncertainty Analysis Of the Model Outputsmentioning

confidence: 99%

Sensitivity analysis of a passive decay heat removal system under a post-loss of coolant accident condition

Homma

2012

Journal of Nuclear Science and Technology

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“…Generally, SA can be divided into two main branches [2,3]: local SA and global SA. Recently, global SA is widely investigated and lots of global SA techniques have emerged, such as non-parametric techniques [4], variance-based techniques [5][6][7], and moment-independent techniques [8][9][10][11][12][13]. In References [14,15], Borgonovo and co-workers ascribed the latter two kinds of sensitivity indices to the same rationale and proved some general results according to their properties.…”

Section: Introductionmentioning

confidence: 99%

An efficient method for estimating global sensitivity indices

Yun

Lü

Jiang

et al. 2016

Numerical Meth Engineering

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Summary An efficient method is proposed to estimate the first‐order global sensitivity indices based on failure probability and variance by using maximum entropy theory and Nataf transformation. The computational cost of this proposed method is quite small, and the proposed method can efficiently overcome the ‘dimensional curse’ due to dimensional reduction technique. Ideas for the estimation of higher‐order sensitivity indices are discussed. Copyright © 2016 John Wiley & Sons, Ltd.

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“…(10) During the past few decades, a large number of indices have been developed by different researchers for global SA. (11)(12)(13)(14)(15)(16)(17) Among all these SA indices, the variance-based one proposed by Sobol and Homma and Saltelli (11,12) and the moment-independent one (also called delta index) proposed by Borgonovo (17) have gained the most attention.…”

Section: Introductionmentioning

confidence: 99%

Moment‐Independent Sensitivity Analysis Using Copula

2013

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In risk assessment, the moment-independent sensitivity analysis (SA) technique for reducing the model uncertainty has attracted a great deal of attention from analysts and practitioners. It aims at measuring the relative importance of an individual input, or a set of inputs, in determining the uncertainty of model output by looking at the entire distribution range of model output. In this article, along the lines of Plischke et al., we point out that the original moment-independent SA index (also called delta index) can also be interpreted as the dependence measure between model output and input variables, and introduce another moment-independent SA index (called extended delta index) based on copula. Then, nonparametric methods for estimating the delta and extended delta indices are proposed. Both methods need only a set of samples to compute all the indices; thus, they conquer the problem of the "curse of dimensionality." At last, an analytical test example, a risk assessment model, and the levelE model are employed for comparing the delta and the extended delta indices and testing the two calculation methods. Results show that the delta and the extended delta indices produce the same importance ranking in these three test examples. It is also shown that these two proposed calculation methods dramatically reduce the computational burden.

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A New Importance Measure for Sensitivity Analysis

Cited by 5 publications

References 29 publications

Sensitivity analysis of a passive decay heat removal system under a post-loss of coolant accident condition

Sensitivity analysis of a passive decay heat removal system under a post-loss of coolant accident condition

An efficient method for estimating global sensitivity indices

Moment‐Independent Sensitivity Analysis Using Copula

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