2016
DOI: 10.13182/nse15-80
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Second-Order Adjoint Sensitivity and Uncertainty Analysis of a Heat Transport Benchmark Problem—II: Computational Results Using G4M Reactor Thermal-Hydraulic Parameters

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Cited by 14 publications
(15 citation statements)
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“…As has been shown in [15][16][17][18], the 2nd-order response sensitivities have the following major impacts on the computed moments of the response distribution: (a) they cause the "expected value of the response" to differ from the "computed nominal value of the response"; and (b) they contribute decisively to causing asymmetries in the response distribution. Indeed, neglecting the second-order sensitivities would nullify the third-order response correlations, and hence would nullify the skewness of the response.…”
Section: Discussionmentioning
confidence: 95%
“…As has been shown in [15][16][17][18], the 2nd-order response sensitivities have the following major impacts on the computed moments of the response distribution: (a) they cause the "expected value of the response" to differ from the "computed nominal value of the response"; and (b) they contribute decisively to causing asymmetries in the response distribution. Indeed, neglecting the second-order sensitivities would nullify the third-order response correlations, and hence would nullify the skewness of the response.…”
Section: Discussionmentioning
confidence: 95%
“…The definition of "system parameters" used in this work include, in the most comprehensive sense, all computational input data, correlations, initial and/or boundary conditions, etc. The 2 nd -ASAM builds on the "first-order adjoint sensitivity analysis methodology" (1 st -ASAM) for nonlinear systems originally introduced ( [11,12]) and developed ( [13]) by Cacuci; see also…”
Section: Discussionmentioning
confidence: 99%
“…Since the comparative discussion presented in [1] continues to remain valid in the context of the new 2 nd -ASAM for nonlinear systems which will be introduced in this work, that discussion will not be repeated here. The efficiency of the "2 nd -ASAM for linear systems" for computing exactly first-and second-order sensitivities (i.e., functional derivatives) of model responses to model parameters has since been also demonstrated [9][10][11] in several recent applications to particle diffusion and heat transport problems.…”
Section: Introductionmentioning
confidence: 99%
“…In general, the model parameters are experimentally derived quantities and are therefore For illustrating the effects of second-order response sensitivities for the paradigm nonlinear heat conduction benchmark considered in this work, it suffices to take from Ref. [7] response correlations up to third-order, for the very simple case when: (i) the parameters are uncorrelated and normally distributed; and (ii) only the first-and second-order response sensitivities are available. For these particular conditions, the response correlations derived in [7] reduce to the following expressions for the first three response moments:…”
Section: Application Of the 2 Nd -Asam For Quantifying Non-gaussianmentioning
confidence: 99%
“…The 2 nd -ASAM builds on the first-order adjoint sensitivity analysis methodology (1 st -ASAM) for nonlinear systems originally introduced in [2,3], and extends the work presented in [4]. For as has been shown in [5][6][7].…”
Section: Introductionmentioning
confidence: 99%