Significance of Lagrange multipliers in cross-section adjustment

Wagschal, J. J.; Yeivin, Y.

doi:10.2172/5281859

Cited by 3 publications

(2 citation statements)

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“…(3), using Lagrange multipliers, in [5,6], and in a more elegant way in [7]. This method has important advantages over the alternative method of using the linearity, Eq.…”

Section: The Adjustment Formulasmentioning

confidence: 99%

Some Insight into the Generalized Linear Least Squares Parameter Adjustment Methodology

Wagschal

2016

EPJ Web of Conferences

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Abstract. Some features of the generalized linear least squares parameter adjustment procedure have been discussed and proved. In particular: the equivalence of the adjusted measured response values and their recalculated values with the adjusted parameters, the proper way to iterate when the responses are not a linear function of the parameters and the equivalence of the simultaneous adjustment of the parameters with two not correlated measured responses and the consecutive adjustment first with one response and then with the second response.

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“…(3), using Lagrange multipliers, in [5,6], and in a more elegant way in [7]. This method has important advantages over the alternative method of using the linearity, Eq.…”

Section: The Adjustment Formulasmentioning

confidence: 99%

Some Insight into the Generalized Linear Least Squares Parameter Adjustment Methodology

Wagschal

2016

EPJ Web of Conferences

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“…The TSURFER) module of the ORNL's SCALE code system [1] uses the generalized linear least squares (GLLS) approach to reduce discrepancies between the measured and calculated responses by adjusting nuclear data and experimental values [2]. Traditionally, TSURFER has only been applied to criticality experiments.…”

Section: Introductionmentioning

confidence: 99%

Fission Product Yield Data Adjustment in a Prototype Version of TSURFER

Bledsoe¹,

Pigni²

2021

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The TSURFER (Tool for Sensitivity/Uncertainty analysis of Response Functionals using Experimental Results) module of Oak Ridge National Laboratory's (ORNL's) SCALE code system has been updated to perform nuclear data adjustments for fixed-source irradiation/depletion problems. TSURFER uses a generalized linear least squares (GLLS) approach to consolidate a prior set of measured responses and corresponding calculated values to create the most self-consistent set of nuclear data. Traditionally, TSURFER adjustments have been performed for multigroup nuclear data such as reaction cross sections. In this work, TSURFER is expanded to perform adjustments to independent fission product yields and branching ratios that need equality constraints. To preserve equality constraints after the data adjustment procedure, an updated GLLS formulation includes a new Lagrange multiplier that forces data adjustment to sum to 0 for a given fission yield/branching ratio parent. A test problem illustrates that the newly updated TSURFER module satisfies the required constraint that adjustments for fission yield data sum to 0.

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Information fusion method for system identification based on sensitivity analysis

Barhen

Rao

2000

Proceedings of the Third International Conference on Information Fusion

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W e wnsider the identification of a parametrized time-invariant non-linear plant using a smooth model such as a sigmoid non-linear network. There is measurement noise associated with the plant parameters as well as it's input and output. An initial plant model is obtained by utilizing the domain-specific knowledge in terms of the fundamental plant equations, which in general only partially capture the plant dynamics. Once the initial model is fized, measurements are collected on the plant pammeters and input/output. W e show that the iid measurements can be fused with the initial plant model by recomputing the parameters. The updated parameters yield a more accurate identifier of the original plant both in parameter and input/output space. The method is based on empirical versions of the closed-form solutions derived in the nuclear engineering literature for an ideal version of the problem based the sensitivity analysis. W e show the asymptotic convergence of our wmputational procedure as well as derive its finite sample results. W e illustrate the method wing an identifier based on a sigmoid feedforward neural network.

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Significance of Lagrange multipliers in cross-section adjustment

Abstract: This note offers what we believe is the natural derivation of the explicit prescriptions incorporated in least-squares adjustment codes. We do not pretend to present any really new results, except perhaps for underlining the central role of the Lagrange multipliers,

Cited by 3 publications

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Some Insight into the Generalized Linear Least Squares Parameter Adjustment Methodology

Some Insight into the Generalized Linear Least Squares Parameter Adjustment Methodology

Fission Product Yield Data Adjustment in a Prototype Version of TSURFER

Information fusion method for system identification based on sensitivity analysis

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