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Title: ARIADNE – a program estimating covariances in detail for neutron experiments

Abstract

The python program ARIADNE is a tool developed for evaluators to estimate detailed uncertainties and covariances for experimental data in a consistent and efficient manner. Currently, it is designed to aid in the uncertainty quantification of prompt fission neutron spectra, and was employed to estimate experimental covariances for CIELO and ENDF/B-VIII.0 evaluations. It provides a streamlined way to estimate detailed covariances by (1) implementing uncertainty quantification algorithms specific to the observables, (2) defining input quantities for typically encountered uncertainty sources and correlation shapes, and (3) automatically generating plots of data, uncertainties and correlations, GND formatted XML and plain text output files. Covariances of the same and between different datasets can be estimated, and tools are provided to assemble a database of experimental data and covariances for an evaluation based on ARIADNE outputs. The underlying IPython notebook files can be easily stored, including all assumptions on uncertainties, leading to more reproducible inputs for nuclear data evaluations. Here, the key inputs and outputs are shown along with a representative example for the current version of ARIADNE to illustrate its usability and to open a discussion on how it could address further needs of the nuclear data evaluation community.

Authors:
ORCiD logo [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1489949
Report Number(s):
LA-UR-17-30469
Journal ID: ISSN 2491-9292
Grant/Contract Number:  
89233218CNA000001; AC52-06NA25396
Resource Type:
Accepted Manuscript
Journal Name:
EPJ Nuclear Sciences and Technologies
Additional Journal Information:
Journal Volume: 4; Journal ID: ISSN 2491-9292
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Neudecker, Denise. ARIADNE – a program estimating covariances in detail for neutron experiments. United States: N. p., 2018. Web. doi:10.1051/epjn/2018012.
Neudecker, Denise. ARIADNE – a program estimating covariances in detail for neutron experiments. United States. doi:10.1051/epjn/2018012.
Neudecker, Denise. Wed . "ARIADNE – a program estimating covariances in detail for neutron experiments". United States. doi:10.1051/epjn/2018012. https://www.osti.gov/servlets/purl/1489949.
@article{osti_1489949,
title = {ARIADNE – a program estimating covariances in detail for neutron experiments},
author = {Neudecker, Denise},
abstractNote = {The python program ARIADNE is a tool developed for evaluators to estimate detailed uncertainties and covariances for experimental data in a consistent and efficient manner. Currently, it is designed to aid in the uncertainty quantification of prompt fission neutron spectra, and was employed to estimate experimental covariances for CIELO and ENDF/B-VIII.0 evaluations. It provides a streamlined way to estimate detailed covariances by (1) implementing uncertainty quantification algorithms specific to the observables, (2) defining input quantities for typically encountered uncertainty sources and correlation shapes, and (3) automatically generating plots of data, uncertainties and correlations, GND formatted XML and plain text output files. Covariances of the same and between different datasets can be estimated, and tools are provided to assemble a database of experimental data and covariances for an evaluation based on ARIADNE outputs. The underlying IPython notebook files can be easily stored, including all assumptions on uncertainties, leading to more reproducible inputs for nuclear data evaluations. Here, the key inputs and outputs are shown along with a representative example for the current version of ARIADNE to illustrate its usability and to open a discussion on how it could address further needs of the nuclear data evaluation community.},
doi = {10.1051/epjn/2018012},
journal = {EPJ Nuclear Sciences and Technologies},
number = ,
volume = 4,
place = {United States},
year = {2018},
month = {11}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Figures / Tables:

Fig. 1 Fig. 1: The total time resolution uncertainty relative to the PFNS is compared for shape, shape ratio and shape ratio calibration data for a time resolution of 1 ns, a TOF length of 1m for all measurements and Maxwellian temperatures of 1.33 and 1.42MeV for the investigated and the monitormore » isotope, respectively.« less

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Works referenced in this record:

Prompt Fission Neutron Spectra of Actinides
journal, January 2016


Template for estimating uncertainties of measured neutron-induced fission cross-sections
journal, January 2018

  • Neudecker, Denise; Hejnal, Brooke; Tovesson, Fredrik
  • EPJ Nuclear Sciences & Technologies, Vol. 4
  • DOI: 10.1051/epjn/2018026

The Need for Precise and Well-documented Experimental Data on Prompt Fission Neutron Spectra from Neutron-induced Fission of 239Pu
journal, January 2016


Evaluations of Energy Spectra of Neutrons Emitted Promptly in Neutron-induced Fission of 235 U and 239 Pu
journal, February 2018


Web Tool for Constructing a Covariance Matrix from EXFOR Uncertainties
journal, January 2012


Generalized Nuclear Data: A New Structure (with Supporting Infrastructure) for Handling Nuclear Data
journal, December 2012


    Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.