FRENDY: A new nuclear data processing system being developed at JAEA

Tada, Kenichi; Nagaya, Yasunobu; Kunieda, S.; Suyama, Kenya; Fukahori, Tokio

doi:10.1051/epjconf/201714602028

Cited by 6 publications

(3 citation statements)

References 8 publications

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“…The GNDS format and the ENDF-6 format are both released in some new version libraries, including ENDF-B/VIII.0 and TENDL-2021. Fudge is the first code to parse GNDS format [4] , and most nuclear data, including NJOY [5] , AMPX [6] , FRENDY [7] , GALILEE [8] are developing this function to process GNDS format.…”

Section: Introductionmentioning

confidence: 99%

Development and Verification of Capability for Processing the Generalised Nuclear Database Structure (GNDS) in Nuclear Data Processing Code NECP-Atlas

Huang

Cao

et al. 2023

EPJ Web of Conf.

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The latest evaluated nuclear data libraries, including ENDF/B-VIII.0, TENDL2019, all have two formats, the Evaluated Nuclear Data File (ENDF-6) nuclear data format, and the Generalised Nuclear Database Structure (GNDS) format. The first official public documentation of all of the options for storing data in GNDS was released by the Working Party on International Nuclear Data Evaluation Cooperation (WPEC) of the Nuclear Energy Agency. The generalized derived class is designed to be compatible with ENDF-6 and GNDS in nuclear data processing code NECP-Atlas, and the GNDS-Toolkit is developed in NECP-Atlas to parse and convert GNDS. ACE format library and multi-group library are generated based on GNDS, and they are used in the Monte-Carlo code and deterministic based code to compare with ENDF-6. The numerical results show that GNDS libraries can be processed by NECP-Atlas competently to generate specific format library and the difference in ENDF-6 and GNDS is very small.

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Section: Introductionmentioning

confidence: 99%

Development and Verification of Capability for Processing the Generalised Nuclear Database Structure (GNDS) in Nuclear Data Processing Code NECP-Atlas

Huang

Cao

et al. 2023

EPJ Web of Conf.

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“…Nevertheless, the accuracy and robustness of the developed solutions contemplating the

distribution can only be appropriately verified if it is applied in a nuclear data processing code, e.g., FRENDY [ 19 , 20 ], NJOY [ 21 ], PREPRO [ 22 ] and NECP-Atlas [ 23 ]. These systems can process official evaluated nuclear data libraries such as ENDF [ 24 ], CENDL [ 25 ], JEFF [ 26 ] or JENDL [ 27 ].…”

Section: Introductionmentioning

confidence: 99%

Doppler Broadening of Neutron Cross-Sections Using Kaniadakis Entropy

Abreu

Maciel

Martinez

et al. 2022

Entropy

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In the last seven years, Kaniadakis statistics, or κ-statistics, have been applied in reactor physics to obtain generalized nuclear data, which can encompass, for instance, situations that lie outside thermal equilibrium. In this sense, numerical and analytical solutions were developed for the Doppler broadening function using the κ-statistics. However, the accuracy and robustness of the developed solutions contemplating the κ distribution can only be appropriately verified if applied inside an official nuclear data processing code to calculate neutron cross-sections. Hence, the present work inserts an analytical solution for the deformed Doppler broadening cross-section inside the nuclear data processing code FRENDY, developed by the Japan Atomic Energy Agency. To do that, we applied a new computational method called the Faddeeva package, developed by MIT, to calculate error functions present in the analytical function. With this deformed solution inserted in the code, we were able to calculate, for the first time, deformed radiative capture cross-section data for four different nuclides. The usage of the Faddeeva package brought more accurate results when compared to other standard packages, reducing the percentage errors in the tail zone in relation to the numerical solution. The deformed cross-section data agreed with the expected behavior compared to the Maxwell–Boltzmann.

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“…There are also some newly developed nuclear data processing codes. For example, RXSP (Jian-kai et al, 2013) (Li and WangKan, 2017) (Liu et al, 2020) (Li, 2012) (Yu, 2015) of Tsinghua University and FRENDY (Tada et al, 2017) of the Japan Atomic Energy Agency (JAEA) have developed to produce an ACE format library for the Monte Carlo code. Ruller (Liu et al, 2016) of the China Institute of Atomic Energy and NECP-Atlas (Zu et al, 2019) of Xi'an Jiao Tong University have been developed to provide a multigroup library.…”

Section: Introductionmentioning

confidence: 99%

Development and verification of a new nuclear data processing code AXSP

et al. 2022

Front. Energy Res.

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The advanced reactor design needs an accurate cross-section generation code. In this study, a new nuclear data processing code AXSP is developed, and the method and performance of which are described. Compared with the NJOY program, the precision of the unresolved resonance processing module UnresXS has been significantly improved due to the adoption of a more accurate solution method and the consideration of in-sequence overlap integrals. The time consumption of PUnresXS has been decreased significantly due to an optimized sorting algorithm. At the same time, other modules of AXSP are relatively comprehensive. The function of resolved resonance cross-section reconstruction and linearization is the ReconXS module. The Doppler broadening module is BroadXS by using Gauss–Hermite quadrature and Gauss–Legendre quadrature from 0 K temperature pointwise cross section to any temperature which is defined by the user. The shielding factor in the unresolved resonance energy region is calculated by the UnresXS or the PUnresXS module, which are developed based on the Bondarenko method and the probability table method, respectively. The ACE formatted cross sections for the Monte Carlo code is processed by the ACEXS module, and the multigroup cross sections are generated by the GroupXS module. The cross sections processed by different modules were verified by the NJOY2016 code, and the multigroup cross sections were also verified by using the critical benchmarks. The multiplication factor difference between AXSP and NJOY2016 is less than 20 pcm. In addition to this, the ZPR6/7 fast reactor is used for ACE format library verification. The results show that the criticality calculated by AXSP has a good agreement with that of NJOY2016.

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FRENDY: A new nuclear data processing system being developed at JAEA

Cited by 6 publications

References 8 publications

Development and Verification of Capability for Processing the Generalised Nuclear Database Structure (GNDS) in Nuclear Data Processing Code NECP-Atlas

Development and Verification of Capability for Processing the Generalised Nuclear Database Structure (GNDS) in Nuclear Data Processing Code NECP-Atlas

Doppler Broadening of Neutron Cross-Sections Using Kaniadakis Entropy

Development and verification of a new nuclear data processing code AXSP

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