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Introduction
Published in Alireza Haghighat, Monte Carlo Methods for Particle Transport, 2020
The above brief history indicates that early development of Monte Carlo particle transport techniques were mainly conducted by the scientists at LANL. As a result, LANL has been the main source of general-purpose Monte Carlo codes, starting with MCS (Monte Carlo Simulation) in 1963 and followed by MCN (Monte Carlo Neutron) in 1965, MCNG (Monte Carlo coupled Neutron and Gamma) in 1973, and MCNP (Monte Carlo Neutron Photon) in 1977. MCNP has been under continuous development and the latest version, MCNP6, was released in 2013 [80]. The progress made over the past 50 years demonstrates the sustained effort at LANL on development, improvement, and maintenance of Monte Carlo particle transport codes. There has also been simultaneous development of and improvement in nuclear physics parameters, i.e., cross sections, in the form of the cross-section library referred to as the Evaluated Nuclear Data File (ENDF). Currently, ENDF/B-VIII, the 8th version, is in use.
Cross Section Libraries and Sources of Practical Nuclear Data
Published in Robert E. Masterson, Introduction to Nuclear Reactor Physics, 2017
The same approach can also be extended to other situations where the volume of a particular material is known, but its physical weight is not. For example, if we know that we had 1000 cm3 of water in Example Problem 5.3, but we did not know the weight, we could have still solved the problem with the information provided because Table 5.7 provides us with its physical density ρ to calculate its physical mass. So the quantity of a material, its microscopic cross sections, and the value of the neutron flux are all that is needed to calculate the reaction rates (scattering, absorption, capture, or fission) for any common nuclear material. If the neutron flux is subdivided into a number of different energy groups where we know the values of ϕ1, ϕ2, …, ϕN, etc., then the reaction rates for each energy group can be found as well. The only subject we have not discussed so far is how the fast and thermal cross sections shown in Tables 5.1, 5.2, and 5.6 can be found from experimental data collected by nuclear physicists in the laboratory. In one-group and multigroup theory, there is a specific approach for doing this that guarantees the reaction rates will be conserved. In the remainder of this chapter, we would like to show how nuclear cross section libraries with more than one energy group can be derived from raw nuclear data.
Cross Section Libraries and Sources of Nuclear Data
Published in Robert E. Masterson, Nuclear Engineering Fundamentals, 2017
The same approach can also be extended to other situations where the volume of a particular material is known, but its physical weight is not. For example, if we know that we had 1000 cm3 of water in Example Problem 5.3, but we did not know the weight, we could have still solved the problem with the information provided because Table 5.7 provides us with its physical density ρ to calculate its physical mass. So the quantity of a material, its microscopic cross sections, and the value of the neutron flux are all that is needed to calculate the reaction rates (scattering, absorption, capture, or fission) for any common nuclear material. If the neutron flux is subdivided into a number of different energy groups where we know the values of ϕ1, ϕ2, …, ϕN, etc., then the reaction rates for each energy group can be found as well. The only subject we have not discussed so far is how the fast and thermal cross sections, shown in Table 5.1, 5.2, and 5.6 can be found from experimental data collected by nuclear physicists in the laboratory. In one-group and multigroup theory, there is a specific approach for doing this that guarantees the reaction rates will be conserved. In the remainder of this chapter, we would like to show how nuclear cross section libraries with more than one energy group can be derived from raw nuclear data.
A Nonintrusive Nuclear Data Uncertainty Propagation Study for the ARC Fusion Reactor Design
Published in Nuclear Science and Engineering, 2023
Alex Aimetta, Nicolò Abrate, Sandra Dulla, Antonio Froio
Because of the huge range of the incident neutron energy and of the great variety of reaction channels featuring the various isotopes composing the reactor media, the nuclear data are stored in a specific file format, known as Evaluated Nuclear Data Files (ENDF). The ENDF format cannot be read as it is by Serpent, which requires the nuclear data to be processed as a compact ENDF (ACE) file. The conversion of the ENDF files into the ACE format is usually performed using suitable nuclear data processing tools. Among the various codes available to perform this task, NJOY is certainly the most popular and reliable one.23 To ensure the full consistency in the ENDF-to-ACE conversion process for the different libraries selected for the calculations, namely, the ENDF-B/VIII.0, the Joint Evaluated Fission and Fusion-3.3 (JEFF-3.3) and the beta version of JEFF-4, and the Fusion Evaluated Nuclear Data Library-3.2b (FENDL-3.2b), an in-house, open-source Python class has been conceived to manage automatically and efficiently the file processing with NJOY, guaranteeing that the same processing settings are adopted for the various libraries, and thus, that the differences obtained in the best-estimate calculations are only due to the nuclear data evaluations.
Experimental analysis of small sample reactivity measured in the SEG experiment by a deterministic reactor physics code system CBZ
Published in Journal of Nuclear Science and Technology, 2022
Nuclear data is one of the important fundamental data in the field of nuclear engineering. Significant efforts have been devoted to improve the accuracy and quality of the nuclear data since the accuracy of the nuclear data has large impact on the feasibility of the nuclear systems from the viewpoint of sustainability of nuclear fission chain reactions and radiation shielding. In order to achieve this, there are several approaches such as measurements of nuclear data itself or physical quantity directly related to specific nuclear data, and development of the sophisticated nuclear physics theory and model. Measurement of integral parameters, which are dependent on various nuclear data, are also important since the direct measurement of specific nuclear data is sometimes quite difficult. The measurement data on the integral parameters are also called integral data.
Uncertainty Propagation in SINBAD Fusion Benchmarks with Total Monte Carlo and Imprecise Probabilities
Published in Fusion Science and Technology, 2021
Ander Gray, Andrew Davis, Edoardo Patelli
Nuclear data are a fundamental input to any nuclear application. They effectively define all of the complex particle-matter interaction rules for the transport simulation. Nuclear data libraries usually provide at least three quantities for every nuclide-interaction pair: interaction cross sections: characterize the probability of a particular reactionexit energy/angle distributions: if the reaction has an exit particle, its next energy/angle state is sampledcovariances: the variance, autocorrelation, and cross-correlation information of the interaction cross sections.