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Examples of Use of SINBAD Database for Nuclear Data and Code Validation
Benchmark experiments can serve several purposes and the availability of suitable experimental data is fundamental to ensure that modelling tools meet the requirements of nuclear industry and licensing needs. Essentially, they are used for: - validation of nuclear cross-section data, - validation of nuclear codes and models used, - qualification and training of users through benchmarking and code comparison exercises. The Shielding Integral Benchmark Archive and Database (SINBAD) project was started in the early 1990's at the OECD Nuclear Energy Agency Data Bank (NEA DB) and the Radiation Safety Information Computational Center (RSICC) as a collection of quality experiments for validating and benchmarking computer codes and data for radiation transport and shielding applications. Currently, the SINBAD database comprises over 100 benchmark compilations and evaluations of relevance to: - reactor shielding, pressure vessel dosimetry (48); - fusion blanket neutronics (31); - accelerator shielding (23). In order to facilitate their use, the data are organized in the standardized format structure. The index and the master document (called abstract) use the Hyper Text Markup Language (HTML) format with links to text files, figures, Portable Document Format (pdf) documents and computer code inputs. The format allows easy access and forward/backward navigation among the data and has proved to be suitable, general enough and above all easy (and low-cost) to maintain. In addition to the characterization of the radiation source, description of the shielding set-up, the instrumentation and the relevant detector measurements, most sets in SINBAD contain also the deterministic or Monte Carlo radiation transport computer model used for the interpretation of the experiment and, where available, results from uncertainty analysis. The set of primary documents used for the benchmark compilation and evaluation are provided in computer readable form. The database is intended for different types of users, including nuclear data evaluators, computer code developers, experiment designers and university students. SINBAD is available from the NEA Data Bank and RSICC (see https://www.oecdnea.org/science/wprs/shielding/sinbad/). Up to now several hundreds of SINBAD packages were distributed from the NEA DB and RSICC. Since 2011 the maintenance and further development of the database is coordinated in the scope of the OECD NEA Nuclear Science Committee (NSC) Working Party on Scientific Issues of Reactor Systems (WPRS) Expert Group on Radiation Transport and Shielding (EGRTS). A key objective of the group is to identify, evaluate and preserve experimental data on shielding benchmarks. The Expert Group maintains close links with the International Reactor Physics Experiment Evaluation (IRPhE) and International Criticality Safety Benchmark Evaluation (ICSBEP) projects, as well as in co-ordination with the JEFF and EFF NEA Data Bank projects and with the SATIF community of accelerator shielding specialists. In the last years, much effort was devoted to the quality review of the available benchmark information.
NCSP Analytical Methods Subtask 3, AMPX Development and Maintenance, and NCSP Nuclear Data Subtask 6, SAMMY Modernization
The modernization of SAMMY continued with the removal of all container array access for the main program. The container array was used due to the computer limitations at the time of the initial writing of SAMMY, but it prevented the use of some modern code testing options. Additionally, the authors continued to make the code more modular by shifting the storage of the energy grid and the covariance information to C++ storage, thus allowing for better unit testing and the elimination of scratch files. For AMPX, the authors continued to implement the new Evaluated Nuclear Data File format to allow AMPX to read new evaluations as they become available.
Re-analysis of HCPB/HCLL Blanket Mock-up Experiments Using Recent Nuclear Data Libraries
We have re-analysed the two breeding blankets experiments performed previously in the frame of the European fusion program on two mock-ups of the European Helium-Cooled-Lithiium Lead (HCLL) and Helium-Cooled-Pebble-Bed (HCPB) test blanket modules for ITER. The tritium production rate and the neutron and photon spectra measured in these mock-ups were compared with calculations using FENDL-3 Starter Library, release 4 and state-of-the-art nuclear data evaluations, JEFF-3.1.2, JENDL-4.0 and ENDF/B-VII.0. The tritium production calculated for the HCPB mock-up underestimates the experimental result by about 10%. The result calculated with FENDL-3/SLIB4 gives slightly smaller tritium production by 2% than the one with FENDL-2.1. The difference attributes to the slight modification of the total and elastic scattering cross section of Be. For the HCLL experiment, all libraries reproduce the experimental results well. FENDL-3/SLIB4 gives better result both for the measured spectra and the tritium production compared to FENDL-2.1.
Improvements of Nuclear Data and Its Uncertainties by Theoretical Modeling
This document reports on the results obtained during the 3-year AFCI-NEUP project #09-247, which aimed at improving the modeling and evaluation of nuclear data and their uncertainties for use in advanced nuclear energy transport simulations.
Nuclear Data Sheets for A=143
The evaluators present in this publication spectroscopic data and level schemes from radioactive decay and nuclear reaction studies for all nuclei with mass number A = 143. The evaluation, which includes all data received by May 2011, supersedes the 2001 evaluation by J.K. Tuli, published in Nuclear Data Sheets94, 605 (2001).
The Half Monte Carlo Method: Combining Total Monte Carlo with Nuclear Data Sensitivity Profiles
Both Total Monte Carlo (TMC) and Generalized Linear Least Squares (GLLS) algorithms have been used extensively to perform nuclear uncertainty propagation. Both methods have strengths and weaknesses, for example, the time required to perform TMC limits its attractiveness, while GLLS cannot generate higher order moments of output distributions and also has trouble dealing with nonlinear distributions. This work uses a new method that overcomes many of the aforementioned limitations of TMC and GLLS, while at the same time reasonably reproduces the TMC result. The concept is a simple combination of the two methods i.e., generate the random nuclear data files using the TMC approach, and then propagate the effect on the integral parameters like k{sub eff} using sensitivity coefficients, as opposed to cumbersome neutron transport calculations. Agreement is demonstrated for the Jezebel sphere ICSBEP benchmark. Since the method is part TMC part GLLS, the term Half Monte Method (HMM) will be used.
EXCALIBUR-at-CALIBAN: a neutron transmission experiment for {sup 238}U(n,n'{sub continuum}γ) nuclear data validation
Two recent papers justified a new experimental program to give a new basis for the validation of {sup 238}U nuclear data, namely neutron induced inelastic scattering and transport codes at neutron fission energies. The general idea is to perform a neutron transmission experiment through natural uranium material. As shown by Hans Bethe, neutron transmissions measured by dosimetric responses are linked to inelastic cross sections. This paper describes the principle and the results of such an experience called EXCALIBUR performed recently (January and October 2014) at the CALIBAN reactor facility. (authors)
Aleatoric and epistemic uncertainties in sampling based nuclear data uncertainty and sensitivity analyses
Sampling based uncertainty and sensitivity analyses due to epistemic input uncertainties, i.e. to an incomplete knowledge of uncertain input parameters, can be performed with arbitrary application programs to solve the physical problem under consideration. For the description of steady-state particle transport, direct simulations of the microscopic processes with Monte Carlo codes are often used. This introduces an additional source of uncertainty, the aleatoric sampling uncertainty, which is due to the randomness of the simulation process performed by sampling, and which adds to the total combined output sampling uncertainty. So far, this aleatoric part of uncertainty is minimized by running a sufficiently large number of Monte Carlo histories for each sample calculation, thus making its impact negligible as compared to the impact from sampling the epistemic uncertainties. Obviously, this process may cause high computational costs. The present paper shows that in many applications reliable epistemic uncertainty results can also be obtained with substantially lower computational effort by performing and analyzing two appropriately generated series of samples with much smaller number of Monte Carlo histories each. The method is applied along with the nuclear data uncertainty and sensitivity code package XSUSA in combination with the Monte Carlo transport code KENO-Va to various critical assemblies and a full scale reactor calculation. It is shown that the proposed method yields output uncertainties and sensitivities equivalent to the traditional approach, with a high reduction of computing time by factors of the magnitude of 100. (authors)
Our Future Nuclear Data Needs
A well-established knowledge of nuclear phenomena including fission, reaction cross sections, and structure/decay properties is critical for applications ranging from the design of new reactors to nonproliferation to the production of radioisotopes for the diagnosis and treatment of illness. However, the lack of a well-quantified, predictive theoretical capability means that most nuclear observables must be measured directly and used to calibrate empirical models, which in turn provide the data needed for these applications. In many cases, either there is a lack of data needed to guide the models or the results of the different measurements are discrepant, leading to the development of evaluation methodologies to provide recommended values and uncertainties. In this review, we describe the nuclear data evaluation process and the international community that carries it out. We then discuss new measurements and improved theory and/or modeling needed to address future challenges in applied nuclear science.
Improving the Nuclear Data on Fission Product Decays at CARIBU: LL18-FissProdCARIBU-PD3Jb TRA 2018
The scope of the project is to improve the fundamental nuclear data of fission products relevant to applications. Per the TRA guidance document “We will improve the precision of the absolute g-ray branching ratios for longlived fission products by nearly an order of magnitude to 1-2% precision” describes the goal of the project. This goal is unlikely to change during the course of the project.
Public Release of the MENDF80 and MT80 Nuclear Data Libraries for NDI
This document describes the MENDF80 and MT80 data libraries, which are multi-group neutron cross section libraries based on ENDF/B-VIII.0 for LANL’s Nuclear Data Interface (NDI). MENDF80 is a downscatter-only library, while MT80 is multi-temperature. Both libraries also have 30-group pre-collapsed versions, MENDF80 30 and MT80 30.
Chlorine Nuclear Data Needs for Advanced Reactors [Slides]
The key physics parameters of the SSR-W have been shown to exhibit high sensitivity to chlorine nuclear data, particularly the Cl-35 (n,p) cross section. This sensitivity will be a feature for any fast chloride reactor. The sensitivity, together with large uncertainty in the fast region, results in significant uncertainty in important output reactor physics parameters, such as reactivity, and hence the required fuel loading for criticality.
Nuclear Data Advisory Group Technical Support for the US Nuclear Criticality Safety Program
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Generalized Nuclear Data - WPEC Subgroup 43
This repository describes the goals and governance of WPEC Subgroup 43 (SG43). This subgroup is tasked with creating infrastructure for the Generalized Nuclear Data (GND) format.
Sample Generation for Nuclear Data
This report summarizes a NEAMS (Nuclear Energy Advanced Modeling and Simulation) project focused on developing a sampling capability that can handle the challenges of generating samples from nuclear cross-section data. The covariance information between energy groups tends to be very ill-conditioned and thus poses a problem using traditional methods for generated correlated samples. This report outlines a method that addresses the sample generation from cross-section matrices. The treatment allows one to assume the cross sections are distributed with a multivariate normal distribution, lognormal distribution, or truncated normal distribution.