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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

PROBLEM DEPENDENT DOPPLER BROADENING OF CONTINUOUS ENERGY CROSS SECTIONS IN THE KENO MONTE CARLO COMPUTER CODE

For many Monte Carlo codes cross sections are generally only created at a set of predetermined temperatures. This causes an increase in error as one moves further and further away from these temperatures in the Monte Carlo model. This paper discusses recent progress in the Scale Monte Carlo module KENO to create problem dependent, Doppler broadened, cross sections. Currently only broadening the 1D cross sections and probability tables is addressed. The approach uses a finite difference method to calculate the temperature dependent cross-sections for the 1D data, and a simple linear-logarithmic interpolation in the square root of temperature for the probability tables. Work is also ongoing to address broadening theS (alpha , beta) tables. With the current approach the temperature dependent cross sections are Doppler broadened before transport starts, and, for all but a few isotopes, the impact on cross section loading is negligible. Results can be compared with those obtained by using multigroup libraries, as KENO currently does interpolation on the multigroup cross sections to determine temperature dependent cross-sections. Current results compare favorably with these expected results.

Monte Carlo↗
DOE OSTI2013

Resonance self-shielding effects on Eigenvalue sensitivity

We present a quick and accurate way to compute the eigenvalue sensitivity coefficients in multigroup lattice cell calculations. We look at both the explicit and implicit sensitivities, the latter resulting from the resonance self-shielding process. A self-shielding model is presented, and we show how to obtain cross section sensitivities to a variation on a light isotope density. As an example, we look at how a perturbation on the hydrogen density affects the multigroup cross sections for resonant reactions such as U'capture and U'fission, in two uranium spheres with different enrichments. Explicit sensitivities are also computed, and we discuss the relative importance of the implicit sensitivities. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

A multilevel method for coupling the neutron kinetics and heat transfer equations

We present a computational method for adequate and efficient coupling the neutron transport equation with the precursor and heat transfer equations. It is based on the multilevel nonlinear quasidiffusion (QD) method for solving the multigroup transport equation. The system of equations includes the time-dependent high-order transport equation and time-dependent multigroup and effective one-group low-order QD equations. We also formulate a method applying the {alpha}-approximation for the time-dependent high-order transport equation. This approach enables one to avoid storing the angular flux from the previous time step. Numerical results for a model transient problem are presented. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Continuous-energy eigenvalue sensitivity coefficient calculations in TSUNAMI-3D

Two methods for calculating eigenvalue sensitivity coefficients in continuous-energy Monte Carlo applications were implemented in the KENO code within the SCALE code package. The methods were used to calculate sensitivity coefficients for several test problems and produced sensitivity coefficients that agreed well with both reference sensitivities and multigroup TSUNAMI-3D sensitivity coefficients. The newly developed CLUTCH method was observed to produce sensitivity coefficients with high figures of merit and a low memory footprint, and both continuous-energy sensitivity methods met or exceeded the accuracy of the multigroup TSUNAMI-3D calculations. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Interactive Visualization of Multi-Group Cross Sections on High-Fidelity Spatial Meshes

Core simulation tools utilizing Monte Carlo transport methods represent the 'Holy Grail' for nuclear reactor analysis. However, deterministic transport methods pose a number of advantages to Monte Carlo from a computational perspective, which seems likely to make these methods more viable in the near to intermediate term. Deterministic methods almost universally discretize the energy domain in a few to hundreds of energy groups. One of the key challenges for deterministic transport-based methods to be viable is accurate, reactor agnostic multi-group cross section generation. This paper describes tools for data processing and visualization of multigroup cross sections generated on high-fidelity spatial meshes from the OpenMC Monte Carlo code. Next generation deterministic transport reactor core modeling tools will require multi-group cross section (MGXS) generation on high-fidelity spatial meshes. High-fidelity MGXS are necessary for the accurate simulation of neutron physics in nuclear reactors with a high degree of spectral heterogeneity - e.g., large localized neutron flux gradients throughout a reactor core. Although many local (e.g., pin cell) approximations have been developed to model the scalar flux to compute spectral-averaged MGXS, these techniques cannot account for complex intra-pin and intra-assembly spatial self-shielding effects. Monte Carlo presents the most accurate method for reactor agnostic multi-group cross section generation since it does not require the use of local approximations to the flux. Monte Carlo has been proposed as a highly desirable framework for reactor agnostic cross section generation for many years. Monte Carlo methods can effectively embed all of the relevant spectral effects into the MGXS through the random particle tracking and interaction sampling processes. Previous work has applied MCNP and Serpent to compute few-group constants for diffusion calculations, and OpenMC to compute multi-group cross sections for transport-based methods. The primary difficulty with using Monte Carlo for MGXS generation is the tremendous computational resources required to adequately converge multi-group cross sections in each spatial region and energy group. Recent development of the OpenMC Monte Carlo code for high-performance computing platforms has made multigroup cross section generation from Monte Carlo more tractable in the foreseeable future. The recent release of OpenMC v0.7.1 includes a new Python-based module for MGXS generation. The MGXS generation module leverages many of the algorithms and features for 'big data' analysis of large tally datasets on complex spatial meshes. This paper describes the data management workflow and visualization tools which have been developed to explore the plethora of MGXS data generated with OpenMC. It is the authors' hope that the development of the visualization tool described in this paper will ultimately enable the design of machine learning algorithms to accelerate the convergence rate of high-fidelity multi-group cross section generated with Monte Carlo. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

NJOY21: Making NJOY Suitable for the 21. Century - 14409

NJOY has a long history of nuclear data processing. NJOY began as a successor to MINX (Multigroup Interpretation of Nuclear X-Sections), a Los Alamos code and was first publicly released in the summer of 1977. The initial version included modules such as RECONR for resonance reconstruction on a union energy grid, BROADR for Doppler broadening plus a new Multigroup averaging program, GROUPR and an associated output module, DTR. Soon thereafter the HEATR, ERRORR, and THERMR modules were added to NJOY. By the mid 1980's, NJOY had a worldwide user community. The current version of NJOY2012 was released in December 2012. NJOY2012 builds on the success of more than 45 years of nuclear data processing at Los Alamos National Laboratory. NJOY2012 was rewritten using Fortran 90/95, utilizing among other things the concepts of public and private variables, eliminating common blocks in lieu of Fortran modules and taking advantage of allocatable arrays. A new version of NJOY is being developed at Los Alamos National Laboratory; NJOY21: NJOY for the 21. Century. NJOY21 uses modern programming standards of quality, reliability, and maintainability. It is being designed from the ground up to utilize modern methods of interacting with computer codes by providing an interactive and scripting (e.g., Python) interface. This will allow scientists the ability to more easily work with the results of the various steps in the processing of nuclear data. NJOY21 will continue the legacy of NJOY by providing a trusted and verified processing code that is fast, flexible, easy to use and customize and capable of handling both modern and established nuclear data formats. This paper introduces NJOY21 by first relating the history of NJOY; the majority of the paper will discuss NJOY21. NJOY21 will take advantage of the many decades of nuclear data processing experience that is contained in NJOY2012 and previous versions of NJOY and extend the capabilities and convenience of processing nuclear data. We will discuss how NJOY21 will remain backwards compatible with NJOY2012 - i.e., how current NJOY2012 input decks will continue to work with NJOY21. We will also discuss the verification and validation of the NJOY21 code base. Finally we will discuss new features in NJOY21 that do not exist in NJOY2012. These features include changes in how a scientist can interact with NJOY to process and verify and validate nuclear data; and the ability to read and write new nuclear data formats. (authors)

42 ENGINEERING↗
DOE OSTI2024

Advanced Cross Section Library Generation using Reduced Order Models

Deterministic neutronics calculations rely on multigroup neutron cross section libraries, which consist of databases of tabulated values, used to calculate the neutron cross sections through multivariate linear interpolation. However, interpolation of the multidimensional cross section data becomes memory inefficient and time consuming as the number of tabulations increases, significantly slowing down the neutronics calculation, especially in the case of microscopic cross section libraries where every isotope (on the order of hundreds) has its own set of specific reactions and cross sections. In order to address this challenge, this work constructs efficient and robust reduced-order models (ROMs) of the multi-group cross sections to support the Griffin simulation of high-temperature gas-cooled reactors (HTGRs). The first part of the study investigates the linearity of the multigroup cross section data across isotopes, reaction types, and energy groups on pre-generated datasets for the purpose of dimensionality reduction. Secondly, a down-selection of ROM techniques is presented on representative classical machine learning (ML) techniques, including variants of linear regression, kernel-based methods, tree-based algorithms, and artificial neural networks. The selection criteria jointly consider the memory efficiency, predictive accuracy, prediction speed, and scalability in comparison to the multidimensional interpolation. Among all the ML techniques, deep neural networks (DNNs) have proven to be the best selection with sufficient accuracy, high robustness, good memory efficiency, great scalability, and superior flexibility. DNNs have been trained for all isotopes in this work and systematic Griffin testing is ongoing to ensure the feasibility of this ROM technique for predicting cross section and reducing memory requirements without a significant sacrifice in computational performance.

42 - ENGINEERING↗
DOE OSTI2010

Development and Validation of Scale Nuclear Analysis Methods for High Temperature Gas-Cooled Reactors

In support of the U.S. Nuclear Regulatory Commission, ORNL is updating the nuclear analysis methods and data in the SCALE code system to support modeling of HTGRs. Development activities include methods used for reactor physics, criticality safety, and radiation shielding. This paper focuses on the nuclear methods in support of reactor physics, which primarily include lattice physics for cross-section processing of both prismatic and pebble-bed designs, Monte Carlo depletion methods and efficiency improvements for double heterogeneous fuels, and validation against relevant experiments. These methods enhancements are being validated using available experimental data from the HTTR and HTR-10 startup and initial criticality experiments. Results obtained with three-dimensional Monte Carlo models of the HTTR initial core critical configurations with SCALE6/KENO show excellent agreement between the continuous energy and multigroup methods and the results are consistent with results obtained by others. A three-dimensional multigroup Monte Carlo model for the initial critical core of the HTR-10 has been developed with SCALE6/KENO based on the benchmark specifications included in the IRPhE Handbook. The core eigenvalue obtained with this model is in very good agreement with the corresponding value obtained with a consistent continuous energy MCNP5 core model.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2010

SCALE Sensitivity Calculations Using Contributon Theory

The SCALE TSUNAMI-3D sensitivity and uncertainty analysis sequence computes the sensitivity of k-eff to each constituent multigroup cross section using adjoint techniques with the KENO Monte Carlo codes. A new technique to simultaneously obtain the product of the forward and adjoint angular flux moments within a single Monte Carlo calculation has been developed and implemented in the SCALE TSUNAMI-3D analysis sequence. A new concept in Monte Carlo theory has been developed for this work, an eigenvalue contributon estimator, which is an extension of previously developed fixed source contributon estimators. A contributon is a particle for which the forward solution is accumulated, and its importance to the response, which is equivalent to the adjoint solution, is simultaneously accumulated. Thus, the contributon is a particle coupled with its contribution to the response, in this case keff. As implemented in SCALE, the contributon provides the importance of a particle exiting at any energy or direction for each location, energy and direction at which the forward flux solution is sampled. Although currently implemented for eigenvalue calculations in multigroup mode in KENO, this technique is directly applicable to continuous-energy calculations for many other responses such as fixed-source sensitivity analysis and quantification of reactor kinetics parameters. This paper provides the physical bases of eigenvalue contributon theory, provides details of implementation into TSUNAMI-3D, and provides results of sample calculations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Reduced-order modeling for efficient cross section library development in high-temperature gas reactor pebble-bed depletion analysis

Accurate modeling of running-in and equilibrium conditions in pebble-bed reactors (PBRs) requires precise microscopic multigroup neutron cross sections. In Griffin, deterministic neutronics calculations rely on multivariate interpolation over large cross section libraries, resulting in significant memory usage and performance bottlenecks. This work, together with a companion paper on Griffin integration, explores reduced-order models (ROMs) to replace interpolation with lightweight surrogates. Several ROM techniques are benchmarked, with deep neural networks (DNNs) demonstrating superior memory efficiency, scalability, and predictive accuracy. A total of 295 DNNs were trained to build a comprehensive isotope library, integrated into Griffin through a custom LibTorch interface for depletion analysis. Initial results demonstrate that DNN-based ROMs drastically reduce memory demands while preserving accuracy, enabling finer tabulations and additional state variables without overhead. In conclusion, the framework also supports online cross section generation and real-time DNN updates through transfer learning, improving fidelity by capturing self-shielding and evolving nuclide compositions during burnup.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Group structure selection with random forests

Choosing an appropriate group structure for multigroup transport is far from an exact science. For some applications, one blindly uses a group structure developed years ago by forgotten methods. Furthermore, one sometimes uses the same group structure for a variety of problems, even if the group structure was originally developed with a certain application in mind. In this work, we create optimized group structures with simulated annealing for critical assembly test problems and apply a random forest regressor with bagging to choose the best group structure based on parameters of the different test problems. The optimized group structures were generated using a simulated annealing optimizer for several simple, spherical, and unreflected problems. The optimization was performed to minimize a cost function that included fission rate, absorption rate, leakage, and k{sub eff}. A random forest regressor was then trained on a set of International Criticality Safety Benchmark Evaluation Project inputs and used to select one of these six group structures. The trained machine learning model chose the best group structure 65% of the time, and one of the three best 89% of the time. Furthermore, it decreased the L2 error over all test problems by a factor of 25 when compared to the standard Los Alamos 70-group structure. In other words, the model chose group structure that were far more appropriate for the test problems than the traditional LANL group structure. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Setup and verification of a SCALE/KENO platform for generic FHR benchmark calculations

The work presented in this article is preliminary to downstream analysis of a generic fluoride salt-cooled high-temperature reactor (gFHR) core performed by the University of Tennessee in collaboration with Kairos Power (KP). A Monte Carlo transport model of the publicly available gFHR equilibrium core is developed in SCALE/KENO with multigroup energy treatment. Several output quantities of interest are used to verify the simulations against a benchmark model developed by KP using the continuous energy Monte Carlo code Serpent 2. Good agreement is seen in flux and fission rate profiles with a maximum relative difference of 1.4% and 2.8% respectively. Furthermore, an effective multiplication factor bias of 44 pcm was observed between the two simulations. The fuel temperature reactivity coefficient calculated with SCALE is within uncertainty to the reference model. This verification acts as a publicly reproducible benchmark for the gFHR in SCALE/KENO. A simplified depletion model is also presented where a single fuel pebble is depleted to discharge burnup through the equilibrium core while the equilibrium core is assumed to be invariant. This method produces results that intercept the equilibrium core concentrations in every case, however, an interesting artifact of this particular depletion model is uncovered. The phenomenon is shown to be a fundamental feature of the differential rate equations and inspires questions about how this system behaves when the time evolution of the equilibrium core is considered. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Adjoint sensitivity analysis and data assimilation for verification of dry storage cask contents

Dry cask storage is a method for interim storage of spent fuel assemblies which contain fissile isotopes of uranium and plutonium. These can present a proliferation concern and consequently there is a need for non-destructive testing methods to verify a dry cask's contents for proliferation protection. We present an application of adjoint sensitivity analysis and data assimilation to a multigroup diffusion model of dry cask storage. Adjoint sensitivity analysis allows the efficient calculation of sensitivities for use in data assimilation to calibrate imprecisely known parameter values and data consistency tests to detect diversion scenarios. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

POLCA8 - modelling of cross section variations inside hexagonal assemblies

This paper presents the POLCA8 approach for modelling non-constant cross section distributions inside hexagonal fuel assemblies. The multigroup diffusion equation is modified to account for intranodal cross section variations. The obtained equation is solved in a node-wise manner based on the Fourier expansion method. As a result of varying cross sections, the solution includes a particular part additionally to the homogeneous one. A method for obtaining the particular solution is derived. Numerical tests on a VVER-1000 core are presented showing the impact of cross-section variations to some key parameters for reactor operation. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Performing k eff Validation of As-Loaded Criticality Safety Calculations Using UNF-ST&DARDS: Sensitivity Calculations

The general method for performing validation of as loaded criticality safety calculations using UNF ST&DARDS is presented in a paper by Clarity, which includes a description of the UNF-ST&DARDS system. Proof-of-principle analyses were performed in the summer of 2019 for MPC-32 dual purpose canisters (DPCs) containing pressurized water reactor (PWR) fuel assemblies. Summaries of these results are presented in this and a companion paper for this conference. The current paper describes the TSUNAMI-3D calculations performed to generate sensitivity data, and the companion paper discusses the selection of critical experiments applicable for validation of the 11 MPC-32 DPCs considered. The generation of sensitivity data for as-loaded spent nuclear fuel (SNF) DPCs is a challenge given the detailed model of the fuel compositions generated by UNF ST&DARDS. Each fuel assembly is modeled with its own irradiation history in 18 axial nodes, unless the fuel assembly is damaged and thus considered as fresh by design basis. This results in a set of 576 fuel compositions, each of which must be processed separately in a multigroup (MG) calculation. Therefore, a continuous-energy (CE) TSUNAMI-3D method was chosen to alleviate this challenge. Two CE TSUNAMI-3D methods are available in SCALE 6.2.3: the iterated fission probability (IFP) and contribution-linked eigenvalue sensitivity/uncertainty estimation via track-length importance characterization (CLUTCH). Since the IFP method is not feasible because of memory requirements associated with its implementation in SCALE, the CLUTCH method was selected for these calculations. CLUTCH has been implemented in SCALE in parallel, allowing long calculations to be performed in reasonable timeframes. The two primary user inputs necessary for CLUTCH calculations are the F*(r) mesh and the number of latent generations used in determining the F*(r) function. This F*(r) function is used as the importance function for fission chains originating in a given volume element (voxel), and it is calculated using the IFP method in the skipped generations. A large number of skipped generations is thus required to ensure accurate calculation of this importance function. In these calculations, 500 generations were used to calculate the F*(r) function. For more information regarding the calculation of F*(r), see Jones [4]. The remainder of this paper is focused on the selection of the F*(r) mesh and the number of latent generations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Analysis of SCALE Criticality and Sensitivity Calculations for Reflected HEU Cylinders

The SCALE code package offers multiple nuclear data libraries and sensitivity and uncertainty (S/U) methods supporting and derived from Monte Carlo (MC) transport. The CSAS and TSUNAMI-3D sequences use KENO MC, utilizing either continuous-energy (CE) cross sections or multigroup (MG) cross section libraries. TSUNAMI-3D has two CE calculational methods: the iterated fission probability (IFP) method, and the Contribution-Linked eigenvalue sensitivity/Uncertainty estimation via Tracklength importance CHaracterization (CLUTCH) method. Previous work has shown poor agreement between CLUTCH and confirmatory direct perturbation calculations in specific applications (e.g., fissionable and polyethylene reflectors). The HEU-MET-FAST-084 (HMF-084) International Criticality Safety Benchmark Evaluation Project evaluation consists of 27 cylindrical highly enriched uranium metal cores with 14 unique reflector materials of 0.5 and 1 in. thicknesses. Included in this list of reflector materials are natural uranium and polyethylene. This work utilized SCALE 6.2.4 models of the HMF-084 evaluation, with additional non-physical configurations to test both the MG bias and CLUTCH functionality across a variety of reflector material thicknesses. The evaluation’s use of concentric cylinders allowed for examination of several MG self-shielding methods: infinite homogenous, cylindrical, and spherical. The results indicate that the use of polyethylene reflectors with CLUTCH is not fundamentally impossible but sensitive to geometry. The poor performance of CLUTCH with fissionable reflectors was reaffirmed. The 2 in. and greater polyethylene-reflected calculations demonstrate the necessity of using the 302-group library for fast systems. The nickel MG bias was substantial, as discussed in a companion paper, as were cobalt and iron.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2015

FY15 Status Report on NEAMS Neutronics Activities

This report summarizes the current status of NEAMS activities in FY2015. The tasks this year are (1) to improve solution methods for steady-state and transient conditions, (2) to develop features and user friendliness to increase the usability and applicability of the code, (3) to improve and verify the multigroup cross section generation scheme, (4) to perform verification and validation tests of the code using SFRs and thermal reactor cores, and (5) to support early users of PROTEUS and update the user manuals.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

SCEPTRE 1.4 Quick Start Guide

This report provides a summary of notes for building and running the Sandia Computational Engine for Particle Transport for Radiation Effects (SCEPTRE) code. SCEPTRE is a general purpose C++ code for solving the Boltzmann transport equation in serial or parallel using unstructured spatial finite elements, multigroup energy treatment, and a variety of angular treatments including discrete ordinates. Either the first-order form of the Boltzmann equation or one of the second-order forms may be solved. SCEPTRE requires a small number of open-source Third Party Libraries (TPL) to be available, and example scripts for building these TPL’s are provided. The TPL’s needed by SCEPTRE are Trilinos, boost, and netcdf. SCEPTRE uses an autoconf build system, and a sample configure script is provided. Running the SCEPTRE code requires that the user provide a spatial finite-elements mesh in Exodus format and a cross section library in a format that will be described. SCEPTRE uses an xml-based input, and several examples will be provided.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗