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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 109 records · Page 6

Development and testing of the VITAMIN-B7/BUGLE-B7 coupled neutron-gamma multigroup cross-section libraries

The U.S. Nuclear Regulatory Commission's Regulatory Guide 1.190 states that calculational methods used to estimate reactor pressure vessel (RPV) fluence should use the latest version of the evaluated nuclear data file (ENDF). The VITAMIN-B6 fine-group library and BUGLE-96 broad-group library, which are widely used for RPV fluence calculations, were generated using ENDF/B-VI.3 data, which was the most current data when Regulatory Guide 1.190 was issued. We have developed new fine-group (VITAMIN-B7) and broad-group (BUGLE-B7) libraries based on ENDF/B-VII.0. These new libraries, which were processed using the AMPX code system, maintain the same group structures as the VITAMIN-B6 and BUGLE-96 libraries. Verification and validation of the new libraries were accomplished using diagnostic checks in AMPX, 'unit tests' for each element in VITAMIN-B7, and a diverse set of benchmark experiments including critical evaluations for fast and thermal systems, a set of experimental benchmarks that are used for SCALE regression tests, and three RPV fluence benchmarks. The benchmark evaluation results demonstrate that VITAMIN-B7 and BUGLE-B7 are appropriate for use in RPV fluence calculations and meet the calculational uncertainty criterion in Regulatory Guide 1.190. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Multigroup computation of the temperature-dependent Resonance Scattering Model (RSM) and its implementation

A multi-group formulation for the exact neutron elastic scattering kernel is developed. This formulation is intended for implementation into a lattice physics code. The correct accounting for the crystal lattice effects influences the estimated values for the probability of neutron absorption and scattering, which in turn affect the estimation of core reactivity and burnup characteristics. A computer program has been written to test the formulation for various nuclides. Results of the multi-group code have been verified against the correct analytic scattering kernel. In both cases neutrons were started at various energies and temperatures and the corresponding scattering kernels were tallied. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Adaptive Sparse-Grid Stochastic Collocation Uncertainty Quantification Convergence for Multigroup Diffusion

Advanced methods in uncertainty quantification for numerical models in computational physics continue to gain acceptance in nuclear modeling. Previously, the efficiency of sparse-grid stochastic collocation in comparison with Monte Carlo for uncertainty quantification through convergence studies was demonstrated. An adaptive method for anisotropic sparse grid collocation and its convergence compared to previous efforts is considered. The physical system in consideration is a two-dimensional quarter-core reactor, consisting of 5 materials distributed in 121 regions. The two-group neutron diffusion criticality approximation is solved. Vacuum boundaries are applied on the top and right, and reflecting boundaries on the bottom and left. The material cross sections, neutron multiplication factors, and diffusion coefficients are potential sources of uncertainty. Uniformly-distributed uncertainty within 5% of the reference values is introduced for material properties. The distribution of the uncertain parameters make up the uncertainty space Γ included in R{sup N}, where N is the number of uncertain parameters. The input parameter uncertainties are independently distributed. As expected, the convergence of Monte Carlo on the benchmark as a function of computational solves is nearly linear and lethargic compared to the other methods. The static isotropic index set, in which each input dimension is treated with equal importance, converges much more efficiently than Monte Carlo, but lacks the benefit of emphasizing some dimensions over others. The anisotropic case is most efficient, where first-order sensitivity information was used to determine anisotropic weights for polynomials to use in the polynomial chaos expansion. Interestingly, the adaptive algorithm converges slightly less efficiently than the anisotropic case, while still performing better than the isotropic case. Because the adaptive case has to determine the importance of each input dimension, it occasionally predicts inaccurately and wastes computation solves compared to the more ideal anisotropic case. However, in circumstances when an ideal anisotropy is not understood a priori, the adaptive algorithm may be optimally efficient in representing the original model. Given the potential loss of efficiency when using a poorly-chosen anisotropic weighting, the adaptive algorithm may be an effective choice for initial uncertainty quantification in problems with a low-dimensionality input space. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

GPU Acceleration of History-Based Multigroup Monte Carlo

Accurate solutions of the radiation transport equation play an important role in the analysis of many nuclear systems. Because there is no need to discretize the problem, Monte Carlo methods offer the most accurate possible solutions to the transport equation. However, significant computational effort is required to reduce the stochastic noise inherent to Monte Carlo methods. Current trends in high performance computing are moving towards vectorized, single instruction multiple data (SIMD), architectures such as Intel Xeon Phis and graphics processing units (GPUs) due to their favorable ratio of performance to power consumption. The challenge of adapting Monte Carlo transport to vectorized computing architectures was first addressed by Brown with an algorithm known as event-based Monte Carlo. In this approach, rather than simulating individual particle histories from birth to death, groups of particles are processed one event at a time. This allows each event batch to perform the same operations in lockstep, enabling use of the vector hardware. Although modern vectorized hardware is more versatile than the early vector machines, reducing so-called thread divergence is nonetheless still an important consideration for algorithm design. Many of the algorithms proposed so far for Monte Carlo transport on advanced architectures have focused on variants of event-based transport. Some evidence, however, suggests that low-level thread divergence, resulting from short-lived branching statements, may not be detrimental to overall performance on GPUs as long as the effect on achievable memory bandwidth is considered. This paper characterizes the performance of a traditional history-based Monte Carlo algorithm on GPUs. We show that with only minor modifications to traditional algorithms, significant performance gains relative to CPUs are possible. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Application of Machine Learning to Multigroup Microscopic Cross Sections

Presentation discussing the research and development of deep neural network models for modeling microscopic neutron cross-section data in the Griffin reactor physics application for pebble-bed reactors. This work details advancements made between the last review meeting in July 2024 until July 2025.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

An improved random walk algorithm for the implicit Monte Carlo method

In this work, we introduce a modified Implicit Monte Carlo (IMC) Random Walk (RW) algorithm, which increases simulation efficiency for multigroup radiative transfer problems with strongly frequency-dependent opacities. To date, the RW method has only been implemented in “fully-gray” form; that is, the multigroup IMC opacities are group-collapsed over the full frequency domain of the problem to obtain a gray diffusion problem for RW. This formulation works well for problems with large spatial cells and/or opacities that are weakly dependent on frequency; however, the efficiency of the RW method degrades when the spatial cells are thin or the opacities are a strong function of frequency. To address this inefficiency, we introduce a RW frequency group cutoff in each spatial cell, which divides the frequency domain into optically thick and optically thin components. In the modified algorithm, opacities for the RW diffusion problem are obtained by group-collapsing IMC opacities below the frequency group cutoff. Particles with frequencies above the cutoff are transported via standard IMC, while particles below the cutoff are eligible for RW. This greatly increases the total number of RW steps taken per IMC time-step, which in turn improves the efficiency of the simulation. We refer to this new method as Partially-Gray Random Walk (PGRW). We present numerical results for several multigroup radiative transfer problems, which show that the PGRW method is significantly more efficient than standard RW for several problems of interest. In general, PGRW decreases runtimes by a factor of ∼2–4 compared to standard RW, and a factor of ∼3–6 compared to standard IMC. While PGRW is slower than frequency-dependent Discrete Diffusion Monte Carlo (DDMC), it is also easier to adapt to unstructured meshes and can be used in spatial cells where DDMC is not applicable. This suggests that it may be optimal to employ both DDMC and PGRW in a single simulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Many-Group Cross-Section Adjustment Techniques for Boiling Water Reactor Adaptive Simulation

Computational capability has been developed to adjust multigroup neutron cross sections, including self-shielding correction factors, to improve the fidelity of boiling water reactor (BWR) core modeling and simulation. The method involves propagating multigroup neutron cross-section uncertainties through various BWR computational models to evaluate uncertainties in key core attributes such as core k{sub eff}, nodal power distributions, thermal margins, and in-core detector readings. Uncertainty-based inverse theory methods are then employed to adjust multigroup cross sections to minimize the disagreement between BWR core modeling predictions and observed (i.e., measured) plant data. For this paper, observed plant data are virtually simulated in the form of perturbed three-dimensional nodal power distributions with the perturbations sized to represent actual discrepancies between predictions and real plant data. The major focus of this work is to efficiently propagate multigroup neutron cross-section uncertainty through BWR lattice physics and core simulator calculations. The data adjustment equations are developed using a subspace approach that exploits the ill-conditioning of the multigroup cross-section covariance matrix to minimize computation and storage burden. Tikhonov regularization is also employed to improve the conditioning of the data adjustment equations. Expressions are also provided for posterior covariance matrices of both the multigroup cross-section and core attributes uncertainties.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

On the Degradation of the Effectiveness of Nonlinear Diffusion Acceleration with Parallel Block Jacobi Splitting

MOOSE's radiation transport module Rattlesnake comprises a first order S N solver that can be accelerated with a flexible Nonlinear Diffusion Acceleration. At each NDA iteration, the streaming and collision operator of the S{sub N} equations are (approximately) inverted using a transport sweep. When executed on multiple processors parallel block Jacobi (PBJ) splitting is utilized lagging the processor sub-domain's incoming angular fluxes making the implemented method asynchronous, i.e. the convergence properties of NDA become dependent on the number of concurrent tasks and details of the partitioning. Within this work, we study the NDA convergence properties for the two-dimensional C5G7 benchmark problem PBJ with p = 1, 2, 4, 8, 12, 16, 24, 32, 48, 60, 72, 96 and 144 concurrent tasks. Rosa studied the convergence properties of PBJ splitting methods with and without transport synthetic acceleration (TSA) in slab geometry and two-dimensional Cartesian geometry, respectively. Rosa's iteration scheme lags both the incoming angular fluxes and the scattering source making it very similar to the method described here. Rosa found by means of Fourier analysis that convergence of unaccelerated PBJ can degrade for optically thin subdomains, i.e. for a large number of processors given a fixed domain size. Depending on the choice of parameters application of TSA can lead to an effective algorithm. In contrast to Rosa's work, this work focuses on PBJ splitting for NDA accelerated solution of the multigroup eigenvalue problem. Later, Zerr and Anistratov used their integral transport matrix method in conjunction with PBJ. This iteration scheme is different as it does not lag the scattering source. Nevertheless, Fourier analysis with Diamond Difference spatial discretization showed that the method degrades with increasing the overall size of the spatial domain while keeping the sub-domain size constant. In the case of an infinite medium, the observed spectral radius becomes unity. These references establish the iterative performance of PBJ for one-group fixed source problems discretized on rectangular cells, but for the Rattlesnake first order NDA method, an emphasis lies on multigroup eigenvalue problems. In this setting, the additional complication arises that the low order equations are not exactly inverted, but only to some iterative criterion. Further, as the low order problem is solved using Jacobian-Free Newton Krylov methods, a suitable preconditioner for the GMRES iterations is required. As the effectiveness of the preconditioners may decrease when more concurrent processes are used, we expect the low order solve to impact the overall effectiveness of the NDA method in parallel execution as well. Therefore, this work focuses on the question of how detrimental the asynchronicity of the high and low order iterative solutions is for the effectiveness of NDA solutions of realistic, unstructured grid, multigroup eigenvalue problems. The iterative convergence properties of Rattlesnake's NDA method for multigroup eigenvalue problems are studied for varying number of concurrent processes. Rattlesnake's NDA method is asynchronous because the high order transport sweep uses PBJ splitting and because the low order solve's preconditioners, algebraic multigrid and additive Schwarz, are asynchronous. We found that up to 144 processes the number of Picard iterations increases by a factor of 2-3 affecting but not destroying NDA's parallel performance for the C5G7 benchmark problem, a representative LWR (light water reactor) configuration. The solution of the NDA low order eigenvalue problem posed greater problems than expected for the solvers currently available in Rattlesnake mainly because of problems to effectively precondition the modified low-order problem. As a matter of fact, the low order problem becomes an advection-diffusion problem. Non-robustness was observed for the AMG preconditioned coarse mesh acceleration for more than 60 concurrent processes, which was fixed by increasing the number of permissible V-cycles per AMG call. For fine mesh acceleration AMG proved to be ineffective and we resorted to ASM. For both AMG and ASM, increasing number of linear iterations per nonlinear are observed when increasing the number of processes, but for ASM this problem appears to be worse. The results from this work also indicate that initial development efforts should be diverted from implementation of a high-order parallel sweeping algorithm to the effective and robust iterative solution of the low order NDA multigroup eigenvalue problem. (authors)

97 MATHEMATICS AND COMPUTING↗

Molten Salt Reactor Experiment Simulation using Shift/Griffin

The Department of Energy (DOE)’s NEAMS focuses its efforts on the development of advanced modeling and simulation (M&S) tools for light-water reactors (LWRs) and non–LWRs (i.e., molten salt reactors, high-temperature gas reactors, microreactors, and fast reactors). In the previous fiscal year, the Multiphysics Applications Driver Technical Area funded molten salt reactor (MSR) M&S at Oak Ridge National Laboratory (ORNL) to generate multigroup macroscopic cross sections with Shift for a MSRE 2D lattice model in Griffin. In addition, Shift’s capability to calculate gamma dose rates from activated components in the primary exchangers in a molten salt breeder reactor was also demonstrated. In fiscal year 2023, ORNL generated multigroup macroscopic cross sections using Shift for a 3D MSRE core model. MSRE depletion calculations using Griffin were also demonstrated in this fiscal year. For the depletion calculation, one-group microscopic cross sections for the 3D MSRE core were generated using Shift, and the decay transmutation library from ORIGEN was converted to an ISOXML file, which is required as input in Griffin. Several Monte Carlo codes, such as OpenMC and Serpent, were also used to benchmark and supplement multigroup cross sections generated by Shift. Multigroup libraries were generated with 8 and 20 group structures, and the study found the 8-group structure to be more accurate when comparing Griffin results to continuous energy (CE) Monte Carlo results. The average flux from CE Shift calculations is up to ~6% higher than the CE Serpent calculations because of different values applied for the energy released per fission (κ values). The average flux in the fuel salt calculated by Griffin using cross sections generated with Shift agrees well with the reference CE Shift solution; the same is valid for the corresponding Serpent results. The maximum relative error is ~6% and ~2% compared to the CE Shift and Serpent reference solutions, respectively. Meanwhile, the average flux calculated by Griffin in the graphite moderator shows a higher difference in the thermal range when compared to both reference Monte Carlo solutions; this result suggests a need for improvement in cross section generation for the graphite moderator in the thermal range in both Monte Carlo codes. Griffin depletion calculations using cross sections from Shift and Serpent were performed and compared against ORIGEN calculations, and the nuclide densities calculated by Griffin were found to be generally in agreement with those of ORIGEN. Because a different approach was taken to calculate the energy released per fission ( κ values) in Shift and Serpent, a difference in nuclide densities from differences in the average flux was observed between Griffin using Serpent and Shift cross sections. Griffin calculations with Shift cross sections produced higher average flux in the salt than with Serpent cross sections, leading to higher consumption of 235 U and higher production of 135 Xe. For time-dependent depletion calculations, cross sections were generated with Serpent, and Griffin’s results using these cross sections were compared to CE Serpent depletion results, demonstrating good agreement. The average difference in keff between Serpent and Griffin as a function of burnup is about 155 pcm. Similarly, good agreement with small differences up to ~0.5% was also noticed in the nuclide density of 235 U and 135 Xe. More details regarding the methodologies invoked to generate the cross section to make code-to-code comparisons are discussed further in this report. User feedback on Griffin and Shift capabilities that will enhance these calculations is provided in this report for future consideration. The work performed this fiscal year can be extended further for multiphysics coupling of Griffin-Pronghorn/SAM with Mole to study precursor flow and salt chemistry.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

CEPXS

CEPXS is a multigroup-Legendre cross-section generating code. The cross sections produced by CEPXS enable coupled electron-photon transport calculations to be performed with multigroup radiation transport codes, e.g. MITS and SCEPTRE. CEPXS generates multigroup-Legendre cross sections for photons, electrons and positrons over the energy range from 100 MeV to 1.0 keV. The continuous slowing-down approximation is used for those electron interactions that result in small-energy losses. The extended transport correction is applied to the forward-peaked elastic scattering cross section for electrons. A standard multigroup-Legendre treatment is used for the other coupled electron-photon cross sections. CEPXS extracts electron cross-section information from the DATAPAC data set and photon cross-section information from Biggs-Lighthill data. The model that is used for ionization/relaxation in CEPXS is essentially the same as that employed in ITS.

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