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Results for “Nuclear Criticality Safety Program (NCSP)”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Adapting CLUTCH methodology to multigroup TSUNAMI-3D for eigenvalue sensitivity calculations

The sensitivity of the eigenvalue to uncertainties in nuclear data and its evaluation are important for nuclear criticality safety. TSUNAMI-3D sequences within the SCALE code system offer several options to the user community for calculating eigenvalue sensitivity coefficients with multigroup (MG) and continuous energy (CE) 3D transport capabilities. TSUNAMI-3D sequences implement the adjoint-based perturbation theory with MG KENO code, the Contributon Linked eigenvalue sensitivity/Uncertainty estimation via Track length importance CHaracterization (CLUTCH) method with CE KENO code, and the Iterated Fission Probability (IFP) method with CE KENO and Shift codes. Each method has benefits and limitations depending on the problem that is run. The work presented here aims to adapt the CLUTCH method, which enables the Contributon method's mesh-free, memory-efficient approach for calculating adjoint-weighted tallies for sensitivity calculations, to the MG TSUNAMI-3D sequence. This application would eliminate the explicit adjoint KENO calculation, as well as the memory-consuming mesh flux moment tallies required by the conventional MG TSUNAMI-3D. Smaller memory footprints in the CLUTCH methodology and relatively shorter runtimes in MG KENO transport can make MG TSUNAMI-3D a viable method for some complex problems. Moreover, this adaptation allows MG sensitivity calculations with Shift, ORNL's next-generation high-performance Monte Carlo transport code, which currently does not offer any sensitivity capabilities with MG particle transport simulations. Initial implementation of the new MG TSUNAMI-3D sequence and its preliminary results with a selected critical benchmark experiment in the Verified, Archived Library of Inputs and Data (VALID) are presented in this study.

KENO↗
DOE OSTI2024

Independent Review of Non-Destructive Assay for the K-25/K-27 D&D Project: November 30-December 3, 2004, Oak Ridge, TN

The DOE with concurrence from the D&D contractor has chartered an assessment of the methods and procedures used to obtain the original NDA results of holdup deposits at the K-25 and K-27 uranium gaseous diffusion facilities in Oak Ridge. The assessment has been performed by an external review team with the participation of the D&D contractor, DOE, and DOE/OR. This document is the final report for the assessment. The DOE provided the charter for this review. The review team spent a week in Oak Ridge attending meetings and participating in discussions with expert contractor staff. Substantial additional input for the review came from numerous written materials, unpublished and published. This final report of observations, findings, and recommendations in areas defined by the charter is based on information from the meetings, discussions, and documents. The assessment of the Review Team is that the DOE/OR and BJC approach in using historical NDA data for the D&D of K-25 and K-27 is appropriate and generally acceptable. Resolving issues, addressing findings, and implementing the recommendations documented in this report will reconcile specific technical concerns.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Flattop-HEU Benchmark Reevaluation Summary

The Flattop critical assembly was first constructed in the 1950’s at Los Alamos National Laboratory as a follow-on to the Topsy experiment. Flattop is composed of a sphere of special nuclear material (SNM) surrounded by a thick spherical reflector made of natural uranium (NU). Two SNM cores currently exist: a highly-enriched-uranium (HEU) core and a plutonium core. The reflector is composed of three parts: a stationary hemisphere and two movable quarter spheres. For fine reactivity control, there are three control rods of NU that are inserted into the stationary hemisphere from underneath the assembly. The final components that allow for reactivity adjustment are the glory hole pieces, mass adjustment buttons, and hemispherical caps. These pieces can be loaded in various configurations to change the available reactivity loaded in the system.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

The MUSIC Critical Benchmark and Nuclear Data

The Measurement of Uranium Subcritical and Critical (MUSIC) experiment was a series of measurements of critical and subcritical configurations of bare highly enriched uranium. The goal was to compare measurement methods, analysis techniques, and simulation methods across regimes of criticality and to provide high-quality validation of 235 U nuclear data. A benchmark evaluation of the two critical configurations of the MUSIC experiments will soon be published in the release of the International Criticality Safety Benchmark Evaluation Project Handbook. The recent execution of the experiment aids in proper quantification of model simplifications and all uncertainties associated with the experiment. Historical benchmark evaluations are heavily relied on for uranium nuclear data validation despite the fact that the same level of documentation and comparable uncertainty analysis may not be present. The MUSIC evaluation is less likely to include “unknown unknowns” that could impede accurately modeling the system. Presented are both highly detailed and very simplified models, which represent the experimental configurations accurately, aiding the users of the benchmark for nuclear data or transport code validation. The sensitivities of k eff to nuclear data and nuclear data–related uncertainties are very similar between this experiment and previous bare uranium sphere experiments. In addition, the nuclear data uncertainties to any nuclides other than 235 U are small. For all these reasons, the recently evaluated MUSIC benchmark critical configurations could prove very useful for 235 U nuclear data validation. Currently, major libraries have good agreement with the experimental results, within 200 pcm for all nuclear data libraries, and within one standard deviation of the experimental result for most. Suggested nuclear data adjustments based on MUSIC and Lady Godiva are also presented, with posterior improvements to both the agreement in k eff and the uncertainty associated with the nuclear data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Measurement of the prompt fission neutron spectrum from 800 keV to 10 MeV for 240 Pu(sf) and for the 240 Pu($n,f$) reaction induced by neutrons of energy from 1–20 MeV

Here, the presence of 240 Pu in nuclear fuels for reactors has resulted in high uncertainties in the results of reactor and nuclear transmutation calculations because of deficiencies in 240 Pu-related nuclear data. Specifically for the prompt fission neutron spectrum (PFNS) of 240 Pu, there is only one neutron-induced, (n,f), measurement at 0.85 MeV incident neutron energy and only one complete spontaneous fission, (sf), measurement. This limited availability of data does not sufficiently guide nuclear data evaluations of these quantities. Here we report on a measurement of both the 240 Pu(sf) and the 240 Pu(n,f) PFNS, both over the emitted neutron energy range of 0.79–10.0 MeV, and from incident neutron energies of 1.0–20.0 MeV for the (n,f) reaction. Measurements were made with a hemispherical array of liquid scintillators at the high-energy Los Alamos Neutron Science Center white neutron source at the Weapons Neutron Research facility as part of the joint LANL-LLNL Chi-Nu experimental campaign to measure actinide fission neutron spectra. These measurements are the first of their kind, and provide clear experimental evidence for second-chance fission, third chance fission, and pre-equilibrium neutron emission processes in neutron-induced fission of 240 Pu, and are the first ever measurements above 1 MeV incident neutron energy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Annual Report on NCSP Technical Support task in BNL during FY25

This work reports on the investigations done during FY 25 in collaboration with one 2025 Summer undergraduate intern through the DOE SULI program. These efforts were partially funded by the Nuclear Criticality Safety Program through the Technical Support Succession Plan task. This project, developed by Matthew Molnar, aimed to apply the BNL’s machine-learning code to correct spin mis-assignments in neutron resonances, the Bayesian Resonance Reclassifier (BRR), to the odd-even nucleus 143 Nd. For this, the handling of spingroup classification had to be further investigated and improved.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

NCSP Outlook and Interest for Collaboration on HST Experiments [Slides]

The majority of the NCSP budget goes to Integral Experiments. The goal is to produce needed integral data for criticality safety needs in DOE, largely resulting in ICSBEP benchmarks. NCSP has a well defined process for allocating funding through proposals and expert review. NCSP is a fairly small program and funding is prioritized for experiments that would address DOE criticality safety needs. The majority of the currently identified DOE criticality safety needs are HEU and Pu systems. NCSP has a formal mechanism to ensure quality and benefit through the phase gates and approvals within the CED process.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

A Resolved Resonance Evaluation for 51 V with Resonance Parameter Covariance

In this presentation the 51 V evaluation in response to NCSP need is completed. Issues in connection to RR representation are addressed. Uncertainty and covariance information derived with the evaluation. Evaluation proposed and accepted for inclusion in ENDF/B-VIII.1 library.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

NCSP supports 240 Pu prompt fission neutron spectrum (PFNS) evaluation

A new 240 Pu PFNS evaluation was recently undertaken at LANL as a strategic priority. It truly is an NCSP end-to-end product. It factors in a new differential experiment funded by NCSP, builds on theoretical work coming out of a previous NCSP nuclear data evaluation milestone and was validated with an NCERC experiment that was recently evaluated as an integral benchmark with NCSP funds.

240Pu↗
DOE OSTI2024

TEX-HEU: Integral Experiment Execution with Polyethylene at Very Low Temperatures

The low-temperature variant of the TEX HEU (called Low-Temperature TEX or sometimes LT TEX) campaign is a highly anticipated and necessary experimental series by the greater nuclear science community. Fundamentally, the need for low-temperature integral experiments is required to perform validation of cross sections below room temperature. There has been substantial international interest in low-temperature benchmarks to validate below room temperature cross sections, namely talks given at the 2019 International Conference on Nuclear Criticality (ICNC): UK (Watson, 2019), France (Milin, 2019), and UK (Gan & Wilson, 2019). Additionally, NCSP funded thermal scattering laws (TSLs) were produced by North Carolina State University and require low-temperature benchmarks to validate them. Validation of low-temperature cross sections is also necessary for criticality safety applications. One particularly important application is to ensure that during transportation, fissile materials must remain subcritical under normal ambient conditions which is defined as temperatures down to -40°C/°F by the United States 10 CRF 71 as well as a regulation put forward by the International Atomic Energy Agency (IAEA).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Automated Resonance Fitting for Nuclear Data Evaluation

Global and national efforts to deliver high-quality nuclear data to users have a wide-ranging impact, affecting applications in national security, reactor operations, basic science, medicine, and more. Cross section evaluation is a major part of this effort, combining theory and experimentation to produce recommended values and uncertainties for reaction probabilities. Resonance region evaluation is a specialized type of nuclear data evaluation that can require significant manual effort and months of time from expert scientists. In this article, non-convex non-linear optimization methods are combined with concepts of inferential statistics to infer a resonance model from experimental data in an automated manner that is not dependent on prior evaluation(s). This methodology aims to enhance the workflow of a resonance evaluator by minimizing time, effort, and the potential for bias from prior assumptions, while enhancing reproducibility and documentation, thereby addressing well-known challenges in the field.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

A new 181 Ta neutron resolved resonance region evaluation

A new 181 Ta neutron resolved resonance region evaluation has been performed from the thermal energy range up to approximately 2.5 keV. The R-matrix SAMMY code was used with the Reich–Moore approximation to evaluate resonance parameters from several experimental data sets. A Monte Carlo approach was used for resonance spin assignments and generating 59 small fictitious resonance levels which were shown to improve the cumulative level, Porter-Thomas, and Wigner distributions as compared to theoretical predictions. Covariance information was also generated for the entire resolved resonance region. Finally, the positive impact of the new evaluation was validated through benchmark calculations which were sensitive to the 181 Ta cross section and showed improvement in the reactivity bias for several benchmark cases.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Direct NeTS sampling of nuclear graphite $S(α, β, T)$ in Serpent

For advanced reactor applications, Neural Thermal Scattering (NeTS) modules were developed to predict the thermal scattering law (TSL or $S(α, β, T)$) of a nuclear graphite neutron moderator. NeTS are multi-layer, feedforward artificial neural networks, which act as universal function approximators designed for TSL datasets. In this case, a 4-layer neural network with 164 neurons per layer is trained using FLASSH evaluated data in PyTorch and serialized as a torchscript dictionary to predict $S(α, β, T)$ on-the-fly. Relative, absolute and maximum percent deviations of NeTS from File 7 data generated using the FLASSH code are on the order of 0.01%, 0.1% and 1%, respectively, with low inference latencies of 0.000172 s per $S(α, β, T)$ at a given temperature. Capturing the full dimensionality of possible inelastic neutron-lattice interactions, NeTS functionality is embedded in the Serpent Monte Carlo code, where $S(α, β, T)_{NeTS}$ sampling is conducted on-the-fly and compared to ACE look-up-tables for predicting TREAT criticality. k-eff differences between sampling algorithms of 6 pcm are observed and are within the order of Monte Carlo uncertainty. Compared to discrete and continuous-energy ACE files (30 MB and 131 MB per temperature), the NeTS format is on the order of 200–300 kB for a continuous-temperature, interpolation-free representation of $S(α, β, T)$ and cross sections. NeTS-in-Serpent runtimes comparable with ACE look-up tables are achieved by scaling NeTS for high performance computing architectures with hybrid OpenMP + MPI parallelization. This work validates a novel, self-contained reactor physics framework for predictive cross sections, and demonstrates a general methodology for embedding modern machine learning libraries within existing neutronic analysis frameworks.

Nuclear Criticality Safety Program (NCSP)↗
DOE OSTI2024

Fast neutron leakage spectra of the EUCLID experiment

Special nuclear material in sub-critical and critical configurations measured in integral experiments are important for validation and adjustment of nuclear data. Many different evaluations of nuclear data exist, and these different evaluations can provide different values for individual cross sections that vary due to the uncertainties in differential experiments or lack of such data. For integral experiments, differences in these individual cross sections can have compensating errors, which lead to the same answer. One example of this is the Jezebel critical assembly, where k eff of the system is correctly computed by both ENDF/B-VIII.0 and JEFF-3.3, despite having substantially different underlying evaluated values for specific reactions (such as elastic and inelastic cross sections). To reduce compensating errors in nuclear data, the Experiments Underpinned by Computational Learning for Improvements in Nuclear Data (EUCLID) project has utilized machine learning to design a set of sub-critical and critical experiments. These experiments include slab- and cube-like configurations of 239 Pu in the form of the ZPPR plates. Six different responses were measured on a total of thirteen different configurations. One of these responses, the neutron leakage spectrum, was measured using an EJ301D detector. Finally, the results of the neutron leakage spectra show good agreement (within 1–2 σ ) with the expected spectrum from simulations and will be used in the subsequent nuclear data adjustment done by the EUCLID team.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗