The Need to Revise the Flattop- Plutonium Benchmark [Slides]
This presentation begins with a flattop description then touches on current benchmark model, path to reevaluation, planned revision configurations and ends with conclusions.
Benchmarks↗
SEARCH · Engineering Papers
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Implementation of Windowed Multipole into MCNP6.3
This work details the implementation of the Windowed MultiPole(WMP) method of generating cross sections into the monte carlo code MCNP6.3, the verification and validation performed, and potential future improvements to be implemented. Further, this work contextualizes WMP within the broader changes to how nuclear data is stored, iterated upon, and used that have been developing over the past decade.
97 MATHEMATICS AND COMPUTING↗
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↗
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↗
Data Evaluations in Support of NCSP [Slides]
Abstract not provided.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
ORNL Neutron Cross Section Measurements of Zr-isotopes ----NCSP Task ND-1 + ND-3 [Slides]
Abstract not provided.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
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↗
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↗
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)↗
Hauser-Feshbach Analysis of Fast Neutron-Induced Reactions on Chlorine
Neutron-induced reactions on 35Cl have recently been measured and analyzed in a Hauser-Feshbach framework at Los Alamos National Laboratory. Particular focus has been applied to the “fast” energy range above 100 keV, where these reactions become important for applications like CLYC (Cs 2 LiYCl 6 :Ce) detector characterization and the development of molten chloride fast reactors. However, challenges to applying a purely statistical analysis to this mass range have presented themselves in the form of cross section fluctuations and deviations due to low-mass structure. In this paper, these challenges and their current solutions will be highlighted, as well as preliminary extensions of the analysis to neighboring isotopes and future plans to extend the measurements down to thermal energies.
38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DICER: A new instrument at LANSCE to constrain neutron capture rates on radionuclides
With very few exceptions, direct measurements of neutron capture rates on radionuclides have not been possible. A number of indirect methods have been pursued such as the surrogate method, the γ-ray strength function method, the Oslo method and the β-Oslo method. Substantial effort has been devoted to quantify the usually large systematic errors that accompany the results from these techniques. A new instrument has been developed at the Los Alamos Neutron Science Center (LANSCE) to provide more accurate data on several radionuclides relevant to nuclear criticality safety, radiochemical diagnostics, astrophysics, nuclear forensics and nuclear security, by measuring the transmission of neutrons through radioactive samples and studying resonance properties. The Device for Indirect Capture on Radionuclides (DICER) and associated radionuclide production at the Isotope Production Facility (IPF), both at LANSCE, as well radioactive sample fabrication, have been under development the last few years. A description of the new apparatus, data on a few mid-weight stable isotopes and efforts on radionuclide measurements will be presented.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Subcritical Neutron and Gamma Noise Measurements at the Seven Percent Critical Experiment (7uPCX)
As part of a collaborative international effort organized by Lawrence Livermore National Laboratory (LLNL), with key participants from L’Institut de radioprotection et de sûreté nucléaire (IRSN), Los Alamos National Laboratory (LANL), and Sandia National Laboratories (SNL), a series of high-multiplication subcritical neutron and gamma noise measurements were planned and executed. The primary aim of this research was to advance detector technology, assess the validity of gamma noise for subcriticality measurements, and nuclear criticality safety, focusing on collecting list-mode or time-series data from various reactor configurations with multiplication values ranging from 20 to 310. This comprehensive dataset enabled a detailed comparative analysis of multiple detector systems and the results of both neutron and gamma noise measurements. In this work we focus on experimentally comparing the results from neutron and gamma noise measurements. We note good agreement between estimations of the prompt neutron decay constant and demonstrate the effects of changing reactor geometry on the efficiency of the differing methods.
Criticality↗
The MCNP ® 6 code: A decade of progress
After several years of effort involved in merging the Los Alamos National Laboratory MCNP5 and MCNPX codes, in 2013 the first production release of version 6 of the Monte Carlo N-Particle ® , or MCNP ® , code MCNP6.1 was distributed publicly. Since then, three significant releases have been issued: MCNP6.1.1beta in 2014, MCNP6.2 in 2018, and MCNP6.3 in 2023. While each release always contains new features, code enhancements, and bug fixes, each version has had a different primary focus, ranging from improved calculational efficiency to new powerful utilities and tools, to software modernization of the code base. With all that has been learned over the first decade of the MCNP6 code, continuous progress is being made toward a modernized, general-purpose Monte Carlo radiation transport code that remains a trusted resource for the global community of practitioners. This paper describes these first 10+ years of the MCNP6 code and its continually improving data libraries, and gives some insight into how the next decade is expected to unfold.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Introduction, Investigation, and Experimental Validation of a Novel Passive Neutron Spectrometer
Unfolding neutron energy spectra are instrumental for determining personal health effects and calculating dose received. This area of study is heavily researched, and Lawrence Livermore National Laboratory (LLNL) is investigating a passive neutron spectrometer for the purpose of acquiring the information needed to determine personnel dose in the event of a criticality accident. A part of this investigation is presented in this article through the examination of four experimental detector responses (DRs). These four DRs were acquired in the presence of 252 Cf, AmBe, GODIVA, and National Ignition Facility (NIF) neutron sources. An algorithm developed at LLNL was used to unfold the neutron fluence from each of the four DRs, and subsequently, fluence-to-dose conversion factors provided by the American National Standards Institute were used to calculate dose. Additionally, a multistep unfolding process was developed and employed to calculate the effects of both direct (from the source) and indirect (from room return) neutrons. The average error when unfolding the direct DR was less than 8%. The dose from 252 Cf was predicted with only 8% error. The multistep approach allowed for the identification of the low-energy neutrons in the 252 Cf, AmBe, and NIF DRs.
Nuclear Criticality Safety Program (NCSP)↗
Design Optimization of a Criticality Experiment for the Molten Chloride Reactor Experiment Facility
Neutronics simulations of Molten Chloride Fast Reactors have quantifiable biases that arise from nuclear data, modeling choices, or numerical methods. The multiphysics nature of molten salt reactors makes it challenging to disentangle neutronics modeling biases from biases originating from other physical phenomena. In comparison to a mock-up reactor, criticality experiments can specifically assess the neutronics modeling bias while limiting multiphysics effects. The criticality experiment must be neutronically representative of the full-scale reactor to be valuable. Here, in this paper, we describe the design of a criticality experiment to validate only the neutronics of TerraPower’s Molten Chloride Reactor Experiment (MCRE) and its criticality safety upset scenarios. The proposed experiment uses different chlorine-containing materials to maximize its similarity to the MCRE. The design process uses a constrained Bayesian optimization algorithm to investigate different objective functions that use covariance information for 35 Cl nuclear data. The experiments could reduce the nuclear data–induced uncertainty in k eff of the MCRE from 2161 to 886 pcm. They would also increase the upper subcritical limit of the MCRE criticality safety upset scenario from 0.94101 to 0.94476 when using the WHISPER analysis framework.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Machine Learning to Select Experiments Driven by Fundamental Science and Applications for Targeted Nuclear Data Improvement
This work describes a blueprint for a process that accelerates progress in science by quantitatively answering the following question: What is the optimal combination of fundamental-science and application-driven experiments to maximally reduce pertinent data uncertainties? Answering this question entails solving a high-dimensional and complex optimization problem that is best solved with advanced statistic techniques often classified as machine learning. We apply this process within the framework of nuclear data with the aim to select an experiment combination that will reduce uncertainties in 239 Pu nuclear data for neutron energies between 1 and 600 keV. In this field, fundamental-physics driven data, called differential, look at one nuclear physics observable at a time. They are contrasted to application-driven, integral, data where one or few resulting values inform a broad set of nuclear data across several nuclides and energies. The candidates for integral experiments are criticality measurements that were refined by a genetic algorithm to be maximally sensitive to 239 Pu fission cross sections in the desired energy range. Twenty-three candidate differential experiments were investigated and span multiple nuclear physics observables (e.g., total, capture cross sections) for isotopes appearing in the integral experiments. The optimal combination among these candidate experiments was investigated via generalized least squares fitting, augmented with Gaussian processes to ameliorate statistical irregularities in data, and the D-optimality criterion. The latter evaluates for each pair of candidates the joint reduction in uncertainties of all 12200 nuclear data appearing in the integral experiments compared to the knowledge we have from 168 past experiments, theory, and nuclear data. We chose as differential measurements those that investigate 63 Cu and 239 Pu total cross sections, based on D-optimality rank and feasibility constraints. Two integral (criticality) experiments were selected: An experiment with Al 2 O 3 and graphite interleaved with Pu and a thick Cu reflector explores 1–30 keV, while we target the 30–600 keV range with an experiment that swaps boron in place of graphite with a different geometry.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Evaluations for Nuclear Criticality Safety Program 12 C, 139 La, minor actinides, 235 U [Slides]
For light nuclei, preliminary work extends the evaluation from 6.5 MeV to ~ 10 MeV. For 139 La, the team delivered full evaluation in fast region to ORNL, including covariances. For sup>235 U, RPI data simulations, the team performed simulations and showed some improvement for neutrons below 5 MeV. Some of the changes needed for more improvement might not be supported by the current format. Some of the changes above 12 MeV to account for the angular distribution of preequilibrium neutrons require a change in the PFNS evaluation procedure.
235U re-evaluation↗