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DOE OSTI2025

Measured Reaction Rate Ratios of 235 U, 238 U, 237 Np, 239 Pu Samples in the PFUNS 235 U Prompt Fission Neutron Spectrum Criticality Experiment

The Prompt Fission Uranium Neutron Spectrum experiment, an experiment to reduce uncertainties in the high energy tail of the 235 U prompt fission spectrum, achieved success by performing two separate irradiations measuring approximately 40 different IRDFF-II reactions total using over 20 different foil materials at the National Criticality Experiments Research Center in February 2024. The criticality experiment utilized a set of highly enriched uranium hemispherical shells of increasing diameters with a large void in the center where the samples were located. The focus of this work is the first of two PFUNS irradiations focused on irradiating two of each fission foils, one bare and one cadmium covered, along with metal activation foils containing reaction products with short half-lives, such as indium, iron, and gold along with nickel fluence monitors. This work focuses on presenting the initial reaction rate ratio results of the fission foils from the aforementioned first irradiation to assist in nuclear data validation of those species in a nearly pure 235 U prompt fission neutron spectrum and compares to the Lady Godiva and Flattop-25 historic experiments at the Los Alamos Critical Experiments Facility. Future work will combine fission foil and metallic activation foil reaction rate ratio results from both the first and second higher power irradiation and reaction rates for a final spectral adjustment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Re-evaluating the prompt fission neutron spectrum of spontaneously fissioning 252 Cf

The prompt fission neutron spectrum (PFNS) of spontaneously fissioning 252 Cf is a Neutron Data Standards observable. Nearly all fission spectra of actinides were measured relative to it, using efficiencies derived from it, or analyzed with simulations validated by it. The current Standards evaluation was published by W. Mannhart in 1987. It could not be updated because the evaluation input, experimental mean values and covariances, were lost. First, we attempt to reproduce it. However, Mannhart’s evaluation can only be reproduced within its one-σ uncertainties as some of its aspects (e.g., experimental covariances, rejected data points) remain unknown. Therefore, a new evaluation is presented: We revisit all existing experimental 252 Cf(sf) PFNS data, including those published after the release of the current Standards evaluation, and re-estimate associated covariances. The newly evaluated 252 Cf(sf) PFNS differs distinctly from Mannhart’s below 300 keV and extends it to lower and higher outgoing neutron energies (500 eV–25 MeV). The new evaluated uncertainties are larger from 3–9 MeV and smaller otherwise. Spectrum averaged cross sections of importance to the International Reactor Dosimetry and Fusion File community calculated with the new spectrum are close to those calculated with Mannhart’s evaluation and agree with experimental values well within their uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Measurement of the 252 Cf ⁢(sf) prompt fission neutron spectrum utilizing 12 C ⁡(𝑛, 𝑛) and 9 Be ⁢(𝑛, 𝑛) neutron scattering reference measurements

The 252 Cf spontaneous fission (sf), prompt fission neutron spectrum (PFNS) is a fundamental quantity for nuclear physics measurements of neutron-emitting reactions. This energy distribution of neutrons emitted from fission has been considered a neutron data standard for decades and has been utilized as a reference for neutron detection efficiency, validation of Monte Carlo simulations, benchmarking of dosimetry standards, and more. A significant portion of the global collection of nuclear data on neutron-induced reactions is correlated with the 252 Cf ⁢(sf) PFNS. Despite the reliance on this quantity by the nuclear physics community, the historical collection of 252 Cf PFNS measurements display systematic disagreements that are not understood or easily explained. These experimental discrepancies could potentially bias the 252 Cf PFNS Standard evaluation. On top of this, these past experiments frequently employed correlated experimental measurement or analysis methods. The artificial intelligence (AI)/machine learning (ML)-informed californium chi-nuclear data experiment (AIACHNE) project was formed to (a) investigate these discrepancies utilizing AI/ML methods to identify outlying regions of literature data, assign these regions to features of the experiment itself, and perform an improved evaluation of the 252 Cf PFNS and (b) perform a new experimental measurement of this quantity designed to improve upon the existing literature database. Here, in this work, we report on the AIACHNE 252 Cf PFNS experiment utilizing a new analysis method uncorrelated with all previous measurements: neutron efficiency determinations based on elastic neutron scattering on 12 C and 9 Be . This new method provides an independent test of the existing literature data and evaluation of the 252 Cf ⁢(sf) PFNS. The method is described with detailed covariance quantification procedures, as well as a direct discussion of the sources of uncertainty described as requirements in the “Templates” series of papers. The 252 Cf ⁢(sf) PFNS reported in this work agrees well with the overall shape of the existing standard PFNS evaluation as well as many literature measurements, thus verifying the current evaluation utilizing new techniques. However, the results suggest that there are deficiencies in the angle-differential 12 C and 9 Be ⁢(𝑛, 𝑛) evaluated nuclear data, which produce unphysical structures in the reported result. While these structures are relatively minor, they become obvious because of the high statistical precision of the data and the expected smooth continuity of the 252 Cf ⁢(sf) PFNS.

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

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

The Prompt Fission Uranium Neutron Spectrum (PFUNS) Experiment: Critical Configurations and Irradiations

The objective of the Prompt Fission Uranium Neutron Spectrum (PFUNS) experiment is to reduce the uncertainty of the Prompt Fission Neutron Spectrum (PFNS) of 235 U above 8 MeV. The experiment was performed at the DOE National Criticality Experiments Research Center (NCERC) at the Nevada National Security Site. To meet the experiment objective, activation foils were placed in a central void region of a critical configuration consisting of concentric highly enriched uranium (HEU) metal hemishells. The set of activation foils were chosen based on threshold reactions to neutron energies across the fission spectrum, but especially those in the high energy tail of the fission spectrum. PFUNS was performed on the Planet critical assembly machine at NCERC and uses the Rocky Flats (RF) HEU hemishells. PFUNS has similarities to the Measurement of Uranium Subcritical and Critical (MUSiC) experiment conducted at NCERC in 2021, which also used RF hemishells, but contains a large central cavity to allow for a sample plate to be inserted. This large void means that much more HEU is needed to achieve a critical configuration (108 kg for PFUNS versus 59 kg for MUSiC). This work describes the 2024 experiment execution of four critical configurations and two irradiations for the PFUNS project.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

An Analytic Benchmark for Neutron Boltzmann Transport with Downscattering—Part IV: PFNS and $\bar{ν}$ Uncertainty Propagation

An analytic benchmark with continuous-energy cross sections was previously derived to validate criticality calculations. Here, to extend the utility of the analytic benchmark to verify the implementation of $\bar{ν}$ and prompt fission neutron spectrum (PFNS) uncertainty propagation methods, new simplified forms that are dependent on the incident (fission-causing) neutron energy, as well as the outgoing neutron energy for the PFNS, are introduced in this work. The analytical forms for the flux and adjoint flux are derived for the extended benchmark and used to determine the 𝑘-eigenvalue sensitivity to $\bar{ν}$ and PFNS. The 𝑘-eigenvalue uncertainty due to $\bar{ν}$ and PFNS is calculated for the analytic benchmark using simplified$\bar{ν}$ and PFNS representations based on the ENDF-B/VIII.0 239 Pu evaluation. Because of the low sensitivity of the analytic benchmark to the physical PFNS, a nonphysical high-sensitivity PFNS is also presented.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

ENDF/B-VIII.1: Neutron Reaction Sublibrary

The neutrons sublibrary aims to describe nuclear reactions between incident neutron particles and different nuclei. For ENDF/B-VIII.1, many neutron files were re-evaluated or received major changes. A new 239Pu evaluation was jointly-produced by IAEA, LANL, LLNL and ORNL bringing important updates to fission neutron multiplicity, Prompt Fission Neutron Spectrum, resonance and fast regions. Around one third of the new neutron evaluations were performed as part of the INDEN collaboration, including 16,18 O, 19 F, 28,29,30 Si, 63,65 Cu, 50,51,52,53,54 Cr, 55 Mn, 54,56,57 Fe, 139 La, 233,235,238 U, 240,241 Pu. Important non-INDEN evaluations include 234,236 U, 206,207,208 Pb, 181 Ta, 88 Sr, 140,142 Ce, Pt and Dy isotopes, and many others. Also, dosimetry reactions from IRDFF-II were adopted for many materials.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

AIACHNE's contribution for Nuclear Energy Agency Working Party on International Nuclear Data Evaluation Co-operation Subgroup 50

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

AIACHNE's contribution for Nuclear Energy Agency Working Party on International Nuclear Data Evaluation Co-operation Subgroup 50

The AIACHNE (AI/ML Informed cAlifornium CHi Nuclear data Experiment) project aims at designing an experiment for the 252 Cf Prompt Fission Neutron Spectrum (PFNS) that explores systematic biases in an experimental database retrieved from the EXFOR databases. To that end, machine learning (ML) methods were applied to pint-point measurement features likely related to bia. From that information, we selected a feature that should be explored by the AIACHNE experiment. Measurement features are metadata encapsulating all pertinent information about the physical measurement and analysis techniques. Examples are, for instance, what neutron and fission detectors were used for the physical metadata, and what background reduction techniques were employed for analysis techniques. Such metadata were retrieved both from EXFOR entries as well as the literature of data sets described in detail in Ref. [2]. The prerequisite for applying machine learning techniques is casting the metadata into a format that can be parsed by the algorithm. This step might seem trivial but requires to find a unique language where metadata that carry the same physics meaning across several experiments must have the same identifier. One example is, for instance, the neutron detector. As seen in Figure 1, the machine learning code identified the use of 6 Li detectors as being related to bias in some datasets of the AIACHNE 252 Cf PFNS experimental database. In fact, here are several experiments that used neutron detectors containing 6Li in the database, for instance for the example below. EXFOR format has a unique keywords describing detectors such as “SCIN” or “GLASD”. One may think that these keywords are already sufficient descriptors for ML to uniquely find an issue. However, “SCIN” (used for [3, 4]) and “GLASD” (used for [5]) fail to inform the algorithm what is the active material in the detector. And, the key common issue leading to bias in 252 Cf related to neutron detectors is not whether it is a glass detector or a scintillator. No, the issue is that 6 Li was within both detector types and that even small mistakes in the detector response functions around approximately 200 keV are amplified by the 6 Li(n,α) resonance there leading to bias in data as highlighted in Fig. 1 and Ref. [1]. Hence, the features describing the neutron detector must call out the active material in the detector, rather than the existing EXFOR detector keyword, that the ML algorithm can find physically meaningful features related to bias. The AIACHNE team used a precursor of the WPEC (Working Party on International Nuclear Data Evaluation Co-operation) SG(Subgroup)-50 format to store the metadata for the ML analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Evaluating the 238 U PFNS Including Chi-Nu Experimental Data

This report documents an evaluation of 238 U prompt fission neutron spectra (PFNS) which is a deliverable for a FY2024 Q4 NCSP (Nuclear Criticality Safety Program) milestone. This evaluation is new; its prior input is based on extended Los Alamos and exciton models implemented in the code CoH. Experimental covariances were estimated for five experimental data sets. One of these data sets that was measured by the Chi-Nu team of LANL and LLNL. It covers the 238 U PFNS for continuous incident-neutron energies of 1–20 MeV and outgoing-neutron energies from 10 keV– 10 MeV with high precision. Contrary to Chi-Nu data, previous data sets were measured in a limited energy range. The resulting evaluated data correspond well to the experimental PFNS taken into account for the evaluation. The evaluated PFNS also produce average mean energies in agreement with associated Chi-Nu data. If one uses the new evaluated data to predict the neutron multiplication factor, k eff , of the Flattop, Flattop-Pu and BigTen ICSBEP critical assemblies (which all have thick reflectors with high percentages of 238 U), the differences of simulated values compared to those using ENDF/B-VIII.1β3 is modest (less than 25 pcm). In addition to that, the new PFNS predict on average 238 U LLNL pulsed-sphere neutron-leakage spectra slightly better than ENDF/BVIIII.0 and ENDF/B-VIII.1β3 PFNS. The differences are, however, well within the experimental uncertainties.

238U↗

DOE OSTI2024

Impact of Source Geometry on Detector Response Matrix Efficiency: Simulations of the PFUNS-MUSiC Experiments

This work looks at two different bare highly enriched uranium (HEU) systems, configuration one from Measurements of Uranium Subcritical and Critical (MUSiC) and Prompt Fission Uranium Neutron Spectrum (PFUNS) to see the effect geometry has on detector efficiency and the response matrix. The distance from the multiplying source, the medium between the source and detector, and the geometry of the source all play a part in the efficiency of the detector. These factors are especially important when performing spectrum unfolding. Spectrum unfolding is a process used to reconstruct a true spectrum from measured detector response data. It involves interpreting a set of measured values, such as a light signal from a scintillator, to recover the original neutron energy spectrum. This leads to the question, how much will the efficiency of a detector change when you measure a point source compared to an extended source? The distance and solid angle from the source to the detector may be different. It may only be a minuscule change, but in the spectrum unfolding process it can have a considerable effect on the unfolded spectrum

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Evaluating 240 Pu Prompt Fission Neutron Spectra Including Chi-Nu Experimental Data

This report documents an evaluation of 240 Pu prompt fission neutron spectra (PFNS) including Chi-Nu experimental data. This work is a FY2025 Q4 NCSP (Nuclear Criticality Safety Program) milestone and named a “strategic priority”. This evaluation is new; it differs substantially from the most recent evaluation included in the ENDF/B library, which was for ENDF/B-VII.1 and then carried over unchanged to ENDF/B-VIII.1. The key difference between ENDF/B-VIII.1 and the new evaluation is that we have, for the first time, realistic experimental 240 Pu PFNS covering a broad incident and outgoing neutron energy range.

240Pu↗

DOE OSTI2025

Experimental Investigations of Energy Dependent Gamma-Neutron Noise [Slides]

PFUNS was an integral experiment performed at the National Criticality Experiments Research Center (NCERC) by Los Alamos National Laboratory in 2024.

EJ-309 Liquid Scintillators↗

DOE OSTI2024

Godiva IV central cavity neutron environment characterization with threshold neutron detectors

Godiva IV is a cylindrical fast burst reactor comprised of approximately 65 kg of highly enriched uranium that is operated by Los Alamos National Laboratory and sited at the National Criticality Experiments Research Center at the Nevada National Security Site in Nevada in the United States. Godiva IV is typically operated at delayed critical and in the regime spanning from sub-prompt to super-prompt bursts. Godiva IV is used for sample irradiations, criticality safety demonstrations, dosimetry studies, and for studying super-prompt behavior. In preparation for both an upcoming experiment to reduce uncertainties in the prompt fission spectrum for 235U using threshold neutron detectors, and for future research using Godiva IV, it was desired to exercise the process of the selection of threshold neutron detectors/activation foils, radiation metrology, and the subsequent adjustment of the neutron spectrum. For this exercise, nine high purity threshold neutron detectors/activation foils were irradiated in a Godiva IV burst. The foils were then analyzed using a high-purity germanium detector in the NCERC counting laboratory to determine end of irradiation specific activities for available IRDFF-II reactions. This work summarizes the Godiva IV foil irradiation, radiation metrology results, and adjusted neutron spectrum. The results of this exercise ultimately characterized the neutron environment inside the sample irradiation cavity inside Godiva IV to a higher degree than previously performed, informed decisions for the upcoming larger scale experiment, and will inform future neutron spectrum characterizations at NCERC.

Whitman, Nicholas H.↗

DOE OSTI2026

Resolving root causes of experiment discrepancies guided by machine learning

Abstract Scientists rely on accurate experimental data to explain nature and then harness this knowledge for applications addressing human needs. However, discrepancies between experiments of the same observable can impede scientific progress if one does not understand the underlying causes. Here, we developed a process that unravels data discrepancies by first using Bayesian machine learning to relate discrepancies to few of many, potentially biasing metadata features that encode experiment procedures. This machine learning output guides human experts to study discrepancy causes by simulating suspicious aspects of historical experiments or designing modern ones to address open questions. The study findings then lead to rejecting or correcting historical data on firm scientific bases. This process is demonstrated for the energy spectrum of neutrons emitted promptly (<1 ns) after fission of 252 Cf, a trusted nuclear physics Standard. It reduces the spread in experimental 252 Cf spectra by up to a factor of 6.

Neudecker, D. (ORCID:0000000339200627)↗

DOE OSTI2024

Godiva IV Simulated Radiation Field Characterization and Variance Reduction

Godiva IV is a system comprised of highly enriched uranium alloyed with molybdenum in the form of fuel plate rings. The reactor, along with its predecessors, was designed with the unique ability to satisfy interests in the super-prompt-critical reactor operation space. Originally, the reactor was part of the Los Alamos Critical Experiments Facility (LACEF) at Technical Area-18 (TA-18). The radiation field around Godiva at this facility was well characterized and understood. As a fast neutron system, the neutron spectrum in and around Godiva was close to a Watt Fission spectrum. The Kiva where Godiva IV was located at LACEF was made of thin, sheet metal walls which did not contribute significantly to the neutron spectrum. Following the transition of LACEF to the National Critical Experiments and Research Center (NCERC) in Nevada, Godiva-IV was moved from TA-18 to the Device Assembly Facility (DAF) at the Nevada National Security Site (NNSS). Part of this move brought renewed interest in radiation field characterization. The new facility introduced significant changes to the environment surrounding Godiva, and preliminary foil irradiation results suggested that the room contribution to the neutron spectrum was significant. Unlike at TA-18, a large thermal neutron signature was added to the fast spectrum from Godiva due to significant room return. A primary goal due to the additional complexity that the room return adds to the Godiva IV radiation emission spectrum was the development of an efficient Monte Carlo N-Particle (MCNP) calculation capable of characterizing the neutron spectrum anywhere in the room around Godiva. A campaign of activation foil irradiations and analysis were completed to support the validation of the MCNP model. The modeling of these foils in MCNP can be easily done with a standard volumetric neutron flux tally. However, given the multitude of locations and reaction rates to be modeled, further steps must be taken to increase the efficiency of these calculations in MCNP. During this study, a benchmark model currently under development for Godiva IV was used. A qualitative assessment of the thermal neutron contributors was performed using spatial neutron distribution plots. Additional detail was added to the model based on the qualitative results showing the thermal spectrum’s large sensitivity to hydrogenous material. Neutron energy spectra was evaluated at discrete locations in the room around Godiva to quantify the relative contribution of various components. It was discovered that the concrete walls are the largest contributor to the thermal signature, with minor contributions from plastic components surrounding Godiva. Following these results, two different variance reduction techniques were implemented to improve the problem efficiency in these calculations. In the first approach, an F5 point detector tally was implemented in the standard Godiva IV criticality problem. The second approach involved a weight-window generator implementation with an F5 point detector tally in a fixed source problem. The weight window implementation reduced the runtime from 42739.55 minutes to 1803.34 minutes (computer time), compared to the F5 KCODE implementation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2026

Fission Evaluation Tools and Analytics (FETA)

This living document presents the Python package FETA. FETA computes observables resulting from the fission process. This document provides the definition of these observables as well as the physics models that are implemented to compute them. Some of these models are used to determine the initial conditions of fission fragments, e.g., the excitation energy E* and spin distribution p(J, π) at scission for prompt decay, while others are related to the nuclear structure and decay properties of the fragments, e.g. the ground-state properties, level density and low-lying excitation spectrum, γ-strength functions and electromagnetic transitions, and neutron transmission coefficients. The end goal for FETA is to enable users to substitute every one of these models by their own files providing these quantities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗