Interchange, Extension and Validation of R-matrix fits for gamma production
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The Hauser-Feshbach fission fragment decay model, HF3D, calculates the statistical decay of fission fragments through both prompt and delayed neutron and γ-ray emissions in a deterministic manner. While previously limited to the calculation of only first-chance fission, the model has recently been extended to include multi-chance fission, up to neutron incident energies of 20 MeV. The deterministic decay takes as input prescission quantities–fission probabilities, pre-fission neutron energies, and the average energy causing fission– and post-scission quantities–yields in mass, charge, total kinetic energy, spin, and parity. From those fission fragment initial conditions, the full decay is followed through both prompt and delayed particle emissions. The evaporation of the prompt neutrons and γ rays is calculated through the Hauser-Feshbach statistical theory, taking into account the competition between neutron and γ-ray emission, conserving energy, spin, and parity. The delayed emission is taken into account using time-independent calculation using decay data. This whole formulation allows for the calculation of prompt neutron and γ-ray properties, such as multiplicities and energy distributions, both independent and cumulative fission yields, and delayed neutron observables, in a consistent framework. Here, we describe the implementation of multi-chance fission into the HF 3 D model, and show an example of prompt and delayed quantities beyond first-chance fission, using the example of neutron-induced fission on 239 Pu. This expansion represents significant progress in consistently modeling the emission of prompt and delayed particles from fissile systems.
An evaluation of the average prompt fission neutron multiplicity, $\bar{ν}_p$, of 239 Pu(n,f) is shown. This evaluation includes (a) the correlated fission model CGMF, and (b) a detailed analysis of past and recently published experimental data. Using CGMF-calculated $\bar{ν}_p$ as prior enables to link, through the use of evaluated model input parameters, $\bar{ν}_p$ to other fission observables such as the prompt fission neutron spectrum (PFNS), preneutron emission fission yields as a function of mass, and the average total kinetic energy of the fragments. These evaluated parameters produce realistic predictions of many fission observables, while the evaluated $\bar{ν}_p$ agrees well (χ 2 ≈ 1) with data. Moreover, with the new evaluated $\bar{ν}_p$, the effective neutron multiplication factor of fast Pu ICSBEP critical assemblies are predicted with a mean bias of 58 pcm compared to 18 pcm with ENDF/B-VIII.0, when paired with a new 239 Pu PFNS and fission cross section. Due to these encouraging validation results, the evaluated $\bar{ν}_p$ is currently part of a release candidate for the 239 Pu ENDF/B-VIII.1 file. Hence, a correlated fission model was used for the first time for evaluating $\bar{ν}_p$ that is of evaluation quality. This is an important step towards consistent evaluations of prompt fission observables.
The thermal neutron capture cross section of 88 Zr was recently reported to be the second largest in nature with the largest resonance integral measured. Presumably, these very large values are caused by a resonance or resonances very near thermal energy. Determining their energies and widths, and hence the shape of the cross section away from thermal energies,is useful for applications. The short half-life (83.4 days) and associated large background, renders direct measurements of the neutron capture cross section impossible using current techniques. However, it is possible to measure the total neutron cross section, and hence the resonance properties, using the newly commissioned Device for Indirect Capture Experiments on Radionuclides (DICER) at the Los Alamos Neutron Science Center (LANSCE). Transmission measurements are utilized as a surrogate method to perform capture measurements. The 88 Zr needed for a DICER measurement was produced at the Isotope Production Facility (IPF) and cleanly separated from the production target material. A description of the new instrument, efforts and preliminary results on 88 Zr will be presented.
Conventional nuclear data evaluation methods using generalized linear least squares make the following assumptions: prior and posterior probability distribution functions (PDFs) of all model parameters and data are normal (Gaussian); the linear approximation is sufficiently accurate to minimize the cost function (even for nonlinear models); the model (e.g., of neutron cross section) and experimental data (including covariance data) are without defect and prior PDFs of parameters and measured data are known perfectly. Neglect of covariance between model parameters and measured data in conventional evaluations contributes to imperfections. These assumptions are inherent to the generalized linear least squares minimization method commonly used for resolved resonance region neutron cross section evaluations but are often not justified due to the presence of non-normal PDFs, nonlinear models (e.g., R-matrix formalism), and inherent imperfections in data and models (e.g., imperfect covariance data). Here, these assumptions are removed in a mathematical framework of Bayes’ theorem, which is implemented using the Metropolis-Hastings Monte Carlo method. Most importantly, new parameters are introduced to parameterize discrepancies between the theoretical model and measured data to quantify judgement about discrepancies or imperfections in a reproducible manner. An evaluation of 233U in the eV region using the ENDF-B/VIII.0 library and transmission data (Guber et al.) is presented, and posterior parameters are compared to those obtained by conventional evaluation methods. This example illustrates the effects of removing the most harmful assumption: that of model-data perfection.
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Recently, great interest has been generated in using lead as a coolant for fast neutron systems and as a result it is important to investigate the ENDF/B-VIII.0 isotopic evaluations that comprise stable le ad. To this end, resonance parameters for 206 Pb, 207 Pb, and 208 Pb were re-evaluated because their resolved resonance regions extend beyond 0.5 MeV meaning resonance parameters used in reconstructing cross sections and elastic scattering angular distributions impact fast systems. The impact of resonance parameters is demonstrated by the differences between the evaluations in predicting experimental results from the fully modeled RPI Quasi-Differential Scattering Experiment via MCNPv6.2. In addition, MCNP KCODE calculations of lead-sensitive fast spectra critical benchmarks showed variations of keff on average of 400 pcm, caused solely from differences in elastic scattering angular distributions in 208 Pb. Re-evaluation entailed fitting data with the program SAMMY.
An effort is now underway to produce a new evaluation of the neutron standards. It is important to maintain experimental programs to increase the quality and extend the database for the neutron cross section standards in order to improve evaluations of them that will be used to convert cross section measurements made relative to those standards. Measurements have been made for most of the standard cross sections since the last evaluation of the standards. The improved database includes the cross sections for the H(n,n), 6Li(n,t), 10B(n,αγ), 10B(n,α), C(n,n), Au(n,γ), 235U(n,f) and 238U(n,f) standard reactions and ratios among them. The database also includes the 238U(n,γ) and 239Pu(n,f) cross sections in addition to the standard cross sections. Those data were included since there are many ratio measurements of those cross sections with the standards and absolute data are available for them.
Nuclear data are used for a variety of applications, including criticality safety, reactor performance, and material safeguards. Despite the breadth of use-cases, the effective neutron multiplication factor, keff, of ICSBEP critical assemblies are primarily used for nuclear data validation; these are sensitive to specific energy regions and nuclides and are unable to uniquely constrain nuclear data. As a consequence, general-purpose nuclear data libraries, such as ENDF/B-VIII.0, may have deficiencies that, while not apparent in criticality applications, negatively impact other applications, such as non-destructive analysis of special nuclear material and neutron diagnosed subcritical experiments. Recent work by the Experiments Underpinned by Computational Learning for Improvements in Nuclear Data (EUCLID) project developed a machine learning tool, RAFIEKI, which uses random forests and the SHAP metric to determine which nuclear data contribute most to predicted bias between measured and simulated responses (e.g. keff). This paper contrasts RAFIEKI analysis applied to keff only against RAFIEKI analysis with keff paired with either LLNL pulsed sphere measurements or subcritical benchmarks. Two examples show that a) including pulsed sphere measurements substantially increases 9Be nuclear data importance to bias between 2 and 15 MeV, and b) including subcritical benchmarks has the potential for disentangling compensating errors between 240Pu (n,el) and (n,il) cross-sections between 0.1 and 10 MeV. These results show that RAFIEKI analysis applied to response sets that include, but go beyond, keff can aid nuclear data evaluators in identifying issues in nuclear data.
Unconstrained physics spaces between two or more nuclear data observables in a library occur when their values can be simultaneously adjusted without violating the uncertainties in either differential information or simulations of relevant integral experiments. Differential data are often too imprecise to fully bound all nuclear data observables of interest for application simulations. Integral data are simulated with combinations of nuclear data so that an error in one observable may be hidden by a counterbalancing error in another. In this manner compensating errors may lurk within nuclear data libraries and these errors have the potential to undermine the predictive power of neutron transport simulations, particularly in situations where there is no conclusive validation experiment that resembles the application of interest. The EUCLID project (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) developed a preliminary workflow to identify these unconstrained physics spaces by bringing together results from a large collection of integral experiments with their simulated counter-parts as well as differential information that have a one-to-one correspondence to nuclear data. This wealth of information is processed by machine learning tools for subsequent refinement by human experts. Here, we show how the EUCLID work-flow is executed by applying it first to 239 Pu and then to 9 Be nuclear data in ENDF/B-VIII.0.
In order to test the performance of new neutron thermal scattering law (TSL) evaluations it is desirable to have experimental data that is highly sensitive to the TSL and provides high fidelity information on the energy dependent performance of TSL evaluations. Three relevant experiments are discussed including: accurate thermal total cross section measurements, thermal neutron die-away experiments, and neutron leakage experiments. The experimental setups and results are reviewed, and examples provided for some moderators including polyethylene, Plexiglas, and YHx. For the experiments preformed thus far, there is generally good agreement between the measured total cross section and simulations using current TSL evaluations, however in certain energy ranges differences were observed. Similarly, neutron die-away and leakage measurements for samples at room temperature are in good agreement with data computed from TSLs, however leakage measurements for polyethylene at 29K show discrepancies with TSL evaluations.
With the rise of interest in thermal neutron scattering data for advanced reactor, criticality safety, and shielding applications, new experimental data are required for evaluation of new materials or for re-evaluation (or validations) of previously evaluated materials. New experimental data are evaluated in a three-step process: (1) computing the phonon characteristics, (2) computing the dynamic structure factor (DSF) from the data, and (3) using the experimental setup to simulate the experimental data. All three steps have challenges, ranging from the need for a sufficiently general material simulation code—a processing code that can compute the corresponding DSF—to having a detailed layout of the instrument/beamline/facility where the data were measured. Whereas phonon characteristics of materials can be computed using various methods (molecular dynamics, density functional theory, etc.), a high-fidelity computation of the DSF and the simulation of the experiment based on the DSF is vital to the accuracy of the evaluation. The latter two steps can be achieved by using the two corresponding code systems developed by instrument scientists at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory: (1) OCLIMAX, a program that calculates the dynamic structure factor from DFT and MD simulation results, and (2) MCViNE, a Monte Carlo neutron ray-tracing program designed to simulate neutron scattering experiments. Recently, polyethylene and yttrium hydride were measured at the Wide Angular-Range Chopper (ARCS) and SEQUOIA instrument stations of the SNS. These experiments are simulated using the density functional theory code, the Cambridge Serial Total Energy Package (CASTEP), to compute its phonon characteristics (eigenvalues/vectors and PDOS), which is then processed using OCLIMAX to yield the DSF, and finally the data at each instrument station are simulated by the MCViNE for comparison to the measured data for evaluation. For comparison to conventional evaluation methods, the scattering data processed from OCLIMAX are compared against those processed from the LEAPR module of NJOY, and the results from MCViNE simulations are compared against previously used simplified beamline models implemented in the Monte Carlo N-Particle (MCNP) code.
The Organisation for Economic Co-operation and Development (OECD) Nuclear Energy Agency (NEA) Working Party on International Nuclear Data Evaluation Co-operation (WPEC) subgroup (SG) 50 was formed in 2020 to develop an automatically readable, comprehensive and curated experimental nuclear reaction database. This database is called MEDUSAL (Machine-readable Experimental Data User Application & Library), and will draw from EXFOR. The EXFOR database preserves experimental nuclear reaction data true to its original documentation and information from the authors of the data. MEDUSAL will deviate from EXFOR by storing additional information from users of the data for their fields of work (evaluation, model development, validation, etc.). This includes expert judgment on the data sets, identification of data points as outliers, renormalization of the data to the newest monitor reactions, and estimations of missing uncertainty sources. The format for MEDUSAL is being developed to enable easy automatic parsing of large amounts of data. Here, we will summarize the use cases, high-level requirements and first steps towards developing the database MEDUSAL and the API to access it.
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A simple and efficient target preparation method is developed combining spin coating and solution combustion synthesis. Multiple smooth and uniform UO 2 targets have been prepared using this method on a variety of backings (aluminium, carbon, silicon) used in nuclear physics experiments. The thicknesses of the targets can be precisely tuned by changing the number of coatings within the range of ~50-1000 µm/cm 2 . These targets are highly uniform (<5% deviation), robust, and remain strongly adherent to their backings even after being irradiated by high doses (10 17 ions/ cm 2 ) of 1.7 MeV Ar 2+ ions.
We report on a microscopic modeling of the first order of multistep direct emission based on one phonon excitations, given by the QRPA model, and an effective in-medium nucleon nucleon interaction, described within the JLM folding model. The results of our coupled channels framework for deformed target are illustrated in the case of low energy discrete state excitations in 152 Sm. Pre-equilibrium predictions and their impact on inclusive and exclusive (n,xn) cross sections and fission cross sections are discussed for actinides. We discuss the importance of i) collective excitations to describe the neutron emission spectra and of ii) spin distribution of the residual nucleus formed after the neutron pre-equilibrium emission, that is a key ingredient to model the residual nucleus decay.
We show how the multi-step direct reaction series can be evaluated using Monte Carlo methods. Nucleon-nucleon collisions occur according to the random selection of a nucleon’s attenuation factor along its classical trajectory. The particles and hole excited in a collision are selected from a local Fermi distribution. We assume that the particles continue to propagate and possibly collide again before leaving the nucleus. We assume that holes collide in place, to possibly produce other particles and holes.