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At least 1,027 records · Page 57

LANL/LLNL 240 Pu( n,f ) Prompt Fission Neutron Spectrum Measurement (Q4 FY2022 Progress Report)

The report details the joint LANL/LLNL measurement of the 240 Pu( n,f ) prompt fission neutron spectrum (PFNS) for incident neutron energies from 1–20 MeV. A summary of the experimental setup, including details of the parallel-plate avalanche counter (PPAC) used for this experiment, beam time awarded and received, and adaptations made for specifically for this experiment are described in Sec. II. Some preliminary results obtained with a portion of the total available statistics from the executed experiment are then described in Sec. III with a discussion of potential benefits and losses if more data were collected. Finally, some primary tasks remaining to convert these data to final results are discussed in Sec. IV.

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Coincident Capture through Post-processing PTRAC [Slides]

This presentation discusses the new PTRAC capabilities and workflows. The PTRAC capability in MCNP6.3 has seen a massive overhaul since MCNP6.2. The new HDF5 file format allows for both MPI- and thread-based parallelism. MCNPTools has been updated to handle the new HDF5 PTRAC format and is now open sourced on GitHub. Built-in capabilities, such as the pulse-height tally coincident capture special treatment, can largely be replicated through separate postprocessing scripts that leverage both PTRAC and MCNPTools. This allows for greater flexibility in user-specified and controlled detector response functionality, ultimately using the MCNP code for what it is best at (i.e., particle transport).

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Producing ENDF/B-quality Evaluations of 239 Pu(n,f) and 235 U(n,f) Average Prompt Neutron Multiplicities using the CGMF Model

This report documents evaluations of the neutron-induced 239 Pu and 235 U average prompt neutron multiplicities, $\overline{v}_p$, using the CGMF model developed at LANL. These evaluations are not updates of existing ENDF/B-VIII.0 nuclear data, but were both re-done from "scratch". That is, all experimental data were extracted from EXFOR, re-normalized to the newest nuclear data representing monitor observables, and detailed uncertainties were estimated from information in EXFOR as well as from templates of expected measurement uncertainties. We also included experimental data that were not yet available for ENDF/B-VIII.0, for instance, the data of Marini et al. for 239 Pu(n,f) $\overline{v}_p$ or the data of Khoklov et al. for 235 U(n,f) $\overline{v}_p$. Finally, we include the CGMF model; it computes $\overline{v}_p$ based on model parameters that at the same time calculate fission fragments as a function of mass, Y (A), the average total kinetic energy as a function of incident-neutron energy, $\langle TKE \rangle$(E inc ), etc. Such a detailed fission model that ties together many fission quantities has not been used to date for any $\overline{v}_p$ evaluation in ENDF/B. Here, we show that we can get evaluated 235 U(n,f) and 239 Pu $\overline{v}_p$ that not only correspond well to experimental $\overline{v}_p$, but that the associated evaluated model parameters also yield parameterizations of Y (A), $\langle TKE \rangle$(E inc ), etc., that correspond well to their respective experimental data. The new evaluated 239 Pu(n,f) $\overline{v}_p$ was also combined into a 239 Pu test file with the newest nuclear data for the 239 Pu prompt-fission neutron spectrum and fission cross sections. This new 239 Pu file performed reasonably well in predicting PU-MET-FAST assemblies, reaction rates in Jezebel and Flattop and three LLNL pulsed spheres. Due to that, the new 239 Pu(n,f) $\overline{v}_p$ evaluation presented here is being considered for ENDF/B-VIII.1. Hence, we can show here that CGMF is able to produce ENDF/B quality $\overline{v}_p$ nuclear data.

239Pu, 235U, Average Prompt-fission Neutron Multip↗

How can a diverse set of integral and semi-integral measurements inform identification of discrepant nuclear data? [Slides]

Importance of nuclear data to bias changed significantly when including diverse measurement sets. LLNL pulsed sphere measurements provided information for 9 Be nuclear data above 2 MeV and subcritical benchmarks provided information for 240 Pu nuclear data between 100 keV and 10 MeV. Pulsed sphere leakage spectra and neutron noise observables are differently sensitive to nuclear data compared to critical benchmarks. Leakage spectra are sensitive to nuclear data above 5 MeV. Count rate and Feynman Y are more sensitive to nuclear data. A change in bias can help evaluators identify discrepant nuclear data. In the future, EUCLID plans to perform RAFIEKI analysis with additional benchmark and measurement sets.

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Comparison of URR Implementations in GNDS Format [Slides]

LLNL implemented infrastructure to include treatment of URR in GNDS. There are two options to store URR probabilities: cross-sections pdf and ACE-like probability tables. Issues were found with both options during verification with criticality benchmarks. Projected future steps include resolving issues in the next year and adding criticality benchmarks sensitive to URR.

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Questionable Benchmarks [Slides]

An investigation and initial review of ‘questionable benchmarks’ was performed at LANL. Multiple methods were used, including machine learning techniques, to identify 'questionable benchmarks' and/or benchmarks with low uncertainties. Those benchmarks were then reviewed for obvious errors. This is not a recommendation to ICSBEP, but can be used as a starting point for a more comprehensive review. A journal paper is being written on this work.

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MCNP6.3 Workshop [Slides]

This workshop presentation revisits several new features of MCNP6.2 and tools. Additionally, it offers a preview of the new features and improvements included in the upcoming MCNP6.3 code release that are most relevant to the nuclear radiation protection and shielding communities.

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Open-source release of CGMF 1.1 and Integration into the MCNP6.3 ® Code [Slides]

As a result of a multi-year NA-22 project, CGMF was integrated into MCNP6.2 and publicly released. CGMF was open-sourced and publicly released and MCNP6.3 was updated to include the latest version and is in the process of being publicly released. Current and future plans include global optimization and uncertainty quantification within CGMF, model parameter fitting such that CGMF may be used in ENDF/B evaluations, and improving both standalone and MCNP-integrated CGM (non-fission) simulations.

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Data Assimilation using Non-invasive Monte Carlo Sensitivity Analysis of Reactor Kinetics Parameters [Slides]

Sensitivity coefficients of prompt neutron decay constant (α) and effective delayed neutron fraction (β eff ) to Pu-239 nuclear data were calculated using a newly available tool (ACEtk). Uncertainty calculations showed the following trends: (1) The prompt neutron decay constant can be used to reduce nuclear data-induced uncertainty in Pu-239(n,f) and (2) the effective delayed neutron fraction can be used to effectively reduce nuclear data-induced uncertainty in Pu-239 total fission $\tilde{v}$. Sensitivity/uncertainty analysis can be used to determine optimal experiment/detector setup to identify compensating errors in nuclear data. Upcoming work includes investigating other nuclide-reaction pairs and response sensitivities, such as Δ$\rho$, neutron leakage spectra, and reaction rate measurements to constrain nuclear data of interest.

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Which nuclear data can be validated with LLNL pulsed-sphere experiments? [Slides]

LLNL pulsed sphere are a very valuable experiment series to validate scattering and fission nuclear data. It would be great if they could be evaluated as benchmarks and make it into SINBAD! We see potential issues in ENDF/B-VIII.0 6 Li, 12 C, 16 O, 24- 26 Mg, 27 Al, 48 Ti, 56 Fe, and 208 Pb nuclear data. Good agreement is found with 1,2 H, 7 Li, 9 Be, 14 N, 235,238 U, and 239 Pu nuclear data.

16O and 12C Spheres↗

239 Pu(n,f) Neutron Multiplicity Evaluation with CGMF-Very First Release Candidate. [Slides]

239 Pu(n,f) nu-bar evaluated with CGMF from E inc = 0.1-20 MeV. Changes compared to VIII.0: Prior: CGMF model included via Kalman and sensitivities of CGMF model parameters to nu-bar. Evaluation technique: Kalman including correction for PPP. Experimental data: Nearly all data that Phil took into account (I rejected: Huanqiao, Johnstone, Leroy, Nesterov, Smirenkin); New UQ for all experimental data; Marini; No correlations between unc. of different exp., except for Cf-252(sf) nu-bar uncertainty cross-correlating all uncertainties.

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Status of Shift for NCS Applications in SCALE 6.3 [Slides]

Shift can run most KENO V.a and KENO-VI inputs, but beware of small geometry fudge factors. Shift is faster than KENO for fast spectrum systems, but has a higher uncertainty per particle. KENO FoM is higher for thermal systems. KENO V.a in MG is significantly faster than KENO V.a in CE, so this may exacerbate Shift difference. Shift generally has greater speedup for parallel calculations. Shift has only IFP available for TSUNAMI-3D, but parallel calculations are enabled.

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Using the “Inner” Array Boundary with KENO-VI [Slides]

Topics include: SGGP Array definition basics, what is meant by the "Inner" Boundary of an array, a critical experiment with flux filter, and NRC verification of criticality calculations with UNF-ST&DARDS.

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