TN update plans and advances for 16 O and 9 Be [Slides]
Abstract not provided.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
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Nuclear Data Adjustment with Whisper for Criticality Safety Applications [Slides]
Nuclear data adjustment is used by Whisper to compute residual nuclear data uncertainties within a full suite of benchmarks; in order to do so, a complete set of nuclear data covariances, benchmarks and k-effective sensitivity profiles (for both benchmarks and applications) is required. For applications that are similar to the full benchmark suite, the residual uncertainties add a small margin to the overall USL calculation. For applications that are dissimilar to the full benchmark suite, the residual uncertainties add a reasonable margin to the overall USL calculation (more conservative). This methodology helps to overcome any issues in the released covariance libraries where nuclear data uncertainties appear to be too large.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Investigating Fission Reaction Rate Ratio Sensitivities [Slides]
One EUCLID project goal is to create a NEW capability in the MCNP6 code. This is being tested on reaction rate sensitivities and compared with SENSMG results. Reaction rate ratio sensitivities were added to EUCLID sensitivity library and investigated to determine value toward designing optimized experiments aimed at reducing compensating errors in nuclear data. The use of adjustment using multiple responses (and underlying/required capabilities) may benefit many applications. These include a tool for adjustment using multiple integral responses (ND adjustment and validation community); sensitivities of additional responses (ND adjustment and validation community); sensitivity capabilities (users in many application areas including safeguards/nonproliferation, criticality safety, etc.); and experiment optimization capability (applications which can benefit from integral experiments). Team is working to build and test future tools and to understand compensating errors
235U↗
Bayesian Monte-Carlo Evaluation Framework for Imperfect Nuclear Data [Slides]
BMC evaluation is a tool used to address imperfect data and models, non-linear models, and non-normal PDFs. ENDF-6 format does not allow non-normal parameter PDFs. Storing posterior sets allows for variance, covariance, skewness, etc. To better predict criticality, we should document non-normal parameter PDFs (i.e. asymmetric uncertainty) and consider non-linear sensitivity of $k_{\text{eff}}$ to resonance parameters.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Bayesian Monte-Carlo Framework: New Methods for Resonance Parameter Evaluation [Slides]
BMC evaluation is a tool to address imperfect data & models, non-linear models, and non-normal PDFs. ENDF-6 format does not allow non-normal parameter PDFs. Storing posterior sets allow for variance, covariance, skewness, etc. To better predict criticality, we could document non-normal parameter PDFs (i.e. asymmetric uncertainty), consider non-linear sensitivity of $\kappa$ eff to resonance parameters, and reduce uncertainty in key resonance parameters.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
CritView Database Expansion [Slides]
This presentation is intended to provide the audience with the current status of CritView and the recent database expansion.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
MCNP ® Code Version 6.3.0 Theory & User Manual
This document acts as a repository of knowledge for the Monte Carlo N-Particle (MCNP) transport computer code. It is maintained alongside the source code and attempts to introduce new users and re-familiarize experienced users with the theory and practices of using the MCNP code for the wide range of particle transport analyses that it is appropriate for. The latest version of the MCNP code, version 6.3.0, provides the Monte Carlo particle transport community with the latest feature developments and bug fixes in the MCNP code. The MCNP code version 6.0 and later is also known as the MCNP6 code.
96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
Generalized Bayesian Monte Carlo Evaluation [Slides]
Bayesian Monte Carlo is a tool to address imperfect data & models, non-linear models, non-normal PDFs, and integration of differential and integral data. Simple propagation to criticality shows effects of new $\mathcal{L}$($β|z,γ$).
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Example on how to (intelligently) augment the nuclear-data pipeline with machine learning [Slides]
The presentation discusses how machine learning has helped the Los Alamos National Laboratory (LANL) nuclear-data pipeline. It also discusses the strengths of machine learning as it finds trends in large amounts of data where human brains are overwhelmed and that this information may be crucial to improve our nuclear data. It does stress, however, that machine learning is no "silver bullet" and that it is critical to feed it expert knowledge and use physics intuition to interpret the results. The presentation discusses the need to develop infrastructure and tools to provide data in an easily readable and unambiguously interpretable format (e.g., EXFOR format), to develop experimental data and theory to solve physics questions, and that statisticians and nuclear-data experts must be brought together to correctly interpret the results. The presentation concludes by stating that machine learning is a great tool and that LANL needs to use the algorithms along with developing physics data, tools and infrastructure.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Updated ENDF-6 Format Approval Process [Slides]
The presentation begins by discussing the original ENDF/B-VIII.0 format proposal lifecycle and states that the GNDS Expert Group has developed a gitlab-friendly review process that addresses concerns raised by the format proposal lifecycle. As a result, a revised ENDF/B-VIII.0 format proposal lifecycle has been created. The presentation then discusses the necessary steps in the lifecycle that are as follows: create an issue in the issue tracker, make your changes directly to the manual, submit it for review and final approval. The presentation concludes by discussing two other things, including the transition CI/CD from buildbot system to built-in gitlab CI/CD and that the revised format review process document will follow, pending approval.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
RECENT AMPX developments [Slides]
This presentation covers recent AMPX developments. Presentation highlights include the news of AMPX being openly available, link to source and configure options are included. The interconnections between AMPX and Generalized Nuclear Database Structure (GNDS) are additionally highlighted as well.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
ORNL’s Continuing Efforts in Evaluating and Validating TSLs [Slides]
This presentation finds that INS measurements are not as variable based on sample composition, because phonon spectra is a properly of the bulk material. Additionally, INS and transmission measurements are and should be the most significant part of TSL validation, as they are the fundamental quantities used by Monte Carlo neutronics codes. This presentation reasons that relaying solely on theoretical atomistic calculations for TSL evaluation is not enough, they are highly dependent on inter-atomic potentials (which are not the most accurate depending on the quantity trying to be reproduced) and evaluators knowledge and understanding of the material being studied. Finally on Critical benchmarks, while extremely useful for validation of nuclear data at all energies, critical benchmarks are not the best tool to provide a definitive answer on conflicting TSLs. The presentation concludes that INS and transmission measurements need to be the basis of validation of TSLs.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Format Proposal for Isotopic Distribution in TSL Files for ENDF/B-VIII.1 [Slides]
This presentation proposes a format of an ‘footer’ file for ENDF6-format TSL files. This would contain several pieces of pertinent information for the scattering atom. such as the Number of scattering atoms in molecule, Isotopic distribution within scattering atom, and free atom and atomic weight ratios for each isotope. This setup will not require significant changes to processing codes or to other sections of the MF7 file.
07 ISOTOPE AND RADIATION SOURCES↗
Validation of New MCNP6.3 Features for Critical and Subcritical Benchmark Simulations [Slides]
A separate MCNP6.3 V&V document reports on all the default calculations for all test suites was introduced. Here, we look at new optional features of the MCNP6.3 code. Then, Fission-matrix-based options with Convergence and population testing and Automated acceleration of the fission source and Doppler Broadening Resonance Correction and HDF5 Particle Track Output (PTRAC) and Validation benchmarks: criticality, Rossi-α, and subcritical multiplication. All the new MCNP6.3 options give statistically equivalent results and should be considered for default usage in criticality and subcritical multiplication calculation work. Discussed are two separate papers at the upcoming 2023 International Conference on Nuclear Criticality Safety (ICNC 2023) that give more details on the results presented here.
97 MATHEMATICS AND COMPUTING↗
2021 MCNP ® User Symposium Developer Abstracts
Abstracts are provided from the 1st Annual 2021 MCNP ® User Symposium.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Verification of Upcoming MCNP Features For Estimating Nuclear Data Sensitivities in Fixed Source Simulations [Abstract]
Predictive simulation codes, like the Monte Carlo N-Particle (MCNP) transport code, are used throughout the nuclear community. These simulations are based on nuclear data. Maximizing the accuracy and precision of nuclear data maximizes the accuracy and precision of the overall simulation. This is imperative to applications that rely on simulations. For example, improving nuclear data for special nuclear material improves simulation accuracy in stockpile stewardship applications, which results in larger safety margins and decreased operational costs. The improvement and validation of nuclear data is completed through integral benchmark experiments. Past benchmarks have primarily been limited to focus on the effective multiplication factor ($\kappa$ eff ); broadening the purview of benchmarks beyond $\kappa$ eff -dependent nuclear data addresses nuclear data deficiencies. Different response types depend on different areas of nuclear data. This dependence is quantified as nuclear data sensitivity: the change in response due to perturbation of a contributing parameter. The larger the nuclear data sensitivity of a response, the more the experiment is influenced by the uncertainties of the nuclear data. The optimization of nuclear data sensitivities in future benchmarks would result in more detailed validation of lesser studied areas of nuclear data. Currently, direct sensitivity capabilities are not easily found for all experiment types and parameters. An MCNP tool to directly estimate the cross section sensitivities of tallied values is under development. Additionally, updates have been made to the perturbation feature of MCNP, which can be used in a less direct approach to estimating sensitivities. This work verifies these features to estimate nuclear data sensitivities in fixed source simulations of a 4.5-kg sphere of alpha- phase weapons-grade plutonium surrounded by differing amounts of copper and polyethylene. Integrated estimates made using MCNP’s tools were found to statistically agree with integrated estimates made from manual perturbation of nuclear data proving the validity of the MCNP tools.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Hybrid Particle Swarm-Interpolation Algorithm for Improved Critical Experiment Design
The typical goal of designing a critical experiment is twofold: a system that is both critical and optimized for some other value. This value could be an energy-integrated sensitivity, percent fissions in a certain energy range, or some other value that can be calculated by a transport code. By simulating different combinations of reflector, moderator, and fuel thicknesses a designer can identify such a desirable configuration. The domain of all possible combinations of these thicknesses is referred to as the experiment search space. As more dimensions are added, the search space increases in size exponentially. For a three-dimensional case, which includes three thickness values between zero and ten centimeters to the nearest tenth of a millimeter, a total of 1,000 3 , configurations exists. Rather than check each configuration individually, which would be extremely computationally expensive, it has been shown to be more efficient to use a conventional particle swarm optimization (PSO) algorithm to identify critical and optimal configurations. This work presents the theory and implementation of a novel hybrid PSO interpolation algorithm to perform these optimizations faster than a conventional PSO algorithm. To demonstrate this, an example optimization will be carried out by the conventional and hybrid PSO algorithms and their performances will be compared.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗