Validation Testing at LANL with ENDF/B-VIII.1 Official Release Files [Slides]
Abstract not provided.
Nuclear Criticality Safety Program (NCSP)↗
Engineering topics
Kleedtke, Noah
Publications and source records attributed to Kleedtke, Noah.
Impact of Higher Fidelity Design Iterations on Critical System Criteria
Nuclear criticality experiments are effective at informing the performance of nuclear data libraries across many applications. This work explores the implications of refining critical experiment MCNP models from their low fidelity optimization phase to penultimate neutronic models. Specifically, this work is focused on two series of plutonium fueled experiments funded through internal programs at Los Alamos National Laboratory building off previous efforts under the EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) collaboration. Thales, the first of the two collaborations, is a fast spectrum Ta-reflected plutonium experiment to support operations at PF-4. The second experiment are twin configurations designed to target the intermediate energy cross sections in 239 Pu. Motivation for this experiment stems from the PARallel Approach of Differential and InteGral Measurements (PARADIGM) collaboration which hopes to achieve a significant reduction in 239 Pu cross section uncertainties in the intermediate region.
97 MATHEMATICS AND COMPUTING↗
Chlorine Worth Study Nuclear Data
The Chlorine Worth Study (CWS) was a series of experiments that took place at the National Criticality Experiments Research Center (NCERC), operated by Los Alamos National Laboratory (LANL). The focus of the experiments was to develop new integral benchmarks for the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook with high sensitivity to chlorine in the thermal neutron energy region and which match sensitivities of aqueous chloride operations at LANL. This work discusses the experiment and how the experimental and simulated results using different nuclear data libraries compare to each other.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Reaction Rate Ratios for Recent Fast Metal Experiments with Large Plutonium Masses
Not Available
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Validation of ENDF/B-VIII.1 Nuclear Data Files [Slides]
ENDF-6 formatted files were processed into A Compact ENDF (ACE) files using NJOY2016. Several validation tests were performed: (1) LANL Legacy Benchmark Suite (2) “Modern” Benchmark Suite (3) HEU Benchmark Suite (4) LEU Benchmark Suite (5) Mixed (U+Pu) Benchmark Suite (6) Pu Benchmark Suite (7) 233 U Benchmark Suite.
97 MATHEMATICS AND COMPUTING↗
The EUCLID Experiment and Nuclear Data Library Comparisons
The EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) project at Los Alamos National Laboratory (LANL) was a Laboratory Directed Research and Development project which aimed to reduce compensating errors in nuclear data. One major component of the project was a series of critical experiments, both measuring k eff and various other observables with the goal of using these experiments to constrain 239 Pu nuclear data uncertainties and identify compensating errors. This paper details some of the experiment design and how various nuclear data libraries simulate the EUCLID system, including sensitivities compared to Jezebel.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Neutron Leakage Spectra Sensitivities for ICSBEP Benchmarks
Neutron leakage spectra have been measured, simulated, and investigated by many groups. These spectra have many uses, including determining shielding requirements and calculating dose for radiation protection purposes, validating nuclear data, and determining material composition. It has even been proposed to use measurements of neutron leakage spectra to determine the soil composition of Mars. As part of the Los Alamos National Laboratory (LANL) Experiments Underpinned by Computational Learning for Improvements in nuclear Data (EUCLID) Laboratory Directed Research Development (LDRD) project, the authors are working on developing methods to calculate sensitivities to neutron leakage spectra. This may allow nuclear data evaluators to better use neutron leakage spectra data to constrain or adjust nuclear data. This may also be particularly useful as many neutron leakage spectra measurements do not require fissile material and can be performed with well characterized neutron sources. Neutron leakage spectra measurements are usually performed by placing a detector at the outside of a nuclear system. This may be a reactor, a neutron generator, or a neutron source. Certain detection systems can use pulse height data to infer neutron energies, other detector systems rely on other ways of determining neutron energy (for example, a Bonner sphere with multiple moderator thicknesses can be used to measure neutron spectrum). These measurements typically rely on some unfolding of the measured results. For pulsed systems like the "Livermore Pulsed Spheres," time-of-flight information can also help to constrain the neutron energy spectra data.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
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.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
IER 517: Molybdenum Critical Experiment Design [Slides]
Abstract not provided.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Validation of Jezebel Reactivity Coefficients and Sensitivity Analysis
Nuclear data validation is often performed today using criticality measurements. The gold standard for criticality measurements is the International Criticality Safety Benchmark Experiment Project (ICSBEP). The validation specifically focuses on the effective multiplication factor ($k_{eff}$). $K_{eff}$ is a relatively easy parameter to infer and has reduced uncertainty due to being at or above critical. However, while $k_{eff}$ is the most documented parameter and its uncertainties and sensitivities have been evaluated in great detail, it cannot be used as a standalone metric to determine inaccuracies in nuclear data (e.g., cross section data, PFNS, nu), which is based on theory, physics, and differential measurements. The Experiments Underpinned by Computational Learning for Improvements in nuclear Data (EUCLID) project aims to identify compensating errors in specific isotope nuclear data by optimally designing experiments that are, or are not sensitive to a suite of measurement parameters beyond $k_{eff}$. By identifying parameters that are sensitive to each other, oppositely sensitive, or have substantial magnitude differences in sensitivity, experiments can be designed to constrain questionable nuclear data. One sensitivity that is of particular interest to this project includes the sensitivity of reactivity coefficients. Reactivity coefficients compare reactivity, which is related to $k_{eff}$ at two different states therefore being sensitive to small changes in the system. The most common type of reactivity coefficient measurements is comparison to void for a small sample within the assembly. It is key that the sample sizes are small enough to not affect the flux of the full system. Reactivity coefficients were evaluated for many early experiments to better understand transport corrected cross sections. In fact, ICSBEP includes reactivity coefficient results as “Supplemental Measurements” in appendices for a handful of older benchmarks. One of those benchmarks is Jezebel, the bare Pu critical assembly. This paper compares new simulations of reactivity coefficients for Jezebel, and explores the sensitivity of reactivity coefficients to small changes in nuclear data.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Sensitivity-based Experiment Design Optimization for a Molybdenum Critical Experiment
A lack of intermediate molybdenum benchmarks in the ICSBEP has been identified by LANL, Y-12, and IRSN. This lacking adversely effects criticality safety operations and leaves new differential molybdenum data unvalidated. NCERC is proposing a series of intermediate integral experiments to better the understanding of molybdenum systems. Using MCNP6.2 with the ENDF/B-VIII.0 nuclear data library a single unmoderated and four moderated system designs were identified using a sensitivity optimization method. Each proposed system was found to be at least twice as sensitive to the 95 Mo capture cross section in the URR as the sole existing intermediate molybdenum benchmark in the ISCBEP handbook. The addition of a new molybdenum sensitive intermediate system would improve future nuclear data evaluations.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Designing Critical Experiments Using Gaussian Process Optimization
New nuclear applications may lack similarity between the application and existing ICSBEP benchmarks. Without accurate benchmark data, predictive simulations will have high uncertainty in the estimate of a parameter of interest (such as k eff ). The design of critical experiments tuned for specific applications of interest is one solution to reducing uncertainty in the necessarily nuclear data. We propose an optimization technique to design critical experiments that match the cross-section sensitivities of an application model while minimizing the number of simulation runs in the optimization. The optimization of a critical experiment is slow because the potential design space covers many qualitative variables (types of material and geometries) and corresponding quantitative variables (e.g., material dimensions) and the evaluation of any specific design requires running an expensive code like MCNP1 and Whisper. The optimization of expensive black-box computer codes with quantitative variables has been extensively explored in the literature of design of computer experiments. We propose a modified version of standard Gaussian process (GP) optimization that optimizes over multiple discrete configurations of qualitative variables in parallel which reduces the computational cost of the entire optimization. The goal of this work is to minimize the number of MCNP evaluations while still exploring many different design configurations in parallel.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗