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A New Era of Nuclear Criticality Experiments: The First 10 Years of Radiation Test Object Operations at NCERC
The work presented in this paper focuses on the first 10 years (2011–2020) of radiation test object (RTO) operations at the National Criticality Experiments Research Center. RTOs are subcritical configurations of special nuclear material that are built by hand. These configurations are utilized for benchmark experiments, detector testing/characterization, and training. An overview of the types of measurements used in RTO operations is given as well as a history of RTO operations at Los Alamos National Laboratory from 1944–2011.
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.
Active Neutron Multiplicity Counting of Kilogram Quantities of Highly Enriched Uranium [Slides]
LANL seeks to analyze neutron noise techniques for large HEU assemblies, specifically neutron multiplicity counting (NMC). NMC provides the activity and quantity of fissionable and fissile material, which is useful in safeguards and criticality safety.
Neutron Multiplicity Counting Diagnosis of Uranium Assemblies Interrogated by Cf-252 [Poster]
Researchers concluded: First neutron multiplicity counting of tens of kilograms of 235 U with organic scintillators; leakage multiplication estimates to be improved by incorporating detector cross-talk; provides data comparison for “Multiplicity Theory Beyond the Point Model;" promotes continued use of organic scintillators for NCERC and elsewhere.
Kilopower - Powering the Future of Space Exploration [Poster]
The Kilopower Project was initiated by NASA’s Space Technology Mission Directorate to demonstrate subsystem-level technology readiness of small space fission power in a relevant environment (TRL 5) for space science and human exploration power needs. The Kilopower Project centerpiece is the Kilowatt Reactor Using Stirling Technology (KRUSTY) test, which consists of the development and testing of a ground technology demonstrator of a 1 kWe class fission power system. The technologies to be developed and validated by KRUSTY are extensible to space fission power systems from 1 to 10 kWe, which can enable modular surface fission power systems for human exploration, as well as higher power future potential deep space science missions.
IER 500: AWE-LLNL Measurement Campaign at DAF [Slides]
Presentation Hosted at Device Assembly Facility (DAF). Joint collaboration by Atomic Weapons Establishment (AWE) and Lawrence Livermore National Laboratory (LLNL). Multiple measurements were recorded through a two-week period with 12 unique objects measured. LLNL deployed Machine learning software program for diagnostic assessments. Current status notes the dedicated DAF team LLNL maintains. Additionally, LLNL is compiling a report on the AWE-LLNL measurements and designing security benchmark experiments. The presentation concludes with future work envisioned.
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.
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.
Why Lady Godiva Should be Replaced as the Default Validation Experiment for U-235 Nuclear Data
For the past seven decades the Lady Godiva benchmark (HEU-MET-FAST-001) has been the primary experiment used for 235 U nuclear data validation. The papers associated with large nuclear data library releases such as ENDF/B-VII.1 and ENDF/B-VIII.0 refer to it frequently. The reasons why HEU-MET-FAST-001 has been used as the primary validation experiment for 235 U nuclear data validation will be discussed in the following section. However, as discussed among the benchmark community, the standards associated with International Criticality Safety Benchmark Evaluation Project (ICSBEP) evaluations have changed throughout time; this is subject of the OECD/NEA WPEC (Working Party on Nuclear Criticality Safety) Subgroup 8. HEU-MET-FAST-001 is an older benchmark (issued during the inaugural year of ICSBEP in 1996 with only minor revisions occurring since then) and (along with many of the other benchmarks from this era) does not meet the standards for a modern benchmark. This work explores why HEU-MET-FAST-001 is useful for 235 U nuclear data validation and discusses other alternative validation experiments.
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.
Nuclear Criticality Safety Integral Experiment Covariance Determination
Integral benchmarks for criticality safety and nuclear data validation require expensive uncertainty quantification studies. Commonly, the uncertainty quantification ignores correlations between experiments that share components. Experiments such as the TEX (Thermal/Epithermal eXperiments) campaigns consist of many shared parts between experiments, such as fuel, which creates a strong correlation in their errors. While these correlations are known to exist, they are often not estimated due to the complexity of such calculations. This paper describes a software package that uses an intuitive method of determining the covariance for each of the experimental components, providing a correlation matrix for each family of parts across the multiple cases examined within a benchmark. The code uses the TEX-HEU campaign as a proof of concept, and we show that the correlations can be calculated with information commonly found in ICSBEP (International Criticality Safety Benchmark Evaluation Project) benchmarks. The estimated covariances are used in χ 2 trending studies to evaluate their impact on nuclear data validation. The covariance determination code can be easily integrated into current benchmark evaluations as well as reevaluating legacy benchmark uncertainties. Uncertainty correlation calculations should become the baseline for criticality safety integral experiment benchmarks and can now be easily calculated with the described software package.
A Verification of Flux Sensitivity Estimates Using the MCNP Tally Perturbation Tool
Nuclear data is commonly used in applications such as nuclear nonproliferation, safeguards, and criticality safety. More specifically, nuclear data is used in predictive simulation codes like the Monte-Carlo N-Particle (MCNP ® ) transport code, Serpent, and similar radiation transport codes. The improvement of nuclear data enables more precise and accurate simulations, which result in higher fidelity designs and reduced operational/procedural costs. Therefore, the improvement of nuclear data is of paramount importance across the nuclear community. Nuclear data is improved and validated through integral benchmark experiments. The design of benchmark experiments is an extensive process; therefore, these experiments are often optimized on multiple characteristics, including sensitivity to the nuclear data, during the design process. Sensitivity is a measure of how much a quantity changes due to changes in independent variables such as experimental configuration. An experimental design that has a larger sensitivity to the nuclear data of interest will have a larger impact on the accuracy and precision of the validated data. Past integral benchmark experiments have primarily used the effective multiplication factor ($k_{eff}$) as the predominant measured quantity; however, experiments designed with other quantities in mind would be able to optimize on validating different areas of the nuclear data. A primary goal of the EUCLID project is to design, constrain, and reduce compensating errors in experiments focused on quantities other than $k_{eff}$ to better validate nuclear data across the board. Currently, there is a capability in MCNP to easily calculate the sensitivity of $k_{eff}$ to specific nuclear data of numerous reactions types and isotopes (KSEN card); however, the sensitivity of other quantities must be estimated in more strenuous manners. For example, the perturbation feature (PERT card) of MCNP can be used to estimate first-order sensitivities of some response in fixed source simulations. A recent announcement revealed that the first- and second-order perturbation features in previous releases of MCNP contained a bug. It was identified that particles were being scored into the wrong energy bin. The bug is in the most recent public release (MCNP6.2); however, a patch has been added to the most up to date version (MCNP6.2.2) that has not been released publicly. A direct comparison of the PERT card results for an F4 (neutron flux averaged over a cell) tally before and after the patch are shown in figure 1. All simulations used in the sensitivity estimates in this report were performed with MCNP6.2.2. This work verifies the patched MCNP perturbation tool by comparing first order sensitivities made using the PERT card to estimates made using manual perturbation of the compact ENDF (ACE) files.
Design of a Critical Experiment to Validate Yttrium Hydride at Varying Temperatures [Slides]
Abstract not provided.
Uncertainty Analysis for a Criticality Benchmark [Slides]
This presentation discusses how KRUSTY was analyzed with LANL’s MCNP neutron transport code, Monte Carlo N-Particle. In the Monte Carlo method, neutrons are born in fission events and fly around the geometry having events (e.g., scatter, capture, fission, escape) according to the natural probabilities. “Natural probabilities” are given as neutron cross sections , which are measured and evaluated nuclear data. One of the goals of the benchmark project is to improve the nuclear cross sections (and the codes that use them). In this work, the response of interest is called k eff , which describes the neutron multiplication in a near critical system. Like most quantities, k eff is not measured directly; it is only inferred. In summation, MCNP results for k eff matched the measurements extremely well. The evaluated uncertainties are asymmetric and smaller than 0.00100 (e.g., + 0.00080 / – 0.00062). The largest uncertainties are due to alignment.
The First ICNC February 10-12, 1981 [Slides]
The first meeting that became the International Conference on Nuclear Criticality—ICNC—was held at the Los Alamos National Laboratory in February 1981. This presentation includes information on that meeting, including several experiments performed around that time period.
Uncertainty Analysis for a Criticality Benchmark [Slides]
This presentation discusses how KRUSTY was analyzed with LANL’s MCNP neutron transport code, Monte Carlo N-Particle. In the Monte Carlo method, neutrons are born in fission events and fly around the geometry having events (e.g., scatter, capture, fission, escape) according to the natural probabilities. “Natural probabilities” are given as neutron cross sections , which are measured and evaluated nuclear data. One of the goals of the benchmark project is to improve the nuclear cross sections (and the codes that use them). In this work, the response of interest is called k eff , which describes the neutron multiplication in a near critical system. Like most quantities, k eff is not measured directly; it is only inferred. In summation, MCNP results for k eff matched the measurements extremely well. The evaluated uncertainties are asymmetric and smaller than 0.00100 (e.g., + 0.00080 / – 0.00062). The largest uncertainties are due to alignment.
The Los Alamos ARCHIMEDES Project: Application-specific experiments for nuclear data and analytical methods validation [Slides]
ARCHIMEDES is a process in which experiment optimization is performed utilizing sensitivities from MCNP and Whisper. A Gaussian process (GP) optimization is used to guide criticality experiment design. An example of this process is shown for LANL PF-4 plutonium casting.