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At least 19 records

Criticality analysis of nuclear binding energy neural networks

Machine learning methods, in particular deep learning methods such as artificial neural networks (ANNs) with many layers, have become widespread and useful tools in nuclear physics. However, these ANNs are typically treated as ‘black boxes’, with their architecture (width, depth, and weight/bias initialization) and the training algorithm and parameters chosen empirically by optimizing learning based on limited exploration. We test a non-empirical approach to understanding and optimizing nuclear physics ANNs by adapting a criticality analysis based on renormalization group flows in terms of the hyperparameters for weight/bias initialization, training rates, and the ratio of depth to width. This treatment utilizes the statistical properties of neural network initialization to find a generating functional for network outputs at any layer, allowing for a path integral formulation of the ANN outputs as a Euclidean statistical field theory. We use a prototypical example to test the applicability of this approach: a simple ANN for nuclear binding energies. We find that with training using a stochastic gradient descent optimizer, the predicted criticality behavior is realized, and optimal performance is found with critical tuning. However, the use of an adaptive learning algorithm leads to somewhat superior results without concern for tuning and thus obscures the analysis. Nevertheless, the criticality analysis offers a way to look within the black box of ANNs, which is a first step towards potential improvements in network performance beyond using adaptive optimizers.

artificial neural network↗

Sensitivity/Uncertainty Analysis for Nuclear Criticality Safety Validation [Slides]

Sensitivity coefficients predict the expected change in a response ($\kappa$) due to a change in some input parameter ($\Sigma$). These responses can be k eff (or ratios of reaction rates). These input parameters are typically nuclear data. The coefficients are dimensionless ratios. What would happen to the system k eff if some piece of data were changed by some amount? The coefficient is calculated without making the change.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Hand Calculations for Nuclear Criticality Safety – Primer Revision

The document “ Hand Calculation Methods for Criticality Safety – A Primer, ” was published by the authors (Los Alamos National Laboratory report LA-14244-M) in December 2006 to provide an overview of the most common hand calculation methods used for criticality safety analysis. Hand calculation methods can be used as a starting point for more advanced calculations, and in many circumstances, they can provide sensitivity and perturbation information quicker than using a criticality code, such as KENO or MCNP. This report has been revised to augment existing basis information and example problems for each of the methods discussed: 1-group and modified 1- group diffusion theory, core-density conversions, buckling conversions, limiting surface density method, density analog method, surface density method, and solid angle method. This primer discusses the applicability of the various methods, illustrates how they are used, and provides an interpretation of the example problem results. The example problems provided are simple, practical problems, and the reference data to solve each example problem is provided. This paper will provide an overview of the Primer revision and how it can be useful for new Nuclear Criticality Safety practitioners.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Hand Calculations for Nuclear Criticality Safety — Primer Revision [Abstract]

The document “ Hand Calculation Methods for Criticality Safety –A Primer, ” was published by the authors (Los Alamos National Laboratory report LA-14244-M) in December 2006 to provide an overview of the most common hand calculation methods used for criticality safety analysis. Hand calculation methods can be used as a starting point for more advanced calculations, and in many circumstances, they can provide sensitivity and perturbation information quicker than using a criticality code, such as KENO or MCNP. This report has been revised to augment existing basis information and example problems for each of the methods discussed: 1-group and modified 1-group diffusion theory, core-density conversions, buckling conversions, limiting surface density method, density analog method, surface density method, and solid angle method. This primer discusses the applicability of the various methods, illustrates how they are used, and provides an interpretation of the example problem results. The example problems provided are simple, practical problems, and the reference data to solve each example problem is provided. This paper will provide an overview of the Primer revision and how it can be useful for new Nuclear Criticality Safety practitioners.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Criticality Analysis of FSV Spent Nuclear Fuel in the DOE Standard Canister

The U.S. Department of Energy (DOE) is responsible for managing over 300 types of spent nuclear fuel (SNF). To manage this large variety of fuel types, DOE plans to employ standardized canisters for the transportation, long-term storage, and eventual disposal of SNF. Idaho National Laboratory is currently supporting DOE’s SNF Packaging Demonstration Project, in which Fort Saint Vrain (FSV) fuel assemblies will be loaded into a DOE Standard Canister. This paper presents criticality calculations demonstrating that all four or five FSV fuel assemblies loaded into the DOE Standard Canister will remain subcritical in any expected normal or credible abnormal conditions. Previous criticality analyses were performed for one FSV fuel assembly and 12 Peach Bottom Core 2 fuel elements loaded into a DOE Standard Canister. This paper covers the criticality analysis performed for loading both four and five FSV fuel assemblies into a DOE Standard Canister. Various intact and degraded mode configurations were modeled in conducting the criticality calculations. This analysis encompassed three different configurations: (1) a single DOE Standard Canister loaded into a concrete storage overpack, (2) seven DOE Standard Canisters loaded into a concrete storage overpack, and (3) nine DOE Standard Canisters loaded into a concrete storage overpack. The overpack dimensions were varied for each of the three configurations, and transport, storage, and disposal scenarios were analyzed for each configuration. For transport scenarios, a pair of degradation cases was analyzed. In the first case, the fuel compacts became degraded and were removed from the fuel block, then deposited at the bottom of a horizontally placed canister, thereby simulating a drop event. The canister was considered to remain intact. In the second case, the spacing between horizontally placed canisters in a nine-canister overpack was reduced such that the canisters were piled on top of each other, simulating a drop event. For this case, no degradation of the canister internals or fuel was considered. For storage scenarios, the water moderator location in the system was varied to enable identification of the most reactive configurations. Dry and wet conditions were analyzed for the fuel materials, canister, and overpack. For disposal scenarios, two degradation cases were analyzed. In the first, the stainless-steel internals of the canister degraded to either hematite or goethite under both dry and wet conditions. In the second case, degraded FSV fuel formed a uranium-water slurry that filled the coolant/void holes. None of the cases presented exceeded the application specific upper subcritical limit.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Automated Direct Perturbation Calculations with SCALE TSUNAMI [Abstract]

In nuclear criticality safety analysis, the sensitivity of the eigenvalue keff to uncertainties in nuclear data and its evaluation are crucial. The TSUNAMI sequences within the SCALE code system offer users various options with both multigroup (MG) and continuous-energy (CE) 3D Monte Carlo (MC) transport capabilities for calculating keff sensitivity coefficients and storing them in a sensitivity data file (SDF). Each methodology available in TSUNAMI offers distinct advantages and limitations, and its effectiveness can vary based on the specific problem being solved. As a best practice, practitioners typically use the direct perturbation (DP) method as a confirmatory step alongside their sensitivity calculations to verify the accuracy of the sensitivity data generated. In this process, DP calculations are usually performed on select nuclides, those considered most important for validating their total sensitivities. However, because of code limitations, analysts use a workaround method when conducting DP calculations for a single nuclide: rather than perturbing the nuclide's microscopic cross section, an equivalent number density for this nuclide is calculated to reflect the effect of a change in the macroscopic cross section due to a perturbation in the microscopic cross section. The current approach requires rerunning the CSAS criticality calculation several times with model changes. Although this method can yield results with acceptable accuracy, it is labor-intensive and prone to errors.

AZURE: SAMMY↗

KENO-VI Primer: Performing Calculations using SCALE’s Criticality Safety Analysis Sequence (CSAS6) with Fulcrum

The SCALE code system developed at Oak Ridge National Laboratory is widely used and accepted around the world for criticality safety analysis. The well-known KENO-VI three-dimensional Monte Carlo criticality computer code is one of the primary criticality safety analysis tools in SCALE. The KENO-VI primer is designed to help a new user understand and use the SCALE/KENO-VI Monte Carlo code for nuclear criticality safety analysis. It assumes that the user has a college education in a technical field. There is no assumption of familiarity with Monte Carlo codes in general or with SCALE/KENO-VI in particular. The primer is designed to teach by example, with each example illustrating two or three features of SCALE/KENO-VI that are useful in criticality analysis. The primer is based on SCALE 6.2 and 6.3, which includes the Fulcrum graphical user interface. Each example uses Fulcrum to provide the framework for preparing input data and viewing output results. Starting with a Quickstart section, the primer gives an overview of the basic requirements for SCALE/KENO-VI input and allows the user to quickly run a simple criticality problem with SCALE/KENO-VI. Each following section begins with a list of basic objectives identifying the goal of the section and the individual SCALE/KENO-VI features covered in detail in the section’s sample problems. Upon completion of the primer, a new user should be comfortable using Fulcrum to set up criticality problems in SCALE/KENO-VI. The primer provides a starting point for the criticality safety analyst who uses SCALE/KENO-VI. Complete descriptions are provided in the SCALE/KENO-VI manual. Although the primer is self-contained, it is intended as a companion volume to the SCALE/KENO-VI training and documentation. The SCALE manual and training schedule are available at https://scale.ornl.gov. The primer provides specific examples of using SCALE/KENO-VI for criticality analysis; the SCALE/KENO-VI manual provides information on the use of SCALE/KENO-VI and all its modules. The primer also contains an appendix with sample input files. In addition, this primer, its errata, and sample inputs are also available at https://code.ornl.gov/scale/primers/kenovi/.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Optimization Algorithm for Criticality Experiment Design Using Whisper

Many criticality experiments performed to aid in nuclear data evaluation are designed to maximize the sensitivity of the system’s effective neutron multiplication factor to a certain nuclide reaction pair over an energy region of interest. This is typically done by evaluating possible designs in a transport code such as MCNP and selecting the one with the highest desired sensitivity. A designer has many tools to try to maximize this sensitivity such as different moderators, reflectors, fuels, and geometries. This balancing act of identifying a critical and maximally sensitive system become very computationally expensive as more variables are added and higher precisions are desired. In order to identify these optimal configurations more efficiently a Particle Swarm Optimization (PSO) algorithm coupled with MCNP has been developed by Los Alamos National Laboratory (LANL). This algorithm has been used to design two upcoming criticality experiments that will be performed at the National Criticality Experiments Research Center (NCERC), located at the Nevada National Security Site, and operated by LANL, the only general-purpose critical experiments laboratory in the United States. PSO uses a population (swarm) of candidate solutions (particles) on a search space of dimensions such as moderator and reflector thicknesses or enrichments and concentrations. These particles move around the search space from generation to generation according to simple rules. Eventually, the swarm converges on the configuration that is both critical and maximally sensitive to a piece of nuclear data. PSO is well suited for criticality experiments as the algorithm is agnostic to the underlying physics, meaning it is effective on many different experimental setups. This algorithm has been modified to maximize the nuclear data similarity coefficient between an application case and an experiment aimed at replicating the application case using WHISPER, a nuclear criticality safety analysis tool. This allows for the efficient design of critical experiments informed by nuclear data sensitives.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Conduct of Operations and Nuclear Criticality Safety Standards

Since the beginning of the nuclear age in 1943, there have been 22 criticality accidents in process facilities worldwide in which fissionable materials were processed by hand for various purposes. Of these 22 process criticality accidents, 16 involved faulty or flawed conduct of operations. Most of these process accidents (17 of 22) occurred before 1970, mostly due to the implementation of formal conduct of operations—such as the use of operating procedures and training—and the use of consensus standards for nuclear criticality safety (NCS). Obviously, the nuclear facilities applied lessons learned from their accident history, and the rate of criticality accidents was significantly reduced as a result. Over the years, it has been emphasized in NCS training courses and other venues in the United States that the consensus standards, such as ASA N6.1-1964, were the key contributors to this reduction in accidents. The formality of operations required to implement and apply the standards at a facility is also a crucial prerequisite that must be sufficiently robust to ensure NCS. This prerequisite is crucial to success fully implement the NCS consensus and other safety standards at a site.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Resilient design in nuclear energy: Critical lessons from a cross-disciplinary analysis of the Fukushima Dai-ichi nuclear accident

This paper presents a multidisciplinary analysis of the Fukushima Dai-ichi Nuclear Power Plant accident. Along with the latest observations and simulation studies, we synthesize the time-series and event progressions during the accident across multiple disciplines, including in-plant physics and engineering systems, operators’ actions, emergency responses, meteorology, radionuclide release and transport, land contamination, and health impacts. We identify three key factors that exacerbated the consequences of the accident: (1) the failure of Unit 2 containment venting, (2) the insufficient integration of radiation measurements and meteorology data in the evacuation strategy, and (3) the limited risk assessment and emergency preparedness. We conclude with new research and development directions to improve the resilience of nuclear energy systems and communities, including (1) meteorology-informed proactive venting, (2) machine learning-enabled adaptive evacuation zones, and (3) comprehensive risk-informed emergency planning while leveraging the experience from responses to other disasters.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Comparative Analysis of Confidence Metrics for Nuclear Criticality Safety

Nuclear criticality safety standards provide guidance on the requirements and recommendations to establish confidence in computerized model results used to support operation with fissionable materials. By design, the guidance is not prescriptive, leaving the analysts free to determine how various sources of uncertainties are to be statistically aggregated. This report compares the analyses and key assumptions behind four notable methodologies documented in the nuclear criticality safety literature: the parametric, nonparametric, Whisper, and TSURFER methodologies. Because of the involved use of statistics entangled with heuristic recipes, the results of these methodologies are often difficult to interpret. Also, they are augmented by additional large administrative margins, eliminating the incentive to understand their differences. With the new resurgent wave of advanced nuclear systems focused on economizing operation—including advanced reactors, fuel cycles, and fuel concepts—there is a strong need to develop a clear understanding of uncertainties and their fusion methodologies to reduce uncertainties in a scientifically defensible manner. This report offers a deep dive into the various assumptions of the four noted methodologies, their adequacy, and their limitations, to provide guidance on developing confidence for the emergent nuclear systems. These systems are expected to be challenged by the scarcity of experimental data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

An entropy-based debiasing approach to quantifying experimental coverage for novel applications of interest in the nuclear community

This manuscript proposes a novel information-theoretic approach to the quantification of experimental relevance, i.e., coverage, to achieve optimal data assimilation results for nuclear engineering applications. Specifically, this work posits the need for a new metric, called coverage (q C ) of an application’s quantity of interest, i.e., eigenvalue or power peaking for an advanced reactor concept, defined herein as the theoretically maximum achievable reduction in the quantity’s uncertainty given measurements from a pool of experiments in a manner that is independent of the data assimilation procedure employed. Currently, reduction in a quantity’s uncertainty is strongly biased by the underlying assumptions of the assimilation procedure to account for the under-determined nature of such problems and the similarity criterion employed to identify relevant experiments. To address this challenge, this work has developed a coverage metric, q C , based on mutual information, which establishes a new conceptual framework for assessing coverage, one that is independent of the model parameters and responses degree of variations in both the experimental and application domains, i.e., linear vs non-linear, and their prior uncertainty distributions, i.e., Gaussian vs. non-Gaussian. The q C is an entropic measure capable of addressing coverage for general nonlinear problems with non-Gaussian uncertainties and inclusive of the measurement uncertainties from multiple experiments. Numerical experiments from manufactured analytical problems as well as a set of benchmarks from the ICSBEP handbook are employed to demonstrate its theoretical and practical performance as compared to the c k -based experiment selection methodology, commonly employed in the neutronic community. The manuscript then employs other well-known adaptations to existing data assimilation methodologies for nonlinear and non-Gaussian problems capable of achieving the coverage posited by q C .

Bayesian data assimilation↗

Analysis of NCERC Critical Experiments with ENDF/B Nuclear Data Libraries

Nuclear data (ND) libraries are the backbone of the nuclear industry, as they are the collections of tabulated probabilities that define sub-atomic particle interactions with matter. In the areas of criticality safety and experiments, no evaluated nuclear data files (ENDF) are more important than those containing neutron cross section data. It is upon these files, and accompanying radiation transport codes, that practitioners are enabled to safely design both subcritical and critical systems. Likewise, in a symbiotic fashion, it is the same critical assemblies which are used primarily to validate that the cross sections are correct. The ENDF/B library, the United States’ national library maintained by the National Nuclear Data Center (NNDC) at Brookhaven National Laboratory (BNL), is soon releasing a new version, ENDF/B-VIII.1. Prior to the official release, several beta versions of the library were prepared and tested in simulation suites. The work presented here are results comparing the newest ENDF/B beta release (ENDF/B-VIII.1b3) and ENDF/B-VIII.0 with recent experiments done at the National Criticality Experiments Research Center (NCERC) as well as correlated experiments from the Los Alamos Critical Experiments Facility (LACEF). These NCERC and LACEF experiments were performed in part to provide validation for various cross sections that were identified as insufficient in the ENDF/B-VIII.0. In particular, lead, copper, fluorine, and chlorine, as well as the major actinides, were targeted from the last decade of critical experiments.

97 MATHEMATICS AND COMPUTING↗

Analysis of SCALE Criticality and Sensitivity Calculations for Reflected HEU Cylinders [Slides]

The SCALE code package offers multiple nuclear data libraries supporting Monte Carlo transport, with sensitivity and uncertainty methods derived from MC transport solutions. Several libraries are multigroup, which introduce bias differing by system. Previous work has shown poor S/U results in several reflector materials: ICSBEP benchmark HMF-084 was selected to analyze biases and S/U method applicability to a variety of reflectors. Prior and ongoing work found inaccuracies in CSAS and TSUNAMI results, which were further investigated utilizing the HEU-MET-FAST-084 ICSBEP critical benchmark, chosen for its geometrical simplicity and variety of reflector materials. Perturbation of reflector thickness across various reflector materials allowed for an assortment of materials is to be tested swiftly for each sequence and method. Observation was an increasing bias of MG $k_{eff}$ relative to CE, in both direction and magnitude. IFP produced extremely reliable results. >85% of CLUTCH cases were found satisfactory.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗