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At least 721 records · Page 40

Differential and Integral Data Evaluation for Titanium: An Application to Criticality Safety

The intent of this work is to highlight the role of differential and integral data evaluation to address issues in connection with criticality safety applications. Demonstration is made by using, as an example, differential data measurements and evaluation, and the benchmark integral experiments for titanium. Energy differential data are measured analyzed and evaluated to produce nuclear data libraries for criticality safety applications. Alternatively, integral experiments are performed at critical facilities, small experimental reactors, and play an important part in the validation of the differential nuclear data. The demonstration provided here for titanium gives its importance to criticality safety. Titanium is an effective neutron absorber that serves as baseline material for chemical separation in high-activity waste solutions in US. Titanium has not been considered for use in nuclear applications such as reactor design and analysis. Rather, it appears as a structural material that may be present in fuel cycle facilities or canisters for transport and disposition of nuclear waste. Criticality safety evaluations of systems in which titanium is present require an understanding of the nuclear data and its uncertainty.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Plutonium Critical Mass Curve Comparison to Mass at Upper Subcritical Limit (USL) Using Whisper

Whisper is computational software designed to assist the nuclear criticality safety analyst with validation studies with the MCNP ® Monte Carlo radiation transport package. Standard approaches to validation rely on the selection of benchmarks based upon expert judgment. Whisper uses sensitivity/uncertainty (S/U) methods to select relevant benchmarks to a particular application or set of applications being analyzed. Using these benchmarks, Whisper computes a calculational margin. Whisper attempts to quantify the margin of subcriticality (MOS) from errors in software and uncertainties in nuclear data. The combination of the Whisper-derived calculational margin and MOS comprise the baseline upper subcritical limit (USL), to which an additional margin may be applied by the nuclear criticality safety analyst as appropriate to ensure subcriticality. A series of critical mass curves for plutonium, similar to those found in Figure 31 of LA-10860-MS, have been generated using MCNP6.1.1 and the iterative parameter study software, WORM_Solver. The baseline USL for each of the data points of the curves was then computed using Whisper 1.1. The USL was then used to determine the equivalent mass for plutonium metal-water system. ANSI/ANS-8.1 states that it is acceptable to use handbook data, such as the data directly from the LA-10860-MS, as it is already considered validated (Section 4.3 4) “Use of subcritical limit data provided in ANSI/ANS standards or accepted reference publications does not require further validation.”). This paper attempts to take a novel approach to visualize traditional critical mass curves and allows comparison with the amount of mass for which the k eff is equal to the USL (calculational margin + margin of subcriticality). However, the intent is to plot the critical mass data along with USL, not to suggest that already accepted handbook data should have new and more rigorous requirements for validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Rossi-alpha Analysis of CURIE Experiment [Slides]

Critical assembly measurement and operations are crucial to the development of benchmark data. Knowledge of the prompt neutron lifetime informs on the state of the system’s neutron spectrum. Rossi-alpha analysis can give us time-dependent information on the system. Teflon was selected, via genetic algorithm, as a moderator to target the URR in uranium for CURIE. Rossi-alpha measurements of the assembly's approach to critical using He-3 detectors estimated the prompt neutron decay constant (α) at delayed critical. α values of several subcritical measurements were then used to predict the α value at delayed critical.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Planning for the storm: Considering renewable energy for critical infrastructure resilience

This study uses the renewable energy optimization model to assess three critical facilities in North Carolina. Techno-economic results were then compared to analyses completed for critical facilities in California and New York to assess energy system cost effectiveness. Though solar photovoltaic (PV) arrays are cost-effective across each of the three North Carolina facilities, adopting battery storage to enable PV to operate with existing diesel generators in a hybrid energy system reduces the economic value of the system. This is in contrast to more economically viable systems in California and New York. All of these systems also offer unquantified resilience benefits by extending operation from hours to weeks across the facilities. If decision makers were able to value the resilience benefits offered by each system or utility rate structures were changed to incentivize battery storage during normal operations, it would impact these assessments. Even so, this analysis provides decision makers a key set of cost benchmarks when considering how they might improve resilience at their critical operations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Modeling of the Molten Salt Reactor Experiment with SCALE

A SCALE model was developed for the Molten Salt Reactor Experiment (MSRE) benchmark that was recently added to the International Handbook of Evaluated Reactor Physics Benchmark Experiments. This SCALE model served as a basis for criticality calculations and nuclear data sensitivity and uncertainty analyses with the Monte Carlo code Shift and the TSUNAMI computational capabilities in the SCALE code system. The focus of this work is the assessment of the impact of nuclear data on the calculated eigenvalue results in support of the discussion of differences between the calculated and the experimental eigenvalue result. The differences in the eigenvalues obtained using the ENDF/B-VII.0, ENDF/B-VII.1, and ENDF/B-VIII.0 nuclear data libraries cover a relatively small range of ~230 pcm. Since eigenvalue sensitivity of the MSRE is dominated by the neutron multiplicity and neutron capture of 235 U and elastic scattering in graphite, relevant changes in the ENDF/B libraries for nuclear reactions (such as carbon capture) that caused large differences in other graphite-moderated systems did not have a significant impact. Propagation of nuclear data uncertainty results in an eigenvalue uncertainty of ~700 pcm with the major contributors being 235 U neutron multiplicity, graphite elastic scattering, and 7Li neutron capture. All calculations resulted in large differences of ~2000 pcm in eigenvalue compared to the benchmark experimental value. Several potential contributors to this difference—including uncertainties and gaps in the knowledge of the material, geometry, and nuclear data—were identified. Simplified models of the full MSRE core were developed, and similarity assessments were conduced with the full MSRE core model. It was found that simplified models can serve as adequate surrogates of the full-core model such that they can be used for performing selected nuclear data performance assessments with a lower computational burden.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Photo Doppler Velocimetry and Gamma/Neutron Yield Measurements of Godiva-IV Critical Assembly

The purpose of this experiment was to collect data for a dynamic benchmark of the Godiva-IV burst assembly. Data were taken using two different measurement systems. The gamma & neutron flux was measured using a calibrated, high-dynamic-range scintillator detector, the MHD-240. The measurement will be used to determine the total fission yield and alpha throughout the burst and shutdown sequence of Godiva-IV. The Photon Doppler Velocimetry (PDV) measurement detected the surface motion of the burst assembly as a function of time. The combined data will be used in a multi-physics simulation of the Godiva-IV burst assembly.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

THE INFLUENCE OF CHANGES IN NUCLEAR COVARIANCE DATA ON THE CALCULATION OF Ck FOR HIGHLY ENRICHED URANIUM SOLUTION SYSTEMS

Since their initial development nearly 20 years ago, sensitivity/uncertainty (S/U) techniques have been increasingly applied to criticality safety validation. These techniques can generally be applied quickly and for a range of purposes after the initial investment of calculating sensitivities for a safety analysis model and a range of potential benchmark experiments. This paper discusses these applications and how they have been affected by changes in covariance data libraries.Critical experiment selection is the most prominent area in which S/U methods impact validation efforts. These methods allow for rigorous calculation of similarity between safety analysis models and potential benchmarks. The most widely used of these methods is the integral parameter ck, although other integral parameters such as E and some non-integral parameters have also been explored. The ck parameter calculates the fraction of nuclear data–induced uncertainty shared between an application and an experiment; this metric is predicated on the assessment that nuclear data errors are the most likely source of computational bias. Therefore, values of ck are inherently dependent on the nuclear covariance library used to calculate them and inevitably change when these data change.Past studies have shown how much the ck values can vary, especially in difficult validation cases like burnup credit. These significant changes are the result of differences in the relative uncertainties of nuclides with large sensitivities, and they imply differences in benchmark applicability to the safety analysis model. This paper demonstrates that more common criticality safety models involving single fissile species have significantly less variability of ck between covariance libraries, thus enhancing confidence in the application of S/U methods for experiment selection in these scenarios. This paper presents case studies examining the impact of these changes on some hypothetical safety analysis systems.

Clarity, Justin↗

An MLCommons Scientific Benchmarks Ontology

Scientific machine learning research spans diverse domains and data modalities, yet existing benchmark efforts remain siloed and lack standardization. This makes novel and transformative applications of machine learning to critical scientific use-cases more fragmented and less clear in pathways to impact. This paper introduces an ontology for scientific benchmarking developed through a unified, community-driven effort that extends the MLCommons ecosystem to cover physics, chemistry, materials science, biology, climate science, and more. Building on prior initiatives such as XAI-BENCH, FastML Science Benchmarks, PDEBench, and the SciMLBench framework, our effort consolidates a large set of disparate benchmarks and frameworks into a single taxonomy of scientific, application, and system-level benchmarks. New benchmarks can be added through an open submission workflow coordinated by the MLCommons Science Working Group and evaluated against a six-category rating rubric that promotes and identifies high-quality benchmarks, enabling stakeholders to select benchmarks that meet their specific needs. The architecture is extensible, supporting future scientific and AI/ML motifs, and we discuss methods for identifying emerging computing patterns for unique scientific workloads. The MLCommons Science Benchmarks Ontology provides a standardized, scalable foundation for reproducible, cross-domain benchmarking in scientific machine learning. A companion webpage for this work has also been developed as the effort evolves: https://mlcommons-science.github.io/benchmark/

Hawks, Ben [Fermilab] (ORCID:0000000157000288)↗

Lilith: An Enduring Plutonium Critical Assembly [Slides]

A design of an enduring Pu critical assembly has been produced. This is very important to DOE/NNSA missions. This assembly would result in advances/improvements in nuclear data validation, analytical methods validation, dosimetry, reactor kinetics, materials, and more.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

FY21 MCNP ® Updates for the Nuclear Criticality Safety Program [Slides]

LANL has devoted a substantial amount effort toward the MCNP6.3 release over the past year by improving many of their processes, infrastructure, and capabilities. Many new resources in support of the MCNP code and DOE NCSP applications are coming online now. LANL is excited to receive feedback on all of the new and improved capabilities that will be packaged with MCNP6.3.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Case Study in the Application of TSUNAMI-3D - Part 1, Multigroup

The use of the sensitivity and uncertainty tool suite within SCALE, known as the TSUNAMI suite, has grown following its initial introduction more than a decade ago. Proper use of these tools provides a more complete understanding of system responses to perturbations, especially in the area of nuclear cross section uncertainties. Recent advances within TSUNAMI have added generalized perturbation theory to the k{sub eff} sensitivity capability that was included in TSUNAMI originally. The generation of sensitivity data is encouraged in the review process for new critical experiment requests sponsored by the US Department of Energy (DOE) Nuclear Criticality Safety Program (NCSP) to demonstrate that the proposed experiment will satisfy the identified data need. Many individuals participate in this process, but many analysts have not received proper training in the use of the TSUNAMI tools. The adjoint perturbation theory used to calculate sensitivities is not typically included in nuclear engineering curricula, leaving inexperienced engineers particularly at risk for incorrect use of the tools. The first step in the use of the TSUNAMI tools is the generation of a sensitivity data file (SDF), which contains all of the energy-dependent sensitivity data generated for a model. Most often, the SDF is generated from a three-dimensional (3D) model using either the KENO V.a or KENO-VI code within the TSUNAMI-3D sequence. The sensitivity data generated in TSUNAMI-3D must be accurate for correct quantification of system similarity or any other use of the sensitivity data. The sensitivities calculated by TSUNAMI can be affected by many of the input parameters, cross section processing models, and geometry modeling techniques used within the TSUNAMI-3D input. Fortunately, the total sensitivity of the most important nuclides can be confirmed simply by using direct perturbation (DP) calculations. Confirmation of the total sensitivity of these important nuclides provides confidence that the flux and importance function calculated within the TSUNAMI sequence will yield accurate sensitivities for all nuclides, reactions, and energies of interest. This process is essentially identical for the multigroup (MG) methods and the continuous-energy (CE) methods introduced in SCALE 6.2. This paper discusses the use of DP calculations and provides a case study to confirm that accurate sensitivities are generated by TSUNAMI-3D for a particular benchmark experiment. A companion paper provides a similar case study applying the CE TSUNAMI capability to the same critical experiment. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A Case Study in the Application of TSUNAMI-3D - Part 2, Continuous Energy

The use of the sensitivity and uncertainty tool suite within SCALE, which is known as the TSUNAMI suite, has grown following its initial introduction more than a decade ago. Proper use of this tool provides a more complete understanding of system responses to perturbations, especially in the area of nuclear cross section uncertainties. Recent advances within TSUNAMI have added generalized perturbation theory to the k{sub eff} sensitivity capability that was included in TSUNAMI originally. The sensitivities can also be used to quantify the similarity of two systems. As an example, calculated sensitivities can be combined with cross section uncertainties to determine the similarity index ck. The generation of sensitivity data is encouraged in the review process for new critical experiment requests sponsored by the US Department of Energy (DOE) Nuclear Criticality Safety Program (NCSP) to demonstrate that the proposed experiment will satisfy the identified data need. Many analysts participate in this process, but many have not received proper training in the use of the TSUNAMI tools. The adjoint perturbation theory used to calculate sensitivities is not typically included in nuclear engineering curricula, leaving inexperienced engineers particularly at risk for incorrect use of the tools. The first step in the use of the TSUNAMI tools is the generation of a sensitivity data file (SDF), which contains all of the energy-dependent sensitivity data generated for a model. Most often, the SDF is generated from a three-dimensional (3D) model using either the KENO V.a or KENO-VI code within the TSUNAMI-3D sequence. The sensitivity data generated in TSUNAMI-3D must be accurate for correct quantification of system similarity or any other use of the sensitivity data. The sensitivities calculated by TSUNAMI can be affected by many of the input parameters, cross section processing models, and geometry modeling techniques used within the TSUNAMI-3D input. Fortunately, the total sensitivity of the most important nuclides can be confirmed simply by using direct perturbation (DP) calculations. Confirmation of the total sensitivity of these important nuclides provides confidence that the flux and importance function calculated within the TSUNAMI sequence will yield accurate sensitivities for all nuclides, reactions, and energies of interest. This process is essentially identical for multigroup (MG) and continuous-energy (CE) methods introduced in SCALE 6.2. This paper discusses the use of direct perturbation calculations and provides a case study in the use of DP calculations to confirm accurate sensitivities generated by the CE CLUTCH methods in TSUNAMI-3D for a particular benchmark experiment. A companion paper provides a similar case study applying the MG TSUNAMI capability to the same critical experiment. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

The 0E2 benchmarks for PWR UO 2 decay heat: an analysis from the NEA WPNCS

This paper presents the work performed in the subgroup 16 of the Working Party for Nuclear Criticality Safety (WPNCS) of the OECD Nuclear Energy Agency. The main goal was to define two decay heat benchmarks for Spent Nuclear Fuel (one pincell and one assembly), perform calculations and compare and analyze the results in light of existing calorimetric measurements. The selected case is the PWR UO2 assembly 0E2, irradiated at the Ringhals-3 reactor and measured at the Clab facility in Sweden. In total, 21 institutes worldwide participated to the exercise, leading to 55 calculated results (named C). It was found that the measured decay heat values (E) can be satisfactorily reproduced with two-dimensional assembly calculations, leading to an average C/E value of 0.99, with an uncertainty (or one standard deviation) of ±0.01.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A non-intrusive framework using acoustic signals and deep learning for boiling diagnostics in visual-limited environments

Accurate monitoring of boiling heat transfer is critical for safeguarding high-power systems operating in environments where conventional optical diagnostics are hindered by radiation fields or restricted visual accessibility. This study presents a non-intrusive framework that integrates hydroacoustic sensing with deep learning to infer near-wall boiling characteristics and enable predictive thermal assessment without visual access. In a prototypical subcooled flow-boiling facility representative of the Isotope Production Facility (IPF) at Los Alamos, hydrophones capture boiling-induced acoustic emissions that are transformed into background-removed Short-Time Fourier Transform (STFT) spectrograms. A convolutional neural network (CNN) then regresses heat flux, wall superheat, and key bubble parameters directly from these spectrograms. The CNN achieved predictive accuracy under nominal conditions and demonstrated robustness and generalization under acoustic noise for Signal-to-Noise Ratios (SNRs) down to approximately 0 dB. When integrated into an ANSYS CFX wall-boiling model, the acoustically inferred parameters reproduced boiling curve and critical heat flux (CHF) values consistent with image-based benchmarks. Furthermore, the model retained reliable performance under moderate variations in bulk temperature, flow rate, and hydrophone placement, confirming its generalizability across practical boundary conditions. These results demonstrate the feasibility of hydroacoustic-based deep learning as a viable path toward real-time, radiation-tolerant boiling diagnostics and predictive thermal safety assessment in inaccessible systems such as the IPF.

42 ENGINEERING↗

TEX-HEU: Integral Experiment Execution with Polyethylene at Very Low Temperatures

The low-temperature variant of the TEX HEU (called Low-Temperature TEX or sometimes LT TEX) campaign is a highly anticipated and necessary experimental series by the greater nuclear science community. Fundamentally, the need for low-temperature integral experiments is required to perform validation of cross sections below room temperature. There has been substantial international interest in low-temperature benchmarks to validate below room temperature cross sections, namely talks given at the 2019 International Conference on Nuclear Criticality (ICNC): UK (Watson, 2019), France (Milin, 2019), and UK (Gan & Wilson, 2019). Additionally, NCSP funded thermal scattering laws (TSLs) were produced by North Carolina State University and require low-temperature benchmarks to validate them. Validation of low-temperature cross sections is also necessary for criticality safety applications. One particularly important application is to ensure that during transportation, fissile materials must remain subcritical under normal ambient conditions which is defined as temperatures down to -40°C/°F by the United States 10 CRF 71 as well as a regulation put forward by the International Atomic Energy Agency (IAEA).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Overview of the 2014 Edition of the International Handbook of Evaluated Reactor Physics Benchmark Experiments (IRPhEP Handbook)

The International Reactor Physics Experiment Evaluation Project (IRPhEP) is a widely recognized world class program. The work of the IRPhEP is documented in the International Handbook of Evaluated Reactor Physics Benchmark Experiments (IRPhEP Handbook). Integral data from the IRPhEP Handbook is used by reactor safety and design, nuclear data, criticality safety, and analytical methods development specialists, worldwide, to perform necessary validations of their calculational techniques. The IRPhEP Handbook is among the most frequently quoted reference in the nuclear industry and is expected to be a valuable resource for future decades.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗