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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6

PBX-9501 High Explosive Infrared Thermography Test Report

High explosive safety requirements put in place by the Department of Defense necessitate that Los Alamos National Laboratory verify that high melting explosive-based plastic bonded explosive 9501 will not present a health or safety risk to personnel when exposed to various accident scenarios. The JT5R-14C test is being developed to validate this requirement in a scenario where PBX-9501 is exposed to a hydrocarbon fuel fire. Preliminary testing is required to establish benchmark data on the burning characteristics of PBX-9501. The PBX-9501 High Explosive Infrared Thermography test was designed to provide the benchmark burning characteristics of PBX-9501 in a simulated fuel fire environment using propane burners as a fuel source. The PBX-9501-HEIT was successfully completed using a 20.32 cm tall cylindrical sample of PBX-9501 with a radius of 10.16 cm, a volume of 6,589.63 cm 3 , a density of 1.83 g/cm 3 , and a mass of 1.2 kg. The PBX-9501-HEIT test was captured and recorded video sequence using a Telops Inc., Multispectral Infrared camera. The infrared sequence was reviewed to identify key events throughout the test and serves as a visual tool to cross reference against future testing to aid in the identification of PBX-9501 high explosive ignition and deflagration characteristics. The data obtained in the thermographic sequence confirmed that the temperatures emitted by the PBX-9501 were higher than the temperatures of the propane burner ignition source. The propane burner flames had a temperature range of 700-850 °C. The cylindrical sample of PBX-9501 burned at an average temperature of 1000-1200 °C on the surface with off-gassing temperatures averaging 1100-1250 °C. The heat map of the PBX-9501 obtained through the test was between 250-550 °C higher than the propane gas temperatures. The temperature differential between the PBX-9501 and the propane flame allowed for the identification of key burning features.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Proposed Plutonium-Nickel Critical Experiment

The Los Alamos Critical Experiments Facility (LACEF) and subsequently its descendant, the National Criticality Experiments Research Center (NCERC) located at the Nevada National Security Site, have been performing critical experiments for over 75 years. The work done continues to build upon lessons learned from the past. It also builds upon knowledge gained from past experiments. The LACEF and NCERC experiments “provide nuclear criticality benchmark data for a wide variety of fissile and non-fissile materials in all neutron energy spectra systems”. In 2014, a subcritical benchmark with plutonium surrounded by nickel was issued in the International Criticality Safety Benchmark Evaluation Project (ICSBEP). Two years later, a new benchmark experiment was performed, commonly known as Subcritical Copper Reflected $\mathcal{a}$-Phase Plutonium SCR$\mathcal{a}$P. The uncertainties in the SCR$\mathcal{a}$P experiment were significantly reduced from the Pu-Ni experiment and the methods were refined. Additionally, a Pu-lead critical experiment was performed in 2017 which followed different methods and with different objectives. Now, an experiment is proposed that builds on both the subcritical nickel experiment and the critical lead experiment. The proposed experiment has interleaved nickel and plutonium, in a thermal arrangement. This particular experiment would support criticality safety at the Hanford Tank Farms, whose tanks contain a significant amount of nickel credited as a neutron absorber in the criticality safety evaluation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

OSCILLATOR STRENGTHS OF VIBRIONIC EXCITATIONS OF NITROGEN DETERMINED BY THE DIPOLE (γ, γ) METHOD

The oscillator strengths of the valence-shell excitations of molecular nitrogen have significant applicational values in studies of the Earth's atmosphere and interstellar gases. In this work, the absolute oscillator strengths of the valence-shell excitations of molecular nitrogen in 12.3–13.4 eV were measured by the novel dipole (γ, γ) method, in which the high-resolution inelastic X-ray scattering is operated at a negligibly small momentum transfer and can simulate the photoabsorption process. Because the experimental technique used in the present work is distinctly different from those used previously, the present experimental results give an independent cross-check to previous experimental and theoretical data. The excellent coincidence of the present results with the dipole (e, e) and those that were extrapolated indicates that the present oscillator strengths can serve as benchmark data.

74 ATOMIC AND MOLECULAR PHYSICS↗

Experimental Investigation of Forced Convection and Natural Circulation Cooling of a VHTR Core under Normal Operation and Accident Scenarios

This NEUP project #15-8205 entitled “Experimental Investigation of Forced Convection and Natural Circulation Cooling of a VHTR Core under Normal Operation and Accident Scenarios”, has investigated important phenomena in the safety of Very High Temperature Reactors (VHTRs) using the experimental facilities at City College of New York (CCNY) and Kansas State University (KSU), in collaboration with the Idaho State University (ISU) and Idaho National Laboratory (INL). The main objectives of this project were to investigate the forced convection and bypass flow phenomena, natural circulation flow and heat transfer, and graphite oxidation due to air ingress which could occur in a Very High Temperature Reactor (VHTR) with a prismatic core. High pressure/high temperature experiments have been conducted to obtain data that could be used for validation of VHTR design and safety analysis codes. The focus of these experiments was on the generation of benchmark data for design and off-design heat transfer for forced and natural circulation in a VHTR core. This work has built on the previous NEUP project #11-3218 which investigated forced convection and flow laminarization phenomena in a prismatic core of a VHTR and natural circulation of a pure gas under Pressurized Conduction Cooldown (PCC) and Depressurized Conduction Cooldown (DCC) conditions. Under each Task, extensive literature reviews on natural circulation, bypass flow, air ingress and graphite oxidation phenomena were conducted. In Task 1, scaling analyses were conducted by Idaho State University followed by design and construction of experimental facilities needed to conduct both bypass flow and natural circulation experiments at CCNY. Natural circulation experiments were conducted in Task 2 to investigate the air ingress phenomena, and bypass flow phenomena in Task 3, both at CCNY. In Task 4, radiation heat transfer and graphite oxidation tests were performed at Kansas State University. The experimental data were then analyzed to obtain quantitative results on natural circulation of pure gases and gas mixtures under DCC conditions, bypass flow rates, radiation heat transfer and graphite oxidation. In addition, CFD and Direct Numerical Simulations were conducted by INL and CCNY to investigate the flow laminarization phenomenon in strongly heated gas flows. The scaling analyses have shown that the key nondimensional numbers and parameters all have acceptable distortion levels principally because the CCNY facility’s test sections have representative cooling channel dimensions and are using either helium or a scalable gas such as nitrogen at representative state conditions. The natural circulation experiments involving helium and nitrogen gas mixtures at CCNY have elucidated the effect of nitrogen (simulating air) ingress into a lower plenum on the onset of natural circulation, mass flow rates and heat transfer coefficients under different power input levels in the riser section. Also, the transport of nitrogen from the lower plenum to upper plenum due to natural circulation was quantified for the first time. Nusselt number correlations for the heat transfer coefficient under natural circulation as a function of Reynolds and Prandtl numbers was also developed. The experiments at KSU revealed that prior to the onset of natural circulationin a VHTR core. This work has built on the previous NEUP project #11-3218 which investigated forced convection and flow laminarization phenomena in a prismatic core of a VHTR and natural circulation of a pure gas under Pressurized Conduction Cooldown (PCC) and Depressurized Conduction Cooldown (DCC) conditions. Under each Task, extensive literature reviews on natural circulation, bypass flow, air ingress and graphite oxidation phenomena were conducted. In Task 1, scaling analyses were conducted by Idaho State University followed by design and construction of experimental facilities needed to conduct both bypass flow and natural circulation experiments at CCNY. Natural circulation experiments were conducted in Task 2 to investigate the air ingress phenomena, and bypass flow phenomena in Task 3, both at CCNY. In Task 4, radiation heat transfer and graphite oxidation tests were performed at Kansas State University. The experimental data were then analyzed to obtain quantitative results on natural circulation of pure gases and gas mixtures under DCC conditions, bypass flow rates, radiation heat transfer and graphite oxidation. In addition, CFD and Direct Numerical Simulations were conducted by INL and CCNY to investigate the flow laminarization phenomenon in strongly heated gas flows. The scaling analyses have shown that the key nondimensional numbers and parameters all have acceptable distortion levels principally because the CCNY facility’s test sections have representative cooling channel dimensions and are using either helium or a scalable gas such as nitrogen at representative state conditions.The natural circulation experiments involving helium and nitrogen gas mixtures at CCNY have elucidated the effect of nitrogen (simulating air) ingress into a lower plenum on the onset of natural circulation, mass flow rates and heat transfer coefficients under different power input levels in the riser section. Also, the transport of nitrogen from the lower plenum to upper plenum due to natural circulation was quantified for the first time. Nusselt number correlations for the heat transfer coefficient under natural circulation as a function of Reynolds and Prandtl numbers was also developed. The experiments at KSU revealed that prior to the onset of natural circulation(ONC), molecular diffusion plays a significant role in air-ingress, however, at higher temperatures convection currents may be influencing air ingress and in-turn ONC times. Bypass flow experiments faced difficulties in the measurement of gas velocity in the main channel due to the failure of a high temperature Hot Wire Anemometer probe, so an energy balance method was instead employed to estimate the flow distribution between the main and bypass flow channels. In the graphite oxidation experiments conducted at KSU, oxidation was found to increase the thermal diffusivity of nuclear grade graphite. This change is believed to be driven by oxidation decreasing graphite sample density rather than raising the thermal conductivity. Oxidation was also shown to greatly alter graphite emissivity. If large amounts of impurities have built up within the graphite over time and have significantly increased its effective ash content, then air ingress is likely to severely inhibit the radiative heat transfer abilities of the graphite due to the formation of low emissivity, ash layers on its surface. However, if the purity of the graphite at the time of the air ingress is still close to that of its virgin specifications, the oxidation induced roughening of the graphite’s outer surface would have the effect of slightly raising its emissivity. The flow laminarization phenomenon was investigated by INL by examining the results of Direct Numerical Simulations of previous experiments, and by CCNY conducting its own DNS simulations using DOE’s Nek5000 code

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Estimating traffic volumes for signalized intersections using connected vehicle data

Recently connected vehicle (CV) technology has received significant attention thanks to active pilot deployments supported by the US Department of Transportation (USDOT). At signalized intersections, CVs may serve as mobile sensors, providing opportunities of reducing dependencies on conventional vehicle detectors for signal operation. However, most of the existing studies mainly focus on scenarios that penetration rates of CVs reach certain level, e.g., 25%, which may not be feasible in the near future. How to utilize data from a small number of CVs to improve traffic signal operation remains an open question. In this work, we develop an approach to estimate traffic volume, a key input to many signal optimization algorithms, using GPS trajectory data from CV or navigation devices under low market penetration rates. To estimate traffic volumes, we model in this paper vehicle arrivals at signalized intersections as a time-dependent Poisson process, which can account for signal coordination. The estimation problem is formulated as a maximum likelihood problem given multiple observed trajectories from CVs approaching to the intersection. An expectation maximization (EM) procedure is derived to solve the estimation problem. Two case studies were conducted to validate our estimation algorithm. One uses the CV data from the Safety Pilot Model Deployment (SPMD) project, in which around 2800 CVs were deployed in the City of Ann Arbor, MI. The other uses vehicle trajectory data from users of a commercial navigation service in China. Mean absolute percentage error (MAPE) of the estimation is found to be 9–12%, based on benchmark data manually collected and data from loop detectors. Finally, considering the existing scale of CV deployments, the proposed approach could be of significant help to traffic management agencies for evaluating and operating traffic signals, paving the way of using CVs for detector-free signal operation in the future.

97 MATHEMATICS AND COMPUTING↗

Data-centric framework for crystal structure identification in atomistic simulations using machine learning

Atomic-level modeling performed at large scales enables the investigation of mesoscale materials properties with atom-by-atom resolution. The spatial complexity of such cross-scale simulations renders them unsuitable for simple human visual inspection. Instead, specialized structure characterization techniques are required to aid interpretation. These have historically been challenging to construct, requiring significant intuition and effort. Here we propose an alternative framework for a fundamental structural characterization task: classifying atoms according to the crystal structure to which they belong. Our approach is data-centric and favors the employment of Machine Learning over heuristic rules of classification. A group of data-science tools and simple local descriptors of atomic structure are employed together with an efficient synthetic training set. We also introduce the first standard and publicly available benchmark data set for evaluation of algorithms for crystal-structure classification. Further, it is demonstrated that our data-centric framework outperforms all of the most popular heuristic methods—especially at high temperatures when lattices are the most distorted—while introducing a systematic route for generalization to new crystal structures. Moreover, through the use of outlier detection algorithms our approach is capable of discerning between amorphous atomic motifs (i.e., noncrystalline phases) and unknown crystal structures, making it uniquely suited for exploratory materials synthesis simulations.

36 MATERIALS SCIENCE↗

ENDF/B-VIII.1: Updated Nuclear Reaction Data Library for Science and Applications

The ENDF/B-VIII.1 library is the newest recommended evaluated nuclear data file by the Cross Section Evaluation Working Group (CSEWG) for use in nuclear science and technology applications, and incorporates advances made in the six years since the release of ENDF/B-VIII.0. Among key advances made are that the 239 Pu file was reevaluated by a joint international effort and that updated 16,18 O, 19 F, 28–30 Si, 50–54 Cr, 55 Mn, 54,56,57 Fe, 63,65 Cu, 139 La, 233,235,238 U, and 240,241 Pu neutron nuclear data from the IAEA coordinated INDEN collaboration were adopted. Over 60 neutron dosimetry cross sections were adopted from the IAEA's IRDFF-II library. In addition, the new library includes significant changes for 3 He, 6 Li, 9 Be, 51 V, 88 Sr, 103 Rh, 140,142 Ce, Dy, 181 Ta, Pt, 206–208 Pb, and 234,236 U neutron data, and new nuclear data for the photonuclear, charged-particle and atomic sublibraries. Numerous thermal neutron scattering kernels were reevaluated or provided for the very first time. On the covariance side, work was undertaken to introduce better uncertainty quantification standards and testing for nuclear data covariances. The significant effort to reevaluate important nuclides has reduced bias in the simulations of many integral experiments with particular progress noted for fluorine, copper, and stainless steel containing benchmarks. Data issues hindered the successful deployment of the previous ENDF/B-VIII.0 for commercial nuclear power applications in high burnup situations. These issues were addressed by improving the 238 U and 239,240,241 Pu evaluated data in the resonance region. The new library performance as a function of burnup is similar to the reference ENDF/B-VII.1 library.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Uranium integral fission product yields for a spectrally-shaped 14.1 MeV neutron source at the National Ignition Facility

This paper describes the experimental results for an energy tuning assembly created to modify the National Ignition Facility deuterium–tritium fusion neutron source into a notional thermonuclear and prompt fission neutron spectrum, which has applications in integral measurements, nuclear data benchmarks, and radiation effects on microelectronics. The Monte Carlo neutron transport utilized MCNP5 to estimate the ETA-modified fluence using the ENDF-B/VIII.0 and IRDFF-II continuous energy nuclear data libraries, and SCALE Sampler was used to estimate the systematic nuclear data covariance using ENDF-B/VII.1 and IRDFF-II in a 252-group structure. The experiment fielded eight activation foils and a highly enriched uranium sample. This provided fifteen reaction channels that were used in a forward-fit comparison to the modeled results and to unfold the neutron spectrum using STAYSL. Gamma-ray spectrometry was performed on the activation and highly enriched uranium foils, and the reduced Χ 2 between the modeled and experimental values was 1.21. The results from the STAYSL unfold, reduced Χ 2 = 1.62, indicated that the modeled neutron spectrum was achieved and the systematic nuclear data uncertainty associated with the neutron transport and activation product cross sections was representative of the experiment. Integral cumulative fission product yield data were collected for 37 mass chains with a combination of gamma-ray spectrometry and radiochemical analysis. Fission product analysis was generally in agreement with two models using a semi-empirical fit and the General Observables of Fission code, with the exception of mass chains 88, 109, 111, 112, 113, 129, 139, 142, 144, 151, and 156.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Dimensionality reduction using elastic measures

With the recent surge in big data analytics for hyperdimensional data, there is a renewed interest in dimensionality reduction techniques. In order for these methods to improve performance gains and understanding of the underlying data, a proper metric needs to be identified. This step is often overlooked, and metrics are typically chosen without consideration of the underlying geometry of the data. Here, in this paper, we present a method for incorporating elastic metrics into the t-distributed stochastic neighbour embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP). We apply our method to functional data, which is uniquely characterized by rotations, parameterization and scale. If these properties are ignored, they can lead to incorrect analysis and poor classification performance. Through our method, we demonstrate improved performance on shape identification tasks for three benchmark data sets (MPEG-7, Car data set and Plane data set of Thankoor), where we achieve 0.77, 0.95 and 1.00 F1 score, respectively.

97 MATHEMATICS AND COMPUTING↗

A volumetric framework for quantum computer benchmarks

We propose a very large family of benchmarks for probing the performance of quantum computers. We call them volumetric benchmarks (VBs) because they generalize IBM's benchmark for measuring quantum volume \cite{Cross18}. The quantum volume benchmark defines a family of square circuits whose depth d and width w are the same. A volumetric benchmark defines a family of rectangular quantum circuits, for which d and w are uncoupled to allow the study of time/space performance trade-offs. Each VB defines a mapping from circuit shapes — ( w , d ) pairs — to test suites C ( w , d ) . A test suite is an ensemble of test circuits that share a common structure. The test suite C for a given circuit shape may be a single circuit C , a specific list of circuits { C 1 … C N } that must all be run, or a large set of possible circuits equipped with a distribution P r ( C ) . The circuits in a given VB share a structure, which is limited only by designers' creativity. We list some known benchmarks, and other circuit families, that fit into the VB framework: several families of random circuits, periodic circuits, and algorithm-inspired circuits. The last ingredient defining a benchmark is a success criterion that defines when a processor is judged to have ``passed'' a given test circuit. We discuss several options. Benchmark data can be analyzed in many ways to extract many properties, but we propose a simple, universal graphical summary of results that illustrates the Pareto frontier of the d vs w trade-off for the processor being benchmarked.

97 MATHEMATICS AND COMPUTING↗

RIA Experimentation Benchmark

Significant developments have been applied to the Bison code to make it capable for Reactivity- Initiated Accident (RIA) simulations. This report documents efforts to demonstrate the current Bison capabilities for an RIA simulation with a comparison to experimental and benchmark data. A number of CABRI REP and CIP cases have been modeled and compared to experimental and other code prediction results. This work shows that Bison is capable of predicting thermal, mechanical, and fission gas release data in agreement with the experimental results and other fuel performance code predictions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Uncertainty Quantification in GADRAS Inverse Modeling

The Gamma Detector Response and Analysis Software (GADRAS) package includes an inverse modeling tool that is helpful in identifying characteristics of unknown radioactive materials. Traditionally, uncertainties in this analysis were derived solely from measurement data quality and the fit of synthetic spectra. This paper aims to rigorously quantify additional sources of uncertainty, focusing on uncertainties arising from measurements being analyzed, Detector Response Function (DRF) characterization, and DRF extrapolation. Applying these findings to the BeRPBall benchmark data set, we demonstrated the impact of these uncertainties on plutonium and polyethylene estimates. The results underscore the importance of incorporating diverse uncertainty sources to enhance the accuracy and reliability of GADRAS’s inverse modeling capabilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Airborne imaging spectroscopy surveys of Arctic and boreal Alaska and northwestern Canada 2017–2023

Since 2015, NASA’s Arctic Boreal Vulnerability Experiment (ABoVE) has investigated how climate change impacts the vulnerability and/or resilience of the permafrost-affected ecosystems of Alaska and northwestern Canada. ABoVE conducted extensive surveys with the Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) during 2017, 2018, 2019, and 2022 and with AVIRIS-3 in 2023 to characterize tundra, taiga, peatlands, and wetlands in unprecedented detail. The ABoVE AVIRIS dataset comprises ~1700 individual flight lines covering ~120,000 km 2 with nominal 5 m × 5 m spatial resolution. Data include individual transects to capture important gradients like the tundra-taiga ecotone and maps of up to 10,000 km 2 for key study areas like the Mackenzie Delta. The ABoVE AVIRIS surveys enable diverse ecosystem science, provide crucial benchmark data for validating retrievals from the PACE, PRISMA, and EnMAP satellite sensors and help prepare for the SBG and CHIME missions. This paper guides interested researchers to fully explore the ABoVE AVIRIS spectral imagery and complements our guide to the ABoVE airborne synthetic aperture radar surveys.

Miller, Charles E. [California Institute of Techno↗

Empirically-calibrated H100 node power models for accurate AI training energy estimation

Accurately quantifying the energy use of artificial intelligence (AI) training is critical for infrastructure planning, carbon accounting, and sustainable data center operation, but few studies have directly measured the power consumption of production workloads on contemporary hardware. By combining empirical measurements from Brookhaven National Laboratory during AI training on 8-graphics-processing-unit H100 systems with open-source benchmarking data, we develop statistical models relating computational intensity to node-level power consumption. We measure the gap between manufacturer-rated thermal design power (TDP) and actual power demand during AI training. Our analysis reveals that even computationally intensive workloads operate at only 76% of the 10.2 kW TDP rating. Our architecture-specific model, calibrated to floating-point operations, predicts energy consumption with 11.4% mean absolute percentage error, significantly outperforming TDP-based approaches (27%–37% error). We identified distinct power signatures between transformer and convolutional neural network architectures, with transformers showing characteristic fluctuations that may impact grid stability. These results provide a measurement-grounded basis for improving AI training energy estimates, enabling more reliable infrastructure sizing, cost projections, and environmental impact assessments.

Newkirk, Alex C↗

Multi‐Model Ensembles in Ecosystem Modeling: Challenges and Best Practices for Decision‐Making

Ecosystem models are increasingly central to the decision-making for environmental policy, conservation planning, and climate-related investments. Yet, the growing reliance on Multi-Model Ensembles (MMEs) of ecosystem models by practitioners and policymakers, sometimes under tight timelines and imperfect information, has frequently outpaced the scientific rigor required to ensure ensemble reliability. Here, MMEs refer to approaches that combine targeted predictions from multiple models with the expectation of improving robustness and quantifying predictive uncertainty. Poorly designed MMEs may create a false sense of confidence and lead to suboptimal policy and market decisions. This perspective argues that robust decision-making-relevant MMEs must be grounded on two pillars: (1) rigorous Model Intercomparison Projects (MIPs), which identify inter-model agreement and disagreement, characterize model uncertainties, and evaluate robustness with observationally based benchmarks—MIPs' diagnostic evaluation is so critical that it must be needed to drive MME's decision in model selection and weighting, especially when only a limited number of models available; and (2) co-design by both stakeholders and scientists to ensure that scenarios, metrics and uncertainty requirements provide decision-relevant information. Building upon the past success and lessons from the existing MIPs-MMEs efforts (e.g., climate/Earth system/crop), we derived the theoretical basis for MMEs, addressed their specific challenges in ecosystem modeling, and highlighted proper consideration of model numbers and diversity, risk of model inter-dependence, effective calibration of model parameters, possible overdue of some ecosystem model development, critical roles of open benchmark data across a wide range of conditions, and suggested use of Artificial Intelligence to support MIPs-MMEs. We highlighted the under-recognized opportunity for MIPs and MMEs to drive scientific progress and innovation through identifying better performing models, systematic benchmarking, feedback loops, and targeted model improvement. By following actionable best practice guidelines, MMEs can evolve from ad hoc aggregation of models into a trusted backbone of environmental policy and decision-making.

ecosystem modeling↗

Development and Implementation of CFD-Informed Models for the Advanced Subchannel Code CTF

The research described in this PhD thesis contributes to the development of efficient methods for utilization of high-fidelity models and codes to inform low-fidelity models and codes in the area of nuclear reactor core thermal-hydraulics. The objective is to increase the accuracy of predictions of quantities of interests using high-fidelity CFD models while preserving the efficiency of low-fidelity subchannel core calculations. An original methodology named Physics- based Approach for High-to-Low Model Information has been further developed and tested. The overall physical phenomena and corresponding localized effects, which are introduced by the presence of spacer grids in light water reactor (LWR) cores, are dissected in corresponding four building basic processes, and corresponding models are informed using high-fidelity CFD codes. These models are a spacer grid-directed cross-flow model, a grid-enhanced turbulent mixing model, a heat transfer enhancement model, and a spacer grid pressure loss model. The localized CFD-models are developed and tested using the CFD code STAR-CCM+, and the corresponding global model development and testing in sub-channel formulation is performed in the thermal- hydraulic subchannel code CTF. The improved CTF simulations utilize data-files derived from CFD STAR-CCM+ simulation results covering the spacer grid design desired for inclusion in the CTF calculation. The current implementation of these models is examined and possibilities for improvement and further development are suggested. The validation experimental database is extended by including the OECD/NRC PSBT benchmark data. The outcome is an enhanced accuracy of CTF predictions while preserving the computational efficiency of a low-fidelity subchannel code.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Rossi-alpha Analysis of CURIE Experiment

Critical assembly measurement and operations are crucial to the development of benchmark data to support research into criticality safety, radiation-detection development, and the overall application of nuclear technologies. Accurate nuclear data are needed for accurate predictive simulations, and validation using critical experiments is an important part of the nuclear data pipeline. The accuracy of nuclear data are improved using more robust and targeted measurements. In particular, the intermediate energy range of uranium is of great interest. LANL has successfully performed the Zeus series of experiments on the Comet assembly to investigate the intermediate energy range for HEU with various moderators. A successor to these experiments is the benchmark for the Critical Unresolved Region Integral Experiment (CURIE), designed to be sensitive to the unresolved resonance region (URR). This experiment is designed using polytetrafluoroethylene, more commonly known as Teflon, moderators. The CURIE experiment was successfully conducted at the National Criticality Experiments Research Center (NCERC). The Rossi-alpha method was used to evaluate the propensity of the CURIE configurations to sustain fission chains by estimating the prompt neutron decay constant α. This work evaluates the α at delayed critical using Rossi-alpha for different Teflon moderator thicknesses in the CURIE experiment. These results will help improve understanding of the CURIE benchmark experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Preliminary Design of Critical Experiments Involving Commercially Available B 4 C Neutron Absorber Plates with Low-Enriched UO 2 Fuel

The International Criticality Safety Benchmark Evaluation Project (ICSBEP) is an initiative to provide high-quality benchmark data in a standardized format for criticality safety analysts to use to validate calculational tools and nuclear data. In the last released 2022 version, the ICSBEP handbook contains over 5,000 critical experiment descriptions, results, and associated models. This paper describes the critical configurations proposed and calculations performed as part of the conceptual design phase of Integral Experiment Request (IER) 554 (IER-554). The goal of IER-554 is to add to the benchmark experiments available to the criticality safety community by designing critical experiments that can analyze how adding commercially available Boralcan plates to an assembly of low-enriched UO2 fuel rods affects the effective neutron multiplication factor (k eff ). Boralcan, a neutron absorber product developed by Rio Tinto, is made of B4C in an Al 1100 matrix and is commonly used for criticality suppression in fuel storage pools. In the current version of the ICSBEP handbook, only a few dated critical experiments involve B4C materials, and none involve Boralcan in a thin plate shape. The experiments designed as part of IER-554 are intended to be performed at the Sandia Pulsed Reactor Facility/Critical Experiments (SPRF/CX) apparatus at Sandia National Laboratories. SPRF/CX is a well-characterized assembly considered trustworthy by the benchmarking community because of the numerous high-quality evaluations with very low experimental uncertainties included in the ICSBEP handbook. Figure 1 illustrates the assembly for a particular configuration from LCT-078, one of the published benchmarks in the ICSBEP handbook. The experiments will be moderated and reflected by light water at ambient atmospheric pressure. Before the plates are inserted in the critical assembly, they will be characterized with x-ray computed tomography (XCT) to identify the sizes and distribution of the B 4 C powder particles inside the plates. The preliminary design calculations were performed with SCALE 6.3.0 using the KENO V.a sequence for the criticality calculations, the CE-TSUNAMI-3D sequence for the sensitivity and uncertainty studies, and the ENDF/B-VII.1 Continuous Energy cross section library. All the calculation results presented have 10 pcm statistical uncertainties. A set of critical experiments with Boralcan plates could increase the confidence of the criticality safety community in its modeling methods when using this type of neutron absorber material. Experiments would also help validate k eff calculations, and the industry could use these validations to change the B loading credit limits from the US Nuclear Regulatory Commission standard review plan for dry cask storage of spent nuclear fuel. This paper summarizes only part of the analysis documented in the preliminary design report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗