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TPSAS-NF1676L-13122-DND

An approach for assessing the delamination propagation and growth capabilities in commercial finite element codes was developed and demonstrated for the Virtual Crack Closure Technique (VCCT) implementations in ABAQUS?. The Double Cantilever Beam (DCB) specimen was chosen as an example. First, benchmark results to assess delamination propagation capabilities under static loading were created using models simulating specimens with different delamination lengths. Second, starting from an initially straight front, the delamination was allowed to propagate based on the algorithms implemented in the commercial finite element software. The load-displacement relationship obtained from the propagation analysis results and the benchmark results were compared. Good agreements could be achieved by selecting the appropriate input parameters, which were determined in an iterative procedure. A benchmark case to assess the fatigue growth prediction capabilities was also created. Input control parameters were varied to study the effect on the computed delamination growth. The benchmarks enabled the selection of the appropriate input parameters that yielded good agreements between the results obtained from the automated analysis and the benchmark results. Overall, the results are encouraging but further assessment for mixed-mode delamination is required.

Ronald Krueger↗
NASA NTRS2021

Reduced Complexity Model Intercomparison Project Phase 2: Synthesizing Earth System Knowledge for Probabilistic Climate Projections

Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state-of-the-art knowledge in an internally self-consistent modelling framework are the increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and the structural rigidity of ESMs mean that the full range of uncertainties across multiple domains are difficult to capture with ESMs alone. The tools of choice are instead more computationally efficient reduced complexity models (RCMs), which are structurally flexible and can span the response dynamics across a range of domain-specific models and ESM experiments. Here we present Phase 2 of the Reduced Complexity Model Intercomparison Project (RCMIP Phase 2), the first comprehensive intercomparison of RCMs that are probabilistically calibrated with key benchmark ranges from specialized research communities. Unsurprisingly, but crucially, we find that models which have been constrained to reflect the key benchmarks better reflect the key benchmarks. Under the low-emissions SSP1-1.9 scenario, across the RCMs, median peak warming projections range from 1.3 to 1.7°C (relative to 1850-1900, using an observationally-based historical warming estimate of 0.8°C between 1850-1900 and 1995-2014). Further developing methodologies to constrain these projection uncertainties seems paramount given the international community's goal to contain warming to below 1.5°C above pre-industrial in the long-term. Our findings suggest that users of RCMs should carefully evaluate their RCM, specifically its skill against key benchmarks and consider the need to include projections benchmarks either from ESM results or other assessments to reduce divergence in future projections.

Climate↗
DOE OSTI2023

The Jupiter High-240 Experiment

The Jupiter High-240 experiment was performed in May of 2019 by researchers from Los Alamos National Laboratory (LANL) at the National Criticality Experiments Research Center (NCERC) in the Device Assembly Facility (DAF) located at the Nevada National Security Site (NNSS). This experiment has previously been mentioned briefly in prior publication related to a collaborative effort with the Japan Atomic Energy Agency (JAEA) to assess lead void coefficients of reactivity in uranium- and plutonium-fueled systems with lead. This series of experiments supports JAEA’s research into the development of an accelerator driven transmutation system for spent nuclear fuel. The Jupiter High-240 experiment built upon the previous Jupiter experiment by incorporating plutonium fuel plates with higher 240 Pu content. Efforts to formally benchmark the original Jupiter experiment have continued for inclusion in the benchmark handbook of the International Criticality Safety Benchmark Evaluation Project (ICSBEP). Whereas there is much similarity between the two Jupiter experiments, there is a desire to also evaluate and benchmark this second experiment to further contribute towards the availability of lead-sensitive benchmarks. The components utilized in these two experiments have also been used to perform other subcritical and Rossi-α measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Studying CPU and memory utilization of applications on Fujitsu A64FX and Nvidia Grace Superchip

ARM-based manycore CPU architectures are well-positioned to provide the rising memory throughput requirements of modern data intensive scientific applications in High Performance Computing (HPC). The Fujitsu A64FX CPU platform is based on the ARM v8.2A architecture, and is the processor of the flagship Japanese supercomputer - "Fugaku", which was previously ranked as the #1 supercomputer in the world according to the Top500 list. The Nvidia Grace superchip features 144 Neoverse V2 cores based on the ARMv9 architecture with 4x128b SVE2, providing exceptional computational power. The chip supports up to 480GB of memory, making it ideal for AI, machine learning, and scientific computing workloads. In this paper, we conduct a thorough performance exploration of a variety of parallel bandwidth-sensitive benchmarks and applications compiled with the native Fujitsu compiler on a Fugaku A64FX compute node and ARM (LLVM) Compiler on an NVIDIA Grace superchip compute node, engaging all the computational cores per cluster using OpenMP multithreading (assuming the cores can drive the available bandwidth). Our ultimate goals are to study the resource utilization of scientific applications and benchmarks on A64FX and Grace superchip, considering graph application scenarios ( GAP Benchmark suite) and eleven appli- cation proxies from the Rodinia heterogeneous benchmark suite (considering domains such as Data Mining, Bioinformatics, Fluid Dynamics, Pattern Recognition, etc.). Through exhaustive performance monitoring, we quantify the resource utilization of diverse OpenMP-based HPC applications on both the Fujitsu A64FX and the Nvidia Grace Superchip platforms.

benchmarking, Performance Analysis, High performan↗
DOE OSTI2021

A consensus-based ensemble approach to improve transcriptome assembly

Systems-level analyses, such as differential gene expression analysis, co-expression analysis, and metabolic pathway reconstruction, depend on the accuracy of the transcriptome. Multiple tools exist to perform transcriptome assembly from RNAseq data. However, assembling high quality transcriptomes is still not a trivial problem. This is especially the case for non-model organisms where adequate reference genomes are often not available. Different methods produce different transcriptome models and there is no easy way to determine which are more accurate. Furthermore, having alternative-splicing events exacerbates such difficult assembly problems. While benchmarking transcriptome assemblies is critical, this is also not trivial due to the general lack of true reference transcriptomes. In this study, we first provide a pipeline to generate a set of the simulated benchmark transcriptome and corresponding RNAseq data. Using the simulated benchmarking datasets, we compared the performance of various transcriptome assembly approaches including both de novo and genome-guided methods. The results showed that the assembly performance deteriorates significantly when alternative transcripts (isoforms) exist or for genome-guided methods when the reference is not available from the same genome. To improve the transcriptome assembly performance, leveraging the overlapping predictions between different assemblies, we present a new consensus-based ensemble transcriptome assembly approach, ConSemble. Without using a reference genome, ConSemble using four de novo assemblers achieved an accuracy up to twice as high as any de novo assemblers we compared. When a reference genome is available, ConSemble using four genome-guided assemblies removed many incorrectly assembled contigs with minimal impact on correctly assembled contigs, achieving higher precision and accuracy than individual genome-guided methods. Furthermore, ConSemble using de novo assemblers matched or exceeded the best performing genome-guided assemblers even when the transcriptomes included isoforms. We thus demonstrated that the ConSemble consensus strategy both for de novo and genome-guided assemblers can improve transcriptome assembly. The RNAseq simulation pipeline, the benchmark transcriptome datasets, and the script to perform the ConSemble assembly are all freely available from: http://bioinfolab.unl.edu/emlab/consemble/.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Comprehensive compilations of computation results and validations for neutronics start-up tests at China Experimental Fast Reactor

This paper compiles and analyzes refined results of the coordinated research project (CRP) on Neutronics Benchmark of China Experimental Fast Reactor (CEFR) Start-Up Tests conducted by the International Atomic Energy Agency (IAEA) since 2018. Twenty-eight research organizations participated with various code systems. The China Institute of Atomic Energy (CIAE) provided the benchmark specifications and participants conducted the benchmark through blind and refined phases. This paper presents the benchmark results on six experimental measurements, criticality, control rod worth, temperature reactivity coefficients, sodium void worth, assembly swap reactivities, and foil activations. Except for a few outlier results, the simulation results show good agreement with the measured data within 1-σ experiment uncertainties. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Application of the Rossi-alpha method to simulations of HEU and organic scintillators

The International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook contains thousands of high-quality benchmark measurements that include detailed descriptions of experiment designs and exhaustive accounting of uncertainties. These benchmarks are used extensively by the criticality safety and nuclear data communities. A subcritical benchmark involving bare, highly enriched uranium (HEU) has yet to be accepted to the handbook. The Measurement of Uranium Subcritical and Critical (MUSiC) was proposed to address this gap. MUSiC will be performed at the National Criticality Experiments Research Center (NCERC) and will leverage bare HEU hemisphere shells that can be assembled in a variety of configurations. The measurement has the following key benefits: it will be the first set of fast, subcritical measurements of HEU to be submitted to ICSBEP; ten configurations will be measured spanning from nearly no multiplication to critical (e.g., it is a measurement of similar systems with different re activities); measurements of an all-HEU system will be of value for nuclear data validation, providing results that assist in determining biases in both measurements and simulations. A variety of detector systems will be used including a Neutron Multiplicity Array Detector (NoMAD) system (similar to the MC-15), four small volume 0.635 cm (#8960;) × 7.59 cm 3He detectors (ideal for measuring prompt neutron decay constants due to their fast recovery speed), and an array of eight 5.08 cm (#8960;) × 5.08 cm EJ-309 organic scintillator detectors. The focus of this work is the simulation of the subcritical MUSiC configurations including the EJ-309 detectors and the application of the Rossi-α method. The EJ-309 organic scintillator detector array is a new detection system that will be deployed at NCERC. Organic scintillators are ideal for measurements of fast, subcritical systems due to their short time response on the order of nanoseconds.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Expanding standards in viromics: in silico evaluation of dsDNA viral genome identification, classification, and auxiliary metabolic gene curation

Viruses influence global patterns of microbial diversity and nutrient cycles. Though viral metagenomics (viromics), specifically targeting dsDNA viruses, has been critical for revealing viral roles across diverse ecosystems, its analyses differ in many ways from those used for microbes. To date, viromics benchmarking has covered read pre-processing, assembly, relative abundance, read mapping thresholds and diversity estimation, but other steps would benefit from benchmarking and standardization. Here we use in silico-generated datasets and an extensive literature survey to evaluate and highlight how dataset composition (i.e., viromes vs bulk metagenomes) and assembly fragmentation impact (i) viral contig identification tool, (ii) virus taxonomic classification, and (iii) identification and curation of auxiliary metabolic genes (AMGs). The in silico benchmarking of five commonly used virus identification tools show that gene-content-based tools consistently performed well for long (≥3 kbp) contigs, while k -mer- and blast-based tools were uniquely able to detect viruses from short (≤3 kbp) contigs. Notably, however, the performance increase of k -mer- and blast-based tools for short contigs was obtained at the cost of increased false positives (sometimes up to ~5% for virome and ~75% bulk samples), particularly when eukaryotic or mobile genetic element sequences were included in the test datasets. Furthermore, for viral classification, variously sized genome fragments were assessed using gene-sharing network analytics to quantify drop-offs in taxonomic assignments, which revealed correct assignations ranging from ~95% (whole genomes) down to ~80% (3 kbp sized genome fragments). A similar trend was also observed for other viral classification tools such as VPF-class, ViPTree and VIRIDIC, suggesting that caution is warranted when classifying short genome fragments and not full genomes. Finally, we highlight how fragmented assemblies can lead to erroneous identification of AMGs and outline a best-practices workflow to curate candidate AMGs in viral genomes assembled from metagenomes. Together, these benchmarking experiments and annotation guidelines should aid researchers seeking to best detect, classify, and characterize the myriad viruses ‘hidden’ in diverse sequence datasets.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Bayesian estimation of cross-section and errors of experiment and calculation for accurate prediction of neutronic characteristics

In some experiments, there might be a correlation of experimental errors such as an error caused by fabrication. The correlation of calculation errors also might exist among analyses of experiments. In the present study, considering these correlations, the cross-section and errors of experiment and calculation are adjusted for the accurate prediction of neutronic characteristics. The adjustment method is derived based on Bayesian theory. The 'a posteriori' distributions of cross-section and errors of experiment and calculation are obtained by the derivation. The case study is performed by using the benchmarks of light-water moderated experiments reported in ICSBEP. The error from fuel rod fabrication and measurement are included in the experiment error, and the error from the simplification of the benchmark model is included in the calculation error. Since these errors have a positive correlation among the benchmarks, the prediction accuracy is expected to be improved by considering these correlations. For the sensitivity analysis of the correlation among benchmarks, the correlation coefficient of experiment error and that of calculation error is assumed from 0.0 to 0.9. The results indicate that the prediction accuracy of the multiplication factor can be improved by increasing the correlation coefficient of experiment error and that of calculation error. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Contribution to the IRPHEP handbook since Physor 2018

The Organisation for Economic Co-operation and Development (OECD), the Nuclear Energy Agency (NEA), the International Reactor Physics Experiment Evaluation Project (IRPhEP) continue to preserve and evaluate integral reactor physics experiment data to support nuclear energy and technology needs. International contributions are collated within the International Handbook of Evaluated Reactor Physics Benchmark Experiments (IRPhEP Handbook). The 2021 edition of the IRPhEP Handbook now contains data for 57 unique nuclear facilities with benchmark specifications for 169 experimental series, of which four are draft evaluations. Distributed with the IRPhEP Handbook and available online is the IRPhEP Database and Analysis Tool (IDAT), allowing users to search and interrogate the data. Since Physor 2018, there have been 11 minor revisions to existing benchmark evaluations, significant revisions to two evaluations, one draft evaluation, and nine new evaluations. The corona virus pandemic has delayed international activities supporting the production of additional content for the IRPhEP Handbook. However, efforts continue for numerous endeavors to complete new reactor physics benchmark evaluations to support current and future validation needs. Those interested in serving as evaluators and/or reviewers are strongly encouraged to participate. This paper provides a summary of IRPhEP content and activities since Physor 2018. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Development of an Improved RELAP5-3D Model for the High Temperature Test Facility

High-temperature gas-cooled reactors (HTGRs) are rapidly approaching deployment. Confidence in transient analysis of these systems requires modeling and simulation tools that have been validated against data relevant to HTGR conditions. The High Temperature Test Facility (HTTF) is an integral effects thermal hydraulics test facility for prismatic HTGRs. In spring and summer of 2019, HTTF was used for a series of experiments that now serve as the basis for the Organization of Economic Cooperation and Development / Nuclear Energy Agency Thermal Hydraulic Code Validation Benchmark for High Temperature Gas-Cooled Reactors using HTTF Data (HTGR T/H Benchmark). Previous analyses as part of the HTGR T/H benchmark used a RELAP5-3D model developed at Idaho National Laboratory (INL) and demonstrated an ability to reproduce trends in the measured data but difficulties reproducing experimental values within their uncertainty. These difficulties were largely attributed to assumptions made during the development of the initial RELAP5-3D model, which predated the HTTF experiments. A significant cause of difficulty reproducing the measured temperatures may be the radial nodalization of the previous RELAP5-3D model. In this paper, we present a new RELAP5-3D model of HTTF with finer radial nodalization built to assess the impact of radial heat transfer. We describe the new model and compare it against the old one at full-power steady state and for the pressurized conduction cooldown (PCC) transient. These analyses are based on the code-to-code comparison exercise for the PCC problem of the HTGR T/H benchmark. We compare maximum block temperature as the primary figure of merit and include discussion on intracore natural circulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Investigating sol–gel matrix loading capacity toward producing surrogate nuclear explosive debris with realistic composition

Post detonation nuclear forensic materials which resemble the size, color, elemental composition, and radionuclide content of real nuclear debris would be valuable for developing and validating new nuclear forensic techniques. As nuclear fallout types vary significantly, the ability to tailor each of these parameters accurately is desired to produce materials capable of testing analytical methods under a wide array of forensic scenarios. Sol–gel synthesis techniques can provide tunability of size, shape and composition for producing a wide variety of solid nuclear forensics benchmarking materials. Further, the sol–gel process consists of forming a metal oxide material, often silica, through polymerization of a metal-alkoxy precursor. In this work, we characterize the ability to load sol–gel particles with secondary elemental components such as iron, aluminum, and calcium toward producing benchmarking materials approximating the elemental composition of historic nuclear debris from the Nevada National Security Site. We also demonstrate quantitative radionuclide encapsulation toward producing benchmarking materials with controllable radionuclide content. Finally, we employ these techniques to produce nuclear debris benchmarking materials with controllable elemental matrix composition and radionuclide content and compare these samples with the composition of a historic fallout sample previously reported from the Nevada National Security Site.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Two-step neutronics calculations with Shift and Griffin for advanced reactor systems

This research develops the initial coupling of the Shift Monte Carlo (MC) code and the Griffin reactor physics code for reactor analysis of non–light-water reactor systems. The novelty of this work is twofold. It is the first application of Shift to produce the multigroup cross sections needed for Griffin as applied to a non–light-water reactor system; and, the first investigation and analysis of characteristics of the Empire microreactor benchmark that should be considered for steady state and transient reactor physics calculations. This application uses the previously developed two-step neutronics analysis workflow to demonstrate this initial coupling. Here, we outline the two-step neutronics analysis workflow in which the Shift MC code is used to generate the multigroup cross sections and fluxes needed by the Griffin deterministic solver. Details on how these multigroup cross sections are generated using MC tallies are given, as well as the practicalities and limitations of the two-step neutronics workflow. The Empire microreactor benchmark was used to investigate and validate this coupling. Results using this benchmark show good agreement between Griffin calculations using Serpent-generated cross sections and Shift-generated cross sections. Analysis of the characteristics of this Empire benchmark show larger eigenvalue differences between heterogeneous and pin–homogenized solutions compared to those of traditional light-water reactor (LWR) designs, thus requiring super homogenization factor corrections for accurate eigenvalue and power distribution predictions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Resolved resonance region evaluations of n+ 206,207,208 Pb for fast spectrum applications

Resolved resonance region evaluations of the major isotopes of natural lead, 206 Pb, 207 Pb, 208 Pb, have been per formed to support the development of Generation IV reactors. In this study, validation of nuclear data for lead fast reactors was performed with simulations of shielding benchmarks, integral critical benchmarks, and quasi-differential scattering measurements. Sensitivity analyses of these systems showed that elastic scattering reactions above 100 keV were the dominant reactions driving system performance. The resolved resonance regions (RRRs) of the lead isotopes extend past 100 keV, making the RRR an ideal starting point to evaluate lead cross sections. Since the R-matrix requires knowledge of bound, distant, and observed resonances, it was necessary to evaluate from 10 -5 eV up to the respective limit of the RRR. The 208 Pb RRR evaluation was extended to 1.5 MeV in order to obtain resonance parameters used to calculate new elastic scattering angular distributions up to 1.5 MeV. Resonance parameter uncertainties and covariance were generated using the R-matrix code SAMMY. The new RRR parameters show a direct improvement to the scattering kernel below 1.5 MeV which in turn greatly improves fast critical experiments over ENDF/B-VIII.0.

206Pb↗
DOE OSTI2026

Intercomparison of flood inundation models across land use types and hydrological flood stages

Flood Inundation Mapping (FIM) model selection is a key operational decision because accurate, rapid mapping underpins early warning and resource allocation. FIM performance is context-dependent and can vary with hydrograph phase, land-use/land-cover (LULC), and the evaluation benchmark. Intercomparison studies typically assess a single near-peak snapshot against one reference dataset. Here, we provide a context-stratified intercomparison across (i) multiple hydrograph phases, (ii) LULC classes, and (iii) benchmark types, for five FIM approaches spanning a wide range of physical complexity and operational cost (TRITON, LISFLOOD-FP, HEC-RAS 2D, ARC-Curve2Flood, and OWP HAND-FIM). We use the Hurricane Matthew flood (2016) in the Neuse River Basin, North Carolina, USA, as a case study. Using high-resolution remote sensing-derived flood inundation maps, hand-labeled points, and building footprints, we assess model skill across two rising and two falling hydrograph limbs and across major LULC types. Results show that model rankings shift systematically across contexts: LISFLOOD-FP ranks highest in three of four flood phases, while TRITON leads during one rising limb phase; LISFLOOD-FP performs best in vegetated areas, whereas HEC-RAS improves relative performance in agricultural and urban areas; and benchmark choice influences conclusions, with LISFLOOD-FP performing best for flooded-building detection in the late falling limb, while TRITON ranks highest against hand-labeled points. We also report representative wall-clock runtimes for each workflow to provide use-case context for operational feasibility. Together, these results offer transferable guidance for model selection and for designing large-scale, benchmark-aware FIM intercomparison studies.

Nikrou, Parvaneh [University of Alabama]↗
DOE OSTI2020

IRDFF-II: A New Neutron Metrology Library

High quality nuclear data is the most fundamental underpinning for all neutron metrology applications. This paper describes the release of version II of the International Reactor Dosimetry and Fusion File (IRDFF-II) that contains a consistent set of nuclear data for fission and fusion neutron metrology applications up to 60 MeV neutron energy. The library is intended to support: a) applications in research reactors; b) safety and regulatory applications in the nuclear power generation in commercial fission reactors; and c) material damage studies in support of the research and development of advanced fusion concepts. The paper describes the contents of the library, documents the thorough verification process used in its preparation, and provides an extensive set of validation data gathered from a wide range of neutron benchmark fields. The new IRDFF-II library includes 119 metrology reactions, four cover material reactions to support self-shielding corrections, five metrology metrics used by the dosimetry community, and cumulative fission products yields for seven fission products in three different neutron energy regions. In support of characterizing the measurement of the residual nuclei from the dosimetry reactions and the fission product decay modes, the present document lists the recommended decay data, particle emission energies and probabilities for 68 activation products. It also includes neutron spectral characterization data for 29 neutron benchmark fields for the validation of the library contents. Additional six reference fields were assessed (four from plutonium critical assemblies, two measured fields for thermal-neutron induced fission on 233U and 239Pu targets) but not used for validation due to systematic discrepancies in C/E reaction rate values or lack of reaction-rate experimental data. Another ten analytical functions are included that can be useful for calculating average cross sections, average energy, thermal spectrum average cross sections and resonance integrals. The IRDFF-II library and comprehensive documentation is available online at www-nds.iaea.org/IRDFF/. Evaluated cross sections can be compared with experimental data and other evaluations at www-nds.iaea.org/exfor/endf.htm. The new library is expected to become the international reference in neutron metrology for multiple applications.

IAEA IRDFF↗
DOE OSTI2020

Enhancing nuclear data validation analysis by using machine learning

In this work, we demonstrate how machine learning (ML) techniques can be used as an auxiliary tool for nuclear data validation analysis. The output of the ML analysis can inform evaluators and validators on the quality, or lack thereof, of specific nuclear data and benchmark experiments with respect to simulating these experimental benchmark values. To this end, measured and simulated effective neutron multiplication factors, k eff , of 875 selected ICSBEP critical assemblies and the latter's sensitivities with respect to nuclear data as well as benchmarks' features (e.g., material nuclide, core geometry) are used as input for a random forest (RF) regression model. The RF is used to encode the complex inter-dependencies between thousands of nuclear data features (i.e., sensitivity profiles and aspects describing the measurements) and 875 simulated and experimental k eff values in order to understand what nuclear data features are most informative for predicting bias. The complexity of relationships and high-dimensional space is difficult-to-impossible to search fully using simply expert judgment. As a first proof-of-concept—step, it is demonstrated that this technique is able to correctly trace large discrepancies between simulated and experimental k eff back to fabricated shortcomings in nuclear data that were perturbed to simulated k eff values. In a second, real-case scenario, step, the RF algorithm is used to validate the ENDF/B-VIII.0 library in comparison to ENDF/B-VII.1 nuclear data. One case is showcased where the chosen ML algorithms highlighted nuclear data (the 19 F(n,inl) cross section from 0.4–0.9 MeV) that are shown to be problematic by comparing them to associated differential experimental data and nuclear data from other libraries. In addition to that, it is shown that the RF results point towards poor benchmark experiments and associated underestimated uncertainties (e.g., the PU-SOL-THERM-028 series). However, using the RF algorithm for validating nuclear data with respect to k eff is currently limited to pinpointing groups of questionable nuclear data due to the inherent correlations between features introduced by the nuclear data themselves and how k eff is simulated. Due to this, we recommend that the ML methods presented be used to augment—rather than replace—the expert knowledge of evaluators and validators.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

Investigation of thermal hydraulic behavior of the High Temperature Test Facility's lower plenum via large eddy simulation

A high-fidelity computational fluid dynamics (CFD) analysis was performed using the Large Eddy Simulation (LES) model for the lower plenum of the High–Temperature Test Facility (HTTF), a ¼ scale test facility of the modular high temperature gas-cooled reactor (MHTGR) managed by Oregon State University. In most next–generation nuclear reactors, thermal stress due to thermal striping is one of the risks to be curiously considered. This is also true for HTGRs, especially since the exhaust helium gas temperature is high. In order to evaluate these risks and performance, organizations in the United States led by the OECD NEA are conducting a thermal hydraulic code benchmark for HTGR, and the test facility used for this benchmark is HTTF. HTTF can perform experiments in both normal and accident situations and provide high-quality experimental data. However, it is difficult to provide sufficient data for benchmarking through experiments, and there is a problem with the reliability of CFD analysis results based on Reynolds–averaged Navier–Stokes to analyze thermal hydraulic behavior without verification. To solve this problem, high-fidelity 3-D CFD analysis was performed using the LES model for HTTF. It was also verified that the LES model can properly simulate this jet mixing phenomenon via a unit cell test that provides experimental information. As a result of CFD analysis, the lower the dependency of the sub-grid scale model, the closer to the actual analysis result. In the case of unit cell test CFD analysis and HTTF CFD analysis, the volume-averaged sub-grid scale model dependency was calculated to be 13.0% and 9.16%, respectively. As a result of HTTF analysis, quantitative data of the fluid inside the HTTF lower plenum was provided in this paper. As a result of qualitative analysis, the temperature was highest at the center of the lower plenum, while the temperature fluctuation was highest near the edge of the lower plenum wall. The power spectral density of temperature was analyzed via fast Fourier transform (FFT) for specific points on the center and side of the lower plenum. FFT results did not reveal specific frequency-dominant temperature fluctuations in the center part. It was confirmed that the temperature power spectral density (PSD) at the top increased from the center to the wake. The vortex was visualized using the well-known scalar Q-criterion, and as a result, the closer to the outlet duct, the greater the influence of the mainstream, so that the inflow jet vortex was dissipated and mixed at the top of the lower plenum. Additionally, FFT analysis was performed on the support structure near the corner of the lower plenum with large temperature fluctuations, and as a result, it was confirmed that the temperature fluctuation of the flow did not have a significant effect near the corner wall. In addition, the vortices generated from the lower plenum to the outlet duct were identified in this paper. It is considered that the quantitative and qualitative results presented in this paper will serve as reference data for the benchmark.

97 MATHEMATICS AND COMPUTING↗