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At least 973 records · Page 54

NIMROD Development AND Applications for Advanced Simulations of Tokamak Plasmas

Magnetic fusion experiments have the largest gradients in the world that are in steady state. These gradients lead to instabilities, and thus, most of plasma theory over the past four decades have been devoted to the development of instability theory and their use in interpreting plasma results. Instabilities in tokamaks lead to 3 different phenomenological outcomes: coherent saturation, turbulent saturation, and sudden relaxation (which may include disruptions). For long-wavelength instabilities, the NIMROD extended MHD code has emerged as an important tool for understanding tokamak instabilities. Because of the long history of NIMROD, a new version of it has been started at Tech-X to be able to address multi-species capabilities as well as exploit modern GPU systems. The new version builds on the previous version and improves the workflow by enabling new equilibria from experiments to be resolved. The fundamental formulation of the equations underlying NIMROD has also been explored in multiples ways. First, understanding instabilities in tokamaks through numerical methods is aided by being able to understand the rich history of analytic studies. A paper was published which aid in understanding the literature by simplifying some of the analytic machinery inherent in these studies. Extended MHD, like gyrokinetics, are quasineutral models. From a theoretical point of view, plasma quasineutrality approximation is best understood as the same as the magneto-quasistatic approximation of the Maxwell equations. Finally, the standard model of tokamak theory is that of instability theory. A simple dynamical systems model has been developed to better illustrate the strengths and weaknesses of this model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Neutronics and Thermo-Fluids Simulation of Generic Pebble-Bed Fluoride-Salt-Cooled High-Temperature Reactor

The fluoride-salt-cooled high-temperature reactor (FHR) is one of the advanced reactors that has been attracting considerable interest from both the research community and the nuclear industry. To help facilitate the nuclear community's familiarity with the FHR, Kairos Power has developed a generic FHR (gFHR) benchmark. In the research performed here, this benchmark was used to assess innovative modeling methods that combine stochastic and deterministic computer codes to perform the design and analysis of the gFHR. Further, the Monte Carlo code Serpent 2 was used to generate few-group cross sections that were then used in the neutron diffusion and thermal-fluids code AGREE to perform full-core neutronics and thermal-fluids steady-state and transient core analysis. The Argonne National Laboratory code SAM was then used to model the gFHR system and to simulate the load-follow operation of the gFHR.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The Monarch Initiative in 2024: an analytic platform integrating phenotypes, genes and diseases across species

Abstract Bridging the gap between genetic variations, environmental determinants, and phenotypic outcomes is critical for supporting clinical diagnosis and understanding mechanisms of diseases. It requires integrating open data at a global scale. The Monarch Initiative advances these goals by developing open ontologies, semantic data models, and knowledge graphs for translational research. The Monarch App is an integrated platform combining data about genes, phenotypes, and diseases across species. Monarch's APIs enable access to carefully curated datasets and advanced analysis tools that support the understanding and diagnosis of disease for diverse applications such as variant prioritization, deep phenotyping, and patient profile-matching. We have migrated our system into a scalable, cloud-based infrastructure; simplified Monarch's data ingestion and knowledge graph integration systems; enhanced data mapping and integration standards; and developed a new user interface with novel search and graph navigation features. Furthermore, we advanced Monarch's analytic tools by developing a customized plugin for OpenAI’s ChatGPT to increase the reliability of its responses about phenotypic data, allowing us to interrogate the knowledge in the Monarch graph using state-of-the-art Large Language Models. The resources of the Monarch Initiative can be found at monarchinitiative.org and its corresponding code repository at github.com/monarch-initiative/monarch-app.

60 APPLIED LIFE SCIENCES↗

RAPIDS: Reconciling Availability, Accuracy, and Performance in Managing Geo-Distributed Scientific Data

In modern science, big data plays an increasingly important role. Many scientific applications, such as running simulations on supercomputers or conducting experiments on advanced instruments, produce huge amount of data at unprecedented speed. Analyzing and understanding such big data is the key for scientists to make scientific breakthroughs. However, data might become unavailable for scientists to access when outages or maintenance of the storage system occur, which severely hinders scientific discovery. To improve the data availability, data duplication and erasure coding (EC) are often used. But as the scientific data gets larger, using these two methods can cause considerable storage and network overhead.In this paper, we propose RAPIDS, a hybrid approach that combines the multigrid-based error-bounded lossy compression with erasure coding, to significantly reduce the storage and network overhead required for maintaining high data availability. Our experiments show that RAPIDS reduces the storage overhead by up to 7.5x and network overhead by up to 3x to achieve the same level of availability compared to the regular EC method. We improve RAPIDS by building two models to optimize the fault tolerance configurations and data gathering strategy. We demonstrate that RAPIDS significantly improves performance when running on many CPU cores in parallel or on GPUs.

Wan, Lipeng↗

COMPILE: a GWAS computational pipeline for gene discovery in complex genomes

Abstract Background Genome-Wide Association Studies (GWAS) are used to identify genes and alleles that contribute to quantitative traits in large and genetically diverse populations. However, traits with complex genetic architectures create an enormous computational load for discovery of candidate genes with acceptable statistical certainty. We developed a streamlined computational pipeline for GWAS (COMPILE) to accelerate identification and annotation of candidate maize genes associated with a quantitative trait, and then matches maize genes to their closest rice and Arabidopsis homologs by sequence similarity. Results COMPILE executed GWAS using a Mixed Linear Model that incorporated, without compression, recent advancements in population structure control, then linked significant Quantitative Trait Loci (QTL) to candidate genes and RNA regulatory elements contained in any genome. COMPILE was validated using published data to identify QTL associated with the traits of α-tocopherol biosynthesis and flowering time, and identified published candidate genes as well as additional genes and non-coding RNAs. We then applied COMPILE to 274 genotypes of the maize Goodman Association Panel to identify candidate loci contributing to resistance of maize stems to penetration by larvae of the European Corn Borer ( Ostrinia nubilalis ). Candidate genes included those that encode a gene of unknown function, WRKY and MYB-like transcriptional factors, receptor-kinase signaling, riboflavin synthesis, nucleotide-sugar interconversion, and prolyl hydroxylation. Expression of the gene of unknown function has been associated with pathogen stress in maize and in rice homologs closest in sequence identity. Conclusions The relative speed of data analysis using COMPILE allowed comparison of population size and compression. Limitations in population size and diversity are major constraints for a trait and are not overcome by increasing marker density. COMPILE is customizable and is readily adaptable for application to species with robust genomic and proteome databases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

BEPAM code and results for the publication 'Supplementing Biofuel Mandates with a Carbon Mitigation Policy Can Lead to Water Quality Co-benefits'

The dataset consists of: (1) The replication codes and data for the BEPAM model are contained in the "BEPAM_Supplementary Environment Policy Analysis.zip" (2) Simulation results from the BEPAM model are contained in "ModelOutputs.zip" under the "BEPAM_Supplementary Environment Policy Analysis.zip"

Fan, Xinxin [Center for Advanced Bioenergy and Bio↗

Effect of Impurity Atoms on Thermonuclear Yield

The presence of impurity atoms in an inertial confinement fusion (ICF) implosion can greatly affect the burning of the thermonuclear fuel. This is a serious concern for attaining ignition as high atomic number atoms, such as carbon, can mix into the hot spot and reach the deuterium–tritium (DT) fuel, absorb energy from the implosion, and radiate away that energy. The temperature of the DT fuel drops and reduces the reactivity of the fuel resulting in lower thermonuclear yield. Fuel impurities can also be a useful diagnostic as when higher-Z atoms, such as Ar, Kr, and Xe, are purposefully mixed into the fuel. From the spectra emitted by these atoms, the temperature and density of the fuel can be deduced. The long history of using such tracer atoms by the national ICF program shows the great advances in experimental technique, diagnostic instruments, and atomic-physics modeling over the past 50 years. A particular set of experiments, the “High-Z” campaign, is reviewed in depth as this was the most systematic study of tracer element composition and quantity ever reported. Difficulties in interpreting the results of those experiments due to the limited code capabilities at that time are discussed. A main concern for the High-Z campaign was the then current state of non-Local Thermodynamic Equilibrium (nLTE) atomic physics models. The present state of nLTE modeling and its implementation in Los Alamos’s multi-physics codes is discussed in this report. To further the understanding of the complex interaction of high-Z atoms in the gas, a survey of relevant existing experimental platforms at the National Ignition Facility (NIF) and the Omega Laser Facility are presented along with the current state of pertinent diagnostics at NIF and Omega. This review concludes with a discussion of the trade-off available between temperature and volume of the imploded ICF capsule with the goal of maximizing the total yield.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

TEAM project review, year 1

This note summarizes our research activities within the TEAM project between October 2019 and November 2020, funded by the ASCR Advanced Research in Quantum Computing program. Three research efforts have begun during the review period. The first effort, resulting in the JuQBox software, implemented a novel algorithm for optimal control in closed quantum systems based on symplectic time integration and exact calculations of the gradient of the discretized objective function. In our second effort, resulting in a code called Quandary, we consider the optimal control problem for open quantum systems. Here the evolution of the quantum system is modeled by the Lindblad master equation. In this code, we are considering both the realization of quantum gates as well as the optimal reset problem in which a general mixed quantum state is driven towards its ground state. In our third research effort we have begun the development of computational software for what we call Lindblad learning, i.e. the process of characterizing the equations governing our quantum computing hardware.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Guided Resilience Self Assessment Application

Reliable electricity access is vital for everything from hospitals to national security. When grid disturbances occur, it is crucial to minimize the amount of time it takes to recover. Grid resiliency considers both the preparation for and recovery from high-impact low-frequency disturbances (HILF) such as weather events and cyber attacks. The Department of Energy (DOE) Wind Energy Technologies Office (WETO) funds the multi-laboratory Microgrids, Infrastructure Resilience, and Advanced Control Launchpad (MIRACL) project to investigate technologies to support and grow distributed wind. Researchers at Idaho National Laboratory (INL) contribute to resilience and cybersecurity efforts for the project, and have produced a resilience framework to evaluate system resilience based on individual system specifications. In order to make this framework easy for anyone to apply, I have coded a web application that allows users to input their power system qualities, goals, and perceived risks and then receive suggestions on how to improve their grid resiliency. The web application follows the seven steps in the planning stage of the framework process, allowing the user to input information about their grid and select from common goals, metrics, and hazards, as well as add their own. The application currently provides information about how to complete each step, requiring minimal prior knowledge of the framework. Future work for this application will include allowing the user to submit line drawings of their system and incorporate modeling tools so that the hazard simulations of applying the framework is completed for the user.

97 MATHEMATICS AND COMPUTING↗

Experiment design for the neutron irradiation of $\mathrm{PM-HIP}$ alloys for nuclear reactors

Here, this article describes the design of an Advanced Test Reactor (ATR) drop-in neutron irradiation experiment aiming to directly compare the performance of nuclear structural alloys fabricated by powder metallurgy with hot isostatic pressing (PM-HIP) against conventional casting or forging. There is growing interest in PM-HIP alloys for nuclear applications because of their microstructural uniformity, superior mechanical properties, and reduced dependence on welding and machining, compared to cast/forged alloys. Nuclear code-qualification of PM-HIP alloys requires neutron irradiation testing to demonstrate performance under relevant conditions. In this experiment, six nuclear structural alloys were irradiated: Ni-based alloys 625 and 690, Grade 91 ferritic steel, SA508 pressure vessel steel, and 304L and 316L austenitic stainless steels. The experiment is assembled into seven capsules in four test trains and irradiated in three ATR inboard A positions. Both the PM-HIP and cast/forged versions of each alloy were irradiated under nearly identical conditions for comparative purposes, to target doses of 1 ± 0.2 and 3 ± 0.2 dpa at temperatures of 300 ± 50 °C and 400 ± 50 °C. A thorough description of the experiment design and thermal, structural and neutronic analyses performed to ensure the targeted irradiation conditions are met is provided. Specimens were configured as small disks, compact tension specimens and tensile bars to facilitate post-irradiation examination (PIE) that will include mechanical testing, microstructure characterization, and fracture toughness testing. Given the considerations for ASTM standardized mechanical testing, comparative fluence and temperature across specimen pairs, and comprehensive PIE planning herein, this work serves as a template for future nuclear materials qualification experiment designs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

RAVEN User Manual

RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7, currently under development at the Idaho National Laboratory (INL). Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism includes providing Application Programming Interfaces (APIs). These APIs are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable of investigating the system response, and investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused to- ward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The development of RAVEN has started in 2012, when, within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the need to provide a modern risk evaluation framework became stronger. RAVEN principal assignment is to provide the necessary software and algorithms in order to employ the concept developed by the Risk Informed Safety Margin Characterization (RISMC) program. RISMC is one of the pathways defined within the Light Water Reactor Sustainability (LWRS) program. In the RISMC approach, the goal is not just the individuation of the frequency of an event potentially leading to a system failure, but the closeness (or not) to key safety-related events. Hence, the approach is interested in identifying and increasing the safety margins related to those events. A safety margin is a numerical value quantifying the probability that a safety metric (e.g. for an important process such as peak pressure in a pipe) is exceeded under certain conditions. The initial development of RAVEN has been focused on providing dynamic risk assessment capability to RELAP-7, currently under development at the INL and, likely, future replacement of the RELAP5-3D code. Most the capabilities that have been implemented having RELAP-7 as principal focus are easily deployable for other system codes. For this reason, several side activates are currently ongoing for coupling RAVEN with soft- ware such as RELAP5-3D, etc. The aim of this document is the explanation of the input requirements, focalizing on the input structure.

97 MATHEMATICS AND COMPUTING↗

Carbon capture, utilization, and storage hub development on the Gulf Coast

Abstract The Gulf Coast of the United States hosts diverse power generation, refining, and petrochemical processing facilities, resulting in the nation's largest volumetric concentration of industrial CO 2 emissions, rivaled only by the Ohio River Valley. These emissions sources are concentrated in specific industrial clusters that allow combining emissions streams to achieve economies of scale. The region is currently undergoing globally significant industrial expansion and investment as a result of abundant and inexpensive regional unconventional natural gas availability, and is a growing exporter of liquefied natural gas (LNG). Opportunities to integrate CO 2 emission management within the diverse energy chains in the region are volumetrically significant and include both concentrated and dilute sources. Significant examples of capture, transport, and storage exist. Offshore storage is particularly attractive, as it provides simplified land leasing models (single governmental land owner), proven reservoir quality, and presents fewer risks to both protected groundwater and populated areas. Projects can now take advantage of recently expanded opportunities under section 45Q of the Internal Revenue Service tax code. The region continues to evolve as an active carbon‐handling hub, and is uniquely suited to justify additional investment in carbon capture, utilization, and storage (CCUS) technologies via a large‐scale integrated project development. Continued development of integrated projects will allow the region to continue to grow economically within its strong fossil‐fuel handling competence focus while advancing low‐carbon energy technologies that maintain globally competitiveness. © 2021 The Authors. Greenhouse Gases: Science and Technology published by Society of Chemical Industry and John Wiley & Sons Ltd.

45Q↗

Effect of spacer grids on high-burnup fuel fragmentation, relocation, and dispersal

Increasing the fuel burnup limit in light-water reactors to improve fuel cycle economics requires a strong technical foundation. Experimental observations from the Halden and Studsvik programs have revealed severe fuel fragmentation during loss-of-coolant accident (LOCA) conditions, highlighting the need for additional technical evaluation. Consequently, further LOCA test data are needed to complement existing findings and improve the understanding of fuel fragmentation, relocation, and dispersal (FFRD) behavior. Oak Ridge National Laboratory’s Severe Accident Test Station has played a significant role in advancing the understanding of high-burnup fuel fragmentation, relocation, and dispersal phenomena. One remaining gap in the available experimental database is the effect of fuel assembly structural features on cladding deformation behavior during a LOCA, and more specifically, their impact on the fuel’s ability to fragment, relocate, and disperse. Recent analyses using the BISON fuel performance code suggest that cladding deformation near grid spacers will remain below the 3% threshold that has been reported in the NRC Research Information Letter, indicating that the cladding could remain mechanically constrained during the LOCA event. This paper builds upon the BISON analyses to design and conduct a series of out-of-cell tests aimed at further evaluating cladding deformation in and around grid spacers. In addition, these tests were used to assess local cladding temperature conditions and compare them against analytical predictions in order to better replicate expected in-reactor behavior. Finally, an in-cell high-burnup LOCA test was designed and performed to evaluate the effects of a grid spacer, or cladding restraint, on fuel fragmentation, relocation, and dispersal susceptibility. The high-burnup test results differed from those of historical LOCA experiments, with a recorded rupture temperature of 861°C. Two ballooned regions and corresponding rupture openings were observed, with rupture widths of approximately 0.64 mm for both ruptures and rupture lengths of 4.8 mm and 5.6 mm, respectively.

Capps, Nathan [ORNL]↗

Comparison of private flux region instability in conventional and super-X divertor configurations

Understanding turbulence in the divertor leg of tokamaks is essential to predicting the heat deposition profile on the divertor plate. This in turn is important for evaluating advanced divertor configurations, such as the super-X divertor. Within the divertor region, the private flux region is of interest because it is relatively unaffected by turbulence extending from the outboard midplane, so instabilities in this region could have a particularly pronounced effect on transport. These instabilities are modeled using the Arbitrary Topology Equation Reader (ArbiTER) eigenvalue code. Eigenmodes are examined further by comparing physics models to determine the fundamental mechanisms behind their formation, and quantifying the effect of individual terms. This analysis is conducted on both conventional and super-X divertors to compare these effects. Here, the resulting analysis reveals the presence of a geodesic curvature driven instability that is significantly more pronounced in the super-X configuration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Quantifying and Zoning Urban Heat Island Effects Using Unsupervised Machine Learning

This work explores the Urban Heat Island (UHI) effects in Maricopa County, Arizona, employing a simulation-based approach that combines large-scale building energy modeling with advanced spatial analysis. Utilizing the Automatic Building Energy Modeling (AutoBEM) software suite, we simulated the energy consumption for approximately 1.35 million buildings based on the Model America version 1.0 (MAv1) dataset. Our methodology incorporated spatial analysis at multiple scales, including individual buildings, clusters of zones determined by K-means clustering, and geographical level evaluation based on Zip codes. The results revealed significant variations in energy consumption and heat emissions across different building types and urban zones. High-emission hotspots identified through clustering pointed to areas most contributing to the UHI effects. Zip code-based area analysis further contextualized these findings, offering an urban context-based perspective on emission distribution and informing potential urban energy policies for mitigating UHI effects.

Chowdhury, Shovan [ORNL]↗

Selection and Ranking of Experiments from the Halden Database in support of Multiscale Model Validation

Validating fuel performance codes, such as BISON, requires an extensive amount of experiments covering a wide range of operating conditions and fuel types. Within the light-water reactor (LWR) space, there have been several international experimental programs that have contributed to the wealth of available experimental data available for use. One of those international programs, the Halden Reactor Project (HRP), began in 1958 and utilized the Halden Boiling Water Reactor to conduct many highly instrumented experiments until the reactor closed in 2018. Idaho National Laboratory, through the U.S. Department of Energy, has utilized several Halden experiments to perform the initial validation of the BISON code based upon their inclusion in international modeling and simulation benchmarks. Recently, the HRP has provided member organizations a complete copy of all available data, reports, and presentations since the HRP began. This report provides an initial exploration of the data available in the database for use in validating the multiscale models under development in the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program for LWR applications. Ranking tables that identify potential validation cases are provided for the high priority models of interest. It was found that some of the recommended high priority experiments correspond to additional rods in existing assemblies already available in the BISON validation suite. It is expected that several of these cases will be incorporated into future NEAMS milestones in the fuels technical area for increased validation of BISON.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Dynamic Probabilistic Safety Assessment Studies for Advanced Reactor Using RAVEN

Probabilistic Safety Assessment (PSA) is used extensively to evaluate the risks associated with complex engineering systems like Nuclear Power Plants (NPPs). Current PSA models are based on the Event-Tree/Fault-Tree (ET/FT) methodology. ET and FT models are static and are based on Boolean logic approaches. In the past, concerns have been raised in the literature regarding the capability of the traditional static modelling approaches to adequately account for the impact of process, hardware, software, firmware and human interactions on the stochastic system behaviour. To overcome the limitations of the traditional approach to PSA, several dynamic PSA methodologies have been proposed. One of the dynamic PSA methodologies used for dynamic evaluations is Dynamic Event Tree (DET) framework which can be used to assess the impact of the parameter variability and scenario dynamics on the PSA model for the initiating event. The DET framework couples the stochastic model (number of component/trains that start on demand, operator action timing, etc.) with a Thermal-Hydraulic (TH) model of the plant. This paper explores the use of DET along with a case study on advanced reactor. The initiating event selected for the study was Class IV power supply failure event. The TH analysis considering uncertainty in various parameters was performed using RELAP5 and Reactor Analysis and Virtual control ENvironment (RAVEN) tool. Based on the uncertainty analysis, it is concluded that the peak clad temperatures (PCT) are within the limits in all the code runs implying a high-degree of safety margin. However, variation in time to reach the PCT was observed among the code runs and the mean time to reach the PCT was found to be around 8590sec (approximately 2.4 hours). Hence, sufficient time margin is available for human intervention and the operator might have a relatively stress-free state during such an accident scenario. Due to the static nature of the traditional PSA models, the safety margin available was lesser, whereas, with the help of dynamic PSA models, one can demonstrate that the actual available safety margin is more in the present case study and is valuable input from the design point of view.

99 GENERAL AND MISCELLANEOUS↗

Nuclear Requalification of the ATR Core

The Advanced Test Reactor (ATR) creates a unique, high neutron flux materials testing environment that subsequently causes neutron embrittlement damage to its beryllium reflector. The reflector is eventually required to be replaced during a reactor Outage. Concurrently, a piece-for-piece core replacement is conducted to maintain reactor functionality called a core internals changeout (CIC). Once changeout is complete, ATR Reactor Engineering utilizes previous CIC data, notably 1977-1994 CIC data, to conduct predictive criticality analysis on the new, unirradiated core. However, CIC data has been inconsistently reported over the years making it difficult, and in some cases impossible, to utilize. These inconsistencies arise in various forms of not using correct units, inconsistent diagram usage, and not portraying the same kind of data similarly across the reports. To work around this inconsistency issue, Reactor Engineering is implementing the use of several new neutronic modeling codes that utilize modern computation speeds and methods to model the new core in different criticality environments. Further validation is then conducted by nuclear testing and bringing the reactor critical and conducting various irradiation tests. Upon completion and certification that the reactor passed all testing requirements, ATR can once again re-start normal operations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗