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At least 433 records · Page 24

University of Missouri Research Reactor LEU Fuel Element Flow Test Conceptual Design—Hydraulic Reactor Design Parameters

The University of Missouri-Columbia Research Reactor (MURR®) is one of five U.S. high performance research reactors (USHPRR), plus one critical facility, that actively collaborates with the National Nuclear Security Administration (NNSA) Material Management and Minimization(M 3 ) Reactor Conversion Program to convert to the use of low-enriched uranium (LEU, < 20 wt.% U-235) fuel. A new type of LEU fuel with very high density, based on an alloy of uranium and 10 weight percent molybdenum (U-10Mo), is expected to allow the conversion to LEU of USHPRR that have been found unable to be converted with previously qualified uranium silicide-aluminum (U 3 Si 2 -Al) dispersion fuel. MURR has been working with the USHPRR Reactor Conversion (RC) Pillar at Argonne National Laboratory to perform fuel element design and fuel cycle performance analyses, steady-state thermal hydraulics safety analyses, and accident safety analyses in preparation for the conversion of MURR and to support a preliminary Safety Analysis Report (SAR) for conversion to LEU fuel. This work is performed in preparation for the flow test campaign that will be conducted by the USHPRR RC Pillar. The purpose of the hydraulic performance evaluation of the MURR LEU fuel element designed by the RC Pillar is to test a prototypic commercially fabricated LEU fuel element to determine whether any failure modes are observed or predicted in the fuel element, including significant deformations such as plate bending, twisting, or plate detachment from the side plate under selected safety-basis limits for reactor hydraulic conditions. To support the design of the flow test for MURR LEU fuel element hydraulic performance evaluation, design parameters for hydraulic testing of the LEU fuel element are laid out in this report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Report of the 2025 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science

This report summarizes insights from the 2025 Workshop on Next-Generation Ecosystems for Scientific Computing: Harnessing Community, Software, and AI for Cross-Disciplinary Team Science, which convened more than 40 experts from national laboratories, academia, industry, and community organizations to chart a path toward more powerful, sustainable, and collaborative scientific software ecosystems. To address urgent challenges at the intersection of high-performance computing (HPC), AI, and scientific software, participants envisioned agile, robust ecosystems built through socio-technical co-design—the intentional integration of social and technical components as interdependent parts of a unified strategy. This approach combines advances in AI, HPC, and software with new models for cross-disciplinary collaboration, training, and workforce development. Key recommendations include building modular, trustworthy AI-enabled scientific software systems; enabling scientific teams to integrate AI systems into their workflows while preserving human creativity, trust, and scientific rigor; and creating innovative training pipelines that keep pace with rapid technological change. Pilot projects were identified as near-term catalysts, with initial priorities focused on hybrid AI/HPC infrastructure, cross-disciplinary collaboration and pedagogy, responsible AI guidelines, and prototyping of public-private partnerships. This report presents a vision of next-generation ecosystems for scientific computing where AI, software, hardware, and human expertise are interwoven to drive discovery, expand access, strengthen the workforce, and accelerate scientific progress.

97 MATHEMATICS AND COMPUTING↗

INTEGRATE - Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements

The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project is developing a new inverse-design capability for the aerodynamic design of wind turbine rotors using invertible neural networks. This AI-based design technology can capture complex non-linear aerodynamic effects while being 100 times faster than design approaches based on computational fluid dynamics. This project enables innovation in wind turbine design by accelerating time to market through higher-accuracy early design iterations to reduce the levelized cost of energy. INVERTIBLE NEURAL NETWORKS Researchers are leveraging a specialized invertible neural network (INN) architecture along with the novel dimension-reduction methods and airfoil/blade shape representations developed by collaborators at the National Institute of Standards and Technology (NIST) learns complex relationships between airfoil or blade shapes and their associated aerodynamic and structural properties. This INN architecture will accelerate designs by providing a cost-effective alternative to current industrial aerodynamic design processes, including: - Blade element momentum (BEM) theory models: limited effectiveness for design of offshore rotors with large, flexible blades where nonlinear aerodynamic effects dominate - Direct design using computational fluid dynamics (CFD): cost-prohibitive - Inverse-design models based on deep neural networks (DNNs): attractive alternative to CFD for 2D design problems, but quickly overwhelmed by the increased number of design variables in 3D problems AUTOMATED COMPUTATIONAL FLUID DYNAMICS FOR TRAINING DATA GENERATION - MERCURY FRAMEWORK The INN is trained on data obtained using the University of Marylands (UMD) Mercury Framework, which has with robust automated mesh generation capabilities and advanced turbulence and transition models validated for wind energy applications. Mercury is a multi-mesh paradigm, heterogeneous CPU-GPU framework. The framework incorporates three flow solvers at UMD, 1) OverTURNS, a structured solver on CPUs, 2) HAMSTR, a line based unstructured solver on CPUs, and 3) GARFIELD, a structured solver on GPUs. The framework is based on Python, that is often used to wrap C or Fortran codes for interoperability with other solvers. Communication between multiple solvers is accomplished with a Topology Independent Overset Grid Assembler (TIOGA). NOVEL AIRFOIL SHAPE REPRESENTATIONS USING GRASSMAN SPACES We developed a novel representation of shapes which decouples affine-style deformations from a rich set of data-driven deformations over a submanifold of the Grassmannian. The Grassmannian representation as an analytic generative model, informed by a database of physically relevant airfoils, offers (i) a rich set of novel 2D airfoil deformations not previously captured in the data , (ii) improved low-dimensional parameter domain for inferential statistics informing design/manufacturing, and (iii) consistent 3D blade representation and perturbation over a sequence of nominal shapes. TECHNOLOGY TRANSFER DEMONSTRATION - COUPLING WITH NREL WISDEM Researchers have integrated the inverse-design tool for 2D airfoils (INN-Airfoil) into WISDEM (Wind Plant Integrated Systems Design and Engineering Model), a multidisciplinary design and optimization framework for assessing the cost of energy, as part of tech-transfer demonstration. The integration of INN-Airfoil into WISDEM allows for the design of airfoils along with the blades that meet the dynamic design constraints on cost of energy, annual energy production, and the capital costs. Through preliminary studies, researchers have shown that the coupled INN-Airfoil + WISDEM approach reduces the cost of energy by around 1% compared to the conventional design approach. This page will serve as a place to easily access all the publications from this work and the repositories for the software developed and released through this pr...

aerodynamics↗

Zero-deadtime processing in beta spectroscopy for measurement of the non-zero neutrino mass

The Project 8 collaboration seeks to measure, or more tightly bound, the mass of the electron antineutrino by applying a novel spectroscopy technique to precisely measure the tritium beta-decay spectrum. The current system produces a single analog signal, which is digitized and processed in several stages before being saved to local disk storage. Online processing includes two stages, an FPGA connected to the analog to digital converter reduces the data down to the region of interest before shipping over the local network for further processing and storage. A normal CPU-based processing stage applies triggering logic to only save data at times when a signal is present, further reducing the total volume of data which needs to be written to disk or transferred for long-term storage. The next stage of the project will need to process many input channels and will integrate a necessary aggregation and combination step prior to applying the event search and triggering logic. We present the online processing system which has successfully been deployed for the current, singlechannel, phase. We also present the status and design for a many-channel platform.

Project 8 Collaboration↗

Massachusetts Institute of Technology Reactor LEU Fuel Element Flow Test Conceptual Design – Hydraulic Reactor Design Parameters

The Massachusetts Institute of Technology Reactor (MITR-II, also referred to as MITR) is one of six U.S. high performance research reactors (USHPRR), including one critical facility, that is actively collaborating with the U.S. National Nuclear Security Administration (NNSA) Material Management and Minimization (M 3 ) Reactor Conversion Program to convert to the use of low-enriched uranium (LEU, < 20 wt% 235 U) fuel. The MIT Nuclear Reactor Laboratory has been working with the USHPRR Reactor Conversion (RC) Pillar at Argonne National Laboratory to perform fuel element design and fuel cycle performance analyses, steady-state thermal hydraulics safety analyses, and accident safety analyses in preparation for the conversion of MITR and support a preliminary Safety Analysis Report (SAR) for conversion to LEU fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Release of a High Temperature Engineering Test Reactor (HTTR) Steady State Multiphysics Model to the Virtual Test Bed

In response to climate change, global governments and private industry have established a common goal of achieving net-zero emissions by 2050 \cite{osti_1865910}. This goal requires a reassessment of current energy demands and production methods. Reducing emissions at an affordable cost while maintaining grid reliability requires a nationwide collaborative effort among government and industry in the United States. Nuclear power is the leading low-carbon electricity generation method. In the past 50 years, the use of nuclear power has reduced carbon dioxide emissions by over 60 gigatons and has played a crucial role in the security of energy supply~\cite{IEA}. In the U.S., nuclear power accounts for 20\% of the electrical supply and provides energy reliably. Advanced reactors will operate at higher temperatures, operate more efficiently, utilize more energy stored within fuel, and reduce the amount of waste produced \cite{osti_1616270}. To face these challenges and goals, the U.S. Department of Energy has created an initiative to focus on the modeling and simulation tools to support future nuclear power plant design, licensing, and operations. The Virtual Test Bed (VTB)~\cite{vtb2023} was launched by the National Reactor Innovation Center (NRIC) in collaboration with the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to support the advanced nuclear reactor community. The VTB involves teams from both Idaho National Laboratory and Argonne National Laboratory and aims to provide example models for a broad range of both current and future advanced reactor designs. A feature of the VTB is the automatic testing of these models to ensure continued functionality as simulation tools are further developed. The VTB and the advanced reactor models documented there are important resources for this initiative. This work describes the inclusion of a new model on the VTB---a High Temperature Engineering Test Reactor (HTTR) steady-state model \cite{LABOURE2023109838}.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Computational tools and data integration to accelerate vaccine development: challenges, opportunities, and future directions

The development of effective vaccines is crucial for combating current and emerging pathogens. Despite significant advances in the field of vaccine development there remain numerous challenges including the lack of standardized data reporting and curation practices, making it difficult to determine correlates of protection from experimental and clinical studies. Significant gaps in data and knowledge integration can hinder vaccine development which relies on a comprehensive understanding of the interplay between pathogens and the host immune system. In this review, we explore the current landscape of vaccine development, highlighting the computational challenges, limitations, and opportunities associated with integrating diverse data types for leveraging artificial intelligence (AI) and machine learning (ML) techniques in vaccine design. We discuss the role of natural language processing, semantic integration, and causal inference in extracting valuable insights from published literature and unstructured data sources, as well as the computational modeling of immune responses. Furthermore, we highlight specific challenges associated with uncertainty quantification in vaccine development and emphasize the importance of establishing standardized data formats and ontologies to facilitate the integration and analysis of heterogeneous data. Through data harmonization and integration, the development of safe and effective vaccines can be accelerated to improve public health outcomes. Looking to the future, we highlight the need for collaborative efforts among researchers, data scientists, and public health experts to realize the full potential of AI-assisted vaccine design and streamline the vaccine development process.

60 APPLIED LIFE SCIENCES↗

Methodology for Good Machine Learning with Multi‐Omics Data

In 2020, Novartis Pharmaceuticals Corporation and the U.S. Food and Drug Administration (FDA) started a 4‐year scientific collaboration to approach complex new data modalities and advanced analytics. The scientific question was to find novel radio‐genomics‐based prognostic and predictive factors for HR+/HER− metastatic breast cancer under a Research Collaboration Agreement. This collaboration has been providing valuable insights to help successfully implement future scientific projects, particularly using artificial intelligence and machine learning. This tutorial aims to provide tangible guidelines for a multi‐omics project that includes multidisciplinary expert teams, spanning across different institutions. We cover key ideas, such as “maintaining effective communication” and “following good data science practices,” followed by the four steps of exploratory projects, namely (1) plan, (2) design, (3) develop, and (4) disseminate. We break each step into smaller concepts with strategies for implementation and provide illustrations from our collaboration to further give the readers actionable guidance.

Pharmacology & Pharmacy↗

Comparative evaluation of analogue front-end designs for the CMS Inner Tracker at the High Luminosity LHC

The CMS Inner Tracker, made of silicon pixel modules, will be entirely replaced prior to the start of the High Luminosity LHC period. One of the crucial components of the new Inner Tracker system is the readout chip, being developed by the RD53 Collaboration, and in particular its analogue front-end, which receives the signal from the sensor and digitizes it. Three different analogue front-ends (Synchronous, Linear, and Differential) were designed and implemented in the RD53A demonstrator chip. A dedicated evaluation program was carried out to select the most suitable design to build a radiation tolerant pixel detector able to sustain high particle rates with high efficiency and a small fraction of spurious pixel hits. The test results showed that all three analogue front-ends presented strong points, but also limitations. The Differential front-end demonstrated very low noise, but the threshold tuning became problematic after irradiation. Moreover, a saturation in the preamplifier feedback loop affected the return of the signal to baseline and thus increased the dead time. The Synchronous front-end showed very good timing performance, but also higher noise. For the Linear front-end all of the parameters were within specification, although this design had the largest time walk. This limitation was addressed and mitigated in an improved design. The analysis of the advantages and disadvantages of the three front-ends in the context of the CMS Inner Tracker operation requirements led to the selection of the improved design Linear front-end for integration in the final CMS readout chip.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A High-Speed, High-Resolution Transition Edge Sensor Spectrometer for Soft X-Rays at the Advanced Photon Source

This project explores the design and development of a transition edge sensor (TES) spectrometer for resonant soft X-ray scattering (RSXS) measurements developed in collaboration between Argonne National Laboratory (ANL) and the National Institute of Standards and Technology (NIST). Soft X-ray scattering is a powerful technique for studying the electronic and magnetic properties of materials on a microscopic level. However, the lack of high-performance soft X-ray spectrometers has limited the potential of this technique. TES spectrometers have the potential to overcome these limitations due to their high energy resolution, high efficiency, and broad energy range. This project aims to optimize the design of a TES spectrometer for RSXS measurements and more generally soft X-ray spectroscopy at the Advanced Photon Source (APS) 29-ID, leading to improved understanding of advanced materials. We will present a detailed description of the instrument design and implementation. The spectrometer consists of a large array of approximately 250 high-speed and high-resolution pixels. The pixels have saturation energies of approximately 1 keV, sub-ms pulse duration and energy resolution of approximately 1 eV. The array is read out using microwave multiplexing chips with MHz bandwidth per channel, enabling efficient data throughput. To facilitate measurement of samples in situ under ultra-high vacuum conditions at the beamline, the spectrometer is integrated with an approximately 1 m long snout.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Massachusetts Institute of Technology Reactor LEU Fuel Element Flow Test Conceptual Design

As part of the U.S. National Nuclear Security Administration’s (NNSA’s) mission to minimize the civilian use of weapon-grade highly enriched uranium (HEU) fuels, the NNSA Office of Material Management and Minimization (M 3 ) Conversion Program is collaborating with six U.S. High Performance Research Reactors (USHPRR), including one critical facility, to convert from the use of HEU to low-enriched uranium (LEU) fuel. The M 3 conversion objectives for the USHPRR are to develop LEU fuel element designs that will ensure safe reactor operations and maintain the existing experimental performance of each facility. The work is being conducted through many interrelated activities that are being completed by stakeholders across organizations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Engineered Barrier System R&D and International Collaborations – LANL (FY20): Spent Fuel and Waste Disposition

The United States Department of Energy’s Spent Fuel and Waste Disposition (SFWD) program is investigating the design and safety function of generic nuclear geologic repositories in a variety of geologic settings (salt, argillite, and crystalline rock). Different configurations and loadings of spent nuclear fuel and waste within disposal canisters are also being investigated, some of which have the potential to generate repository temperatures higher than previously considered (i.e., temperatures >100ºC) by foreign and domestic concepts. This report expands on engineered barrier material stability in a high temperature crystalline rock repository through high temperature hydrothermal experiments. Experiments were designed to develop engineered barrier system (EBS) concepts in a hightemperature crystalline environment in 1) bentonite-Grimsel Granodiorite interactions, 2) bentonite-cement reactions, and 3) interaction between waste canister materials and bentonite. Experiment results are applied to understanding long-term repository performance in terms of radionuclide isolation. One hydrothermal experiment was completed in the rocking autoclaves at LANL in FY-20: IEBS-6 (Grimsel Granodiorite + Wyoming bentonite + cured ordinary Portland cement + Grimsel Granodiorite synthetic groundwater, 250ºC/150 bar, 8 weeks). Several other experiments were planned but were delayed due to the COVID-19 pause in laboratory work. In addition, some characterization of the reaction products of experiments conducted in FY-20 was prevented by COVID-19. Mineral phase chemistry was not measured via electron microprobe analyses for IEBS-6. Quantitative X-ray diffraction results from IEBS-6 and HBT-1 were not completed. The missing analyses and discussion of the results will be included in next year’s report. New characterization that was completed includes scanning electron microscopy of reaction products from IEBS-6, quantitative X-ray diffraction results are presented from IEBS-1 through IBES-5, preliminary scanning electron microscope images and chemical analyses for IEBS-6, X-ray diffraction of the clay fraction from all experiments, measurement/imaging of mineral growth on the surface of steel coupons. Major observations pertaining to bentonite stability in a Grimsel Granodiorite environment include the stability of Na-montmorillonite at 250°C, the formation of trace CSH phases, and the formation of bentonite colloids on experiment cooling. The addition of a cured chip of Portland cement to the bentonite-Grimsel system results in slightly higher pH values and the formation of diverse secondary mineral phases that were not observed in the previous experiments (e.g., analcime, garronite, CSH phases). The new characterization efforts related to the interaction of stainless-steel coupons and bentonite clay focused on thickness and mineralogy of phases that formed at the steel surface. In Wyoming bentonite + Grimsel Granodiorite systems, newly formed minerals at the bentonitesteel coupon interface included alteration of the outermost steel edge to Fe,Cr-oxide phases, followed by Fe-rich phyllosilicates (Fe-saponite, chlorite) and interbedded Fe,Cr,Ni-sulfide phases (pentlandite). Hydrothermal experiments were completed to assess uranium-carbonate complexation at conditions relevant to high-temperature disposal. Autoclave solubility experiments were conducted at 150 to 250ºC with a range of carbonate and uranium concentrations. The experiment results were characterized via situ UV-Visible spectroscopy and synchrotron-based in situ XAS techniques. Results show a significant decrease in the stability of uranyl-carbonate complexes at temperatures above 100ºC along with the precipitation of uranium oxides. Further, at T > 200ºC, results show that uranyl-hydroxyl complexes control solubility of uranium instead of the previously predicted uranyl-carbonate species. These results are significant for understanding the mobility of uranium in the EBS, which will likely contain carbonate-rich fluids. International research efforts focused on three main areas: 1) participation in international conferences, 2) building collaborations with foreign repository programs, and 3) the initiation of an experimental program to complement the full-scale HotBENT test at the Grimsel test site. This experiment included Wyoming bentonite + low carbon steel + Grimsel Granodiorite synthetic groundwater and was run at the planned maximum temperature of the HotBENT test (200°C). Complete characterization of reaction products was hindered by disruptions to laboratory work but will be reported in the next FY. The experimental results obtained in FY-20 continue to document the wide-ranging effects of bulk composition and pressure-temperature conditions in the mineralogical and geochemical evolution of a high-temperature repository environment. Concepts developed will be used to inform models of long-term material stability in a generic crystalline rock-hosted repository.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Lowest-order QED radiative corrections in unpolarized elastic electron–deuteron scattering beyond the ultra-relativistic limit for the proposed deuteron charge radius measurement at Jefferson laboratory

Analogous to the well-known proton charge radius puzzle, a similar puzzle exists for the deuteron charge radius, r d . There are discrepancies observed in the results of r d , measured from electron-deuteron (e - d) scattering experiments, as well as from atomic spectroscopy. In order to help resolve the charge radius puzzle of the deuteron, the PRad collaboration at Jefferson Lab has proposed an experiment for measuring r d , named DRad. This experiment is designed to measure the unpolarized elastic e - d scattering cross section in a low-Q 2 region. To extract the cross section with a high precision, having reliable knowledge of QED radiative corrections is important. Here, in this paper, we present complete numerical calculations of the lowest-order radiative corrections in e - d scattering for the DRad kinematics. The calculations have been performed within a covariant formalism and beyond the ultra-relativistic approximation ($m^2_e$ $\ll$ Q 2 ). Besides, we present a systematic uncertainty on r d arising from higher-order radiative corrections, estimated based on our cross-section results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Lithium-Ion Batteries with Safer Current Collectors

The US Department of Energy’s Oak Ridge National Laboratory and Soteria Battery Innovation Group collaborated to develop a metallized polymer film as a current collector for lithium-ion batteries and design slit patterns for electrodes to improve battery safety. The metallized polymer film serves as a fuse that will break under high temperature resulting from a short circuit. Consequently, the short circuit will be broken and the heat generated from the short circuit will be alleviated to avoid thermal runaway. The electrodes with slit patterns are expected to be broken into small segments upon mechanical impact, which can isolate the damaged electrodes from the rest. Thus, the heat generation associated with the mechanical impact will be reduced, along with the likelihood of thermal runaway. This effort aimed to improve lithium-ion battery safety by replacing traditional metal foils with metallized polymer films as current collector and introducing slit patterns to battery electrodes. The metallized polymer films were polyethylene terephthalate with a thin metal (aluminum for cathodes and copper for anodes) coating on both sides. Slit patterns with various geometries and dimensions were designed via simulation. Temperature distribution on cells with electrodes with and without slit patterns was also simulated via nemerical modeling. Electrodes on traditional metal foils and metallized polymer films were coated via a pilot-scale slot-die coater at the US Department of Energy Battery Manufacturing Facility at Oak Ridge National Laboratory. The electrodes were calendered to 35% porosity and punched out with and without slit patterns. Pouch cells were assembed with the electrodes inside a dry room for electrochemical and safety testing. Electrodes coated on metallized polymer films exhibited comparable electrochemical performance to their counterparts coated on traditional metal foils. They also showed improved safety in nail penetration and indentation tests.

25 ENERGY STORAGE↗

Accelerating Engineered Microbe Optimization through Machine Learning and Multi-Omics Datasets [Abstract]

The Agile Biofoundry (ABF) is a multi-national lab consortium funded by the DOE Bioenergy Technologies Office that has developed a biofoundry enabling the rapid deployment of bioproducts into the market. The ABF is a flexible platform that can adjust to the needs of numerous government, academic and industrial partners, thus enabling them to rapidly develop and optimize the production of a wide range of bioproducts. To demonstrate this capability, three ABF labs (NTESS, LBNL, and PNNL) have collaborated with the biomanufacturer Lygos, Inc. to use the ABF to demonstrate a high-throughput Design-Build-Test-Learn (DBTL) engineering cycle incorporating multi-omics analysis and machine learning with best in industry cycle times.

60 APPLIED LIFE SCIENCES↗

High-Reliability Systems and the Control of National Security Data and Information

High-reliability systems are characterized by catastrophic implications in the event of failure. These implications can include substantive damage to the environment, social order, and loss of life. Examples of high-reliability systems include nuclear submarines, nuclear reactors, the electric grid, and nuclear weapons. Due to the catastrophic implications of failure, there are heightened awareness and control mechanisms surrounding related data and information. However, defining the difference between data and information is often ambiguous across scholarly disciplines and in United States policy and legislation. For high-reliability systems, the implications of ambiguity between data and information may affect the security of United States interests and even cost lives. For security, data are raw facts or figures without context, while information is the compilation or articulation of data that forms context. Security depends on clarity in the differences between data and information and how to control them. Control is necessary to ensure that data and information are not unintentionally released to foreign governments, the public, or those without need-to-know. A primary concern in the practice of security is the control of data to avoid the unintended conversion to information. Intra-institutionally, this control is highly complex given the amalgam of legacy data systems and the numerous and constantly evolving nature of modern data systems that were not necessarily designed to be integrated. The complexity of this concern is augmented when institutions are part of interinstitutional collaborations or networks of public-private partnerships that share data and information. Additionally, institutions that share data as a function of policy and legislative action— particularly formally integrated data and information system infrastructures—may be at higher security risk. This paper will present an intra-institutional paradigm that utilizes and integrates concepts from numerous disciplines to frame a critical and underspecified practical issue in security—controlling for the unintended conversion of data to information.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Simulation of Physics-Based 0-10Hz Strong Motion Using High Performance Computing Supporting Refinements to Regional Ground Motion Models for the Central Eastern US

In collaboration with the U.S. Nuclear Regulatory Commission (NRC) the LLNL has developed a computationally efficient simulation platform designed to perform physics-based ground motion simulations for crustal earthquakes in the Stable Continental Regions of Central and Eastern US (CEUS), using high-performance computing. The main objective of the earthquake simulations was to use synthetic ground motion to provide constrains to refinements of existing ergodic Ground Motion Models (GMMs), for large magnitude earthquakes and near-fault distances, for which these models are less reliable. Physics-based broadband (0-10Hz) ground motion simulations were used to estimate the near-fault ground motion amplitudes and within event and between-event variabilities associated with fault rupture characteristics. In our simulations we used a 3D regional velocity model that was based on Saikia’s 1D velocity model (1994). In simulations performed during the first stage of this project the Saikia’s velocity model demonstrated better performance in modelling high frequency regional wave propagation for the CEUS region recorded during the Mw5.0 November 7, 2016, Cushing Oklahoma (Taylor et al., 2017), and Mw5.8 September 3, 2016, Pawnee Oklahoma earthquakes. The proposed regional 3D model includes random perturbations to the 1D background model using the stochastic scheme of Pitarka and Mellors (2021). In addition, validation analysis of the rupture generator and regional wave propagation models, using comparisons with different GMMs for Mw6.5 and Mw7.0 scenario earthquakes in the CEUS region resulted in a very good match between the simulated and empirical ground motion models. For the purposes of seismic hazard assessment at the existing and planned nuclear power plants, NRC is interested in studies aimed at improving the current ground motion models (GMM) for both Stable Continental Regions (SCR) in the Central and Eastern US and Active Crustal Regions (ACR) in the Western US. Due to lack of recorded data, these improvements require synthetic data for short fault distances and large magnitude earthquakes for which the existing recorded data is not enough to uniquely constrain the GMMs. The need for simulations and strong motion data is especially critical for the CEUS region where we do not have recorded data from potentially large damaging earthquakes with moment magnitudes 6.0 and higher. In this the project, we focused on 10Hz simulations of Mw7.0 scenario earthquakes with strike slip and thrust faulting mechanisms. We used more than 50 Mw7.0 earthquake rupture scenarios to investigate the ground motion uncertainty due to unknown earthquake rupture parameters, in particular, the slip distribution, rupture velocity, and faulting mechanism, and their implication on ground motion amplification due to forward rupture directivity effects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Zero-Export Feeder Through Transactive Markets

This presentation summarizes how HELICS was used during a collaborative project with Energy Web Foundation and Exelon Corporation. The primary focus of the research was on designing a transactive energy market to accomplish zero export at the feeder head. The market was tested in a HELICS co-simulation framework and showed significant promise for eliminating back feed at the substation even under high renewable energy penetration levels.

blockchain↗