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

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At least 793 records · Page 44

A Power-Hardware-in-the-Loop (PHIL) Evaluation of Service Restoration With Networked Microgrids

This paper describes the power-hardware-in-the- loop (PHIL) evaluation of the feasibility of service restoration solutions determined by the PowerModelsONM.jl tool. This tool incorporates microgrids and the networking of microgrids into its determination of an optimal service restoration solution. The paper presents PHIL simulation results for a case study based on a real distribution feeder with multiple microgrids, showcas- ing the effectiveness of networked microgrids in aiding system restoration after an outage. The study leverages high-fidelity, real- time electromagnetic transient models to ensure accuracy in the simulation results. This work is the final output from the Resilient Operation of Networked Microgrids (RONM) project funded by the U.S. Department of Energy Office of Electricity Microgrid Program and led by Los Alamos National Laboratory. RONM focused on the application of PowerModelsONM.jl to enhance the resilience of distribution systems.

fault location isolation and service restoration (↗

S AP F LOWER : an automated tool for sap flow data preprocessing, gap-filling, and analysis using deep learning

Sap flow, a critical process in plant water use and ecosystem water cycles, is often measured using thermal dissipation probes (TDP) due to their ease of installation and continuous data collection. However, sap flow data frequently include noise, outliers, and gaps, creating challenges for analysis and requiring substantial manual processing. We developed S AP F LOWER , a tool that automates data preprocessing, model training, gap-filling, sapwood area scaling and modeling, and water use analysis. It integrates autocleaning, machine learning and deep learning models (e.g. random forest, Gaussian process regression, long short-term memory (LSTM), bidirectional LSTM (BiLSTM)), and efficient workflows to process sap flow data. S AP F LOWER can remove over 90% of noisy data while preserving legitimate variations and achieve high accuracy in gap-filling based on user-determined parameters. Random forest, LSTM, and BiLSTM models reduced root mean square error to 10% or less for long-term gaps. Model training and prediction can be performed efficiently within seconds. S AP F LOWER significantly enhances the efficiency and accessibility of TDP data analysis by automating complex tasks, enabling researchers without programming expertise to employ advanced techniques. Future improvements will focus on species-specific corrections for TDP and support for additional measurement methods. S AP F LOWER is openly available on GitHub (https://github.com/JiaxinWang123/SapFlower) and Zenodo (doi: 10.5281/zenodo.13665919).

ecosystem water balance↗

The QCD phase diagram and Beam Energy Scan physics: A theory overview

Herein we review recent theoretical developments relevant to heavy-ion experiments carried out within the Beam Energy Scan program at the Relativistic Heavy Ion Collider. Our main focus is on the description of the dynamics of systems created in heavy-ion collisions and establishing the necessary connection between the experimental observables and the QCD phase diagram.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Scaling Up: Growth of the Indy Student Cluster Competition

The Indy Student Cluster Competition (IndySCC) completed its second year of competition, expanding and building upon the fist year. The IndySCC is a fully virtual competition, with a focus on education, and is part of the student program within the Supercomputing (SC) conference series. The competition aims to engage teams who do not get into the in-person, Student Cluster Challenge (SCC) and to build and train inexperienced teams to eventually go on to the SCC. The first year featured 5 teams and in the second year, this grew to 11 accepted teams in 2022. This work aims to provide an update to how the competition has grown, the challenges, and the plans to grow in the future.

Dietz, Dan↗

Geometry Mesher

This program implements tetrahedral meshing for implicitly-defined geometries, focusing on meshing unions of geometric primitives like spheres and cylinders. This enables users to quickly generate quality meshes of truss lattice and filament structures.

Watts, SethE [Lawrence Livermore National Laborato↗

Dataset for 'Ombadi et al. (2023). A warming-induced reduction in snow fraction amplifies rainfall extremes, Nature'

This package contains the main codes, sample input data and main result files to reproduce the analysis and results presented in the article: “Ombadi et al. (2023), A warming-induced reduction in snow fraction amplifies rainfall extremes, Nature”. The folder consists of the following: (1) “Raw data”: a folder that contains sample input data which is used in some of the codes for demonstration purposes. It also contains data that was not pre-processed such as Elevation data; (2) “Results”: this folder contains files of the main results presented in the paper including: “Annual-Max-Series”, “Change-rainfall-extremes”, “Change-snow-fraction”, “Warming levels_By scenario_model_year” and “Masks”. Description of these folders is detailed in the "Readme.rtf" file; (3) Python jupyter notebooks (Extract_Annual Max Series (AMS).ipynb, Elevation-dependent amplification of rainfall extremes.ipynb, Sensitivity_to_global_warming.ipynb) demonstrate the main steps of analysis. Further description of those notebooks is provided in the "Readme.rtf" file; (4) R code for extreme value analysis (Extreme_Value_Analysis.R). The sample and pre-processed dataset in "Raw data" is obtained from publicly available repositories of CMIP6 and ERA5 datasets; see Methods for more detail. This research was supported by Office of Science, Office of Biological and Environmental Research of the US Department of Energy under contract no. DE-AC02-05CH11231 for the CASCADE Scientific Focus (funded by the Regional and Global Model Analysis Program area within the Earth and Environmental Systems Modeling Program) and the iNAIADS Early Career Research Project (funded by the Environmental Systems Science program).

54 ENVIRONMENTAL SCIENCES↗

Key Learnings from Hydraulic Fracturing Test Site - 2 (HFTS-2), Delaware Basin

Hydraulic fractures (HF) play a dominant role in oil and gas production from unconventional reservoirs, fracture characteristics, geometry, and extent are generally not well known and are typically inferred from various monitoring methods or subsurface models. The Hydraulic Fracturing Test Site-2 (HFTS-2) is a field-based research experiment performed in the Wolfcamp formation of the Permian (Delaware) Basin. HFTS-2, a unique joint industry program (JIP) that brings together government, academia, and industry, focused on field data acquisition and interpretation. The project has built a comprehensive HF research dataset that includes microseismic (MS), 1,500 ft of core, diagnostic formation injection tests (DFIT), fluid characterization, advanced logs, geochemistry, downhole gauges, varying completions, and permanent fiber optic (FO) cable in vertical and horizontal wells. These data were integrated and used to characterize HF geometry/dimensions and resulting depletion profiles, gain insights for completion design, and achieve a better understanding of parent well depletion effects on child well performance. The analysis and integration of the comprehensive HFTS-2 diagnostics dataset provide insights for optimal well placement and completions and improves understanding about the effects of parent well depletion. Furthermore, this dataset can be used to blind test and develop subsurface workflows for unconventional resources. Key learnings from HFTS-2 and the new technologies tested can easily be transferred to other unconventional plays.

58 GEOSCIENCES↗

Synthesis, Characterization and Properties of Nanoparticles of Intermetallic Compounds

The research program from 2010 to the end of the grant focused on understanding the factors important to the synthesis of single phase intermetallic nano-particles (NPs), their size, crystalline order, surface properties and electrochemical activity. The synthetic method developed is a co-reduction of mixtures of single metal precursors by strong, soluble reducing agents in a non-protic solvent, tetrahydrofuran (THF). With some exceptions, the particles obtained by room temperature reduction are random alloys that need to be annealed at modest temperatures (200 to 600 °C) in order to develop an ordered structure. To avoid significant particle size growth and agglomeration, the particles must be protected by surface coatings. We developed a novel method of coating the metal nanoparticles with KCl, a by-product of the reduction reaction if the proper reducing agents are employed. In that case, a composite product containing individual metal nanoparticles in a KCl matrix is obtained. The composite can be heated to at least 600 °C without significant agglomeration or growth in particle size. Washing the annealed product in the presence of catalyst supports in ethylene glycol removes the KCl and deposits the particles on the support. Six publications present the method and its application to producing and studying new catalyst/support combinations for fuel cell applications. Three publications concern the use of related methods to explore new lithium-sulfur battery concepts.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Clean Energy-Related Economic Development Policy across the States: Establishing a 2016 Baseline

States implement clean energy-related economic development policy to spur innovation, manufacturing, and to address other priorities. This report focuses on those policies most directly related to expanding new and existing manufacturing. The extent to which states invest in this policymaking depends on political drivers and jurisdictional economic development priorities. To date, no one source has collected all of the clean energy-related economic development policies available across the 50 states. Thus, it is unclear how many policies exist within each state and how these policies, when implemented, can drive economic development. Establishing the baseline of existing policy is a critical first step in determining the potential holistic impact of these policies on driving economic growth in a state. The goal of this report is to document the clean energy-related economic development policy landscape across the 50 states with a focus on policy that seeks to expand new or existing manufacturing within a state. States interested in promoting clean energy manufacturing in their jurisdictions may be interested in reviewing this landscape to determine how they compare to peers and to adjust their policies as necessary. This report documents over 900 existing clean energy-related economic development laws, financial incentives (technology-agnostic and clean energy focused), and other policies such as agency-directed programs and initiatives across the states.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Final Technical Report, Wind Generator Project (Ann Arbor)

A Final Technical Report (57 pages) describing educational exhibits and devices focused on wind energy, and related outreach activities and programs. Project partnership includes the City of Ann Arbor, MI and the Ann Arbor Hands-on Museum, along with additional sub-recipients, and U.S. Department of Energy/Office of Energy Efficiency and Renewable Energy (EERE). Report relays key milestones and sub-tasks as well as numerous graphics and images of five (5) transportable wind energy demonstration devices and five (5) wind energy exhibits designed and constructed between 2014 and 2016 for transport and use by the Ann Arbor Hands-on Museum.

17 WIND ENERGY↗

Characterizing Organic Aerosol Processes and Climatically Relevant Properties via Advanced and Integrated Analyses of Aerosol Mass Spectrometry Datasets from DOE Campaigns and ACRF Measurements. Final report for DE-SC0007178

Organic aerosols (OA) are an important but poorly characterized component of the earth’s climate system. Enormous complexities commonly associated with OA composition and life cycle processes have significantly complicated the simulation and quantification of aerosol effects. To unravel these complexities and improve understanding of the properties, sources, formation, evolution processes, and radiative properties of atmospheric OA, we propose to perform advanced and integrated analyses of multiple DOE aerosol mass spectrometry datasets, including two high-resolution time-of-flight aerosol mass spectrometer (HR-AMS) datasets from intensive field campaigns on the aerosol life cycle and the Aerosol Chemical Speciation Monitor (ACSM) datasets from long-term routine measurement programs at ACRF sites. In this project, we will focus on 1) characterizing the chemical (i.e., composition, organic elemental ratios), physical (i.e., size distribution and volatility), and radiative (i.e., sub- and super-saturated growth) properties of organic aerosols, 2) examining the correlations of these properties with different source and process regimes (e.g., primary, secondary, urban, biogenic, biomass burning, marine, or mixtures), 3) quantifying the evolutions of these properties as a function of photochemical processing, 4) identifying and characterizing special cases for important processes such as SOA formation and new particle formation and growth, and 5) correlating size-resolved aerosol chemistry with measurements of radiative properties of aerosols to determine the climatically relevant properties of OA and characterize the relationship between these properties and processes of atmospheric aerosol organics. Our primary goal is to improve a process-level understanding of the life cycle of organic aerosols in the Earth’s atmosphere. We will also aim at bridging between observations and models via synthesizing and translating the results and insights generated from this research into data products and formulations that may be directly used to inform, improve, and evaluate regional and global models. In addition, we will continue our current very active collaborations with several modeling groups to enhance the use and interpretation of our data products. Overall, this research will contribute new data to improve quantification of the aerosol’s effects on climate and thus the achievement of ASR’s science goal of – “improving the fidelity and predictive capability of global climate models”.

54 ENVIRONMENTAL SCIENCES↗

Tri-Lab Co-Design Milestone: In-Depth Performance Portability Analysis of Improved Integrated Codes on Advanced Architecture.

This milestone is a tri-lab deliverable supporting ongoing Co-Design efforts impacting applications in the Integrated Codes (IC) program element Advanced Technology Development and Mitigation (ATDM) program element. In FY14, the trilabs looked at porting proxy application to technologies of interest for ATS procurements. In FY15, a milestone was completed evaluating proxy applications in multiple programming models and in FY16, a milestone was completed focusing on the migration of lessons learned back into production code development. This year, the co-design milestone focuses on extracting the knowledge gained and/or code revisions back into production applications.

97 MATHEMATICS AND COMPUTING↗

Cross-domain Situational Awareness in Computing Networks

Rapidly gaining understanding of an executable file is an extremely hard problem, yet one that is critical to support realistic network defense. Without a strong understanding of what programs do, there is no way that defenders can determine whether the presence of a given program is appropriate or not. This research effort was focused on developing ways to allow a human analyst to rapidly build understanding of the content of executable files.

97 MATHEMATICS AND COMPUTING↗

Advanced Combustion Engines and Fuels 2018 Annual Progress Report

The Advanced Combustion Engines and Fuels Program supports the Vehicle Technology Office’s goal and focuses early-stage research and development (R&D) to improve understanding of the combustion processes, fuel properties, and emission control technologies while generating knowledge and insight necessary for industry to develop the next generation of engines and fuels.

33 ADVANCED PROPULSION SYSTEMS↗

Management and Storage of Scientific Data

Scientific discoveries rely heavily on efficient access, search, and management of massive data sets. Data management technologies have, for decades, provided foundational capabilities for scientific computing. Just as storage, input/output (I/O), and data management have been fundamental to simulation-based science for many years, so too are capable data-management technologies key to the success of today’s scientific workflows utilizing data intensive and machine learning (ML) techniques. The Department of Energy, Office of Science, Advanced Scientific Computing Research (ASCR) program has invested broadly in data-management research focused on high-performance computing (HPC) systems, from parallel file systems that store data to application software that makes these systems more productive. Still, advances in technology combined with growing diversity of supported science strongly motivate continued investment in this area. In January 2022, ASCR convened a workshop to identify priority research directions in the area of data management for high-performance and scientific computing. Attendees were challenged to identify promising approaches that would support the breadth of the DOE mission, including the explosion of artificial intelligence (AI) uses and the growing needs of experimental and observational science. Technological and science drivers were identified and considered as they relate to key aspects of data management such as interfaces, architectural design, and FAIR principles (Findable, Accessible, Interoperable, and Reusable). The thoughts of the workshop participants were distilled into a set of four priority research directions with the potential for high impact on DOE science. These research directions are summarized in the following pages.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Validation of NEAMS Tools Using MSRE Data

This report documents the benchmarks developed and performed for the tools and codes developed under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program utilizing the MSRE experiment data. There are three focus areas explored in this work: fuel evolution, CFD, and system transient analyses. Fuel depletion is important for MSR reactor physics and fuel cycle analysis. Fuel depletion capability is currently being developed in the Griffin reactor physics code. To support this, a benchmark problem is developed using the MSRE data and an existing depletion code with flowing fuel analysis functionality (ADDER) to validate this new capability in Griffin. The ADDER calculation is compared with the TRITON-MSR results as well as the MSRE experimental data. This benchmark can be directly used to verify and validate the Griffin fuel depletion capability in future years. For CFD simulation, the MSRE CAD model is obtained from the Copenhagen Atomics and a mesh is generated for the MSRE inlet plenum. The Nek5000 code will be employed to find the flow distribution in the MSRE inlet plenum based on the mesh generated. For system analysis, a simple benchmark problem for three types of MSR system transients is developed. The SAM and SPECTRA codes are used to solve the simple problem, and the results from the two codes agree well. The SAM code is also employed to obtain the frequency response of the MSRE system at the 5 and 8 MWt power levels. The results agree well with the experiment measurements. These verification and validation efforts gives SAM users more confidence in MSR system transient simulations using SAM. Lastly, the SAM-Griffin Multiphysics coupling work is initiated. A simple one-way coupling of evaluating the precursor drift effect on the MSRE k-eff is demonstrated. This preliminary coupling work serves as the basis for future more complex Multiphysics simulation and modelling.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Translator Plan: A Coordinated Vision for Fiscal Years 2023-2025

Translators serve a unique role in the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) user facility, offering scientific input through various leadership and service roles. The Translators direct the creation of value-added products (VAPs) and analysis tools that make ARM measurements more accessible to the scientific community. Translators also serve as liaisons between users and the ARM infrastructure, collecting information about priorities and communicating ARM data and services. A key group focus is supporting the DOE Atmospheric System Research (ASR) program scientists and ASR’s efforts towards a process-level understanding of cloud-aerosol interactions, and in reducing uncertainty in global climate model projections. The ARM Translator Group (Table 1) consists of the five Translators, a representative of software development, and one from the Data Quality Office (DQO). Additionally, the ARM Engineering and Process Manager participates in this group and provides input and direction from ARM and its programmatic priorities.

54 ENVIRONMENTAL SCIENCES↗

Implementation and testing of physics-based pulverization model in BISON

This report summarizes lower length scale computational research conducted to improve the pulverization criterion for high-burnup UO 2 fuel in the BISON fuel performance code. This research was sponsored by the NEAMS program during FY22. Efforts to improve the model primarily focus on calculating the current pressure of bubbles in the high-burnup structure (HBS) region, as well as the critical bubble pressure at which pulverization occurs in the HBS. The phase-field model for predicting initial bubble pressure in the HBS was improved by implementing a more realistic model for defect production, and by coupling the phase-field model for inter-granular bubble evolution with the spatially-resolved cluster dynamics code Xolotl to simulate intra-granular fission gas evolution. An evolution equation for current bubble pressure was added to BISON, an improvement over the previous model that assumed that bubble pressure was static following HBS formation. To improve calculations of critical bubble pressure for pulverization, 3-D phase-field fracture simulations were performed, and a function for critical bubble pressure was fit—based on the simulation results—to replace the previous function, which had been determined using 2-D simulations. The impacts of these modifications to the existing pulverization assessment cases will be reported in the forthcoming engineering scale milestone on high-burnup UO 2 pulverization. A poromechanics-based approach was used to include the effect of bubble over pressurization on the stress state of the pellet at the engineering scale, and the initial strategy for integration of the pulverization criterion with pellet-scale mechanical degradation using a smeared cracking model was developed. This report also describes the initial research that was conducted to inform a forthcoming transient fission gas release (tFGR) model in BISON. Focusing on the fission gas release caused by pulverization of the outer pellet rim, a model for the amount of fission gas release was developed as a function of fuel porosity, bubble size, and fragment size. Implementation of this model in BISON and its impact of engineering-scale predictions will also be described in the aforementioned engineering-scale milestone on high-burnup UO 2 pulverization.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗