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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 289 records · Page 16

GridDS: Data Science Toolkit for Energy Grid Data

According to the U.S. Energy Information Administration (EIA), the demand for energy is expected to increase 50% by the year 20501. While energy standards, such as the Institute of Electrical and Electronics Engineers (IEEE) Standard 1547, (Basso 2015) and monitoring with wide area management systems (WAMS) (Liu 2017, Zhou 2016) have enabled large scale data collection and storage, the application of this data in mitigating costs associated with increased consumer demand is an ongoing focus for energy research. This ubiquitous data collection presents a promising opportunity for machine learning and data science to improve efficiency of distributed energy resources (DERs). The GridDS software toolkit is designed to leverage advanced metering infrastructure (AMI), outage management systems data (OMS), Supervisory control Data Acquisition (SCADA), and geographic information systems (GIS) to forecast future energy demands and detect incipient grid failures. GridDS is a python software library designed to be modular and generalizable to data recorded by DERs. In adapting to disparate datasets recorded by various WAMS, GridDS provides a range of unique functionality not presently implemented in current WAMS which have highly specific software infrastructure by design. GridDS functionality ranges from data specification and preparation, to training and validation for state of the art machine learning, to interactive data visualization. For data intake, GridDS combines: Pandera: a library for creating data specifications. TimeScaleDB: a postgresSQL database infrastructure for efficient storage of timeseries data. Dataset class: A custom dataset class / interface that ensures modularity between a range of synthetic and live recorded datasets. Is

Ladd, Alexander↗

Near Term Reliability and Resilience: Revisiting Resilience Metrics for the Electric Grid

This report presents the metrics employed in the Near-Term Reliability and Resilience (NTRR) project to study the inter-dependencies between electric and natural gas infrastructures, particularly under challenging conditions. These metrics were developed and applied to evaluate the reliability and resilience of the electric grid and natural gas systems in near-term scenarios (within the next 10 years) involving extreme weather events and major supply disruptions. The report defines the metrics, explains how they are calculated, and describes the process by which they are used to evaluate reliability and resilience across simulated scenarios. It also demonstrates how the resilience metrics integrate with other project activities and summarizes the software tools deployed to calculate and visualize the results.

24 POWER TRANSMISSION AND DISTRIBUTION↗

CyRRL (Cyber Resilient Reinforcement Learning for grid voltage control) [SWR-24-115]

This codebase contains a multi-agent, actor-critic reinforcement learning implementation for cyber-resilient grid voltage control. It uses a 123-bus OpenDSS system as the environment, with three-phase power flow translating nodal power injections into solved nodal voltages. The reward function penalizes deviations from nominal voltage as well as reactive power dispatch, while encouraging agents to take actions that result in fast convergence to nominal conditions. The codebase models false data injection attacks and includes functionality for training, testing, hyper-parameter tuning, and visualization.

Murphy, Sinnott [National Renewable Energy Laborat↗

Xarray Climate Data Analysis Tools

xCDAT is an extension of xarray for climate data analysis on structured grids. It serves as a modern successor to the Community Data Analysis Tools (CDAT) library. Xarray is an "open source project and Python package that introduces labels in the form of dimensions, coordinates, and attributes on top of raw NumPy-like arrays, which allows for more intuitive, more concise, and less error-prone user experience. Xarray includes a large and growing library of domain-agnostic functions for advanced analytics and visualization with these data structures" (source: https://xarray.dev/). The goal of xCDAT is to provide generalizable features and utilities for simple and robust analysis of climate data. xCDAT's design philosophy is focused on reducing the overhead required to accomplish certain tasks in xarray. Some key xCDAT features are inspired by or ported from the core CDAT library, while others leverage powerful libraries in the xarray ecosystem (e.g., xESMF and cf_xarray) to deliver robust APIs.

Vo, Tom↗

NREL and SDG&E Collaboration to Support SDG&E Grid and Storage Efforts: Cooperative Research and Development Final Report, CRADA Number CRD-14-562

This project will enable effective utilization of high penetration of photovoltaics (PV) in islanded microgrids, increasing overall system efficiency, decreased fuel costs and resiliency of the overall system to help meet the SunShot goals of enhancing system integration methods to increase penetration of PV. National Renewable Energy Laboratory (NREL) will collaborate with San Diego Gas & Electric (SDG&E) to provide research and testing support to address their needs in energy storage sizing and placement, Integrated Test Facility (ITF) development, Real Time Digital Simulator (RTDS) Modeling and simulation support at ITF, Visualization and Virtual connection to Energy Systems Integration Facility (ESIF), and microgrid simulation and testing areas. Specifically in this project a real microgrid scenario with high penetration of PV (existing in SDG&E territory) is tested in the ESIF laboratory. Multiple control cases for firming PV using storage in a microgrid scenario will be investigated and tested in the laboratory setup.

14 SOLAR ENERGY↗

Use of Traveling Wave Signatures in Medium-Voltage Distribution Systems for Fault Detection and Location

Protection systems are a critical feature for the proper operation of a power grid. Protection systems should be able to quickly detect, identify, locate, and isolate the faults within a time frame that prevents damage to grid components and reduces customer outages. As more inverter-based photovoltaics (PV) are integrated into the grid, phasor domain based protection schemes become more inaccurate due to low levels of fault current from inverters or respond too slowly to accurately identify fault conditions. This points to the need to identify and develop novel protection approaches for distribution systems with high penetration of inverter based PV. The main objective of the project is to develop new time domain-based protection schemes to enable more accurate and faster detection, identification and location of faults in distribution systems and/or microgrids with high penetration of inverter-based PV. Our approach aims to exploit the traveling waves that are generated during a fault or other disturbances in the grid.

14 SOLAR ENERGY↗

Pass-efficient methods for compression of high-dimensional turbulent flow data

The future of high-performance computing, specifically on future Exascale computers, will presumably see memory capacity and bandwidth fail to keep pace with data generated, for instance, from massively parallel partial differential equation (PDE) systems. Current strategies proposed to address this bottleneck entail the omission of large fractions of data, as well as the incorporation of in situ compression algorithms to avoid overuse of memory. To ensure that post-processing operations are successful, this must be done in a way that a sufficiently accurate representation of the solution is stored. Moreover, in situations where the input/output system becomes a bottleneck in analysis, visualization, etc., or the execution of the PDE solver is expensive, the number of passes made over the data must be minimized. In the interest of addressing this problem, this work focuses on the utility of pass-efficient, parallelizable, low-rank, matrix decomposition methods in compressing high-dimensional simulation data from turbulent flows. Additionally, a particular emphasis is placed on using coarse representation of the data – compatible with the PDE discretization grid – to accelerate the construction of the low-rank factorization. This includes the presentation of a novel single-pass matrix decomposition algorithm for computing the so-called interpolative decomposition. The methods are described extensively and numerical experiments on two turbulent channel flow data are performed. In the first (unladen) channel flow case, compression factors exceeding 400 are achieved while maintaining accuracy with respect to first- and second-order flow statistics. In the particle-laden case, compression factors of 100 are achieved and the compressed data is used to recover particle velocities. These results show that these compression methods can enable efficient computation of various quantities of interest in both the carrier and disperse phases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The 2025 Evaluation of Experimental Thermonuclear Reaction Rates (ETR25)

This work describes the formalism for estimating thermonuclear reaction rates for astrophysical applications, emphasizing modern statistical approaches such as Monte Carlo sampling and Bayesian models. We discuss related topics including the calculation of resonance energies from nuclear Q values, indirect estimates of particle partial widths, and matching of reaction rates at elevated temperatures to statistical model results. We have evaluated available experimental data on cross sections, resonance energies and strengths, partial widths, lifetimes, spin-parities, and spectroscopic factors. Based on these results, we have estimated numerical values of 78 experimental charged-particle thermonuclear reaction rates for target nuclei in the A = 2–40 mass region, for temperatures ranging from 1 MK to 10 GK. For each reaction, three rate values are provided: low, median, and high, corresponding to the 16th, 50th, and 84th percentiles, respectively, of the cumulative reaction rate probability density distribution. Additionally, we present the factor uncertainty of each rate at each temperature grid point. These results enable users to sample the reaction rate probability density in nucleosynthesis calculations, facilitating uncertainty estimates of nuclidic abundances. The rates presented here refer to their laboratory values. For use in stellar model simulations, these values need to be corrected for the effects of thermal excitations of the interacting nuclei. For each reaction, we include graphs that illustrate the fractional contributions to the overall reaction rate along with the associated uncertainty. These visuals are designed to assist both stellar modelers and nuclear experimentalists by identifying the primary sources of rate uncertain=^texttx);ty at specific stellar temperatures. A graphical comparison with earlier Monte Carlo rates is also provided.

Nuclear astrophysics↗

Introduction of heat map to fidelity assessment of compressed CT images

Purpose: This study aimed to introduce heat map, a graphical data presentation method widely used in gene expression experiments, to the presentation and interpretation of image fidelity assessment data of compressed computed tomography (CT) images. Methods: The authors used actual assessment data that consisted of five radiologists' responses to 720 computed tomography images compressed using both Joint Photographic Experts Group 2000 (JPEG2000) 2D and JPEG2000 3D compressions. They additionally created data of two artificial radiologists, which were generated by partly modifying the data from two human radiologists. Results: For each compression, the entire data set, including the variations among radiologists and among images, could be compacted into a small color-coded grid matrix of the heat map. A difference heat map depicted the advantage of 3D compression over 2D compression. Dendrograms showing hierarchical agglomerative clustering results were added to the heat maps to illustrate the similarities in the data patterns among radiologists and among images. The dendrograms were used to identify two artificial radiologists as outliers, whose data were created by partly modifying the responses of two human radiologists. Conclusions: The heat map can illustrate a quick visual extract of the overall data as well as the entirety of large complex data in a compact space while visualizing the variations among observers and among images. The heat map with the dendrograms can be used to identify outliers or to classify observers and images based on the degree of similarity in the response patterns.

60 APPLIED LIFE SCIENCES↗

Historic Submarine Landslides in the Northern Gulf of Mexico

This dataset provides a set of polygons representing the zone of depletion for historic submarine landslides (also referred to as mass transport deposits) within four regions of the US Exclusive Economic Zone in the northern Gulf of Mexico. Landslides were digitized by geologists and spatial scientists at the National Energy Technology Laboratory by visually interpreting landslide boundaries from a seismic-derived, high resolution bathymetric hillshade provided by the Bureau of Ocean and Energy Management (BOEM, 2017). A portion of the landslide features are derived from other spatial sources including the Seismic Water Anomalies dataset by BOEM (2016) as well as from McAdoo et al., 2000 and Twichell et al, 2005. The scale that landslides depletion areas can be interpreted at is limited by the spatial resolution of the gridded bathymetry, which is 12.192 meters (BOEM, 2017). For each landslide feature in the dataset, geometry metrics were calculated including geodesic area (km2) and geodesic perimeter (km) using the North America Albers Equal Area Conic projected coordinate system. The same geometry metrics were calculated for the four inventory regions.

DOE↗

Spatiotemporal mapping of mesoscopic liquid dynamics

The study of liquid dynamics at mesoscopic scales is still strewn with difficulty due to limitations in theory and experiment. Historically, significant attention has been given to the analysis of space-time correlation functions and their frequency-Fourier transforms at a few discrete wave numbers. The massive computing power afforded by modern high performance computing clusters and the advent of a wide-angle neutron spin-echo spectrometer, however, have unlocked a more intuitive and fruitful approach to this problem. Using molecular dynamics simulations, here we demonstrate the benefits of spatiotemporally mapping intermediate scattering functions on a dense grid of correlation times and wave numbers. Four model systems are investigated: a Lennard-Jones liquid, a coarse-grained bead-spring polymer, a molten sodium chloride, and a poly(ethylene oxide) melt. We show that the spatiotemporal mapping approach is particularly useful for elucidating the mesoscopic dynamics in these liquids, where several underlying mechanisms, such as molecular relaxations, hydrodynamic modes, and nonhydrodynamic excitations, are potentially at play. Therefore, compared to the traditional method, direct visualization of density space-time correlation functions on two-dimensional color maps permits appraisals of complicated dynamical behavior at mesoscales in a global manner. For example, the scaling relations between space and time for different types of molecular motions can be straightforwardly identified on these plots, without any model-dependent analysis. Additionally, we show how theoretical ideas regarding collective mesoscopic dynamics, such as the classical hydrodynamic theory, the convolution approximation, and a recently proposed phenomenological model, can be discussed in terms of the global features of spatiotemporal maps of intermediate scattering functions. The new perspective offered by the spatiotemporal mapping method should prove useful for the study of liquid dynamics in general.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Numerical Analysis of Detonability Assessment in a Natural Gas-Air Fueled Rotating Detonation Engine

Rotating Detonation Engines (RDE) offer an alternative combustion strategy to replace conventional constant pressure combustion with a process that could produce a pressure gain without the use of a mechanical compressor. Recent numerical and experimental publications that consider air as the oxidizer have primarily focused on the ability of these annular combustors to sustain a stable continuous detonation wave when fueled by hydrogen. However, for this to be a viable consideration for the land-based power generation it is necessary to explore the ability to detonate natural gas and air within the confines of the annular geometry of an RDE. Previous studies on confined detonations have expressed the importance of permitting detonation cells to fully form within the combustor in order to achieve stability. This poses a challenge for natural gas–air fueled processes as their detonation cell size can be quite large even at moderate pressures. Despite the practical importance, only a few studies are available on natural gas detonations for air-breathing RDE applications. Moreover, the extreme thermodynamic condition (high temperature inside the combustor) allows limited accessibility inside the combustor for detailed experimental instrumentations, providing mostly single-point data. Recent experimental studies at the National Energy Technology Laboratory (NETL) have reported detonation failure at higher methane concentration in an air-breathing RDE fueled by natural gas-hydrogen fuel blends. This encourages to perform a detailed numerical investigation on the wave characteristics of detonation in a natural gas-air fueled RDE to understand the various aspects of instability associated with the natural gas-air detonation.This study is a numerical consideration of a methane-air fueled RDE with varying operating conditions to ascertain the ability to achieve a stable, continuous detonation wave. The simulations have been performed in a 2D unwrapped RDE geometry using the open-source CFD library “OpenFOAM” employing an unsteady pressure-based compressible reactive flow solver with a <em>k</em>–<em>ε</em> turbulence model in a structured rectangular grid system. Both reduced and detailed chemical kinetic models have been used to assess the effect of the chemistry on the detonation wave characteristics and the underlying flow features. A systematic grid sensitivity study has been conducted with various grid sizes to quantify the weakly stable overdriven detonation on a coarse mesh and oscillating features at fine mesh resolutions.The main focus of the current study is to investigate the effects of operating injection pressure on detonation wave characteristics of an air-breathing Rotating Detonation Engine (RDE) fueled with natural gas-hydrogen fuel blends. Wave speeds, peak pressures and temperatures, and dominant frequencies have been computed from the time histories. The flow structures were then visualized using 2D contours of temperature and species concentration.

Saha, Pankaj↗

SU-E-T-362: Automatic Catheter Reconstruction of Flap Applicators in HDR Surface Brachytherapy

Purpose: Catheter reconstruction is crucial for the accurate delivery of radiation dose in HDR brachytherapy. The process becomes complicated and time-consuming for large superficial clinical targets with a complex topology. A novel method for the automatic catheter reconstruction of flap applicators is proposed in this study. Methods: We have developed a program package capable of image manipulation, using C++class libraries of The-Visualization-Toolkit(VTK) software system. The workflow for automatic catheter reconstruction is: a)an anchor point is placed in 3D or in the axial view of the first slice at the tip of the first, last and middle points for the curved surface; b)similar points are placed on the last slice of the image set; c)the surface detection algorithm automatically registers the points to the images and applies the surface reconstruction filter; d)then a structured grid surface is generated through the center of the treatment catheters placed at a distance of 5mm from the patient's skin. As a result, a mesh-style plane is generated with the reconstructed catheters placed 10mm apart. To demonstrate automatic catheter reconstruction, we used CT images of patients diagnosed with cutaneous T-cell-lymphoma and imaged with Freiburg-Flap-Applicators (Nucletron™-Elekta, Netherlands). The coordinates for each catheter were generated and compared to the control points selected during the manual reconstruction for 16catheters and 368control point Results: The variation of the catheter tip positions between the automatically and manually reconstructed catheters was 0.17mm(SD=0.23mm). The position difference between the manually selected catheter control points and the corresponding points obtained automatically was 0.17mm in the x-direction (SD=0.23mm), 0.13mm in the y-direction (SD=0.22mm), and 0.14mm in the z-direction (SD=0.24mm). Conclusion: This study shows the feasibility of the automatic catheter reconstruction of flap applicators with a high level of positioning accuracy. Implementation of this technique has potential to decrease the planning time and may improve overall quality in superficial brachytherapy.

60 APPLIED LIFE SCIENCES↗

PR100 One-Year Progress Update: Preliminary Modeling Results and High-Resolution Solar and Wind Data Sets

The Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100) is a 2-year study by the U.S. Department of Energy's (DOE's) Grid Deployment Office and six national laboratories to comprehensively analyze stakeholder-driven pathways to Puerto Rico's clean energy future. In Year 1 of the study, the PR100 team rigorously modeled and analyzed scenarios that meet Puerto Rico's renewable energy targets and achieve short-term recovery goals and long-term energy resilience. This presentation will be showcased in the form of a public webinar, which summarizes PR100 progress in Year 1, provides considerations that can inform potential funding and implementation decisions by key federal and local agencies and stakeholders. The presentation follows the publication in July 2022 of a PR100 Six-Month Progress Update (in English and Spanish), as well as public webinars in February 2022 to kick off the study and in July 2022 to present the 6-month update. A final written report and web-based visuals will be published in late 2023. All publications and public events associated with the study will be available in Spanish and English. This report is also available in Spanish: https://www.nrel.gov/docs/fy23osti/85201.pdf.

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SU-C-17A-01: MRI-Based Radiotherapy Treatment Planning In Pelvis

Purpose: To support radiotherapy dose calculation, synthetic CT (MRCT) image volumes need to represent the electron density of tissues with sufficient accuracy. This study compares CT and MRCT for pelvic radiotherapy. Methods: CT and multi-contrast MRI acquired using T1- based Dixon, T2 TSE, and PETRA sequences were acquired on an IRBapproved protocol patient. A previously published method was used to create a MRCT image volume by applying fuzzy classification on T1- weighted and calculated water image volumes (air and fluid voxels were excluded using thresholds applied to PETRA and T2-weighted images). The correlation of pelvic bone intensity between CT and MRCT was investigated. Two treatment plans, based on CT and MRCT, were performed to mimic treatment for: (a) pelvic bone metastasis with a 16MV parallel beam arrangement, and (b) gynecological cancer with 6MV volumetric modulated arc therapy (VMAT) using two full arcs. The CT-calculated fluence maps were used to recalculate doses using the MRCT-derived density grid. The dose-volume histograms and dose distributions were compared. Results: Bone intensities in the MRCT volume correlated linearly with CT intensities up to 800 HU (containing 96% of the bone volume), and then decreased with CT intensity increase (4% volume). There was no significant difference in dose distributions between CT- and MRCTbased plans, except for the rectum and bladder, for which the V45 differed by 15% and 9%, respectively. These differences may be attributed to normal and visualized organ movement and volume variations between CT and MR scans. Conclusion: While MRCT had lower bone intensity in highly-dense bone, this did not cause significant dose deviations from CT due to its small percentage of volume. These results indicate that treatment planning using MRCT could generate comparable dose distributions to that using CT, and further demonstrate the feasibility of using MRI-alone to support Radiation Oncology workflow. NIH R01EB016079.

60 APPLIED LIFE SCIENCES↗

Efficient exascale discretizations: High-order finite element methods

Efficient exploitation of exascale architectures requires rethinking of the numerical algorithms used in many large-scale applications. These architectures favor algorithms that expose ultra fine-grain parallelism and maximize the ratio of floating point operations to energy intensive data movement. One of the few viable approaches to achieve high efficiency in the area of PDE discretizations on unstructured grids is to use matrix-free/partially assembled high-order finite element methods, since these methods can increase the accuracy and/or lower the computational time due to reduced data motion. In this paper we provide an overview of the research and development activities in the Center for Efficient Exascale Discretizations (CEED), a co-design center in the Exascale Computing Project that is focused on the development of next-generation discretization software and algorithms to enable a wide range of finite element applications to run efficiently on future hardware. CEED is a research partnership involving more than 30 computational scientists from two US national labs and five universities, including members of the Nek5000, MFEM, MAGMA and PETSc projects. We discuss the CEED co-design activities based on targeted benchmarks, miniapps and discretization libraries and our work on performance optimizations for large-scale GPU architectures. We also provide a broad overview of research and development activities in areas such as unstructured adaptive mesh refinement algorithms, matrix-free linear solvers, high-order data visualization, and list examples of collaborations with several ECP and external applications.

97 MATHEMATICS AND COMPUTING↗

Spatial assignment of symmetry adapted perturbation theory interaction energy components: The atomic SAPT partition

We develop a physically-motivated assignment of symmetry adapted perturbation theory for intermolecular interactions (SAPT) into atom-pairwise contributions (the A-SAPT partition). The basic precept of A-SAPT is that the many-body interaction energy components are computed normally under the formalism of SAPT, following which a spatially-localized two-body quasiparticle interaction is extracted from the many-body interaction terms. For electrostatics and induction source terms, the relevant quasiparticles are atoms, which are obtained in this work through the iterative stockholder analysis (ISA) procedure. For the exchange, induction response, and dispersion terms, the relevant quasiparticles are local occupied orbitals, which are obtained in this work through the Pipek-Mezey procedure. The local orbital atomic charges obtained from ISA additionally allow the terms involving local orbitals to be assigned in an atom-pairwise manner. Further summation over the atoms of one or the other monomer allows for a chemically intuitive visualization of the contribution of each atom and interaction component to the overall noncovalent interaction strength. Herein, we present the intuitive development and mathematical form for A-SAPT applied in the SAPT0 approximation (the A-SAPT0 partition). We also provide an efficient series of algorithms for the computation of the A-SAPT0 partition with essentially the same computational cost as the corresponding SAPT0 decomposition. We probe the sensitivity of the A-SAPT0 partition to the ISA grid and convergence parameter, orbital localization metric, and induction coupling treatment, and recommend a set of practical choices which closes the definition of the A-SAPT0 partition. We demonstrate the utility and computational tractability of the A-SAPT0 partition in the context of side-on cation-π interactions and the intercalation of DNA by proflavine. A-SAPT0 clearly shows the key processes in these complicated noncovalent interactions, in systems with up to 220 atoms and 2845 basis functions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

PR100 One-Year Progress Summary Report: Preliminary Modeling Results and High-Resolution Solar and Wind Data Sets

The Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100) is a 2-year study by the U.S. Department of Energy's (DOE's) Grid Deployment Office and six national laboratories to comprehensively analyze stakeholder-driven pathways to Puerto Rico's clean energy future. In Year 1 of the study, the PR100 team rigorously modeled and analyzed scenarios that meet Puerto Rico's renewable energy targets and achieve short-term recovery goals and long-term energy resilience. This report, which summarizes PR100 progress in Year 1, provides considerations that can inform potential funding and implementation decisions by key federal and local agencies and stakeholders. The summary report follows the publication in July 2022 of a PR100 Six-Month Progress Update (in English and Spanish), as well as public webinars in February 2022 to kick off the study and in July 2022 to present the 6-month update. A final written report and web-based visuals will be published in late 2023. All publications and public events associated with the study will be available in Spanish and English. This report is also available in Spanish https://www.nrel.gov/docs/fy23osti/85144.pdf.

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