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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 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

3-D Geologic Controls of Hydrothermal Fluid Flow at Brady Geothermal Field, Nevada using PCA

In many hydrothermal systems, fracture permeability along faults provides pathways for groundwater to transport heat from depth. Faulting generates a range of deformation styles that cross-cut heterogeneous geology, resulting in complex patterns of permeability, porosity, and hydraulic conductivity. Vertical connectivity (a through going network of permeable areas that allows advection of heat from depth to the shallow subsurface) is rare and is confined to relatively small volumes that have highly variable spatial distribution. This local compartmentalization of connectivity represents a significant challenge to understanding hydrothermal circulation and for exploring, developing, and managing hydrothermal resources. Here, we present an evaluation of the geologic characteristics that control this compartmentalization in hydrothermal systems through 3-D analysis of the Brady geothermal field in western Nevada. A published 3-D geologic map of the Brady area is used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity. The 3-D distribution of these variables is compared to the distribution of productive and non-productive fluid flow intervals along production wells and non-productive wells via principal component analysis (PCA). This comparison elucidates which geologic and structural variables are most closely associated with productive fluid flow intervals. Results indicate that production intervals at Brady are located: (1) within or near to known and stress-loaded macro-scale faults, and (2) in areas of high fault and fracture density. This submission includes the published journal article detailing this work, the published 3-D geologic map of the Brady Geothermal Area used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity, 3-D well data, along which geologic data were sampled for PCA analyses, and associated metadata file. This work was done using existing R programs.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

LoVoCCS. II. Weak Lensing Mass Distributions, Red-sequence Galaxy Distributions, and Their Alignment with the Brightest Cluster Galaxy in 58 Nearby X-Ray-luminous Galaxy Clusters

The Local Volume Complete Cluster Survey is an ongoing program to observe nearly a hundred low-redshift X-ray-luminous galaxy clusters (redshifts 0.03 < z < 0.12 and X-ray luminosities in the 0.1–2.4 keV band L X500c > 10 44 erg s −1 ) with the Dark Energy Camera, capturing data in the u, g, r, i, z bands with a 5σ point source depth of approximately 25th–26th AB magnitudes. Here, we map the aperture masses in 58 galaxy cluster fields using weak gravitational lensing. These clusters span a variety of dynamical states, from nearly relaxed to merging systems, and approximately half of them have not been subject to detailed weak lensing analysis before. In each cluster field, we analyze the alignment between the 2D mass distribution described by the aperture mass map, the 2D red-sequence (RS) galaxy distribution, and the brightest cluster galaxy (BCG). We find that the orientations of the BCG and the RS distribution are strongly aligned throughout the interiors of the clusters: the median misalignment angle is 19° within 2 Mpc. We also observe the alignment between the orientations of the RS distribution and the overall cluster mass distribution (by a median difference of 32° within 1 Mpc), although this is constrained by galaxy shape noise and the limitations of our cluster sample size. These types of alignment suggest long-term dynamical evolution within the clusters over cosmic timescales.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Phenomenology of the Prethermal Many-Body Localized Regime

The dynamical phase diagram of interacting disordered systems has seen substantial revision over the past few years. Theory must now account for a large prethermal many-body localized regime in which thermalization is extremely slow, but not completely arrested. We derive a quantitative description of these dynamics in short-ranged one-dimensional systems using a model of successive many-body resonances. Here, the model explains the decay timescale of mean autocorrelators, the functional form of the decay—a stretched exponential—and relates the value of the stretch exponent to the broad distribution of resonance timescales. The Jacobi method of matrix diagonalization provides numerical access to this distribution, as well as a conceptual framework for our analysis. The resonance model correctly predicts the stretch exponents for several models in the literature. Successive resonances may also underlie slow thermalization in strongly disordered systems in higher dimensions, or with long-range interactions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Enabling Data Exchange and Data Integration with the Common Information Model: An Introduction for Power Systems Engineers and Application Developers

The Common Information Model (CIM) is an open-source information model that is used to model an electrical network and the various equipment used on the network. CIM is widely used for data exchange of bulk transmission power systems and is finding increasing use for distribution systems. Use of a non-proprietary information model (such as CIM) that has been agreed upon and adopted by numerous utilities, vendors, and researchers allows significant reduction in the effort and cost of data integration. Likewise, adoption of open data platforms built around the CIM increases available functionalities for managing and optimizing the smart grid of the future. This report is intended as an introduction to CIM for utility engineers, power systems researchers, and application developers, providing a broad view of the CIM and how particular profiles can be adapted for various use cases. Unlike most other CIM introduction documents and the International Electrotechnical Commission (IEC) standards (which are mostly targeted to an audience of data scientists, enterprise database managers, and platform developers), this report is intended for users of traditional power systems analysis software and other readers without any prior experience with canonical information models, data profiles, or UML modeling.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Cost Reduction of School Bus Fleet Electrification With Optimized Charging and Distributed Energy Resources: Preprint

Considerations for electrifying school buses are presented with an analysis of battery sizing to match bus driving requirements. The charging and vehicle-to-building dispatch of the electric school buses were optimized to evaluate the potential to reduce the impact of the bus charging on the school's electric utility bill. Distributed energy resources (DER) and flexible building loads were also considered with the school bus electrification to evaluate the further reduction in energy costs with enhanced system integration and optimized dispatch. The effect of degradation on the school bus batteries was analyzed to determine if the smart charging and vehicle-to-building battery operation decreases the life of the battery. The results show that there is an opportunity to mitigate the increase of electric utility bills with improved charging controls and bi-directionally operating the school bus batteries to reduce building demand charges. The battery degradation analysis using dispatch with optimized charging and discharging shows acceptable battery life.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Big Data Analysis of Massive PMU Datasets: A Data Platform Perspective

The discovery of `event signatures' and useful insights from very large historical Phasor Measurement Unit (PMU) datasets is predicated on offline Big Data analysis approaches that rely on the generation of predictive features on a massive scale. This paper presents lessons learned from a data platform perspective towards reducing barriers to adoption of Big Data analytics against a real dataset of almost half a trillion data points drawn from over 400 PMUs distributed across the North American power grid. We demonstrate software abstractions and targeted performance optimizations that can lead to significant productivity gains for power systems researchers seeking to perform offline exploratory temporal analysis and modeling tasks, with a focus on feature generation. We describe how our optimized approach goes beyond a naive application of mainstream Big Data technologies, enabling feature generation tasks, that previously took days or even weeks, to now be completed in just a few hours.

Kumar, Vijay S.↗
DOE OSTI2024

Role of Intermolecular Interactions in Deep Eutectic Solvents for CO 2 Capture: Vibrational Spectroscopy and Quantum Chemical Studies

Recent research and reviews on CO 2 capture methods, along with advancements in industry, have highlighted high costs and energy-intensive nature as the primary limitations of conventional direct air capture and storage (DACS) methods. In response to these challenges, deep eutectic solvents (DESs) have emerged as promising absorbents due to their scalability, selectivity, and lower environmental impact compared to other absorbents. However, the molecular origins of their enhanced thermal stability and selectivity for DAC applications have not been explored before. Therefore, the current study focuses on a comprehensive investigation into the molecular interactions within an alkaline DES composed of potassium hydroxide (KOH) and ethylene glycol (EG). Combining Fourier transform infrared (FT-IR) and quantum chemical calculations, the study reports structural changes and intermolecular interactions induced in EG upon addition of KOH and its implications on CO 2 capture. Experimental and computational spectroscopic studies confirm the presence of noncovalent interactions (hydrogen bonds) within both EG and the KOH-EG system and point to the aggregation of ions at higher KOH concentrations. Additionally, molecular electrostatic potential (MESP) surface analysis, natural bond orbital (NBO) analysis, quantum theory of atoms-in-molecules (QTAIM) analysis, and reduced density gradient-noncovalent interaction (RDG-NCI) plot analysis elucidate changes in polarizability, charge distribution, hydrogen bond types, noncovalent interactions, and interaction strengths, respectively. Evaluation of explicit and hybrid models assesses their effectiveness in representing intermolecular interactions. This research enhances our understanding of molecular interactions in the KOH-EG system, which are essential for both the absorption and desorption of CO 2 . The study also aids in predicting and selecting DES components, optimizing their ratios with salts, and fine-tuning the properties of similar solvents and salts for enhanced CO 2 capture efficiency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Residential Vehicle-to-Home Backup Power Capabilities: Key Findings from a ComEd Beneficial Electrification R&D Pilot

This report summarizes key findings from a collaborative technical study of residential, non-grid-tied vehicle-to-home (V2H) backup power systems in Commonwealth Edison’s (ComEd’s) service territory. The work integrates (1) a feeder-level technoeconomic analysis (TEA) using historical outage-event data and simulated electric-vehicle (EV) driving/charging profiles to estimate potential reliability and customer interruption-cost impacts under V2H and vehicle-to-grid (V2G) adoption scenarios; (2) controlled laboratory performance testing of a representative V2H backup ecosystem to characterize transfer-to-backup behavior, sustained power delivery, efficiency trends, and repeatable reliability limitations; and (3) a cybersecurity assessment aligned with NIST Cybersecurity Framework (CSF) 2.0 and ISO/SAE 21434 to evaluate interface-level risk drivers and identify program-relevant mitigations. Results indicate that V2H can provide measurable resilience value, but outcomes are strongly context dependent on outage patterns and the share of events that are “V2H-applicable.” Typical transfer-to-backup behavior clustered on the order of minutes, but rare long-delay edge cases were observed (including an event approaching 30 minutes) and should be treated as a reliability risk. High-power testing showed that peak-rated output is not necessarily continuously deliverable; stable operation may require operation below nameplate ratings and attention to thermal and installation constraints. The cybersecurity assessment highlights a broad attack surface spanning commissioning, home networks, embedded services, and cloud/OTA pathways, motivating minimum controls for secure onboarding, signed updates, patch cadence, and coordinated vulnerability response for any scaled deployment.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

The data acquisition system of the LZ dark matter detector: FADR

The Data Acquisition System (DAQ) for the LUX-ZEPLIN (LZ) dark matter detector is described. The signals from 745 PMTs, distributed across three subsystems, are sampled with 100-MHz 32-channel digitizers (DDC-32s). A basic waveform analysis is carried out on the on-board Field Programmable Gate Arrays (FPGAs) to extract information about the observed scintillation and electroluminescence signals. This information is used to determine if the digitized waveforms should be preserved for offline analysis. The system is designed around the Kintex-7 FPGA. In addition to digitizing the PMT signals and providing basic event selection in real time, the flexibility provided by the use of FPGAs allows us to monitor the performance of the detector and the DAQ in parallel to normal data acquisition. Furthermore, the hardware and software/firmware of this FPGA-based Architecture for Data acquisition and Realtime monitoring (FADR) are discussed and performance measurements are described.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Dynamic Building Load Control to Facilitate High Penetration of Solar Photovoltaic Generation (Final Technical Report)

Solar photovoltaic (PV) resources are the most common form of distributed generation in residential and commercial customer premises within electric distribution networks. A higher penetration of PV generation in distribution circuits will impose challenges on maintaining service voltages within the range of industry standards, power quality, and power flow. Buildings consume 74% of the electricity produced in the United States, and a significant portion of the building load is dispatchable, making them responsive to electrical grid needs. Oak Ridge National Laboratory—in collaboration with Southern Company; the University of Tennessee, Knoxville; and the Georgia Institute of Technology—is examining the PV integration issues in distribution-level electrical grids and developing integrated demand-side control and communication systems to enable responsive loads. The proposed responsive loads mechanism performs renewable generation following to increase the penetration of solar PV within each feeder. The specific objectives of this project are to (1) examine distribution-level PV integration scenarios to understand requirements, (2) undertake an end-to-end simulation-based design of a distributed control strategy of loads geographically near the PV generation asset to minimize the effect on the distribution feeder, (3) deploy and demonstrate the control technology developed in partnership with utilities, and (4) perform a scalability analysis at the utility scale. This 3-year integrated project aims to develop, demonstrate, and validate demand-side control technology to enable increased the penetration of renewables while mitigating challenges that arise due to their intermittency. Activities in Budget Period (BP) 1 focused on a literature review and the formal design of a control system for integrating local distribution with generation and loads. The team used modeling and simulation to evaluate the impact of varying buildings loads, variable PV generation, and power flow dynamics on the distribution circuit. The dynamic models developed in BP 1 were used in BP 2 to develop a model-based control design and a test bed. The test bed has enabled the simulation-based testing and comparison of different control designs and formulations applied to different configurations of the distribution grid, PVs, and building loads. The control approaches developed in BP 2 were implemented in BP 3 in the form of hardware deployed at the Central Baptist Church (CBC) in Knoxville, Tennessee, for testing and evaluation. The outcome of this project was the development and demonstration of open-source, low-cost, low-touch sensing and control retrofits to distributed PV generation and building loads that, in a coordinated fashion, provide the load-shaping response needed to integrate high levels of renewable penetration. This research addresses the target metrics by dynamically controlling a load with solar generation variability to minimize the extent of two-way power flow, enhance reliability, facilitate high PV penetration (>100% of peak load in a line segment), and generate scalable software and hardware solutions adaptable to any penetration levels. The research and development activities are focused and designed to be impactful within the relevant 2020 targets time frame.An accurate open-source integration simulation framework for end-to-end control design was developed and deployed at the CBC facility for testing and evaluation. This final report provides a detailed review of the technical results achieved during this 3-year integrated project. A novel spectral analysis of PV data is demonstrated to derive the requirements of the control design. A detailed simulation-based analysis of PV integration at increasing penetration levels is presented using 1 year of PV data to demonstrate the impact on the distribution circuits. Two different control strategies were developed and demonstrated via simulation to track variable PV generation with adaptive load dispatch. The report concludes with a summary of accomplishments and recommendations for a path forward.

14 SOLAR ENERGY↗
DOE OSTI2026

Affine Transformations to Correlate Experimental and Simulated EDS Spectra for Multi-Element Systems

Energy Dispersive X-ray Spectroscopy (EDS) is an essential technique for determining elemental concentrations and distributions within microstructures, critical for materials discovery, optimization, and qualification. However, most published EDS data is qualitative because current quantitative EDS analysis methods require extensive calibration and post-processing, limiting their practicality and widespread adoption. This work seeks to establish a framework for accelerated EDS characterization and spectrum analysis that can leverage ML to analyze correlations between various elemental compositions and resulting EDS spectra. The complex physics and data result in a high-dimensional problem that grows exponentially with the number of elements in the system and the complexity of the spectrum analysis. ML provides a way to compute and optimize the results of this highly dimensional problem in a flexible way to tailor it to the user’s specific needs and material system. However, the framework emphasizes transparency through a strictly mathematical affine transformation, so the analysis remains understandable and reviewable to facilitate adoption by the scientific community. While currently implemented methods are simplistic and unvalidated, further development and demonstration of this framework could enable high-throughput, accurate, and accessible EDS characterization.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

SBbadger: biochemical reaction networks with definable degree distributions

Abstract Motivation An essential step in developing computational tools for the inference, optimization and simulation of biochemical reaction networks is gauging tool performance against earlier efforts using an appropriate set of benchmarks. General strategies for the assembly of benchmark models include collection from the literature, creation via subnetwork extraction and de novo generation. However, with respect to biochemical reaction networks, these approaches and their associated tools are either poorly suited to generate models that reflect the wide range of properties found in natural biochemical networks or to do so in numbers that enable rigorous statistical analysis. Results In this work, we present SBbadger, a python-based software tool for the generation of synthetic biochemical reaction or metabolic networks with user-defined degree distributions, multiple available kinetic formalisms and a host of other definable properties. SBbadger thus enables the creation of benchmark model sets that reflect properties of biological systems and generate the kinetics and model structures typically targeted by computational analysis and inference software. Here, we detail the computational and algorithmic workflow of SBbadger, demonstrate its performance under various settings, provide sample outputs and compare it to currently available biochemical reaction network generation software. Availability and implementation SBbadger is implemented in Python and is freely available at https://github.com/sys-bio/SBbadger and via PyPI at https://pypi.org/project/SBbadger/. Documentation can be found at https://SBbadger.readthedocs.io. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Computational study of the adsorption of bimetallic clusters on alumina substrate

We performed computational investigation of the adsorption of bimetallic Pd 3 M 2 (where M changes from Ag, Au, Co, Cu, Mn, Ni, Pt, and Ru) cluster on the hydroxylated alumina surface. Previously, it was shown that small silver cluster can control the rate of discharge at the cathode of lithium-oxygen battery. The gap near the fermi energy was shown to control the oxygen reduction, an important reaction for LiO 2 formation. Controlling the gap would ultimately control the rate of LiO 2 formation. One can vary the size of the cluster to vary the gap, however, this "knob" provides limited variance in the gap. Alloying, in combination with size variation offer a much wider control of the gap, hence the LiO 2 formation. Using Density Functional Theory (DFT), we determined the most stable geometry of the bimetallic clusters Pd 3 M 2 and calculated the binding energies of these clusters on the alumina substrate which ranges from 0.2 eV to 0.25 eV depending upon the composition of the alloy-cluster, its orientation and the adsorption site. We also find that Pd atoms bind strongly with the substrate oxygen atoms with an average short bond-length of about 2.2 angstrom. We explored how the gap at the Fermi level of the system varies as a function of elemental composition and the calculated gap ranges from 0 meV to 90 meV. Charges distribution using Bader analysis was also performed to probe how charges are transferred between the cluster and the substrate. These preliminary results will open the door for more systematic studies of alloy clusters of different size and stoichiometry for Li-O 2 battery cathode design.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Real-World Cyber Security Demonstration for Networked Electric Drives

In this article, we present the design and implementation of a cyber-physical security testbed for networked electric drive systems, aimed at conducting real-world security demonstrations. To our knowledge, this is one of the first security testbeds for networked electric drives, seamlessly integrating the domains of power electronics and computer science, and cybersecurity. By doing so, the testbed offers a comprehensive platform to explore and understand the intricate and often complex interactions between cyber and physical systems. The core of our testbed consists of four electric machine drives, meticulously configured to emulate small-scale but realistic information technology (IT) and operational technology (OT) networks. This setup both provides a controlled environment for simulating a wide array of cyber-attacks, and mirrors potential real-world attack scenarios with a high degree of fidelity. The testbed serves as an invaluable resource for the study of cyber-physical security, offering a practical and dynamic platform for testing and validating cybersecurity measures in the context of networked electric drive systems. As a concrete example of the testbed's capabilities, we have developed and implemented a Python-based script designed to execute step-stone attacks over a wireless local area network (WLAN). This script leverages a sequence of target IP addresses, simulating a real-world attack vector that could be exploited by adversaries. To counteract such threats, we demonstrate the efficacy of our developed cyber-attack detection algorithms, which are integral to our testbed's security framework. Furthermore, the testbed incorporates a real-time visualization system using InfluxDB and Grafana, providing a dynamic and interactive representation of networked electric drives and their associated security monitoring mechanisms. This visualization component not only enhances the testbed's usability but also offers insightful, real-time data for researchers and practitioners, thereby facilitating a deeper understanding of cyber-physical security dynamics in networked electric drive systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Efficient Topology Design Algorithms for Power Grid Stability

The dynamic response of power grids to small disturbances influences their overall stability. This letter examines the effect of network topology on the linearized time-invariant dynamics of electric power systems. The proposed framework utilizes H 2 -norm based stability metrics to study the optimal placement of lines on existing networks as well as the topology design of new networks. The design task is first posed as an NP-hard mixed-integer nonlinear program (MINLP) that is exactly reformulated as a mixed-integer linear program (MILP) using McCormick linearization. To improve computation time, graph-theoretic properties are exploited to derive valid inequalities (cuts) and tighten bounds on the continuous optimization variables. Moreover, a cutting plane generation procedure is put forth that is able to interject the MILP solver and augment additional constraints to the problem on-the-fly. Finally, the efficacy of our approach in designing optimal grid topologies is demonstrated through numerical tests on the IEEE 39-bus network.

24 POWER TRANSMISSION AND DISTRIBUTION↗