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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 OSTI2020

Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment

Training neural networks for neuromorphic deployment is non-trivial. There have been a variety of approaches proposed to adapt back-propagation or back-propagation-like algorithms appropriate for training. Considering that these networks often have very different performance characteristics than traditional neural networks, it is often unclear how to set either the network topology or the hyperparameters to achieve optimal performance. In this work, we introduce a Bayesian approach for optimizing the hyperparameters of an algorithm for training binary communication networks that can be deployed to neuromorphic hardware. We show that by optimizing the hyperparameters on this algorithm for each dataset, we can achieve improvements in accuracy over the previous state-of-the-art for this algorithm on each dataset (by up to 15 percent). This jump in performance continues to emphasize the potential when converting traditional neural networks to binary communication applicable to neuromorphic hardware.

Parsa, Maryam↗
DOE OSTI2022

Real-World 20-Hz IBR Subsynchronous Oscillations: Signatures and Mechanism Analysis

This article provides analyses of subsynchronous oscillations associated with solar photovoltaics (PVs) observed in real world. All have oscillation frequencies at approximately 20 Hz in voltage and current magnitudes. On the other hand, in phase voltage and current, the oscillations show very different signatures. Through constructing simplified linear models and conducting sensitivity analysis, we are able to associate dynamic phenomena with the underlying mechanism and speculate the possible causes of the 20-Hz oscillations. The analysis results have all been validated via simulation results from electromagnetic transient (EMT) test beds constructed in MATLAB/Simscape.

inverter-based resources↗
DOE OSTI2025

Developing a Prototype Methodology to Rank CO2-EOR Wells and Assess Their Reuse Potential for Geologic Carbon Storage

This paper presents a prototype methodology to assess the possible transition of Class II carbon dioxide-enhanced oil recovery (CO2-EOR) wells to Class VI wells. The focus is on wellbore construction materials—casing, cement, tubing, and the packer—and includes comprehensive workflows to evaluate these materials, with primary emphasis on compliance with Environmental Protection Agency (EPA) Class VI well construction and conversion guidelines. These workflows systematically assess material properties and performance criteria to ensure regulatory compliance and optimize long-term wellbore integrity and functionality. Utilizing Python scripts and JavaScript Object Notation (JSON) representations, the study automates checks on digitized Texas Railroad Commission (TRRC) data to rank wells based on workflow criteria. By emphasizing critical factors such as casing integrity, cementing techniques, tubing compatibility, and packer selection, the methodology helps well owners and operators prioritize wells for potential reuse as CO2 injection wells. Given limitations in digitized data, manual user verification is required in some sections. Future improvements include integrating non-digitized data through web scraping and machine learning techniques. This research serves as a practical guide for stakeholders, supporting environmental compliance and sustainable well operations.

geologic carbon sequestration↗
DOE OSTI2021

Towards Predictive Plasma Science and Engineering through Revolutionary Multi-Scale Algorithms and Models (Final Report)

This report describes the high-level accomplishments from the Plasma Science and Engineering Grand Challenge LDRD at Sandia National Laboratories. The Laboratory has a need to demonstrate predictive capabilities to model plasma phenomena in order to rapidly accelerate engineering development in several mission areas. The purpose of this Grand Challenge LDRD was to advance the fundamental models, methods, and algorithms along with supporting electrode science foundation to enable a revolutionary shift towards predictive plasma engineering design principles. This project integrated the SNL knowledge base in computer science, plasma physics, materials science, applied mathematics, and relevant application engineering to establish new cross-laboratory collaborations on these topics. As an initial exemplar, this project focused efforts on improving multi-scale modeling capabilities that are utilized to predict the electrical power delivery on large-scale pulsed power accelerators. Specifically, this LDRD was structured into three primary research thrusts that, when integrated, enable complex simulations of these devices: (1) the exploration of multi-scale models describing the desorption of contaminants from pulsed power electrodes, (2) the development of improved algorithms and code technologies to treat the multi-physics phenomena required to predict device performance, and (3) the creation of a rigorous verification and validation infrastructure to evaluate the codes and models across a range of challenge problems. These components were integrated into initial demonstrations of the largest simulations of multi-level vacuum power flow completed to-date, executed on the leading HPC computing machines available in the NNSA complex today. These preliminary studies indicate relevant pulsed power engineering design simulations can now be completed in (of order) several days, a significant improvement over pre-LDRD levels of performance.

42 ENGINEERING↗
DOE OSTI2020

Powering the Blue Economy: Progress Exploring Marine Renewable Energy Integration With Ocean Observations

The blue economy is a dynamic and rapidly growing movement that captures the interplay between economic, social, and ecological sustainability of the ocean and encompasses numerous maritime sectors and activities (e.g., commerce and trade; living resources; renewable energy; minerals, materials, and freshwater; and ocean health and data). The demand for ocean data to inform scientific, risk reduction, and national security needs is leading to a large increase in the number of deployed ocean observation and monitoring systems, most of which require increased power. Because ocean observation systems are often placed in remote locations, they primarily rely on energy storage (or in some cases in situ energy generation) to power instruments and equipment, which imposes limits on sampling rates, deployment times, and spatiotemporal resolution of data. The U.S. Department of Energy Water Power Technologies Office is exploring the potential for marine renewable energy (MRE) devices (largely wave and tidal energy converters) to provide power to support multiple blue economy opportunities. A portion of these opportunities focus on power at sea markets for providing power in off-grid and offshore locations to support a variety of ocean-based activities, including ocean observation and navigation, underwater vehicle charging, marine aquaculture, marine algae farming, and seawater mining. Initially, research has focused on better understanding how and where MRE can provide a consistent source of reliable power to extend ocean observing missions, including operation of autonomous underwater vehicles. Online surveys as well as phone and inperson interviews were conducted with experts in the field of ocean observing systems and observatories to gather end-user requirements, determine energy needs, identify opportunities for codevelopment, and pinpoint constraints for MRE to meet those needs. The surveys and interviews provided feedback on the potential for powering devices and vehicles using MRE, including identifying common themes and challenges that will inform foundational research and development steps needed to advance the integration of MRE with ocean observing systems. In most cases, additional power generation on the order of watts was identified as significantly beneficial to enhancing ocean observations capabilities.

marine renewable energy, powering the blue economy↗
NASA NTRS2013

U.S. Spacesuit Legacy: Maintaining it for the Future

The history of U.S. spacesuit development and its use are rich with information on lessons learned, and constitutes a valuable legacy to those designing spacesuits for the future, as well as to educators, students, and the general public. The genesis of lessons learned is best understood by studying the evolution of past spacesuit programs - how the challenges and pressures of the times influenced the direction of the various spacesuit programs. This paper shows how the legacy of various spacesuit-related programs evolved in response to these forces. Important aspects of how this U.S. spacesuit legacy is being preserved today is described, including the archiving of spacesuit hardware, important documents, videos, oral history, and the rapidly expanding U.S. Spacesuit Knowledge Capture program.

Chullen, Cinda↗
DOE OSTI2021

Illuminating Galaxy Evolution at Cosmic Noon with ISCEA: the Infrared Satellite for Cosmic Evolution Astrophysics

ISCEA (Infrared Satellite for Cosmic Evolution Astrophysics) is a small astrophysics mission whose Science Goal is to discover how galaxies evolved in the cosmic web of dark matter at cosmic noon. Its Science Objective is to determine the history of star formation and its quenching in galaxies as a function of local density and stellar mass when the Universe was 3-5 Gyrs old (1.2 10 Mpc in each of 50 protocluster (cluster and cosmic web) fields at 1.2 < z < 2.1. ISCEA measures the star formation quenching factor in those fields, and galaxy kinematics with a precision < 50 km/s to deduce the 3D spatial distribution in each field. ISCEA will transform our understanding of galaxy evolution at cosmic noon. ISCEA is a small satellite observatory with a 30cm equivalent diameter aperture telescope with a FoV of 0.32 deg^2, and a multi-object spectrograph with a digital micro-mirror device (DMD) as its programmable slit mask. ISCEA will obtain spectra of 1000 galaxies simultaneously at an effective resolving power of R=1000, with 2.8"x2.8" slits, over the NIR wavelength range of 1.1 to 2.0 microns, a regime not accessible from the ground without large gaps in coverage. ISCEA will achieve a pointing accuracy of <= 2" FWHM over 200s. ISCEA will be launched into a Low Earth Orbit, with a prime mission of 2.5 years. ISCEA's space-qualification of DMDs opens a new window for spectroscopy from space, enabling revolutionary advances in astrophysics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Distributed reinforcement learning and consensus control of energy systems

Disclosed herein are methods, systems, and devices for utilizing distributed reinforcement learning and consensus control to most effectively generate and utilize energy. In some embodiments, individual turbines within a wind farm may communicate to reach a consensus as to the desired yaw angle based on the wind conditions.

King, Jennifer Rose Rose↗
DOE OSTI2020

Worldwide Population Estimates for Small Geographic Areas

This chapter discusses the basis for these population estimates, scope, and limitations based on experiences in development of massive global population datasets and usage of these datasets as a basis for sampling design. It presents tools and approaches for using these georeferenced population estimates for complex household survey sampling. The chapter provides a unified resource for understanding current gridded population datasets, their use in survey research, and promising areas of future work toward improved population estimates. It includes an overview of popular gridded population datasets, common methodological frameworks for developing gridded population estimates, and discusses pros and cons for selecting a gridded population dataset from a survey perspective. The chapter focuses on survey methods that use gridded population estimates specifically. It highlights differences between census population estimates and gridded population estimates that may be relevant when planning data collection. The chapter presents a case study of gridded population data and sampling methods in Nigeria.

Amer, Safaa↗
DOE OSTI2024

Distinguishing Elements at the Sub‐Nanometer Scale on the Surface of a High Entropy Alloy

Materials in crystalline form possess translational symmetry (TS) when the unit cell is repeated in real space with long- and short-range orders. The periodic potential in the crystal regulates the electron wave function and results in unique band structures, which further define the physical properties of the materials. Amorphous materials lack TS due to the randomization of distances and arrangements between atoms, causing the electron wave function to lack a well-defined momentum. High entropy materials provide another way to break the TS by randomizing the potential strength at periodic atomic sites. The local elemental distribution has a great impact on physical properties in high entropy materials. It is critical to distinguish elements at the sub-nanometer scale to uncover the correlations between the elemental distribution and the material properties. Here, the use of synchrotron X-ray scanning tunneling microscopy (SX-STM) with sub-nm scale resolution in identifying elements on a high entropy alloy (HEA) surface is demonstrated. By examining the elementally sensitive X-ray absorption spectra with an STM tip to enhance the spatial resolution, the elemental distribution on an HEA's surface at a sub-nm scale is extracted. In conclusion, these results open a pathway towards quantitatively understanding high entropy materials and their material properties.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Tomographic Volumetric Additive Manufacturing of Silica Glass with In Situ Error Calculation and Projection Tiling

The optical, thermal, and chemical properties of glass make it an ideal material for use in a wide range of applications, from optics and chemistry reactionware to consumer products. Tomographic volumetric additive manufacturing (tVAM) creates 3D objects by selectively gelling material within a rotating vial of photo-sensitive material by exposure to a series of tomographically-determined images. Here, in this study, tVAM is investigated for fabrication of complex, centimeter-scale, 3D silica glass parts. By optimizing the post-processing procedure, fully-dense glass parts with up to 2 cm 2 cross sectional area are achieved. The changes in optical properties during printing are leveraged for in situ metrology during printing, and the non-Newtonian nature of the glass-filled photoresin system to facilitate larger fabrication volumes via tiled projections. Printed structures are finally demonstrated for applications as MEMS components, optics, fluidics, and consumer products.

Materials science↗
DOE OSTI2022

Ultrastrong Coupling of Band‐Nested Excitons in Few‐Layer Molybdenum Disulphide

Abstract The 2D transition‐metal dichalcogenides (2D TMDCs) are an intriguing platform for studying strong light–matter interactions because they combine the electronic properties of conventional semiconductors with the optical resonances found in organic systems. However, the coupling strengths demonstrated in strong exciton–polariton coupling in the 2D TMDCs remain much lower than those found in organic systems. In this paper, a new approach is taken by utilizing the large oscillator strength of the above‐band gap C exciton in few‐layer molybdenum disulphide (FL‐MoS 2 ). A k ‐space Rabi splitting of 293 meV is shown when coupling FL‐MoS 2 C excitons to surface plasmon polaritons at room temperature. This value is 11% of the uncoupled exciton energy (2.67 eV or 464 nm), ≈2× what is typically seen in the TMDCs, placing the system in the ultrastrong coupling regime. The results take a step toward finally achieving the efficient quantum coherent processes of ultrastrong coupling in a CMOS‐compatible system—the 2D TMDCs—in the visible spectrum.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Triggering C-N Coupling on Metal Oxide Nanocomposite for the Electrochemical Reduction of CO 2 and NO x ⁻ to Formamide

The co-electroreduction of CO 2 and NO x ⁻ (NO 3 ⁻ /NO 2 ⁻ ) to generate formamide (HCONH 2 ) offers an opportunity for downstream chemical and polymer manufacturing decarbonization; however, significant challenges lie in the C-N coupling and the associated low product selectivity. Herein, p-block metal oxides are incorporated in copper oxides to provide more accessible active sites for reactant adsorption and activation, tuning the reaction selectivity toward the formamide production. Through in situ Raman and synchrotron-based infrared spectroscopy measurements, C-N bond formation is demonstrated in real-time with the CuO x /BiO x catalyst, where the C-N bond is detected via a *CHO and *NH 2 intermediates formation, in agreement with the density functional theory calculations. When tested in a flow electrolyzer, a formamide yield rate of 134 ± 11 mmol h -1 g cat -1 is reported, the first report of co-electroreduction of CO 2 and NO x ⁻ to formamide beyond conventional H-cell measurements. These new insights on the C-N coupling mechanisms and scale-up capability provide directions for further development of electrocatalysts for the formamide production.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Behavioral and neuroinflammatory changes caused by glyphosate: Base herbicide in mice offspring

Abstract Background Glyphosate is a pesticide considered of low toxicity, but scientific evidences show it can be harmful to health. This study aimed to evaluate the toxicity in mice offspring exposed to glyphosate‐based herbicide (GBH) during the intrauterine period. Methods Female matrices received glyphosate 0.3 mg/kg daily per oral throughout the gestational period, which was variable between 18 and 22 days. From the 25th until the 28th days post‐birth, mice offspring were subjected to behavioral tests, and the prefrontal cortex was processed for immunohistochemical analysis. Results Two significant behavioral changes were observed: anxiety in the GLIF0.3 group, increase in the behavior burying marbles in the marble‐burying test and hyperactivity, expressed by the significant increase of the crossing number in the open field test. The increased microglia, TNF‐alpha, and astrocyte expression were also observed in the prefrontal cortex of offspring treated with GLIF0.3. Conclusion Exposure to GBH during mice intrauterine development induces hyperactive and anxious behavior, evidencing neuroinflammation.

de Castro Vieira Carneiro, Carla Larissa↗