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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Grid-scale Energy Storage Hazard Analysis & Design Objectives for System Safety

Battery based energy storage systems are becoming a critical part of a modernized, resilient power system. However, batteries have a unique combination of hazards that can make design and engineering of battery systems difficult. This report presents a systematic hazard analysis of a hypothetical, grid scale lithium-ion battery powerplant to produce sociotechnical "design objectives" for system safety. We applied system's theoretic process analysis (STPA) for the hazard analysis which is broken into four steps: purpose definition, modeling the safety control structure, identifying unsafe control actions, and identifying loss scenarios. The purpose of the analysis was defined as to prevent event outcomes that can result in loss of battery assets due to fires and explosions, loss of health or life due to battery fires and explosions, and loss of energy storage services due to non- operational battery assets. The STPA analysis resulted in identification of six loss scenarios, and their constituent unsafe control actions, which were used to define a series of design objectives that can be applied to reduce the likelihood and severity of thermal events in battery systems. These design objectives, in all or any subset, can be utilized by utilities and other industry stakeholders as "design requirements" in their storage request for proposals (RFPs) and for evaluation of proposals. Further, these design objectives can help to protect firefighters and bring a system back to full functionality after a thermal event. We also comment on the hazards of flow battery technologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Helpful Engineering's Universal Citizen Protection Device (UCPD)

The Universal Citizen Protection Device (UCPD) is a UV-based, filterless PPE concept developed by Helpful Engineering that aims to keep viral particles out of eyes, nose and mouth with a 99%+ reliability. The heart of the device is a concealed UV chamber that decontaminates all air going in and out of the PPE. The objective of this project was to provide measurements as evidence of proof of function of a representative prototype. Sandia utilized its aerosol characterization facility to measure the amount of virus that is inactivated by the device at representative flow rates and concentrations, using MS2 bacteriophage as the BSL-1 viral surrogate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Efficient Implementation of Artificial Neural Networks for Sensor Data Analysis Based on a Genetic Algorithm

The reliability of many industrial processes depends on the sensor system. However, these sensors can be affected by noise, perturbations and failures. Hence, sensor monitoring and diagnosis are fundamental to guarantee the quality of an industrial process. Nowadays, artificial neural networks (ANN) are widely used in sensor signal processing and diagnosis. However, those ANNs usually require many artificial neurons, being difficult to implement in software and hardware due to their high computational costs. This paper presents an optimized implementation of artificial neurons in ANNs for sensor data analysis using a Genetic Algorithm (GA). The objective of GA is to find an adequate segmentation to reduce the activation function approximation error. One of the advantages of the proposed approach is that the cost function used in GA considers the effect of factors such as the ANN architecture or the number of bits used in arithmetic operations. The proposed ANN implementation technique aims to get the best possible approximation for a specific ANN architecture, making easier its implementation in software and hardware. Simulation and experimental results using FPGA (Field Programmable Gate Array) prove the advantages of the proposed approach for implementing sensor data analysis systems based on ANNs.

D estefani, André↗
DOE OSTI2024

Collapse of neutrino wave functions under Penrose gravitational reduction

Models of spontaneous wave function collapse have been postulated to address the measurement problem in quantum mechanics. Their primary function is to convert coherent quantum superpositions into incoherent ones, with the result that macroscopic objects cannot be placed into widely separated superpositions for observably prolonged times. Many of these processes will also lead to loss of coherence in neutrino oscillations, producing observable signatures in the flavor profile of neutrinos at long travel distances. The majority of studies of neutrino oscillation coherence to date have focused on variants of the continuous state localization model, whereby an effective decoherence strength parameter is used to model the rate of coherence loss with an assumed energy dependence. Another class of collapse models that have been proposed posit connections to the configuration of gravitational field accompanying the mass distribution associated with each wave function that is in the superposition. A particularly interesting and prescriptive model is Penrose’s description of gravitational collapse which proposes a decoherence time τ determined through E g τ ∼ ℏ , where E g is a calculable function of the Newtonian gravitational potential. Here we explore application of the Penrose collapse model to neutrino oscillations, reinterpreting previous experimental limits on neutrino decoherence in terms of this model. We identify effects associated with both spatial collapse and momentum diffusion, finding that the latter is ruled out in data from the IceCube South Pole Neutrino Observatory so long as the neutrino wave packet width at production is σ ν , x ≤ 2 × 10 − 12 m . Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2020

The Kalai-Smorodinsky solution for many-objective Bayesian optimization

An ongoing aim of research in multiobjective Bayesian optimization is to extend its applicability to a large number of objectives. While coping with a limited budget of evaluations, recovering the set of optimal compromise solutions generally requires numerous observations and is less interpretable since this set tends to grow larger with the number of objectives. We thus propose to focus on a specific solution originating from game theory, the Kalai-Smorodinsky solution, which possesses attractive properties. In particular, it ensures equal marginal gains over all objectives. We further make it insensitive to a monotonic transformation of the objectives by considering the objectives in the copula space. A novel tailored algorithm is proposed to search for the solution, in the form of a Bayesian optimization algorithm: sequential sampling decisions are made based on acquisition functions that derive from an instrumental Gaussian process prior. Our approach is tested on four problems with respectively four, six, eight, and nine objectives. The method is available in the R package GPGame available on CRAN at https://cran.r-project.org/package=GPGame.

Game theory↗
DOE OSTI2020

Operating Procedure Extender For Novel Systems

Operating procedures that are used in nuclear power plants are primarily paper. These paper documents are functional for normal operations, but the process has remained relatively unchanged for thirty years. This neglects the digital technology advancements that have been made in that time. There are objectively more efficient ways to present a procedure to an operator using a digital interface. These digital interfaces require structured information to be able to function. This tool takes the procedure that has been written and converts it into the structured from required by the presentation system. This is accomplished through a reliable four phase compilation algorithm.

Lehmer, Jacob P↗
DOE OSTI2021

Remote collaboration methods and systems

Apparatus and associated methods relate to immersive collaboration based on configuring a real scene VRE operable from a real scene and a remote VRE operable remote from the real scene with an MR scene model of the real scene, creating an MR scene in each of the real scene VRE and remote VRE based on augmenting the MR scene model with an object model, calibrating the remote MR scene to correspond in three-dimensional space with the real scene MR scene model, and automatically providing immersive collaboration based on the MR scene in the remote VRE and updating the real scene VRE with changes to the remote VRE. In an illustrative example, the MR scene model of the real scene may be determined as a function of sensor data scanned from the real scene. In some embodiments, the MR scene model may be augmented with an object model identified from the real scene. The object model identified from the real scene may be, for example, selected from a known object set based on matching sensor data scanned from the real scene with an object from a known object set. In some embodiments, the remote MR scene may be calibrated based on applying a three-dimensional transform calculated as a function of the real MR scene and remote MR scene geometries. Some designs may recreate a subset of the real scene in the remote VRE and update the real scene VRE with changes to the remote VRE. Various embodiments may advantageously provide seamless multimedia collaboration based on updates to the remote VRE in response to physical changes to the real scene, and updating the real scene VRE in response to changes in the remote VRE.

Neeter, Eduardo J.↗
DOE OSTI2020

The Sizes of z ∼ 9−10 Galaxies Identified in the Brightest of Reionizing Galaxies (BoRG) Survey

Redshift z = 9–10 object selection is the effective limit of Hubble Space Telescope (HST) imaging capability, even when confirmed with Spitzer. If only a few photometry data points are available, it becomes attractive to add criteria based on their morphology in these J- and H-band images. One could do so through visual inspection, a size criterion, or alternate morphometrics. We explore a vetted sample of Brightest of Reionizing Galaxies (BoRG) z ∼ 9 and z ∼ 10 candidate galaxies and the object rejected by Morishita+ to explore the utility of a size criterion in z = 9–10 candidate selection. A stringent, point-spread function (PSF)-corrected effective radius criterion ([[Formula]]) would result in the rejection of 65%–70% of the interlopers visually rejected by Morishita et al. It may also remove up to ∼20% of bona fide brightest (L≫L{sup ∗}) z = 9 or 10 candidates from a BoRG selected sample based on the Mason et al. luminosity functions, assuming the Holwerda et al. z∼9 size–luminosity relation. We argue that including a size constraint in lieu of a visual inspection may serve in wide-field searches for these objects in, e.g., Euclid or HST archival imaging with the understanding that some brightest (L≫L{sup ∗}) candidates may be missed. The sizes of the candidates found by Morishita et al. follow the expected size distribution of z ∼ 9 for bright galaxies, consistent with the log normal in Shibuya et al. and single objects. Two candidates show high star formation surface density (Σ{sub SFR}>25M{sub ⊙} kpc{sup −2}) and all merit further investigation and follow-up observations.

79 ASTRONOMY AND ASTROPHYSICS↗
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 OSTI2024

Concept Study of Robotic Camera-Based Foreign Object Detection for EV Wireless Charging

Wireless charging of an electric vehicle (EV) is an emerging charging technology promising convenient, autonomous, and highly efficient EV charging without requiring heavy gauge cables. However, due to the strong electromagnetic field created by this process that surrounds the wireless charger, the presence of foreign objects can detrimentally interact with it, thus affecting wireless power transfer (WPT) performance or leading to harmful and unwanted safety risks. This paper presents the results for a concept study on a robotic camera-based foreign object detection (FOD) system, as a supplement to the industry-existing overlapped FOD coil array method, for EV wireless charging. A Raspberry PI 4 control board and compatible Raspberry PI Camera Module 2 are used to implement camera-based object detection. The FOD program was developed using a state-of-the-art deep learning object detection model with the OpenCV and Pytorch library and is compatible with camera module hardware. A dry-run test with Raspberry PI and a camera module was conducted and the preliminary FOD function was verified. The feasibility assessment is also validated by comparing the performance of five existing state-of-the-art deep learning object detection models for vehicles, animals, persons, and metals subsets, respectively. Satisfactory performance on the benchmark datasets is observed by the tests, but further improvements are needed in future work when detecting small-sized metallic objects. A programable robotic car is also under development as ongoing work for carrying the Raspberry PI and camera module while moving for the maintenance process.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Power Flow Geometry and Approximation

Here, the power flow equations are important in numerous power systems problems of practical interest which consider alternating current power flow (ACPF) physics. Perhaps the most well studied being the alternating current optimal power flow problem (ACOPF), seeking to optimize the operation of an electric power system. Due to their non-linearity, problems which include the power flow equations are typically challenging, particularly in optimization. Interestingly, the set of solutions to the power flow equations forms a smooth manifold. As a result, differential geometry can be used to describe and analyze this set of equations. This approach has proven effective in several engineering applications (e.g., solving ACOPF and analyzing the solution space boundary). Central to the success of this approach is an understanding of the power flow manifold's geometry. In this work, we develop the geometric and topological properties of this manifold using concepts from differential geometry. After demonstrating the convenience of this manifold's representation as a function's graph, computational methods are emphasized: we develop retractions, error bounds for linear approximation, and formulas for evaluating the Riemannian metric (including associated objects such as geodesics and the curvature tensor). Scalar curvature and the second fundamental form play a new role in quantifying the quality of linear approximations, like the popular direct current approximation. All functions are implemented in Julia and available in an online repository. Proofs are included for completeness.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Response of Subsurface Nitrogen-Cycling Microbial Communities to Environmental Fluctuations (Final Technical Report)

Riparian floodplains are dynamic ecosystems linking terrestrial and riverine systems. These floodplains experience hydrological shifts such as changes in water table height, flooding, and drought and can be ‘hotspots’ of biogeochemical cycling due to shifting sediment moisture (and saturation) and subsurface exchanges of water, nutrients, and other compounds across different sediment layers. Subsurface microbial communities are the primary drivers of biogeochemical processes in floodplains, and thus their structure and function can directly influence both surface and groundwater quality. The microbial nitrogen (N) cycle is particularly important in floodplains as it affects nutrient availability and removal. Two functional guilds of chemoautotrophic (i.e. CO2-fixing) microorganisms are responsible for the first oxidative step of the N cycle, nitrification: ammonia-oxidizing archaea (AOA) and bacteria (AOB) catalyze the oxidation of ammonia to nitrite, while nitrite-oxidizing bacteria (NOB) oxidize nitrite to nitrate. Despite the critical role nitrification plays in N-cycling in both terrestrial and aquatic ecosystems, our understanding of the diversity, ecophysiology, and activity of nitrifying organisms in subsurface floodplain soils/sediments is extremely limited. To help address this critical knowledge gap, the overarching goal of this project was to determine how shifts in key environmental parameters and gradients impact microbial N-cycling communities/processes, with particular emphasis on nitrification, within hydrologically-variable floodplain sediments in the Wind River Basin near Riverton, Wyoming. The three specific objectives of this project were to: (1) to associate in situ environmental drivers of N cycling with distinct functional guilds; (2) determine the guild response to variation in key ecosystem drivers; and (3) develop a dynamic ecosystem model of the microbial N cycle with the Riverton subsurface using community genomic and biogeochemical data collected in the first two objectives. Over the course of this project, we employed both 16S rRNA gene amplicon sequencing and genome-resolved metagenomics to examine the phylogenetic diversity and metabolic potential of subsurface nitrifier communities within 68 samples collected across multiple sites, depths, and time points within the Riverton floodplain, allowing for both spatial and temporal investigations at different scales. This project benefitted tremendously from recent advances in high-throughput sequencing technologies coupled with dramatic improvements in the computational tools and algorithms available for analyzing such large, complex genomic datasets. By pairing these cutting-edge genomic approaches with depth-resolved sampling and detailed geochemical analyses of the Riverton floodplain, we have gained novel insights into the structure and function of subsurface nitrifier communities in relation to both hydrology and biogeochemistry. This project resulted in the most detailed and comprehensive characterization of N-cycling floodplain microbial communities to date and will hopefully inspire and pave the way for future studies using similar approaches in other floodplains. Indeed, such information is critical for understanding subsurface biogeochemical cycling and how elemental stores are altered from perturbations initiated by the water cycle within floodplains. Finally, because of the terrestrial-aquatic nature of the Riverton floodplain, results from this project are also of relevance to disciplines such as soil science, estuarine science, limnology & oceanography, biogeochemistry, geobiology, environmental engineering, as well as genomics and data science.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Oxygen Vacancy Injection as a Pathway to Enhancing Electromechanical Response in Ferroelectrics

Since their discovery in late 1940s, perovskite ferroelectric materials have become one of the central objects of condensed matter physics and materials science due to the broad spectrum of functional behaviors they exhibit, including electro-optical phenomena and strong electromechanical coupling. In such disordered materials, the static properties of defects such as oxygen vacancies are well explored but the dynamic effects are less understood. In this work, the first observation of enhanced electromechanical response in BaTiO3 thin films is reported driven via dynamic local oxygen vacancy control in piezoresponse force microscopy (PFM). A persistence in peizoelectricity past the bulk Curie temperature and an enhanced electromechanical response due to a created internal electric field that further enhances the intrinsic electrostriction are explicitly demonstrated. The findings are supported by a series of temperature dependent band excitation PFM in ultrahigh vacuum and a combination of modeling techniques including finite element modeling, reactive force field, and density functional theory. Furthermore, this study shows the pivotal role that dynamics of vacancies in complex oxides can play in determining functional properties and thus provides a new route toward– achieving enhanced ferroic response with higher functional temperature windows in ferroelectrics and other ferroic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Irradiation of ultrasonic sensors and adhesive couplants for application in light water reactor primary loop piping and components

The Electric Power Research Institute (EPRI) Nuclear Sector and US Department of Energy Light Water Reactor Sustainability Program are committed to engaging in research and development endeavors to address materials aging issues specific to long term operation of light water power reactors. To this effect, EPRI launched an industry initiative to develop nondestructive evaluation systems for online monitoring of existing cracks in light water reactor primary coolant loop piping and components. One of the goals of this initiative is to develop a sensor system (or systems) that can determine nondestructively if cracks are growing or arrested and, in the case of the former, to characterize their growth rates. A missing component of this initiative is an experimental assessment of how sensors and adhesive couplants will perform in service when exposed to chronic energetic neutron radiation, particularly at the primary coolant loop hot and cold leg dissimilar metal welds, which join the primary loop piping to the reactor pressure vessel and reside in the vicinity of the reactor core. The objective of this experimental study was to determine how ultrasonic transducers and adhesive couplants perform when exposed to irradiation in a test reactor to simulate and accelerate in-service exposure. Further, to achieve this objective, the signal stability of piezoelectric transducers and performance of adhesive couplants as a function of accumulated fast neutron fluence were characterized by collecting ultrasonic data in-situ during irradiation. Of particular interest were the ultrasonic signal quality and time decay of the amplitude of acoustic reflections as a function of fast neutron fluence. The results of the study showed that, of the 8 transducer/substrate sample assemblies tested, only 3 generated usable ultrasonic signals through the conclusion of the irradiation campaign. It was found that high temperature epoxy tends to ultrasonically couple the sensors to the substrates better than three types of refractory ceramic cements studied, as is supported by post irradiation examination. The results obtained through this experimental study will be utilized in the achievement of the overall goal of development of a sensor system to perform online monitoring of primary loop components.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

EZFF: Python library for multi-objective parameterization and uncertainty quantification of interatomic forcefields for molecular dynamics

Parameterization of interatomic forcefields is a necessary first step in performing molecular dynamics simulations. This is a non-trivial global optimization problem involving quantification of multiple empirical variables against one or more properties. We present EZFF, a lightweight Python library for parameterization of several types of interatomic forcefields implemented in several molecular dynamics engines against multiple objectives using genetic-algorithm-based global optimization methods. The EZFF scheme provides unique functionality such as the parameterization of hybrid forcefields composed of multiple forcefield interactions as well as built-in quantification of uncertainty in forcefield parameters and can be easily extended to other forcefield functional forms as well as MD engines.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Integrated electro- and chemical characterization of sulfide-based solid-state electrolytes

Sulfide solid-state electrolytes (SSEs) represent a critical advancement towards enabling next-generation lithium metal batteries. However, a profound knowledge gap remains in understanding the structure–property relationships inherent to these sulfide SSEs. Electrochemical assessment and spectroscopic tools, such as Raman spectroscopy, offer bench-top ready, non-invasive, powerful avenues for operando and in situ analyses. Despite this potential, the integration of these methodologies, particularly for real-time interrogation, is markedly under-investigated. This review endeavors to catalog the use of diverse electrochemical techniques and spectroscopic tools in elucidating the structural and functional nuances of sulfide SSEs. Through the harmonization of these multifaceted evaluation strategies, our objective is to chart a course towards optimized sulfide SSEs, thereby aiding in the development of informed protocols for a deeper comprehension and understanding of the structure–property relationship and interfacial engineered design of solid-state batteries using sulfide-based SSEs.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Characterizing Canopy Openness in Open Forests: Spherical Densiometer and Canopy Photography Are Equivalent but Less Sensitive than Direct Measurements of Solar Radiation

In forest ecosystems, canopy openness affects understory light availability, plant growth, and tree species recruitment, thus shaping future forest composition, structure, and functional diversity. Foresters must correctly and quickly measure canopy openness to meet their management objectives. To help guide the selection of an appropriate method for measuring canopy openness, we compared three common techniques that vary in cost, complexity, and time required for measurements and data processing: smartphone-based hemispherical photography, spherical densiometer measurements, and direct measurements of solar radiation (using AccuPAR ceptometer). We measured canopy openness using these three methods on 28 permanent forest health monitoring plots in pine-oak forests of the Central Pine Barrens of Long Island in New York State. By analysis of variance and regression analyses, we found the three methods (particularly densiometer and hemispherical photographs) yielded broadly equivalent and strongly positively correlated descriptions of canopy openness. The direct measurements of solar radiation seemed to have a greater potential to detect subtle variation in forest understory light. Forest managers may sufficiently characterize canopy openness using quick and cheap methods (e.g., spherical densiometers) and avoid larger costs of devices for direct light measurements (e.g., ceptometers) and the larger data processing times of hemispherical photography.

54 ENVIRONMENTAL SCIENCES↗