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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Flying Cages in Traveling Wave Ion Mobility: Influence of the Instrumental Parameters on the Topology of the Host–Guest Complexes

Supramolecular mass spectrometry has emerged in the last decade as an orthogonal method to access, at the molecular level, the structures of noncovalent complexes extracted from the condensed phase to the rarefied gas phase using electrospray ionization. It is often considered that the soft nature of the ESI source confers to the method the capability to generate structural data comparable to those in the condensed phase. In the present paper, using the ammonium ion/cucurbituril combination as a model system, we investigate using ion mobility and computational chemistry the influence of the instrumental parameters on the topology, i.e., internal versus external association, of gaseous host/guest complex ions. MS and theoretical data are confronted to condensed phase data derived from nuclear magnetic resonance spectroscopy to assess whether the instrumental parameters can play an insidious role when trying to derive condensed phase data from mass spectrometry results. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

FASTMap v. 2010.01

FASTMap is mapping application available for the web or on mobile devices (IOS and Android) that browses geospatial data and produces detailed reports of objects within any area of analysis. FASTMap can access any geospatial dataset. The software can provide immediate access to the selected data through a fully symbolized interactive mapping interface. FASTMap can load arbitrary contours that represent a region of interest and can dynamically identify and geospatially select objects that reside within the region. The software can produce a report listing the objects and aggregations for the region, as well as producing publication quality maps. FASTMap also has the ability to post and maintain authored maps, any GIS data included in the map, areas of interest, as well as any titles, and labels. These defining ingredients of a map are called map contexts. These mao contexts can be instantly broadcast via the internet through any of an infinite number of named channels to small or large numbers of users monitouring any of the channels being posted to, so a user can author a map and immediately share that map with others instantly, whether they are on traditional desktop computer, laptop, mobile tablet or smartphone. Further, users receiving broadcast maps can also alter the maps can also alter the maps, or create new ones and publish back to the channel in a collaborative manner. FASTMap can be configured to access virtually any geospatial data.

Bynum, Leo↗
DOE OSTI2022

EVSE Cybersecurity and Resilience

Consequence-driven Cybersecurity Analysis for Extreme Fast Charging Electric Vehicle Infrastructure Electric vehicle (EV) development and associated charging infrastructure are expected to advance rapidly. Thirty percent of all global vehicle sales may be EVs and hybrid EVs by 2025, and they will rely on increasingly sophisticated strategies for grid integration. Next-generation EV charging infrastructure is expected to include interconnected renewable resources, such as photovoltaic (PV) arrays and battery storage systems, along with grid-edge devices. Although distributed energy resources (DERs) are useful in several ways, such as peak shaving at high demand times and backup supply for added resilience, the integration of vehicle charging and DERs could create more avenues for cyberattack. Physical and/or remote access to EV charging station components, including charge ports, power electronics, controllers, and local generation (e.g., PV and energy storage) could be paths to cause power fluctuations, leading to altered operations at the charging station, escalated privileges to administrative systems, exfiltration of financial information (including personally identifiable information), and reduced grid stability. One compromised EV supply equipment component can open the door to a variety of exploitable vulnerabilities. Cloud computing and mobile application control have the potential to expand the threat surface to non-repudiation and firmware integrity challenges. Vendor clouds have access to hundreds of chargers, and if compromised, can scale the attack surface exponentially. The high power and voltage levels of xFC infrastructure (e.g., 400 kW at 1000- V DC) increase the hazards and ability to impact the grid and vehicles more than lower-power charging systems. Legacy communications systems and protocols could also put EV infrastructure at risk of cyberattacks requiring a robust patch management process. Communications networks link EVs and chargers to several stakeholders - including charging station operators, grid operators, vendors/manufacturers, and aggregators - who have both physical and network access to share information for control, monitoring, and analytics. Information in these networks that is vulnerable to compromise includes the state of charge, charging duration, payment information, electricity price, and load control. Analyzing and prioritizing these interconnections risks could help address cybersecurity related to data leakage and manipulation.

charging↗
DOE OSTI2025

Mobility assessment of the BCC and carbide phases in the C-Nb, C-U and Nb-U systems

Uranium carbides with refractory metal additions are considered for Gen IV nuclear reactors and nuclear thermal propulsion as fuels for their high-temperature and corrosion resistant properties. Understanding kinetic effects that dictate microstructural evolution during fabrication and operating conditions is essential to advance technological development of these fuels. This work presents the development of an atomic mobility database for C-Nb-U systems based off available experimental data supported with ab-initio methods. The mobility assessments and uncertainty quantification (using Markov chain Monte Carlo) were conducted in the Kawin software. Carbon diffusion is considered dominant, as metal diffusion is much slower, with niobium diffusion being even slower and rate limiting than uranium metal. We provide a comprehensive and self-consistent thermo-kinetic database that is validated by diffusion couple simulations through Kawin. In conclusion, this enables prediction of microstructural and phase evolution critical for the development and lifetime assessment of next generation nuclear fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

Dielectric relaxation of ethylene carbonate and propylene carbonate from molecular dynamics simulations

Ethylene carbonate (EC) and propylene carbonate (PC) are widely used solvents in lithium (Li)-ion batteries and supercapacitors. Ion dissolution and diffusion in those media are correlated with solvent dielectric responses. Here, we use all-atom molecular dynamics simulations of the pure solvents to calculate dielectric constants and relaxation times, and molecular mobilities. The computed results are compared with limited available experiments to assist more exhaustive studies of these important characteristics. As a result, the observed agreement is encouraging and provides guidance for further validation of force-field simulation models for EC and PC solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Closing the loop between microstructure and charge transport in conjugated polymers by combining microscopy and simulation

A grand challenge in materials science is to identify the impact of molecular composition and structure across a range of length scales on macroscopic properties. We demonstrate a unified experimental–theoretical framework that coordinates experimental measurements of mesoscale structure with molecular-level physical modeling to bridge multiple scales of physical behavior. Here we apply this framework to understand charge transport in a semiconducting polymer. Spatially-resolved nanodiffraction in a transmission electron microscope is combined with a self-consistent framework of the polymer chain statistics to yield a detailed picture of the polymer microstructure ranging from the molecular to device relevant scale. Using these data as inputs for charge transport calculations, the combined multiscale approach highlights the underrepresented role of defects in existing transport models. Short-range transport is shown to be more chaotic than is often pictured, with the drift velocity accounting for a small portion of overall charge motion. Local transport is sensitive to the alignment and geometry of polymer chains. At longer length scales, large domains and gradual grain boundaries funnel charges preferentially to certain regions, creating inhomogeneous charge distributions. While alignment generally improves mobility, these funneling effects negatively impact mobility. The microstructure is modified in silico to explore possible design rules, showing chain stiffness and alignment to be beneficial while local homogeneity has no positive effect. This combined approach creates a flexible and extensible pipeline for analyzing multiscale functional properties and a general strategy for extending the accesible length scales of experimental and theoretical probes by harnessing their combined strengths.

42 ENGINEERING↗
DOE OSTI2017

Solar Living House Final Technical Report

The Solar Living House is a high-performance solar-powered dwelling designed by a team of faculty and students from the University of Florida, in collaboration with Santa Fe College, the National University of Singapore, and Alachua Habitat for Humanity. The project was designed in accordance with the Solar Decathlon 2015, a research, design, education, and outreach program developed by the U.S. Department of Energy (DOE). The Solar Living House is fundamentally a house for living, centered on people and the activities of daily life while quietly introducing advanced design, construction, and engineering technologies. The 993 square-foot two-bedroom one-bath home was designed to embrace and frame an exterior courtyard space. This courtyard acts as an extension of the interior living spaces, maximizing the spatial potentials of a modest building footprint and introducing natural light into the primary living spaces of the house. Research Outcomes: The Solar Living House advances work on high-performance buildings through three principal technological innovations: wet/dry modular construction, a building automation system, and solar dehumidification systems. Wet / Dry Modular Construction: The house is designed as a series of five modules, including one that is designated as the “wet core.” The wet core consolidates the mechanical systems and bathroom into a single module to reduce plumbing runs, efficiency losses, and on-site construction time. The other four modules are designed to eliminate interior load bearing walls to allow for maximum flexibility in the reconfiguring of the space over time. The modules are designed to meet the structural challenges of both Florida’s hurricanes and California’s earthquakes. Building Automation System: The house is equipped with an integrated building automation system, allowing the houses environmental systems, lights, security systems, and smoke detectors to be programmed, monitored, and controlled through any mobile or computing device. These systems allow for more precise calibrations of temperature/humidity/lighting to correspond with user needs and preferences, minimizing energy losses with economical night- or day-time setbacks. Solar Dehumidification System: The most significant technological innovation in the Solar Living House is the solar thermal dehumidification system. This system generates hot water through two rooftop-mounted evacuated tube solar thermal collectors. The hot water is used to continually dry a regenerative solid desiccant material, typically white silica gel. The solid desiccant is used to adsorb moisture and humidity from the air without additional mechanical cooling. This strategy allows humidity to be modulated independently of air temperature, providing greater thermal comfort and reducing the opportunity for the growth of mold spores within the house while also reducing the overall energy consumption of the HVAC system. Economic Feasibility: The team set aggressive goals for affordability, targeting a construction cost of $138,710. An independent professional cost estimator determined the overall project costs, as designed, would be $333,799, or $336.15 per square foot of finished floor area. This is more than 2.4 times the target construction cost. By comparison, the average construction cost for a home in the United States in 2015 was $289,415, or $103.29 per square foot of finished floor area. Following work on the Solar Living House, team leaders incorporated many of its objectives into a net-zero energy home on a site in Gainesville, Florida. This site-built home avoided many of the constraints and complications of modular construction necessitated by the Solar Decathlon, allowing it to be built for a much more modest budget. This two-bedroom two bath 1,800 square foot home was constructed for $135.39 per square foot, including active photovoltaic solar systems, careful attention to continuous air barriers, increased insulation levels, and permanent site constructions. This project suggest that high-performance buildings can be realized for more modest budgets. Public Benefits: Work on the Solar Living House and Solar Decathlon 2015 offered our student team unparalleled learning opportunities. Because of the duration of the project, a number of students participated at different points in their education, from first year undergraduates all the way through to advanced graduate students. The opportunity for collaboration with students and faculty from the National University of Singapore was also extraordinary, allowing for a sharing of technical knowledge and cultural exchange. The wider public has benefited from this work as its findings have been shared through public presentations and publications. It serves as a useful stepping stone along the path towards affordable, high-performance buildings.

14 SOLAR ENERGY↗
NASA NTRS1985

Diffusion and localization of a particle in a periodic potential coupled to a dissipative environment

The phase diagram of a Hamiltonian which describes a particle moving in a periodic potential and coupled to an external heat bath has been analyzed in detail. By renormalization-group methods, it is proved that this system exhibits an unusual transition between diffusive behavior and a self-trapped phase. The dynamics along the transition line is shown to be integrable and the order parameter, the mobility, is computed exactly.

Guinea, F.↗
NASA NTRS1991

Advanced laptop and small personal computer technology

Advanced laptop and small personal computer technology is presented in the form of the viewgraphs. The following areas of hand carried computers and mobile workstation technology are covered: background, applications, high end products, technology trends, requirements for the Control Center application, and recommendations for the future.

Johnson, Roger L.↗
NASA NTRS2019

Ongoing Breakthroughs in Convective Parameterization

While the increase of computer power mobilizes a part of the community towards models with explicit convection or based on machine learning, we review the part of the literature dedicated to convective parameterization development for large-scale forecast and climate models. Recent findings: Many developments are underway to overcome endemic limitations of traditional convective parameterizations, either in unified or multi-object frameworks: scale-aware and stochastic approaches, new prognostic equations or representations of new components such as cold pools. Understanding their impact on the emergent properties of a model remains challenging, due to subsequent tuning of parameters and the limited understanding given by traditional metrics. Summary: Further effort still needs to be dedicated to the representation of the life cycle of convective systems, in particular their mesoscale organization and associated cloud cover. The development of more process-oriented metrics based on new observations is also needed to help quantify model improvement and better understand the mechanisms of climate change.

parameterizations for large-scale models↗
DOE OSTI2016

PHOENIX - Web-Based Application for Accessing Hanford Tank Monitoring Data - 16157

Data volume, complexity, and access issues pose severe challenges for analysts, regulators, and stakeholders interested in evaluating scientific data to support decision making at the Department of Energy's (DOE) Hanford Site. Pacific Northwest National Laboratory (PNNL) has developed a suite of web applications known collectively as PHOENIX (PNNL-Hanford Online Environmental Information exchange) to address data access, transparency, and integration challenges through intuitive query, visualization, and analysis tools that are accessible via desktop computer or mobile device by simply accessing the application web page (http://phoenix.pnnl.gov). Beginning in 2013, DOE's Office of River Protection (ORP) has worked with PNNL to develop a PHOENIX Tank Farm application to provide access to, and visualization of, in-tank monitoring data that had only been available to the public as text downloads for almost two decades. The Tank Farm application's user-friendly web-interface allows the public, stakeholders, regulators, and program managers to quickly and easily visualize in-tank and ex-tank data, facilitating data transparency and high-level decisions related to tank operations and management. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Transportation Secure Data Center: Frequently Asked Questions for Data Owners/Contributors

The Transportation Secure Data Center is a centralized repository for detailed transportation data from travel and transit surveys and studies conducted across the nation. It makes vital transportation data broadly available to users while preserving the privacy of survey participants. Hundreds of datasets from surveys and studies of household travel and transit passenger travel are archived in the TSDC, including surveys and studies conducted by state departments of transportation, metropolitan planning organizations, transit agencies, cities, and other public agencies. Detailed data from travel surveys and studies are extremely valuable for research purposes. However, the fine-grained information they contain could potentially be misused to identify individual travelers, so access to these data should only be granted with safeguards in place to protect participant privacy. The TSDC was created to address this challenge and to relieve public agencies from the burden of archiving their data and responding to data requests.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2014

SU-E-J-252: A Motion Algorithm to Extract Physical and Motion Parameters of a Mobile Target in Cone-Beam Computed Tomographic Imaging Retrospective to Image Reconstruction

Purpose: A motion algorithm was developed to extract actual length, CT-numbers and motion amplitude of a mobile target imaged with cone-beam-CT (CBCT) retrospective to image-reconstruction. Methods: The motion model considered a mobile target moving with a sinusoidal motion and employed three measurable parameters: apparent length, CT number level and gradient of a mobile target obtained from CBCT images to extract information about the actual length and CT number value of the stationary target and motion amplitude. The algorithm was verified experimentally with a mobile phantom setup that has three targets with different sizes manufactured from homogenous tissue-equivalent gel material embedded into a thorax phantom. The phantom moved sinusoidal in one-direction using eight amplitudes (0–20mm) and a frequency of 15-cycles-per-minute. The model required imaging parameters such as slice thickness, imaging time. Results: This motion algorithm extracted three unknown parameters: length of the target, CT-number-level, motion amplitude for a mobile target retrospective to CBCT image reconstruction. The algorithm relates three unknown parameters to measurable apparent length, CT-number-level and gradient for well-defined mobile targets obtained from CBCT images. The motion model agreed with measured apparent lengths which were dependent on actual length of the target and motion amplitude. The cumulative CT-number for a mobile target was dependent on CT-number-level of the stationary target and motion amplitude. The gradient of the CT-distribution of mobile target is dependent on the stationary CT-number-level, actual target length along the direction of motion, and motion amplitude. Motion frequency and phase did not affect the elongation and CT-number distributions of mobile targets when imaging time included several motion cycles. Conclusion: The motion algorithm developed in this study has potential applications in diagnostic CT imaging and radiotherapy to extract actual length, size and CT-numbers distorted by motion in CBCT imaging. The model provides further information about motion of the target.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Multisource Mobile Transfer Learning Algorithm Based on Dynamic Model Compression

With the development of the Internet of Things, the application of computer vision on mobile phones is becoming more and more extensive and people have higher and higher requirements for the timeliness of the recognition results returned and the processing capabilities of the mobile phone for image recognition. However, the processing capability and storage capability of the user terminal equipment cannot meet the needs of identifying and storing a large number of pictures, and the data transmission process will cause high energy consumption of the terminal equipment. At the same time, multisource deep transfer learning has outstanding performance in computer vision and image classification. However, due to the huge amount of calculation of the deep network model, it is impossible to use the existing excellent network model to realize image recognition and classification on the mobile terminal. In order to solve the abovementioned problems, we propose a multisource mobile transfer learning algorithm based on dynamic model compression, this algorithm considers the realization of multisource transfer learning computing in the case of multiple mobile device computing source domains, and the method also guarantees data privacy and security for each device (origin domain). Meanwhile, extensive experiments show that our method can achieve remarkable results in popular image classification datasets.

Gao, Peng↗
DOE OSTI2018

A Magnetoencephalographic/Encephalographic (MEG/EEG) Brain-Computer Interface Driver for Interactive iOS Mobile Videogame Applications Utilizing the Hadoop Ecosystem, MongoDB, and Cassandra NoSQL Databases

In Phase I, we collected data on five subjects yielding over 90% positive performance in Magnetoencephalographic (MEG) mid-and post-movement activity. In addition, a driver was developed that substituted the actions of the Brain Computer Interface (BCI) as mouse button presses for real-time use in visual simulations. The process was interfaced to a flight visualization demonstration utilizing left or right brainwave thought movement, the user experiences, the aircraft turning in the chosen direction, or on iOS Mobile Warfighter Videogame application. The BCI’s data analytics of a subject’s MEG brain waves and flight visualization performance videogame analytics were stored and analyzed using the Hadoop Ecosystem as a quick retrieval data warehouse. In Phase II portion of the project involves the Emotiv Encephalographic (EEG) Wireless Brain–Computer interfaces (BCIs) allow for people to establish a novel communication channel between the human brain and a machine, in this case, an iOS Mobile Application(s). The EEG BCI utilizes advanced and novel machine learning algorithms, as well as the Spark Directed Acyclic Graph (DAG), Cassandra NoSQL database environment, and also the competitor NoSQL MongoDB database for housing BCI analytics of subject’s response and users’ intent illustrated for both MEG/EEG brainwave signal acquisition. The wireless EEG signals that were acquired from the OpenVibe and the Emotiv EPOC headset can be connected via Bluetooth to an iPhone utilizing a thin Client architecture. The use of NoSQL databases were chosen because of its schema-less architecture and Map Reduce computational paradigm algorithm for housing a user’s brain signals from each referencing sensor. Thus, in the near future, if multiple users are playing on an online network connection and an MEG/EEG sensor fails, or if the connection is lost from the smartphone and the webserver due to low battery power or failed data transmission, it will not nullify the NoSQL document-oriented (MongoDB) or column-oriented Cassandra databases. Additionally, NoSQL databases have fast querying and indexing methodologies, which are perfect for online game analytics and technology. In Phase II, we collected data on five MEG subjects, yielding over 90% positive performance on iOS Mobile Applications with Objective-C and C++, however on EEG signals utilized on three subjects with the Emotiv wireless headsets and (n < 10) subjects from the OpenVibe EEG database the Variational Bayesian Factor Analysis Algorithm (VBFA) yielded below 60% performance and we are currently pursuing extending the VBFA algorithm to work in the time-frequency domain referred to as VBFA-TF to enhance EEG performance in the near future. The novel usage of NoSQL databases, Cassandra and MongoDB, were the primary main enhancements of the BCI Phase II MEG/EEG brain signal data acquisition, queries, and rapid analytics, with MapReduce and Spark DAG demonstrating future implications for next generation biometric MEG/EEG NoSQL databases.

McClay, Wilbert↗