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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Diffusion Models to Construct a First Principles Multipole-Based Cable Braid Model for Conducting Wires in the Time Domain

We describe here diffusion models apt to construct a multipole-based, cable braid time domain model for conducting wires. Implementation details of both a ladder network valid for time-domain signals with all frequency content and an approximate single-stage circuit valid for low-frequency dominated time signals (such as electromagnetic pulses) are reported. This time domain model can be leveraged to treat system-generated electromagnetic pulse events, as well as used to further confirm the correctness of the multipole-based, cable braid frequency domain model.

42 ENGINEERING↗
DOE OSTI2017

Electronic structures and physical properties of Na 2 O doped silicate glass

Ab initio molecular dynamics has been applied to construct seven sodium silicate glass models with Na2O concentration ranging from 0 to 50 mol. %. The structures of the simulated (Na 2 O) x (SiO 2 ) 1-x glasses are critically analyzed and validated by comparing with available experimental data. Because the initial seed model is based on a near-perfect continuous random network model for amorphous SiO 2 with periodic boundaries, the structures of these silicate glasses are highly reliable. The electronic structure, interatomic bonding, and the mechanical and optical properties of seven models are calculated using the first-principles density functional method. In particular, a single quantum mechanical metric, the total bond order density (TBOD), is used to characterize the internal cohesion of sodium silicate glass. This is a significant step beyond the traditional analysis of glasses based purely on the geometric parameters. The TBOD value is found to decrease with increasing Na content, indicating the destruction of silica network connectivity. The calculated mass density and refractive index increase with x are in good agreement with experiment. The elastic coefficients and bulk mechanical properties exhibit a nonlinear variation in the series and depend greatly on the internal bonding and cohesion of the glass. The calculated Poisson's ratio indicates that the glass becomes more ductile with the addition of Na 2 O. Our results indicate that sodium silicate glass tends to be unstable for x greater than 0.4 due to the total destruction of the SiO 2 network.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Mechanically tunable conductive interpenetrating network hydrogels that mimic the elastic moduli of biological tissue

Conductive and stretchable materials that match the elastic moduli of biological tissue (0.5–500 kPa) are desired for enhanced interfacial and mechanical stability. Compared with inorganic and dry polymeric conductors, hydrogels made with conducting polymers are promising soft electrode materials due to their high water content. Nevertheless, most conducting polymer-based hydrogels sacrifice electronic performance to obtain useful mechanical properties. Here we report a method that overcomes this limitation using two interpenetrating hydrogel networks, one of which is formed by the gelation of the conducting polymer PEDOT:PSS. Due to the connectivity of the PEDOT:PSS network, conductivities up to 23 S m-1 are achieved, a record for stretchable PEDOT:PSS-based hydrogels. Meanwhile, the low concentration of PEDOT:PSS enables orthogonal control over the composite mechanical properties using a secondary polymer network. We demonstrate tunability of the elastic modulus over three biologically relevant orders of magnitude without compromising stretchability ( > 100%) or conductivity ( > 10 S m-1 ).

36 MATERIALS SCIENCE↗
DOE OSTI2017

Analysis framework for systematically studying ionospheric response to impulsive events from below: Analysis Framework Ionospheric Responses

We present that impulsive phenomena in the Earth's atmosphere produce acoustic and gravity waves which perturb the ionosphere. Such perturbations are often measured using total electron content fluctuations (TEC), derived from ground-based Global Positioning System data. Using TEC data from the Japanese GEONET ground network after the Tōhoku earthquake on 11 March 2011, we demonstrate capabilities of a new framework of methodologies for analyzing ionospheric perturbations. The framework consists of several new techniques: calculating velocity along a single direction to reduce error due to anisotropic propagation, producing normalized bidirectional band-pass spectra that preserve relative timing between various frequencies and allowing a more systematic determination of broadband pulses, and utilizing a wavelet-based technique that considers instantaneous wave phase changes, rather than best fit time differences, to evaluate wave characteristics (speed, direction, and wavelength) within spectral ranges of interest. Using these techniques together decreases subjectivity and reduces errors in attributing fluctuations to given sources. In validating this framework using the Tōhoku case, we consistently identify three kinds of waves: a broad-band pulse (speed: >2000 m/s, max range: >1400 km) arriving in the ionosphere 10–15 min after the quake, acoustic waves following the pulse (period: 3–5 min, speed: 700–1000 m/s, max range: <500 km), and gravity waves (period: 10–15 min, speed: 150–500 m/s, max range: >1400 km) propagating away from the epicenter, consistent with theory and demonstrated in previous studies. Lastly, this framework also can be applied to other impulsive events in the atmosphere that are more difficult to detect and attribute to sources.

58 GEOSCIENCES↗
NASA NTRS1975

Set processing in a network environment

A combination of a local network, a mass storage system, and an autonomous set processor serving as a data/storage management machine is described. Its characteristics include: content-accessible data bases usable from all connected devices; efficient storage/access of large data bases; simple and direct programming with data manipulation and storage management handled by the set processor; simple data base design and entry from source representation to set processor representation with no predefinition necessary; capability available for user sort/order specification; significant reduction in tape/disk pack storage and mounts; flexible environment that allows upgrading hardware/software configuration without causing major interruptions in service; minimal traffic on data communications network; and improved central memory usage on large processors.

Hardgrave, W. T.↗
DOE OSTI2014

Smart Grid Information Clearinghouse (SGIC)

Since the Energy Independence and Security Act of 2007 was enacted, there has been a large number of websites that discusses smart grid and relevant information, including those from government, academia, industry, private sector and regulatory. These websites collect information independently. Therefore, smart grid information was quite scattered and dispersed. The objective of this work was to develop, populate, manage and maintain the public Smart Grid Information Clearinghouse (SGIC) web portal. The information in the SGIC website is comprehensive that includes smart grid information, research & development, demonstration projects, technical standards, costs & benefit analyses, business cases, legislation, policy & regulation, and other information on lesson learned and best practices. The content in the SGIC website is logically grouped to allow easily browse, search and sort. In addition to providing the browse and search feature, the SGIC web portal also allow users to share their smart grid information with others though our online content submission platform. The Clearinghouse web portal, therefore, serves as the first stop shop for smart grid information that collects smart grid information in a non-bias, non-promotional manner and can provide a missing link from information sources to end users and better serve users’ needs. The web portal is available at www.sgiclearinghouse.org. This report summarizes the work performed during the course of the project (September 2009 – August 2014). Section 2.0 lists SGIC Advisory Committee and User Group members. Section 3.0 discusses SGIC information architecture and web-based database application functionalities. Section 4.0 summarizes SGIC features and functionalities, including its search, browse and sort capabilities, web portal social networking, online content submission platform and security measures implemented. Section 5.0 discusses SGIC web portal contents, including smart grid 101, smart grid projects, deployment experience (i.e., use cases, lessons learned, cost-benefit analyses and business cases), in-depth information (i.e., standards, technology, cyber security, legislation, education and training and demand response), as well as international information. Section 6.0 summarizes SGIC statistics from the launch of the portal on July 07, 2010 to August 31, 2014. Section 7.0 summarizes publicly available information as a result of this work.

Rahman, Saifur↗
NASA NTRS1989

Terminal attractors in neural networks

A new type of attractor (terminal attractors) for content-addressable memory, associative memory, and pattern recognition in artificial neural networks operating in continuous time is introduced. The idea of a terminal attractor is based upon a violation of the Lipschitz condition at a fixed point. As a result, the fixed point becomes a singular solution which envelopes the family of regular solutions, while each regular solution approaches such an attractor in finite time. It will be shown that terminal attractors can be incorporated into neural networks such that any desired set of these attractors with prescribed basins is provided by an appropriate selection of the synaptic weights. The applications of terminal attractors for content-addressable and associative memories, pattern recognition, self-organization, and for dynamical training are illustrated.

Zak, Michail↗
DOE OSTI2018

NUMA-Aware Thread Scheduling for Big Data Transfers over Terabits Network Infrastructure

The evergrowing trend of big data has led scientists to share and transfer the simulation and analytical data across the geodistributed research and computing facilities. However, the existing data transfer frameworks used for data sharing lack the capability to adopt the attributes of the underlying parallel file systems (PFS). LADS (Layout-Aware Data Scheduling) is an end-to-end data transfer tool optimized for terabit network using a layout-aware data scheduling via PFS. However, it does not consider the NUMA (Nonuniform Memory Access) architecture. In this paper, we propose a NUMA-aware thread and resource scheduling for optimized data transfer in terabit network. First, we propose distributed RMA buffers to reduce memory controller contention in CPU sockets and then schedule the threads based on CPU socket and NUMA nodes inside CPU socket to reduce memory access latency. We design and implement the proposed resource and thread scheduling in the existing LADS framework. Experimental results showed from 21.7% to 44% improvement with memory-level optimizations in the LADS framework as compared to the baseline without any optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Evaluation of Advanced Signal Processing Techniques to Improve Detection and Identification of Embedded Defects

By the end of 1996, 109 Nuclear Power Plants were operating in the United States, producing 22% of the Nation’s electricity [1]. At present, more than two thirds of these power plants are more than 40 years old. The purpose of the U.S. Department of Energy Office of Nuclear Energy’s Light Water Reactor Sustainability (LWRS) Program is to develop technologies and other solutions that can improve the reliability, sustain the safety, and extend the operating lifetimes of nuclear power plants (NPPs) beyond 60 years [2]. The most important safety structures in an NPP are constructed of concrete. The structures generally do not allow for destructive evaluation and access is limited to one side of the concrete element. Therefore, there is a need for techniques and technologies that can assess the internal health of complex, reinforced concrete structures nondestructively. Previously, we documented the challenges associated with Non-Destructive Evaluation (NDE) of thick, reinforced concrete sections and prioritized conceptual designs of specimens that could be fabricated to represent NPP concrete structures [3]. Consequently, a 7 feet tall, by 7 feet wide, by 3 feet and 4-inch-thick concrete specimen was constructed with 2.257-inch-and 1-inch-diameter rebar every 6 to 12 inches. In addition, defects were embedded the specimen to assess the performance of existing and future NDE techniques. The defects were designed to give a mix of realistic and controlled defects for assessment of the necessary measures needed to overcome the challenges with more heavily reinforced concrete structures. Information on the embedded defects is documented in [4]. We also documented the superiority of Frequency Banded Decomposition (FBD) Synthetic Aperture Focusing Technique (SAFT) over conventional SAFT when probing defects under deep concrete cover. Improvements include seeing an intensity corresponding to a defect that is either not visible at all in regular, full frequency content SAFT, or an improvement in contrast over conventional SAFT reconstructed images. This report documents our efforts in four fronts: 1) Comparative study between traditional SAFT and FBD SAFT for concrete specimen with and without Alkali-Silica Reaction (ASR) damage, 2) improvement of our Model-Based Iterative Reconstruction (MBIR) for thick reinforced concrete [5], 3) development of a universal framework for sharing, reconstruction, and visualization of ultrasound NDE datasets, and 4) application of machine learning techniques for automated detection of ASR inside concrete. Our comparative study between FBD and traditional SAFT reconstruction images shows a clear difference between images of ASR and non-ASR specimens. In particular, the left first harmonic shows an increased contrast and sensitivity to ASR damage. For MBIR, we show the superiority of model-based techniques over delay and sum techniques such as SAFT. Improvements include elimination of artifacts caused by direct arrival signals, and increased contrast and Signal to Noise Ratio. For the universal framework, we document a format for data storage based on the HDF5 file format, and also propose a modular Graphic User Interface (GUI) for easy customization of data conversion, reconstruction, and visualization routines. Finally, two techniques for ASR automated detection are presented. The first technique is based on an analysis of the frequency content using Hilbert Transform Indicator (HTI) and the second technique employees Artificial Neural Network (ANN) techniques for training and classification of ultrasound data as ASR or non-ASR damaged classes. The ANN technique shows great potential with classification accuracy above 95%. These approaches are extensible to the detection of additional reinforced, thick concrete defects and damage.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1996

A Sundial-Atlas Precursor to the TIMED Mission: A Quick-Response Global Investigation into Coupled Lower Thermospheric, Ionospheric, and Mesospheric Physics

The SUNDIAL-ATLAS effort was a global-scale investigation which responded to the science priorities of the ITM Panel, the Integrated SPD Strategy Implementation Plan as a whole, and the need for potential cost-saving design criteria for the TIMED mission. The investigation focused on coupling processes in the ionospheric-thermospheric system, taking advantage of the timelines of the ATLAS-1 mission (March 1992), and the global-scale ground-based measurement and modeling activities of the SUNDIAL program. The collaborative SUNDIAL-ATLAS activity was the first opportunity for global measurements of the chemistry, kinetics, and electrodynamics which couple the E-, Fl-, and F2-regions into a single interactive system. As such, the program represented an important first step in studying global issues; and accordingly, was an important proof of concept experiment relevant to the strategic mission plans for the ITM community and the upcoming intermediate class satellite program called TIMED. To meet its projected goals, TIMED must perform a number of critical measurements and execute a number of correlations that were to be tried and tested for the first time in the SUNDIAL-ATLAS investigation. This was designed to include global correlations of thermospheric and ionospheric composition during quiet and disturbed conditions and the co-registration of global-scale ground-based measurements with along-track satellite diagnostics. The SUNDIAL component of the current investigation addressed this need by acquiring, reducing, and analyzing a multi-sensor database that complemented and extended that which was generated in the ATLAS mission (Atmospheric Laboratory for Applications and Science). The SUNDIAL data defined the state and condition of the global-scale ionosphere in the altitude range from 100 km to the F2-peak. These data specified the peak heights and densities of the E-, Fl-, and F2-regions, along with the global distributions of intermediate, descending, and sequential layers which play a critical role in the dynamo region of the lower ionospheric-thermospheric domain. The data were collected by the SUNDIAL network of more than 50 ground-based stations utilizing ionosondes, radars, photometers, Fabry-Perot interferometers, and total electron content measurements. The data were acquired during a three-week period centered on the eight-day ATLAS-1 mission, which provided image and photometric sensing of the altitude distributions of the major and minor ions and neutrals in the ITM system. This report focuses on the scientific contributions of the SUNDIAL component of the overall investigation. Specific findings are described in seven papers (attached) published in the Journal of Geophysical Research.

Szuszczewicz, E. P.↗
DOE OSTI2021

Prediction of social media postings as trusted news or as types of suspicious news

Disclosed are systems, techniques, and non-transitory storage media for predicting social media postings as being trusted news or a type of suspicious news. The systems, techniques, and non-transitory storage media are based on unique neural network architectures that learn from a combined representation including at least representations of social media posting content and a vector representation of communications among connected users.

Volkova, Svitlana↗
DOE OSTI2018

The MidAmerica Regional Microgrid Education and Training (MARMET) Consortium

The primary goal of this project was to integrate cutting-edge research and advanced instructional methods to create a flexible, evolving approach to microgrid and distributed energy resources training for all levels of student. This goal entailed the rapid development of modular material to capture and reflect the newest trends in electric power microgrid engineering and to make it available in traditional and non-traditional settings. It was our goal to develop course material that can be readily integrated into either existing courses or organized into new courses. The target audiences include technicians, contractors and consultants, inspectors, policy makers, supervisors, and engineers and undergraduate and graduate students. The main project objectives were to: 1) Perform a gap analysis to identify the research/educational/training needs and define specific implementation plans for these activities in distributed technology and Smart Grid power engineering by working with Department of Energy, the National Network Administrator (NNA) and other Distributed Technology Training Consortia (DTTC). 2) Develop learning content related to, and driven by, microgrid research, consisting of one or more multimedia-based modules. Over the life of the project MARMET provided training to 11,012 students and developed 154,432 contact hours of material (see the IREC NNA, DE-EE0006342, final project report for added details on MARMET evaluation and assessment metrics, as well as an overview of the entire GEARED network. 3) Provide a variety of delivery mechanisms and venues for face-to-face and on-line instruction in power system engineering and related smart grid operations, including university-based courses, short courses, and workshops. 4) Assemble and engage highly-qualified advisory and steering committees of experts from utilities, universities, national laboratories, and product suppliers for this DTTC, to guide and advise the activities of the DTTC, and to assist in creating student internships, coops, research projects and academic competitions for GEARED students within the DTTC and nationally. 5) Convene regular meetings of Consortia partners to disseminate research results among the participants (universities, utilities, and industry). 6) Develop recruitment mechanisms to publicize GEARED student opportunities and highlight the educational benefits of GEARED participation to assure long-term sustainability of student recruitment and retention. 7) Participate in GEARED National Network activities to identify and adopt best practices across all GEARED consortia. 8) Organize, host and manage at least one annual Student-Centered Research Conference on behalf of the GEARED Network during the period of performance; participate in each annual national Student-Centered Research Conference.

14 SOLAR ENERGY↗
DOE OSTI2023

Signal Processing Based Method for Real-Time Anomaly Detection in High-Performance Computing

Performance anomalies can manifest as irregular execution times or abnormal execution events for many reasons, including network congestion and resource contention. Detecting such anomalies in real-time by analyzing the details of performance traces at scale is impractical due to the sheer volume of data High-Performance Computing (HPC) applications produce. In this paper, we propose formulating HPC performance anomaly detection as a signal-processing problem where anomalies can be treated as noise. We evaluate our proposed method in comparison with two other commonly used anomaly detection techniques of varying complexity based on their detection accuracy and scalability. Since real-time in-situ anomaly detection at a large scale requires lightweight methods that can handle a large volume of streaming data, we find that our proposed method provides the best trade-off. We then implement the proposed method in Chimbuko, the first online, distributed, and scalable workflow-level performance trace analysis framework. We compare our proposed signal-based anomaly detection algorithm with two other methods using a function of their accuracy, F1 score, and detection overhead. Our experiments demonstrate that our proposed approach achieves a 99% improvement for the benchmark datasets and a 93% improvement with Chimbuko traces.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2017

Geochemical and Microbial Community Attributes in Relation to Hyporheic Zone Geological Facies

The hyporheic zone (HZ) is the active ecotone between the surface stream and groundwater, where exchanges of water, nutrients, and organic matter occur in response to variations in discharge and riverbed properties. Within this region, a confluence of surface-derived organic carbon and subsurface nitrogen (in the form of nitrate) has been shown to stimulate microbial activity and transformations of carbon and nitrogen species. For example, production of gases such as CO 2 , N 2 and N 2 O indicate hyporheic zones might have a significant effect on energy and nutrient flows between the atmosphere and the subsurface. Managed and seasonal river stage changes and geomorphology-controlled sediment texture drive water flow within the HZ of the Columbia River. To examine the relationship between sediment texture, biogeochemistry, and biological activity in the HZ, the grain size distributions for sediment samples taken across 320 m of shoreline were characterized to define geological facies, and the relationships among physical properties of the facies, physicochemical attributes of the local environment, and the structure and activity of associated microbial communities were examined. Mud and sand content and the presence of carbon and nitrogen oxidizers were found to explain the variability in many biogeochemical attributes. Microbial community analysis revealed a high relative abundance of putative ammonia-oxidizing Thaumarchaeota and nitrite-oxidizing Nitrospirae, together comprising ~20% of the total community across all samples, but scant ammonia-oxidizing Bacteria. Network analysis of operational taxonomic units and the measured geophysical, chemical, and functional parameters showed negative relationships between abundance-based modules of organisms and sand and mud contents, and positive relationships with total organic carbon. The relationships identified in this work indicate grain size distribution is a good predictor of biogeochemical properties, and that subsets of the overall microbial community respond to different sediment texture. Some member populations of these sub-communities appear to respond directly to environmental conditions, while others may be dependent on the function of the first group. For example, nitrification is a strong primary response to the observed conditions, and this activity appears to support a larger heterotrophic community. Relationships between facies and hydrobiogeochemical properties enables facies-based conditional simulation/mapping of these properties to inform multiscale modeling of hyporheic exchange and biogeochemical processes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2008

Ground-based Network and Supersite Measurements for Studying Aerosol Properties and Aerosol-Cloud Interactions

From radiometric principles, it is expected that the retrieved properties of extensive aerosols and clouds from reflected/emitted measurements by satellite (and/or aircraft) should be consistent with those retrieved from transmitted/emitted radiance observed at the surface. Although space-borne remote sensing observations contain large spatial domain, they are often plagued by contamination of surface signatures. Thus, ground-based in-situ and remote-sensing measurements, where signals come directly from atmospheric constituents, the sun, and the Earth-atmosphere interactions, provide additional information content for comparisons that confirm quantitatively the usefulness of the integrated surface, aircraft, and satellite datasets. The development and deployment of AERONET (AErosol RObotic NETwork) sunphotometer network and SMART-COMMIT (Surface-sensing Measurements for Atmospheric Radiative Transfer - Chemical, Optical & Microphysical Measurements of In-situ Troposphere) mobile supersite are aimed for the optimal utilization of collocated ground-based observations as constraints to yield higher fidelity satellite retrievals and to determine any sampling bias due to target conditions. To characterize the regional natural and anthropogenic aerosols, AERONET is an internationally federated network of unique sunphotometry that contains more than 250 permanent sites worldwide. Since 1993, there are more than 480 million aerosol optical depth observations and about 15 sites have continuous records longer than 10 years for annual/seasonal trend analyses. To quantify the energetics of the surface-atmosphere system and the atmospheric processes, SMART-COMMIT instrument into three categories: flux radiometer, radiance sensor and in-situ probe. Through participation in many satellite remote-sensing/retrieval and validation projects over eight years, SMART-COMMIT have gradually refine( and been proven vital for field deployment. In this paper, we will demonstrate the capability of AERONET SMART-COMMIT in current Asian Monsoon Year-2008 campaigns that are designed and being executed to study the compelling variability in temporal scale of both anthropogenic and natural aerosols (e.g., airborne dust, smoke, mega-city pollutant). Feedback mechanisms between aerosol radiative effects and monsoon dynamics have been recently proposed, however there is a lack of consensus on whether aerosol forcing would be more likely to enhance or reduce the strength of the monsoon circulation. We envision robust approaches which well-collocated ground-based measurements and space-borne observations will greatly advance our understanding of absorbing aerosols (e.g., "Global Dimming" vs. "Elevated Heat-Pump" effects) on aerosol cloud water cycle interactions.

Tsay, Si-Chee↗
DOE OSTI2023

Understanding oxidation of Fe-Cr-Al alloys through explainable artificial intelligence

Abstract The oxidation resistance of FeCrAl based on alloying composition and oxidizing conditions is predicted using a combinatorial experimental and artificial intelligence approach. A neural network (NN) classification model was trained on the experimental FeCrAl dataset produced at GE Research. Furthermore, using the SHapley Additive exPlanations (SHAP) explainable artificial intelligence (XAI) tool, we explore how the NN can showcase further material insights that are unavailable directly from a black-box model. We report that high Al and Cr content forms protective oxide layer, while Mo in FeCrAl creates thick unprotective oxide scale that is vulnerable to spallation due to thermal expansion. Graphical abstract

Materials Science↗