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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Rapid Identification of Synthetic Routes to Functional Metastable Phases Using X-ray Probed Laser Anneal Mapping (XPLAM) Time-Temperature Quench Maps

Many material systems have known or predicted functional phases that are metastable at standard temperature and pressure. While substantial advances have been made in the high-throughput and combinatorial synthesis of materials with a range of stoichiometries, investigation of thermal processing remains largely the domain of iterative uniform anneals or static gradients. Here we develop X-ray probed laser anneal mapping (XPLAM), a high throughput technique coupling spatially resolved X-ray diffraction with microsecond to millisecond laser gradient anneals to produce temperature–dwell–transformation (TDT) diagrams of the phase as a function of quench time and temperature. In addition to showing regimes where specific metastable phases form preferentially, TDT diagrams provide insight into the submillisecond kinetics of solid–solid phase transitions. This is a unique tool for mapping reaction pathways for metastable phases. As a first demonstration of XPLAM, we study Bi2O3, which has a rich set of polytypes, including the d-phase with an exceptionally high oxygen ion conductivity. We demonstrate the first annealing-driven synthesis of room temperature d-Bi2O3. We expect XPLAM to prove a powerful technique for rapid identification of synthetic routes to metastable phases and to generate the exhaustive data sets required for machine learning-guided exploration of materials processing.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A Software/Hardware Framework for Efficient and Safe Emergency Response in Post-Crash Scenarios of Battery Electric Vehicles

The adoption rate of battery electric vehicles (EVs) is rapidly increasing. Electric vehicles differ significantly from conventional internal combustion engine vehicles and vary widely across different manufacturers. Emergency responders (ERs) and recovery personnel may have less experience with EVs and lack timely access to critical information such as the extent of the stranded energy present, high-voltage safety hazards, and post-crash handling procedures in a user-friendly manner. This paper presents a software/hardware interactive tool named Electric Vehicle Information for Incident Response Solutions (EVIRS) to aid in the quick access to emergency response and recovery information. The current prototype of EVIRS identifies EVs using the VIN or Make, Model, and Year, and offers several useful features for ERs and recovery personnel. These features include integration and easy access to emergency response procedures tailored to an identified EV, vehicle structural schematics, the quick identification of battery pack specifications, and more. For EVs that are not severely damaged, EVIRS can perform calculations to estimate stranded energy in the EV’s battery and discharge time for various power loads using either EV dashboard information or operational data accessed through the CAN interface. Knowledge of this information may be helpful in the post-crash handling, management, and storage of an EV. The functionality and accuracy of EVIRS were demonstrated through laboratory tests using a 2021 Ford Mach-E and associated data acquisition system. The results indicated that when the remaining driving range was used as an input, EVIRS was able to estimate the pack voltage with an error of less than 3 V. Conversely, when pack voltage was used as an input, the estimated state of charge (SOC) error was less than 5% within the range of 30–90% SOC. Additionally, other features, such as retrieving emergency response guides for identified EVs and accessing lessons learned from archived incidents, have been successfully demonstrated through EVIRS for quick access. EVIRS can be a valuable tool for emergency responders and recovery personnel, both in action and during offline training, by providing crucial information related to assessing EV/battery safety risks, appropriate handling, de-energizing, transport, and storage in an integrated and user-friendly manner.

25 ENERGY STORAGE↗
NASA NTRS1973

Land Use and Mapping

From the standpoint of technology, the most encouraging thing about ERTS has been the level of land-use identification. Land-use detail has exceeded the expectations of the Interagency Steering Committee and the requirements of land-use classification proposed by the Department of Interior. Whereas in the latter instance it was anticipated that only nine classes of land use would probably be identifiable, in fact some 14 to 18 classes have been identified. The success in the level of land-use identification results primarily from the various attributes of the ERTS system. These include the ability to provide repetitive coverage, and in particular seasonal coverage; the ability to image in four bands of the electromagnetic spectrum (green, red, and two near-infrared), which allows for manipulation of various combinations of bands; and the provision by the ERTS system of computer-compatible tapes for machine processing of data. Furthermore, the resolution of ERTS imagery has been better than expected. Although there is some question as to its exact resolving power, it is safe to say objects as small as 100 meters (300 feet) in diameter have been identified. Linear features as narrow as 16 meters (50 feet) can be detected (Figure 1).

Lindgren, D. T.↗
NASA NTRS1999

Mars Spark Source Prototype

The Mars Spark Source Prototype (MSSP) hardware has been developed as part of a proof of concept system for the detection of trace metals such as lead, cadmium, and arsenic in Martian dusts and soils. A spark discharge produces plasma from a soil sample and detectors measure the optical emission from metals in the plasma that will allow their identification and quantification. Trace metal measurements are vital for the assessment of the potential toxicity of the Martian environment for human exploration. The current method of X-ray fluorescence can yield concentrations only of major species. Other instruments are incompatible with the volume, weight, and power constraints for a Mars mission. The instrument will be developed primarily for use in the Martian environment, but would be adaptable for terrestrial use in environmental monitoring. This paper describes the Mars Spark Source Prototype hardware, the results of the characterization tests, and future plans for hardware development.

Eichenberg, Dennis J.↗
NASA NTRS2000

Characteristics of Monolithically Integrated InGaAs Active Pixel Imager Array

Switching and amplifying characteristics of a newly developed monolithic InGaAs Active Pixel Imager Array are presented. The sensor array is fabricated from InGaAs material epitaxially deposited on an InP substrate. It consists of an InGaAs photodiode connected to InP depletion-mode junction field effect transistors (JFETs) for low leakage, low power, and fast control of circuit signal amplifying, buffering, selection, and reset. This monolithically integrated active pixel sensor configuration eliminates the need for hybridization with silicon multiplexer. In addition, the configuration allows the sensor to be front illuminated, making it sensitive to visible as well as near infrared signal radiation. Adapting the existing 1.55 micrometer fiber optical communication technology, this integration will be an ideal system of optoelectronic integration for dual band (Visible/IR) applications near room temperature, for use in atmospheric gas sensing in space, and for target identification on earth. In this paper, two different types of small 4 x 1 test arrays will be described. The effectiveness of switching and amplifying circuits will be discussed in terms of circuit effectiveness (leakage, operating frequency, and temperature) in preparation for the second phase demonstration of integrated, two-dimensional monolithic InGaAs active pixel sensor arrays for applications in transportable shipboard surveillance, night vision, and emission spectroscopy.

Kim, Q.↗
DOE OSTI2026

High-Torque Heavy-Rare-Earth-Free Electric Motor Thermal Management

This project is part of a multi-lab Next-Generation Reliable Electric Drive Systems for Medium and Heavy-Duty Vehicles (NEXT-DRIVE) project led by Oak Ridge National Laboratory (ORNL), and including NREL, Sandia National Laboratories (SNL), and Ames Laboratory that leverages research expertise and facilities of these national labs to develop tools and approaches for reducing the design and development time of new electric drive technologies for medium and heavy-duty vehicles (MHDVs) and their associated costs while increasing reliability and asset utilization. The Next-Drive project aligns with the DOE's goals by introducing high-fidelity multi-physics and AI/ML-based modeling to design low-cost, highly reliable, and longer-lifetime drivetrains, aiming to achieve 25 years of progress in 5 years. The efforts of this project will focus on NEXT-DRIVE Task 4 (led by ORNL, NREL, and AMES) - developing high-fidelity modeling framework and identifying technologies enabling heavy-rare-earth-free electric motors for medium- and heavy-duty vehicles to achieve 1 million miles of operation. Contrary to conventional approaches that optimize the motor for power density, the focus will be to identify motor designs that achieve the best trade-off between motor power density and durable operation. NREL tasks include development of high-fidelity motor thermal models incorporating rotor windage losses and identification, evaluation and measurement of motor interface materials in key thermal pathways. The poster summarizes NREL's accomplishments for the first half of FY 2025 and outlines future plans.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Charaterization of Emerging Computing Architectures for Dynamic Simulation of Future Power Grids with Large-Scale Power Electronics

The increasing penetration of power electronics in power grids significantly raises the computing requirements in a real-time (and/or fast) simulation of the power grid. The real-time simulation is an enabler for evaluating controllers, protection systems, new equipment, and twinning. In this paper, emerging computing architectures such as tensor processing units (TPU), neural/neuromorphic processing units (NPU), and quantum processing units (QPU) are introduced and characterized for the real-time (and/or fast) simulation of power electronics-dominated power grids. The metrics and the process to characterize emerging computing architectures to perform real-time (and/or fast) simulations of future power grids with power electronics are discussed. Three of the emerging computing units are characterized based on these metrics and the process developed. This characterization will enable identification and comparison of emerging computing architectures that can perform real-time (and/or fast) simulation of future power grids.

Choi, Jongchan↗
NASA NTRS1986

Thioredoxins in evolutionarily primitive organisms

Thioredoxins are low molecular weight redox proteins, alternating between the S-S (oxidized) and SH (reduced) states, that function in a number of biochemical processes, including DNA synthesis, DNA replication, and enzyme regulation. Until recently, reduced ferredoxin was known to serve as the source of reducing power for the reduction of thioredoxins only in oxygenic photosynthetic cells. In all other organisms, the source of hydrogen (electrons) for thioredoxin reduction was considered to be NADPH. It was found that Clostridium pasteurianum, an anaerobic organism normally living in the soil unexposed to light, resembles photosynthetic cells in using ferredoxin for the reduction of thioredoxin. The results reveal the existence of a pathway in which ferredoxin, provides the reducing power for the reduction of thioredoxin via the flavoprotein enzyme, ferredoxinthioredoxin reductase. In related studies, it was found that Chromatium vinosum, an anaerobic photosynthetic purple sulfur bacterium, resembles evolutionarily more advanced micro-organisms in having an NADP-thioredoxin system composed of a single thioredoxin which is reduced by NADPH via NADP-thioredoxin reductase. The adoption of the NADP-thioredoxin system by Chromatium seems appropriate in view of evidence tha the organi sm utilizes ATP-driven reverse electron transport. Finally, results of research directed towards the identification of target enzymes of the ferredoxin/thioredoxin system in a cyanobacterium (Nostoc muscorum), show that thioredoxin-linked photosynthetic enzymes of cyanobateria are similar to those of chloroplasts. It now seems that the ferredoxin/thioredoxin system functions in regulating CO2 assimilation via the reductive pentose phosphate cycle in oxygenic but not anoxygenic photosynthetic cells.

Buchanan, B. B.↗
DOE OSTI2021

Rootkit detection system

A system and method (referred to as the system) detect infectious code. The system injects a repetitive software code that causes malware in a monitored device to render a detectable direct current power consumption profile. A guide wave generator generates a guide wave signal that establishes an observational window that is applied to data that represent a direct current source power consumption of the monitored device. An extraction device extracts a portion of the data that represent the direct current source power consumption of the monitored device. A deviation engine identifies the malware on the monitored device without processing data associated with a prior identification of the malware or identifying a source of the malware or identifying a location of the malware on the monitored device.

Dawson, Joel↗
DOE OSTI2021

Advanced Performance Metrics and their Application to the Sensitivity Analysis for Model Validation and Calibration

High-quality generator dynamic models are critical to reliable and accurate power systems studies and planning. With the availability of PMUs, measurement-based approach for model validation has gained significant prominence. In this approach, the quality of a model is analyzed by visually comparing measured generator response with the model-based simulated response for large system disturbances. This paper proposes a new set of performance metrics to assess the model validation results to facilitate automation of the model validation process. In the proposed methodology, first, the slow governor response and comparatively faster oscillatory response are separated, and then a separate set of performance metrics is calculated for each of these two components. These proposed metrics quantify the mismatch between the actual and model-based response in a comprehensive manner without missing any information enabling automation of the process. Furthermore, in this paper, we are also proposing that the sensitivity analysis for model calibration be performed with respect to the proposed metrics for the systematic identification of key parameters. In this work, results obtained using both simulated and real-world case-studies validate the effectiveness of the proposed performance metrics for model validation and their application to the sensitivity analysis for model calibration.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1992

Identification of the nebula G70.7 + 1.2 as a bow shock powered by a pulsar/Be-star binary

New data are presented here that firmly establish the nonthermal nature of the radio emission from the enigmatic radio and optical nebula G70.7 + 1.2. H-alpha and forbidden O I Fabry-Perot observations are used to argue that the extended optical emission from the nebula arises from a bow shock powered by a mass-losing luminous star moving supersonically through dense gas. The strong nonthermal radio emission from the object is then explained as the shocked relativistic wind from a pulsar, which is proposed here as a companion to the Be star. The coincidence of the optical and radio emission requires the pulsar and stellar winds to be mixed together. The system has a large overall velocity of about 60 km/s which is inexplicable in all other models but which is typical of binary pulsars.

Kulkarni, S. R.↗
NASA NTRSDate not supplied

A Case Study on the Challenges and Opportunities for the Deployment of PHM Capabilities in Existing Engineering Systems

The field of Prognostics and Health Management (PHM) of engineering systems has experienced considerable growth over the last decade. From benefits associated with faster and more powerful hardware in the form of wireless sensors, edge devices, and general computing capabilities (GPU’s and cloud computing), to development of powerful algorithms for anomaly detection and remaining useful life (RUL) estimation, the number of engineering systems featuring advanced diagnostics and prognostics capabilities continues to grow at an increasingly faster pace. However, the deployment of PHM capabilities as part of the upgrade of existing engineering systems presents multiple challenges to the PHM practitioner charged with retrofitting such systems. Issues include a lack of specific instrumentation needed to capture the signals of interest; insufficient data and sampling rates required for fault detection and diagnosis, and for detection of failure/degradation indicators; and difficulties in the identification of a system’s nominal behavior as a result of age induced degradation. Today’s PHM practitioner must be able to quickly identify and assess these types of issues to effectively evaluate and select the optimal PHM strategies required to achieve the desired results. This paper presents results from the preliminary evaluation of the High-Pressure Gas Facility (HPGF) infrastructure at NASA’s Stennis Space Center in Hancock County, Mississippi. This evaluation is part of a feasibility study conducted prior to the deployment of prognostics and diagnostics capabilities in the pumps skids of the liquid nitrogen (LN2) system of the HPGF.

Condition Based Maintenance↗
DOE OSTI2021

Using Mask R-CNN to detect and mask ghosting and scattered-light artifacts in astronomical images

Wide-field astronomical surveys are often affected by the presence of undesirable reflections (often known as “ghosting artifacts” or “ghosts”) and scattered-light artifacts. The identification and mitigation of these artifacts is important for rigorous astronomical analyses of faint and low-surface-brightness systems. In this work, we use images from the Dark Energy Survey (DES) to train, validate, and test a deep neural network (Mask R-CNN) to detect and localize ghosts and scattered- light artifacts. We find that the ability of the Mask R-CNN model to identify affected regions is superior to that of conventional algorithms that model the physical processes that lead to such artifacts, thus providing a powerful technique for the automated detection of ghosting and scattered-light artifacts in current and near-future surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Bio-Based Phase Change Materials (PCMs) for Thermal Energy Storage (Final Scientific/Technical Report)

The goal of this project is to develop a novel bio-based phase change material (PCM) derived from squid ring teeth (SRT) proteins, and design a prototype heat exchanger based on these bio-based PCMs for energy storage and dynamic heat exchange for building thermal energy storage systems. The PCMs, derived from SRT proteins, will demonstrate room temperature energy storage capacities and switchable thermal conductivities that redefine the current state-of-the-art (SOA) for building thermal energy storage. Further, in a single material and with a single manufacturing processes, our proposed thermal battery will be developed with “on demand” thermal conductivity for rapid charging/discharging but superior insulation during energy storage periods. More specifically, our bio-based PCMs have demonstrated: 1) the potential for increased energy storage capacity (i.e., greater than paraffines at room temperature); 2) tunability in thermal conductivity with the largest thermal conductivity switching ratios for an intrinsic material reported to date, and 3) a 100% recyclable and biodegradable PCM with low volatility and toxicity and scalability in its manufacture for both residential and commercial applications. The already established ability for roll-to-roll processing of these non-toxic, non-flammable SRT composites along with their carbon-neutral manufacturing processes that has been pioneered by our team make this solution a disruptive and impactful technology to redefine the current SOA of energy storage technologies. The outcomes of this effort have been: 1) the identification of new bio-based PCM that establishes a new SOA for thermal conductivity and energy storage density at room temperature and 2) the development of a new experimental technique to measure the energy storage density via latent heat measurements during melting of thin films. This new technique can be applied to thin films (as thin as < 1 micrometer), and represents a novel approach for thin film energy storage density measurements. Dynamic thermal energy storage is the missing technology that will enable a grid- interactive efficient building (GEB). For a “smart” building capable of connecting with the power grid, the media must be inexpensive and possess thermal switching capabilities to control the time-dependent heat flow into (and out of) the PCM on demand. Unique to the material system in this program, programmable SRT-based PCM show improvements as compared to traditionally used PCMs, and thus its technical performance will represent a leap forward for the future GEB concept.

25 ENERGY STORAGE↗
DOE OSTI2023

Development of a Scalable Risk-informed Predictive Maintenance Cloud-based Strategy at Nuclear Power Plants

The fact that light-water reactor operation and maintenance costs are prohibitively expensive and contribute to the premature decommissioning of nuclear power plants is partly due to how the equipment is monitored. In recent years, cloud computing has emerged as a dominant technology, as its low cost, computing and storage adaptability, and ability to host applications across numerous virtual infrastructures potentially make it a cost-effective alternative to onsite storage and diagnostics. In this paper, a technological assessment is carried out on a provisional cloud deployment architecture for a nuclear power plant predictive monitoring system. This cloud-based monitoring system would enable maintenance and diagnostic analysts and other authorized plant users to remotely monitor equipment functionality, thus enabling early fault detection and effective predictive maintenance practices. To provide data processing and storage, sensor device networking, and database management, the Microsoft Azure cloud platform is utilized as part of the proposed cloud architecture; however, this analysis could be extended to other cloud computing service providers as well. The focus of this paper is on application of cloud resources for enabling predictive maintenance, identification of technological hurdles associated with moving to a cloud-computing-based architecture, and potential benefits from moving to a centralized cloud system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRSDate not supplied

Extending ISS Life Beyond 2030

The United States On-orbit Segment (USOS) of the International Space Station (ISS) was designed to meet a 15-year on-orbit life. Since the first hardware was launched in late 1998, the ISS would have reached its end of life in 2013. With the realization that the ISS would be needed well into the next decade, and beyond, a multi-disciplinary effort was undertaken to extend the ISS’ life through 2028 and to show that further extension to 2040 and beyond is not only feasible but achievable. Currently, NASA and the ISS international partners have agreed to extend its operations through 2030. This collaborative effort ensures that the ISS will continue to serve as a hub for scientific research, international cooperation, and educational endeavors for the next decade. Maintaining a continuous human presence in Low Earth Orbit (LEO) is desirable for testing new LEO, lunar, and deep-space technologies; conducting scientific research in micro-gravity for the benefit of life on Earth; and enabling a seamless transition of capabilities to one or more commercially owned and operated destinations. This paper provides an overview of the ISS life extension project with a particular focus on the analytical approach used to assess the primary structure. This analytical approach includes future operations planning, critical location screening, on-orbit dynamic load simulation, on-orbit optical property degradation studies, on-orbit thermal analyses, spectra generation, crack model idealization, fracture analyses, and post processing. Structural life results and identification of the most critical on-orbit events are presented. Also addressed are life extension approaches for other affected sub-systems, including: 1. Secondary Structure. 2. Materials. Evaluations consider environmental exposure to atomic oxygen, ionizing and gamma radiation, fluids, etc. Life limited materials, wear, and usage effects are also considered. 3. Environmental Control and Life Support Systems, including oxygen supply and generation, water recovery and management, and regenerative hardware. Evaluations are performed to determine which hardware can be run to failure and which are assessed for life extension. 4. Electrical power system. ISS is powered by eight channels of solar arrays and an electrical energy storage system providing 357 kWh power. Power generation and balance analyses are performed considering hardware degradation and increasing power demand. 5. Logistics and maintenance. Analyses are performed to determine critical spares required to maintain functionality. Consideration is given to supply chain health, obsolescence issues, onboard stowage availability, and up-mass capability. The successful life extension results have built confidence to safely operate, maintain and enhance the ISS well beyond the current decade. Extending the operational life of the ISS maintains an international presence in LEO and serves to avoid a gap in capability necessary to fulfill the exploration and research needs of NASA, international partners, and industry without interruption until a commercial space station is operational.

design life↗
DOE OSTI2020

Automated Threat Recognition For Aviation Security Applications

We have developed a framework for automated threat recognition (ATR) of explosive threat materials for both single-energy and dual-energy X-ray CT systems. Under this framework, two different types of ATR have been developed. The first type of ATR employs supervised machine learning with statistical characterization of target materials for threat identification training. The reliance only on statistical characterization information for threat training uniquely enables this style of ATR to adapt quickly to evolving threats. The second type of ATR employs deep learning through convolutional neural networks. Convolutional neural networks are attractive due to their human-like capacity for learning and strong ability to identify trends and patterns. Although this method is more powerful than the first type, it requires large amounts of training data and therefore is less agile. Each ATR performs threat characterization at the voxel neighborhood level. This approach avoids the use of threat shape as a detection criterion, which is prohibited by DHS and TSA guidelines.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Bus Clustering for Distribution Grid Topology Identification

Recovering the distribution grid topology is essential to perform several distribution system operator functions. Many algorithms that address the topology recovery problem have already been proposed in the literature. Most are based on a priori information regarding which buses are fed by which substation; however, this information might not be available because frequent grid reconfigurations change the distribution grid portion connected to each substation. This paper addresses the problem of assigning every substation the set of buses that it is feeding, given field data. First, the aforementioned task is cast as a nonconvex optimization problem. Second, a relaxed version of the optimization problem is solved via the alternating direction method of multipliers. Finally, the performance of our approach is validated through numerical simulations of realistic scenarios using a standard IEEE benchmark feeder.

bus clustering↗