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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Orbit Determination and Navigation of the Solar Terrestrial Relations Observatory (STEREO)

This paper provides an overview of the required upgrades necessary for navigation of NASA's twin heliocentric science missions, Solar TErestrial RElations Observatory (STEREO) Ahead and Behind. The orbit determination of the STEREO spacecraft was provided by the NASA Goddard Space Flight Center's (GSFC) Flight Dynamics Facility (FDF) in support of the mission operations activities performed by the Johns Hopkins University Applied Physics Laboratory (APL). The changes to FDF's orbit determination software included modeling upgrades as well as modifications required to process the Deep Space Network X-band tracking data used for STEREO. Orbit results as well as comparisons to independently computed solutions are also included. The successful orbit determination support aided in maneuvering the STEREO spacecraft, launched on October 26, 2006 (00:52 Z), to target the lunar gravity assists required to place the spacecraft into their final heliocentric drift-away orbits where they are providing stereo imaging of the Sun.

Mesarch, Michael A.↗
NASA NTRSDate not supplied

Deep Learning-Based Negotiation Strategy Selection for Cooperative Conflict Resolution in Urban Air Mobility

This paper presents a collaborative conflict resolution technique using deep neural network-based intelligent search of the solution space. This approach offers a rapid convergence to a mutually acceptable solution for real-time conflict resolution, suitable for urban air mobility operations. Furthermore, the presented technique allows operational flexibility to the urban air mobility agents where these agents can collaboratively devise the solution via integrative negotiation, based on their local utility functions, as long as such a solution does not violate the global safety thresholds. The presented machine-to-machine negotiation method is built on our prior work on holistic assessment of the airspace and potential conflict detection implemented at-the-edge, onboard the unmanned aircraft systems. This paper extends the prior work to augment decision-making at-the-edge, thereby, promising a true distributed control architecture for urban air mobility. In this approach, each agent (a) builds a potential in-flight conflict map, (b) identifies the conflicting agents, (c) dynamically prepares a list of alternatives based on its current utility functions, (d) negotiates with the conflicting agents to pick one of these alternatives, and (e) implements the negotiated alternative to mutually resolve the conflict. Note that such an approach does not require a contingency plan to be made pre-flight, as the conflict resolution strategies are decided and negotiated in real time based on the present state of the agent. The contingency plan, if available, can serve as an input to the real-time conflict resolution strategy formulation, and also can be used as a fallback plan in case the negotiation fails and the impacted agents need to switch to a rule-based/supervisory resolution mode from the discussed distributed resolution mode. The presented collaborative negotiation-based conflict resolution technique incorporates a time-dependent reward function to catalyze collaborative resolution by incentivizing the agents with local and global rewards beneficial to their business operations.

Advanced Air Mobility↗
NASA NTRS2023

Flexible User Radio for Lunar Missions

NASA’s Artemis program and other lunar exploration and development programs are planning over 40 lunar missions before 2030. Lunar missions, both crewed and uncrewed, include orbiters, landers, rovers, and surface stations. All these missions require communications with Earth, either via Direct to Earth (DTE) links or through relays in lunar orbit. Multiple DTE options are available among existing and planned ground stations: Deep Space Network (DSN), European Space Agency, and others. Relay options include the planned Lunar Gateway, LunaNet compliant relays, and some lunar landers propose to launch dedicated orbiters. The dilemma for lunar system designers is to identify a communication link which meets mission requirements but does not have issues of limited access (e.g. DSN is in high demand supporting deep space missions with high priority and some with inflexible schedules), system impacts (high power Radio Frequency (RF) for DTE links), cost (dedicated relay), or operational date. To avoid this difficult decision, a Flexible Radio for Lunar Missions is proposed, which will enable system designs to proceed prior to any final decision on the communication network to be used, by enabling compatibility with any of multiple DTE or orbital relay communication systems. The Flexible Radio will support the necessary frequency, bandwidth, modulation, and power requirements to interoperate with the majority of known or planned DTE or relay systems, and can be designed into a lunar mission without prior knowledge of which link will ultimately be used. Furthermore, the link being used can be changed as needed during the mission, in near real time. The Flexible Radio design will leverage work already completed at NASA in the areas of Wideband RF, Software Defined Radio, Adaptive Coding and Modulation, and Phased Array antennas. The Flexible Radio requires sufficient bandwidth to cover the allocated frequencies for both the operation of links in cislunar space and for space-to-Earth links; the flexibility to support multiple modulations, data rates, and coding schemes; the ability to identify available relays, detect and recognize the signals of those relays, and adapt its own frequency, modulation, symbol rate, and code rate to operate with the detected relay (or DTE station); and finally, it requires appropriate software to support network configuration and interoperability with the detected network. The Flexible Radio can be designed in a sufficiently small, lightweight, and low-power package to be used in a wide variety of lunar systems. The initial implementation, as proposed, will focus on the Ka-band, supporting up to 2 GHz bandwidth around the 27 GHz frequency for return links, and 23 GHz for forward links. Other frequency bands are under consideration for future configurations. The software defined modem will support OQPSK, BPSK, and NASA-defined modulations which also support two-way ranging with data. For near-real time adaptation, the Flexible Radio will scan the sky for available relays, using a phased array antenna with Adaptive/Cognitive Communications. It will then configure for network interoperability supporting DTN and other protocol options. The Flexible Radio will support scheduled connections and on-demand use when available.

Lunar Space Communications↗
NASA NTRSDate not supplied

Flexible User Radio for Lunar Missions

NASA’s Artemis program and other lunar exploration and development programs are planning over 40 lunar missions before 2030. Lunar missions, both crewed and uncrewed, include orbiters, landers, rovers, and surface stations. All these missions require communications with Earth, either via Direct to Earth (DTE) links or through relays in lunar orbit. Multiple DTE options are available among existing and planned ground stations: Deep Space Network (DSN), European Space Agency, and others. Relay options include the planned Lunar Gateway, LunaNet compliant relays, and some lunar landers propose to launch dedicated orbiters. The dilemma for lunar system designers is to identify a communication link which meets mission requirements but does not have issues of limited access (e.g. DSN is in high demand supporting deep space missions with high priority and some with inflexible schedules), system impacts (high power Radio Frequency (RF) for DTE links), cost (dedicated relay), or operational date. To avoid this difficult decision, a Flexible Radio for Lunar Missions is proposed, which will enable system designs to proceed prior to any final decision on the communication network to be used, by enabling compatibility with any of multiple DTE or orbital relay communication systems. The Flexible Radio will support the necessary frequency, bandwidth, modulation, and power requirements to interoperate with the majority of known or planned DTE or relay systems, and can be designed into a lunar mission without prior knowledge of which link will ultimately be used. Furthermore, the link being used can be changed as needed during the mission, in near real time. The Flexible Radio design will leverage work already completed at NASA in the areas of Wideband RF, Software Defined Radio, Adaptive Coding and Modulation, and Phased Array antennas. The Flexible Radio requires sufficient bandwidth to cover the allocated frequencies for both the operation of links in cislunar space and for space-to-Earth links; the flexibility to support multiple modulations, data rates, and coding schemes; the ability to identify available relays, detect and recognize the signals of those relays, and adapt its own frequency, modulation, symbol rate, and code rate to operate with the detected relay (or DTE station); and finally, it requires appropriate software to support network configuration and interoperability with the detected network. The Flexible Radio can be designed in a sufficiently small, lightweight, and low-power package to be used in a wide variety of lunar systems. The initial implementation, as proposed, will focus on the Ka-band, supporting up to 2 GHz bandwidth around the 27 GHz frequency for return links, and 23 GHz for forward links. Other frequency bands are under consideration for future configurations. The software defined modem will support OQPSK, BPSK, and NASA-defined modulations which also support two-way ranging with data. For near-real time adaptation, the Flexible Radio will scan the sky for available relays, using a phased array antenna with Adaptive/Cognitive Communications. It will then configure for network interoperability supporting DTN and other protocol options. The Flexible Radio will support scheduled connections and on-demand use when available.

Lunar Space Communications↗
DOE OSTI2023

Spatio-Temporal Deep Graph Network for Event Detection, Localization, and Classification in Cyber-Physical Electric Distribution System

This work proposes a deep graph learning framework to identify, locate, and classify power, cyber, and cyber power events at the distribution system level. The proposed algorithm jointly exploits spatial, temporal, and node-level cyber and physical data features. The developed graph neural network, together with a deep autoencoder, utilizes physical measurements from distribution level phasor measurement units and cyber data from communication network logs. The spatial structure of the synchrophasor measurements and network is incorporated through a weighted adjacency matrix. The temporal structure is incorporated by defining a spatial operation in the gated recurrent unit. This spatio-temporal learning element resides inside a power event detection, localization, and classification module that provides the degree of confidence for an event label. To accurately pinpoint the location of an event to the nearest bus equipped with a measurement unit, a combination of squared error and proximity score is utilized. Also included is a cyber event detection module that employs heteroskedasticity to analyze the significance of various cyber features during different types of attacks. Finally, a dual-bit cyber-power decision table determines the nature of the event. The proposed method is validated on two distribution systems modeled in OPAL-RT/Hypersim with limited phasor measurement units for different possible physical and cyber events. Further analyses include comparison with other state-of-the-art methods and validation in the presence of measurement noise. As a result, our method outperforms existing approaches and achieves an average detection accuracy of 97.97%, F1-score of 96.88%, precision of 96.53%, and recall of 98.57%.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Enhanced physics-constrained deep neural networks for modeling vanadium redox flow battery

Numerical simulation has become indispensable in advancing cost-effective process optimization and control of flow batteries. We propose an enhanced version of the physics-constrained deep neural network (PCDNN) approach to provide high-accuracy voltage predictions in the vanadium redox flow batteries (VRFBs). The purpose of the PCDNN approach is to enforce the physics-based zero-dimensional (0D) VRFB model in a neural network to assure model generalization for various battery operation conditions. However, limited by the simplifications of the 0D model, the PCDNN cannot capture sharp voltage changes in the extreme SOC regions. To improve the accuracy of voltage prediction at extreme ranges, we introduce a second (enhanced) DNN to mitigate the prediction errors carried from the 0D model itself and call the resulting approach enhanced PCDNN (ePCDNN). By comparing with experimental data, we demonstrate that the ePCDNN approach can accurately capture the voltage response throughout the charge–discharge cycle, including the tail region of the voltage discharge curve. The loss function for training the ePCDNN is designed to be flexible by adjusting the weights of the physics-constrained DNN and the enhanced DNN. In conclusion, this allows the ePCDNN framework to be transferable to battery systems with variable physical model fidelity.

25 ENERGY STORAGE↗
DOE OSTI2025

Resistive Switching of Spinel Li 4 Ti 5 O 12 Lithium-Ion Battery Material for Neuromorphic Computing

The rapid rise of AI has exposed significant limitations in conventional Von Neumann computing architecture, particularly in regard to speed and energy efficiency. To address these challenges, researchers are exploring a brain-inspired neuromorphic architecture that mimics biological neural networks, enabling massive parallel processing with reduced power consumption for complex AI computational demands. Recent interest has focused on utilizing battery electrodes and solid electrolyte materials for their resistive switching properties in developing a neuromorphic architecture. These properties are precisely tuned through local- and bulk-level chemical composition modifications via voltage bias stimuli. In this study, we demonstrate fabricating a three-terminal lithium-ion electrochemical transistor based on lithium titanium oxide (Li 4 Ti 5 O 12 ), a popular lithium-ion battery anode material. We deposited and characterized LTO thin films using RF sputtering, demonstrating a 6 orders of magnitude increase in electronic conductivity upon lithiation, with conductivity plateauing after 20% lithiation. Density functional theory calculations revealed transformation from the insulating to conducting state, supported by experimental characterization through X-Ray Photoelectron Spectroscopy (XPS) and Direct Current (DC) polarization analyses. The fabricated transistor consisted of LTO as the channel layer, gold as source/drain terminals, lithium phosphorus oxynitride (LiPON) as the lithium-ion conductor, and copper as the gate terminal. The device exhibited clear hysteresis in transfer characteristics due to lithium insertion/extraction processes. Long-term potentiation (LTP) and long-term depression (LTD) measurements showed an asymmetric ratio of 1.425 and maximum/minimum conductance ratio of 7.83. When implemented in a deep neural network (DNN) for MNIST handwritten digit recognition, the device achieved 92.03% accuracy over 20 training epochs. Detailed transport mechanism analysis revealed the crucial role of oxygen vacancies and interface effects in device operation. Our preliminary findings establish LTO-based lithium-ion electrochemical transistors as promising candidates for energy-efficient neuromorphic computing applications, offering potential solutions to traditional Von Neumann architecture limitations.

25 ENERGY STORAGE↗
DOE OSTI2021

Ensemble learning-iterative training machine learning for uncertainty quantification and automated experiment in atom-resolved microscopy

Deep learning has emerged as a technique of choice for rapid feature extraction across imaging disciplines, allowing rapid conversion of the data streams to spatial or spatiotemporal arrays of features of interest. However, applications of deep learning in experimental domains are often limited by the out-of-distribution drift between the experiments, where the network trained for one set of imaging conditions becomes sub-optimal for different ones. This limitation is particularly stringent in the quest to have an automated experiment setting, where retraining or transfer learning becomes impractical due to the need for human intervention and associated latencies. Here we explore the reproducibility of deep learning for feature extraction in atom-resolved electron microscopy and introduce workflows based on ensemble learning and iterative training to greatly improve feature detection. This approach allows incorporating uncertainty quantification into the deep learning analysis and also enables rapid automated experimental workflows where retraining of the network to compensate for out-of-distribution drift due to subtle change in imaging conditions is substituted for human operator or programmatic selection of networks from the ensemble. This methodology can be further applied to machine learning workflows in other imaging areas including optical and chemical imaging.

36 MATERIALS SCIENCE↗
DOE OSTI2026

PowerMappeR: Power-Optimized Mapping of SNNs onto ReRAM Crossbars coupled via Packet-Switched NoCs

Many recent efforts in developing hardware-accelerated spiking neural networks (SNNs) are characterized by deep co-design between algorithms, architectures, and devices. Architectural advances overcome device constraints by coupling together many small resistive-RAM (ReRAM) crossbars via a network-on-chip (NoC) for neuromorphic component operation. Concurrently, improved SNN training methods increase accuracy and structural sparsity in networks despite growing problem sizes. Finally, compilers leverage these attributes to minimize area and inter-crossbar communication while mapping large SNNs to sophisticated architectures. However, for compiler-driven co-design to realize increasingly complex and profitable optimizations, a compile-time view of power consumption is critical. We present PowerMappeR to express and optimize over mapping-, architecture-, and device-specific power consumption information. By modeling the dynamic power of well-established components, we develop an integer linear programming (ILP)-based, encoding-agnostic, parametric power estimation model. Using this model, we demonstrate practical improvements in area and inter-crossbar communication by 0%–9.5% and 1.4%–5.1%, respectively. We also limit hotspot formation during optimization, achieving comparable or better results in targeted metrics with up to 96.4%–97.1% restriction of hotspot magnitude. Finally, we introduce profile-guided formulations to reduce worst-case and expected-case hotspot magnitude by 40.7%–69.5% and 40.6%–56.3%, respectively. Optimizing worst-case hotspot magnitude incidentally improves expected-case magnitude by 10.85%–33.45%. Reciprocally, optimizing expected-case magnitude incidentally improves worst-case magnitude by 4.33%–39.87%. Validation against hardware simulators confirms that PowerMappeR can decrease dynamic power consumption by 12.6%–27.3%.

Pohl, Devin [ORNL] (ORCID:0009000040149027)↗
NASA NTRS1978

Network Operations Control Center Block 3 modifications

The Network Operations Control Center (NOCC) Block 3 configuration is in the process of being upgraded to provide the capabilities required to support Voyager and Pioneer Venus 1978 Project commitments as well as to support Deep Space Station changes arising from the Mark 3 DSN Data Subsystem implementation. Information is given on the hardware and software changes necessary to implement such capabilities.

Garcia, E. A.↗
NASA NTRS1982

Receiver-exciter controller design

A description of the general design of both the block 3 and block 4 receiver-exciter controllers for the Deep Space Network (DSN) Mark IV-A System is presented along with the design approach. The controllers are designed to enable the receiver-exciter subsystem (RCV) to be configured, calibrated, initialized and operated from a central location via high level instructions. The RECs are designed to be operated under the control of the DMC subsystem. The instructions are in the form of standard subsystem blocks (SSBs) received via the local area network (LAN). The centralized control provided by RECs and other DSCC controllers in Mark IV-A is intended to reduce DSN operations costs from the Mark III era.

Jansma, P. A.↗
NASA NTRS1981

Consolidation of NASA tracking stations into a single ground network in the TDRSS era

NASA has operated two separate worldwide ground-based tracking and data acquisition networks for support of its various missions. The Spaceflight Tracking and Data Network (STDN) has provided support to all NASA earth orbiting spacecraft. The Deep Space Network (DSN) supports almost exclusively those unmanned exploratory spacecraft which have been sent far from earth. The Tracking and Data Relay Satellite System (TDRSS), which is conceptually a part of the STDN, will soon be added to the first two networks. The TDRSS will consist of two geosynchronous satellites together with a single ground terminal in White Sands, New Mexico. The TDRSS was conceived as a means of providing improved tracking and data relay service for a large class of the earth orbiting satellites. An investigation was conducted with the objective to reduce the costs of providing support to those spacecraft which were not TDRS-compatible. It was recommended that the core sites of the Ground segment of the STDN (GSTDN) be consolidated into the DSN

Layland, J. W.↗
NASA NTRS2003

Tracking capability for entry, descent and landing and its support to NASA Mars Exploration Rovers

This paper described a new capability recently deployed in the NASA Deep Space Network to support the entry, descent and landing of the two Mars Exploration Rovers - Spirit and Opportunity. This final segment of a 7-month journey was critical step in enabling successful mission operation. The EDL Data Analysis (EDA) equipment processed the open loop recording samples from the existing radio science receivers, extracted the MFSK-modulated tones, and provided information on the occurrence of associated events happened onboard spacecraft. The EDA software supported real-time as well as post pass processing. The design flexibility allowed the track to be divided into different segments, each could be processed with a configuration optimized for its signal conditions and uncertainties. The use of dynamic lock state concept enabled signal detection be done with minimum required computing power - less was spent when signal was steadily detected and more when signal fluctuated. With the server-client design, the EDA supported connections to different remote operation centers for monitor purpose. The paper also presented the field results from both Spirit and Opportunity landings. The detection were much better than anticipated. All critical event tones were seen in real time. Surprising detection of LCP signal was found with Spirit landing, resulted in a reconfiguration for Opportunity landing to maximize signal detection.

tracking↗
NASA NTRS2011

An Analysis of Near Fields of 34m Antennas of JPL/NASA Deep Space Network

This paper addresses the issue of calculating near fields of the 34m Beam Waveguide (BWG) antennas of the NASA/JPL Deep Space Network (DSN). Calculating the near fields of DSN antennas are of interest in receive mode where the transmitting signals from nearby flying objects such as helicopters and airplanes could interfere with the operation of sensitive RF receiving system of DSN antennas, and in the transmit mode where fields from high-powered DSN antennas interfere with receivers on nearby flying objects, as well as safety considerations for the operators and visitors to the grounds surrounding the antenna sites. A complete and detailed analysis has been performed using PO/PTD techniques, including surface errors and support struts effects. Some results are presented, including comparisons with preliminary field tests.

near fields↗
NASA NTRS2015

Deploying the NASA Meter Class Autonomous Telescope (MCAT) on Ascension Island

NASA has successfully constructed the 1.3m Meter Class Autonomous Telescope (MCAT) facility on Ascension Island in the South Atlantic Ocean. MCAT is an optical telescope designed specifically to collect ground-based data for the statistical characterization of orbital debris ranging from Low Earth Orbit (LEO) through Middle Earth Orbits (MEO) and beyond to Geo Transfer and Geosynchronous Orbits (GTO/GEO). The location of Ascension Island has two distinct advantages. First, the near-equatorial location fills a significant longitudinal gap in the Ground-based Electro-Optical Deep Space Surveillance (GEODSS) network of telescopes, and second, it allows access to objects in Low Inclination Low-Earth Orbits (LILO). The MCAT facility will be controlled by a sophisticated software suite that operates the dome and telescope, assesses sky and weather conditions, conducts all necessary calibrations, defines an observing strategy (as dictated by weather, sky conditions and the observing plan for the night), and carries out the observations. It then reduces the collected data via four primary observing modes ranging from tracking previously cataloged objects to conducting general surveys for detecting uncorrelated debris. Nightly observing plans, as well as the resulting text file of reduced data, will be transferred to and from Ascension, respectively, via a satellite connection. Post-processing occurs at NASA Johnson Space Center. Construction began in September, 2014 with dome and telescope installation occurring in April through early June, 2015. First light was achieved in June, 2015. Acceptance testing, full commissioning, and calibration of this soon-to-be fully autonomous system commenced in summer 2015. The initial characterization of the system from these tests is presented herein.

Lederer, S. M.↗
NASA NTRS2019

GPS Based Autonomous Navigation Study for the Lunar Gateway

This paper describes and predicts the performance of a conceptual autonomous GPS-based navigation system for NASA's planned lunar Gateway. This system is based on the flight-proven Magnetospheric Multiscale (MMS) GPS navigation system, augmented with an earth-pointed high-gain antenna and with an option for an atomic clock. High-fidelity simulations, calibrated against MMS flight data and making use of GPS transmitter patterns from the GPS Antenna Characterization Experiment (ACE) project are developed for operation of the system in the Gateway Near-Rectilinear Halo Orbit (NRHO). The results indicate that GPS can provide an autonomous, realtime navigation capability with comparable, or superior, performance to traditional Deep Space Network approach with eight hours of tracking per day.

Winternitz, Luke B.↗
NASA NTRS2018

NASA’s and ESA’s Tracking Networks, A Decade of Strategic Partnership for Solar System Exploration

Planetary missions travel vast distances in the Solar System for valuable scientific exploration. Spacecraft return data to Earth via radio links that suffer power losses inversely proportional to the square of the distance, which forms a tremendous engineering challenge compounded by relatively low onboard transmitter power, typically 20 Watts at X-band (~8 GHz). Deep space missions are enabled only because leading space agencies invested in developing very large communications antennas as well as provided a sophisticated suite of tracking, telemetry and command standard services. NASA’s Deep Space Network and ESA’s ESTRACK network are distributed geographically to provide global coverage and utilize stations ranging in size from 34 meters to 70 meters in diameter. Over time, the expanding number of missions, increased requirements for redundancy during critical events as well as the drive for improved navigation accuracy via long-baseline interferometric techniques, increased the networks’ loading and strongly motivated collaboration between the two agencies. Ten years ago, NASA and ESA established a cross-support agreement in addition to multiple on-going mission-specific agreements to meet this need. This strategic partnership was enabled by the development of international inter-operability technical standards and compatible spectrum usage. Over recent years, many critical events were supported via these agreements and some scientific breakthroughs were enabled. A multi-nation tracking contention period envisioned in the near future will also benefit from this partnership. Due to its success over the last decade, the DSN-ESTRACK partnership is serving as a model for other agencies with deep space communication facilities and similar interest. This paper reviews the benefits and lessons learned from collaborative deep space exploration, especially via communications networks, and discusses the potential implementation of similar NASA agreements with other space agencies.

Costrell, Jim↗