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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Ensuring reliable connectivity to cellular-connected UAVs with up-tilted antennas and interference coordination

To integrate unmanned aerial vehicles (UAVs) in future large-scale deployments, a new wireless communication paradigm, namely, the cellular-connected UAV has recently attracted interest. However, the line-of-sight dominant air-to-ground channels along with the antenna pattern of the cellular ground base stations (GBSs) introduce critical interference issues in cellular-connected UAV communications. In particular, the complex antenna pattern and the ground reflection (GR) from the down-tilted antennas create both coverage holes and patchy coverage for the UAVs in the sky, which leads to unreliable connectivity from the underlying cellular network. To overcome these challenges, in this paper, we propose a new cellular architecture that employs an extra set of co-channel antennas oriented towards the sky to support UAVs on top of the existing down-tilted antennas for ground user equipment (GUE). To model the GR stemming from the down-tilted antennas, we propose a path-loss model, which takes both antenna radiation pattern and configuration into account. Next, we formulate an optimization problem to maximize the minimum signal-to-interference ratio (SIR) of the UAVs by tuning the up-tilt (UT) angles of the up-tilted antennas. Since this is an NP-hard problem, we propose a genetic algorithm (GA) based heuristic method to optimize the UT angles of these antennas. After obtaining the optimal UT angles, we integrate the 3GPP Release-10 specified enhanced inter-cell interference coordination (eICIC) to reduce the interference stemming from the down-tilted antennas. Our simulation results based on the hexagonal cell layout show that the proposed interference mitigation method can ensure higher minimum SIRs for the UAVs over baseline methods while creating minimal impact on the SIR of GUEs.

3GPP↗
DOE OSTI2023

I/O Access Patterns in HPC Applications: A 360-Degree Survey

The high-performance computing I/O stack has been complex due to multiple software layers, the inter-dependencies among these layers, and the different performance tuning options for each layer. In this complex stack, the definition of an “I/O access pattern” has been reappropriated to describe what an application is doing to write or read data from the perspective of different layers of the stack, often comprising a different set of features. It has become common to have to redefine what is meant when discussing a pattern in every new study, as no assumption can be made. This survey aims to propose a baseline taxonomy, harnessing the I/O community’s knowledge over the past 20 years. This definition can serve as a common ground for high-performance computing I/O researchers and developers to apply known I/O tuning strategies and design new strategies for improving I/O performance. We seek to summarize and bring a consensus to the multiple ways to describe a pattern based on common features already used by the community over the years.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Demystifying asynchronous I/O Interference in HPC applications

With increasing complexity of HPC workflows, data management services need to perform expensive I/O operations asynchronously in the background, aiming to overlap the I/O with the application runtime. However, this may cause interference due to competition for resources: CPU, memory/network bandwidth. The advent of multi-core architectures has exacerbated this problem, as many I/O operations are issued concurrently, thereby competing not only with the application but also among themselves. Furthermore, the interference patterns can dynamically change as a response to variations in application behavior and I/O subsystems (e.g. multiple users sharing a parallel file system). Without a thorough understanding, I/O operations may perform suboptimally, potentially even worse than in the blocking case. To fill this gap, here we investigate the causes and consequences of interference due to asynchronous I/O on HPC systems. Specifically, we focus on multi-core CPUs and memory bandwidth, isolating the interference due to each resource. Then, we perform an in-depth study to explain the interplay and contention in a variety of resource sharing scenarios such as varying priority and number of background I/O threads and different I/O strategies: sendfile, read/write, mmap/write underlining trade-offs. The insights from this study are important both to enable guided optimizations of existing background I/O, as well as to open new opportunities to design advanced asynchronous I/O strategies.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

Digital tracking loops for a programmable digital modem

In this paper, an analysis and hardware emulation of the tracking loops for a very flexible programmable digital modem (PDM) will be presented. The modem is capable of being programmed for 2, 4, 8, 16-PSK, 16-QAM, MSK, and Offset-QPSK modulation schemes over a range of data rates from 2.34 to 300 Mbps with programmable spectral occupancy from 1.2 to 1.8 times the symbol rate; these operational parameters are executable in burst or continuous mode. All of the critical processing in both the modulator and demodulator is done at baseband with very high-speed digital hardware and memory. Quadrature analog front-ends are used for translation between baseband and the IF center frequency. The modulator is based on a table lookup approach, where precomputed samples are stored in memory and clocked out according to the incoming data pattern. The sample values are predistorted to counteract the effects of the other filtering functions in the link as well as any transmission impairments. The demodulator architecture was adapted from a joint estimator-detector (JED) mathematical analysis. Its structure is applicable to most signalling formats that can be represented in a two-dimensional space. The JED realization uses interdependent, mutually aiding tracking loops with post-detection data feedback. To expedite and provide for more reliable synchronization, initial estimates for these loops are computed in a parallel acquisition processor. The cornerstone of the demodulator realization is the pre-averager received data filter which allows operation over a broad range of data rates without any hardware changes and greatly simplifies the implementation complexity. The emulation results confirmed tracking loop operation over the entire range of operational parameters listed above, as well as the capability of achieving and maintaining synchronization at BER's in excess of 10(exp -1). The emulation results also showed very close agreement with the tracking loop analysis, and validated the resolution apportionment of the various hardware elements in the tracking loops.

Poklemba, John J.↗
NASA NTRS1989

Detecting and diagnosing SSME faults using an autoassociative neural network topology

An effort is underway at the University of Tennessee Space Institute to develop diagnostic expert system methodologies based on the analysis of patterns of behavior of physical mechanisms. In this approach, fault diagnosis is conceptualized as the mapping or association of patterns of sensor data to patterns representing fault conditions. Neural networks are being investigated as a means of storing and retrieving fault scenarios. Neural networks offer several powerful features in fault diagnosis, including (1) general pattern matching capabilities, (2) resistance to noisy input data, (3) the ability to be trained by example, and (4) the potential for implementation on parallel computer architectures. This paper presents (1) an autoassociative neural network topology, i.e. the network input and output is identical when properly trained, and hence learning is unsupervised; (2) the training regimen used; and (3) the response of the system to inputs representing both previously observed and unkown fault scenarios. The effects of noise on the integrity of the diagnosis are also evaluated.

Ali, M.↗
NASA NTRS2002

Design of an Airborne L-Band Cross-Track Scanning Scatterometer

In this report, we describe the design of an airborne L-band cross-track scanning scatterometer suitable for airborne operation aboard the NASA P-3 aircraft. The scatterometer is being designed for joint operation with existing L-band radiometers developed by NASA for soil moisture and ocean salinity remote sensing. In addition, design tradeoffs for a space-based radar system have been considered, with particular attention given to antenna architectures suitable for sharing the antenna between the radar and radiometer. During this study, we investigated a number of imaging techniques, including the use of real and synthetic aperture processing in both the along track and cross-track dimensions. The architecture selected will permit a variety of beamforming algorithms to be implemented, although real aperture processing, with hardware beamforming, provides better sidelobe suppression than synthetic array processing and superior signal-to-noise performance. In our discussions with the staff of NASA GSFC, we arrived at an architecture that employs complete transmit/receive modules for each subarray. Amplitude and phase control at each of the transmit modules will allow a low-sidelobe transmit pattern to be generated over scan angles of +/- 50 degrees. Each receiver module will include all electronics necessary to downconvert the received signal to an IF offset of 30 MHz where it will be digitized for further processing.

Hilliard, Lawrence M.↗
DOE OSTI2023

Engineering catalytical electrodes for applications in energy areas

An ink formulation and electrode that enhances hydrogen production, oxygen production, carbon dioxide reduction and other electrocatalytic reactions. Embodiments include an ink formulation with polymer binders having different catalytical precursors and a 3D electrode produced by additive manufacturing from the inventor's ink formulation. Various embodiments of the inventor's apparatus, systems, and methods provide inks that that are 3D-printed into patterns that optimize surface area and flow. The catalytic materials are imbedded into the ink matrix which is then printed into a 3D structure that has architecture that optimizes surface area and flow properties.

Liang, Siwei↗
NASA NTRS1987

Distributed phased array architecture study

Variations in amplifiers and phase shifters can cause degraded antenna performance, depending also on the environmental conditions and antenna array architecture. The implementation of distributed phased array hardware was studied with the aid of the DISTAR computer program as a simulation tool. This simulation provides guidance in hardware simulation. Both hard and soft failures of the amplifiers in the T/R modules are modeled. Hard failures are catastrophic: no power is transmitted to the antenna elements. Noncatastrophic or soft failures are modeled as a modified Gaussian distribution. The resulting amplitude characteristics then determine the array excitation coefficients. The phase characteristics take on a uniform distribution. Pattern characteristics such as antenna gain, half power beamwidth, mainbeam phase errors, sidelobe levels, and beam pointing errors were studied as functions of amplifier and phase shifter variations. General specifications for amplifier and phase shifter tolerances in various architecture configurations for C band and S band were determined.

Bourgeois, Brian↗
NASA NTRS2003

Mission interactive scenarion studio for autonomous spacecraft

We propose building a Studio enabling the use of diverse existing mission activity and scenario patterns, the creation of new ones, and the modeling of their effects using existing modeling tools. The core of the Studio is a component-based Type Library, which captures years of mission adaptation patterns in various forms. The Studio works as a content server to capture the developed adaptation knowledge for reuse and provides bridging into different mission uplink implementations, including the Mission Data System [l] (MDS) state/goal machinery. Various activities can be coordinated, controlled, and reused through the Studio's component interface to establish and model a mission scenario. A special component Factory mechanism will be in place to facilitate the adaptation of projects into the Studio. The architecture of the Studio reflects and enforces a division of knowledge and actions into three parts: Model, Controller, Viewer. The Model contains information about (a proposed version of) the spacecraft and mission. The Controller contains logic for constructing scenarios of mission activities. The information in the Model and Controller is principally in the form of reusable patterns. A Viewer can be a simple or complex software system. For example, Apgen [2,3] is one possible viewer, MDS is another. A 3-tiered infrastructure is used for the Studio, reflecting the Model, Controller, Viewer architecture [4,5]. The Studio is useful in pre-phase A of a project by enabling spacecraft design options to be played against desired mission scenarios. In later design phases of a project, the construction and modeling of more detailed scenarios is supported by the Studio.

autonomous spacecraft↗
DOE OSTI2021

Resilient Information Architecture Platform for Smart Grid (RIAPS)

A number of emerging trends will substantially alter the operation and control of the electric grid over the next several decades. These trends include ensuring resiliency under severe weather events, increasing integration of renewable electricity generation, supporting changing electricity demand patterns, and the improving cost effectiveness of distributed energy resources. To address these challenges, the future “Smart Grid” management will need to transition from centralized to coordinated distributed control paradigm. Reliable operation of the Smart Grid depends on distributed intelligence realized through software applications that run on distributed computing devices attached to the power system to collect data and collaboratively manage resources. However, much of the existing software for Smart Grid-enabled devices is either proprietary or developed with custom solutions, which limits interoperability among the heterogeneous devices and hinders the ability to manage system-level reliability, security, and resiliency requirements. Additionally, this approach makes Smart Grid applications hard to maintain, evolve, verify, and replace; resulting in high development and deployment costs. Further development of the Smart Grid requires a reusable software base-layer to move from hard-coded functionality to a plug-and-play architecture capable of managing system-level objectives and constraints in addition to providing consistent common services across heterogeneous devices and applications. Vanderbilt University, in collaboration with North Carolina State University and Washington State University has developed a foundation ‘software platform’ for developing and deploying robust, reliable, effective and secure software applications for the Smart Grid. The Resilient Information Architecture Platform for the Smart Grid (RIAPS) provides core services for building effective and powerful smart grid applications. It offers unique services for real-time data dissemination, fault tolerance, and coordination across apps distributed over the network.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Explore Spatio‐Temporal Learning of Large Sample Hydrology Using Graph Neural Networks

Abstract Streamflow forecasting over gauged and ungauged basins play a vital role in water resources planning, especially under the changing climate. Increased availability of large sample hydrology data sets, together with recent advances in deep learning techniques, has presented new opportunities to explore temporal and spatial patterns in hydrological signatures for improving streamflow forecasting. The purpose of this study is to adapt and benchmark several state‐of‐the‐art graph neural network (GNN) architectures, including ChebNet, Graph Convolutional Network (GCN), and GraphWaveNet, for end‐to‐end graph learning. We explicitly represent river basins as nodes in a graph, learn the spatiotemporal nodal dependencies, and then use the learned relations to predict streamflow simultaneously across all nodes in the graph. The efficacy of the developed GNN models is investigated using the Catchment Attributes and MEteorology for Large‐sample Studies (CAMELS) data set under two settings, fixed graph topology (transductive learning), and variable graph topology (inductive learning), with the latter applicable to prediction in ungauged basins (PUB). Results indicate that GNNs are generally robust and computationally efficient, achieving similar or better performance than a baseline model trained using the long short‐term memory (LSTM) network. Further analyses are conducted to interpret the graph learning process at the edge and node levels and to investigate the effect of different model configurations. We conclude that graph learning constitutes a viable machine learning‐based method for aggregating spatiotemporal information from a multitude of sources for streamflow forecasting

Sun, Alexander Y.↗
DOE OSTI2025

DOE Repository Metadata Profile (DRMP): A Metadata Framework for Advancing Interoperability and AI Readiness Across Scientific Repositories

The Department of Energy (DOE) funds a diverse and distributed ecosystem of repositories that steward scientific data, publications, and software across its research programs, user facilities, and national laboratories. While significant progress has been made in standardizing dataset-level metadata, the metadata describing repositories themselves (their identity, governance, access interfaces, policies, and technical capabilities) remains inconsistent and fragmented across DOE-funded systems. This variability limits discoverability, interoperability, automated validation, and AI-driven analysis, all of which are increasingly essential for modern scientific workflows. To address this gap, the DOE Data Curation Working Group (DCWG) developed the DOE Repository Metadata Profile (DRMP). The DRMP is a practical, community-driven framework that defines how repositories can describe themselves in a consistent, machine-actionable, and scalable manner. The DRMP is not a new metadata schema. Instead, it is a mapping profile and structured element set capturing the essential characteristics of DOE repositories. It harmonizes repository-level metadata across six widely adopted community schemas: RE3Data; DCAT-US v3; Schema.org; Dublin Core; DataCite 4.6; and PREMIS 3.0. This harmonization eliminates reinvention and enables interoperability within DOE and across the broader scientific ecosystem. A core objective of the DRMP is to reduce burden on repositories by allowing them to reuse their existing metadata through a Rosetta-style crosswalk rather than redesigning local implementations. The profile introduces a three-level conformance model that supports incremental adoption: • Level 1 – Minimum Viable Record (MVR): foundational identification elements required for workflows, project registration, and basic repository presence. • Level 2 – Interoperable: structured metadata enabling alignment with national and international discovery systems. • Level 3 – AI-Ready: enhanced provenance, policy transparency, fixity, semantic context, and capabilities that support automated reasoning, model training governance, and machine-assisted curation. To support implementation, the DRMP includes JSON Schema definitions, OpenAPI patterns, and MCP templates that allow repositories to publish machine-readable metadata directly within existing platforms. These resources are modular and lightweight, enabling adoption without major architectural change. Adopting the DRMP enables repositories to: • Enhance discoverability and interoperability by aligning identifiers, classifications, and descriptive elements across widely used schema standards. • Support federated discovery and cross-registration across DOE systems, Data.gov, and international catalogs. • Enable AI agents and workflow orchestration systems to interpret repository-level metadata within the American Science Cloud (AmSC) through Model Context Protocol (MCP)-based context publication. • Demonstrate alignment with DOE’s open science, stewardship, and FAIR data priorities. This guidance represents a community-driven step forward. Through voluntary adoption and continued feedback, the DRMP advances a cohesive, machine-actionable description of DOE repositories that supports FAIR data practices, preparing the infrastructure for AI-enabled research, and strengthening the discoverability and reuse of DOE’s scientific outputs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRS1981

Optical processing for landmark identification

A study of optical pattern recognition techniques, available components and airborne optical systems for use in landmark identification was conducted. A data base of imagery exhibiting multisensor, seasonal, snow and fog cover, exposure, and other differences was assembled. These were successfully processed in a scaling optical correlator using weighted matched spatial filter synthesis. Distinctive data classes were defined and a description of the data (with considerable input information and content information) emerged from this study. It has considerable merit with regard to the preprocessing needed and the image difference categories advanced. A optical pattern recognition airborne applications was developed, assembled and demontrated. It employed a laser diode light source and holographic optical elements in a new lensless matched spatial filter architecture with greatly reduced size and weight, as well as component positioning toleranced.

Casasent, D.↗
NASA NTRS1987

Binary synaptic connections based on memory switching in a-Si:H for artificial neural networks

A scheme for nonvolatile associative electronic memory storage with high information storage density is proposed which is based on neural network models and which uses a matrix of two-terminal passive interconnections (synapses). It is noted that the massive parallelism in the architecture would require the ON state of a synaptic connection to be unusually weak (highly resistive). Memory switching using a-Si:H along with ballast resistors patterned from amorphous Ge-metal alloys is investigated for a binary programmable read only memory matrix. The fabrication of a 1600 synapse test array of uniform connection strengths and a-Si:H switching elements is discussed.

Thakoor, A. P.↗
NASA NTRS2016

Detectors and Focal Plane Modules for Weather Satellites

Weather satellite instruments require detectors with a variety of wavelengths ranging from the visible to VLWIR. One of the remote sensing applications is the geostationary GOES-ABI imager covering wavelengths from the 450 to 490 nm band through the 13.0 to 13.6 micron band. There are a total of 16 spectral bands covered. The Cross-track infrared Sounder (CrIS) is a Polar Orbiting interferometric sensor that measures earth radiances at high spectral resolution, using the data to provide pressure, temperature and moisture profiles of the atmosphere. The pressure, temperature and moisture sounding data are used in weather prediction models that track storms, predict levels of precipitation etc. The CrIS instrument contains SWIR (lamba(sub c) approximately 5 micron at 98K), MWIR (lambda(sub c) approximately 9 micron at 98K) and LWIRs (lamba(sub c) approximately 15.5 micron at 81K) bands in three Focal Plane Array Assemblies (FPAAs). GOES-ABI contains three focal plane modules (FPMs), (i) a visible-near infrared module consisting of three visible and three near infrared channels, (ii) a MWIR module comprised of five channels from 3.9 micron to 8.6 micron and (iii) a 9.6 micron to 13.3 micron, five-channel LWIR module. The VNIR FPM operates at 205 K, and the MWIR and LWIR FPMs operate at 60 K. Each spectral channel has a redundant array built into a single detector chip. Switching is thus permitted from the primary selected array in each channel to the redundant array, given any degradation in performance of the primary array during the course of the mission. Silicon p-i-n detectors are used for the 0.47 micron to 0.86 micron channels. The thirteen channels above 1 micron are fabricated in various compositions of Hg1-xCdxTe, and in this particular case using two different detector architectures. The 1.38 micron to 9.61 micron channels are all fabricated in Hg1-xCdxTe grown by Liquid Phase Epitaxy (LPE) using the HDVIP detector architecture. Molecular beam epitaxy (MBE)-grown Hg1-xCdxTe material are used for the LWIR 10.35 micron to 13.3 micron channels fabricated in Double layer planar heterostructure (DLPH) detectors. This is the same architecture used for the CrIS detectors CrIS detectors are 850 micron diameter detectors with each FPAA consisting of nine photovoltaic detectors arranged in a 3 x 3 pattern. Each detector has an accompanying cold preamplifier. SWIR and MWIR FPAAs operate at 98 K and the LWIR FPAA at 81 K, permitting the use of passive radiators to cool the detectors. D* requirements at peak wavelength are ≥ 5.0E+10 Jones for LWIR, ≥ 9.3E+10 Jones for MWIR and ≥ 3.0E+11 Jones for SWIR. All FPAAs exceeded the D* requirements. Measured mean values for the nine photodiodes in each of the LWIR, MWIR and SWIR FPAAs are D* = 5.3 x 10(exp 10) cm-Hz(exp 1/2)/W at 14.0 micron, 1.0 x 10(exp 11) cm-Hz(exp 1/2)/W at 8.0 micron and 3.1 x 10(exp 11) cm-Hz(exp 1/2)/W at 4.64 micron.

satellite instruments↗
NASA NTRS2024

Assessing Mechanical Properties of Spacecraft Materials under Simulated Low Earth Orbit Atomic Oxygen Conditions

During a space mission, spacecraft surface materials are exposed to various damaging environmental factors including high-energy photons, electrons, atomic oxygen (AO) neutrals and ions, micrometeoroids and orbital debris, vacuum, and large temperature fluctuations. The resulting change in spacecraft material properties can significantly impact the performance and durability of spacecraft systems. Even though all aspects of the space environment can lead to the deterioration of spacecraft components, in low Earth orbit (LEO), the threat posed by AO is especially severe in terms of structural and optical damage, particularly to exterior spacecraft components that are susceptible to oxidation. A comprehensive understanding of material AO-induced weathering is essential for mission planning in the LEO environment. The presented work aims to evaluate the alterations in mechanical properties of selected innovative spacecraft materials and surface electronic system designs, such as Kapton® CR film coated front and back-side with polyimide coating containing AO-resistant filler, Kevlar EXO, and Bendable Electrodynamic Dust Shield (BEDS) architecture, under simulated AO exposure, utilizing the photoelasticity phenomenon in which birefringence is induced in a material when it is subjected to mechanical stress. Changes in stress patterns during the deformation of AO-exposed polymers were assessed using a large-field polariscope under varied deformation types. Patterns of colors were used for qualitative evaluations of residual stress. The stress patterns of the AO-exposed polymers were compared to those of the unexposed ones. Also, these patterns were correlated with data from Bidirectional Reflectance Distribution Function (BRDF) and surface morphology studies.

Yuliya Kuznetsova↗
DOE OSTI2020

Evaluation of Graph Analytics Frameworks Using the GAP Benchmark Suite

The analysis of connected data is an increasingly important application in high-performance computing. Such analyses can reveal fraudulent patterns in financial transactions, optimize telecommunications networks, predict information flow in social networks, etc. However, the landscape of graph analytics is highly diverse. Graph algorithms stress processor architectures differently, and no one graph can represent all topologies. Consequently, no single approach or framework is expected to be optimal for all graph analytics problems. To help make sense of this diverse landscape, we evaluated four approaches to graph analytics: GraphBLAS, Galois, BGL17, GraphIt; and compare them against hand-tuned implementations that take advantage of hardware features on our test platform. Graph- BLAS formulates graph analytics as sparse linear algebra. Galois provides syntactic constructs for data parallelism over irregular data structures. BGL17 is a generic C++ template library for implementing graph algorithms. GraphIt provides a domain- specific language to describe and optimize graph algorithms. We use the GAP Benchmark Suite to establish baseline performance and guide the side-by-side evaluation of each framework. GAP consists of 30 tests: six graph analytics algorithms (breadth- first search, single-source shortest path, PageRank, betweenness centrality, connected components, and triangle counting) run on five graphs, each with different topological characteristics (e.g., high diameter, skewed degree distribution, high average degree). High-performance reference implementations are included for each benchmark algorithm. Because a graph can be loaded into memory a number of ways (e.g., flat file on disk, compressed sparse format, data frames, retrieved from SQL or NoSQL databases), our evaluation focused on computational performance rather than I/O. Our results show the relative strengths of each framework.

Graph algorithms, Benchmarking, shared-memory prog↗
DOE OSTI2022

DUNE Software and High Performance Computing

DUNE, like other HEP experiments, faces a challenge related to matching execution patterns of our production simulation and data processing software to the limitations imposed by modern high-performance computing facilities. In order to efficiently exploit these new architectures, particularly those with high CPU core counts and GPU accelerators, our existing software execution models require adaptation. In addition, the large size of individual units of raw data from the far detector modules pose an additional challenge somewhat unique to DUNE. Here we describe some of these problems and how we begin to solve them today with existing software frameworks and toolkits. We also describe ways we may leverage these existing software architectures to attack remaining problems going forward. This whitepaper is a contribution to the Computational Frontier of Snowmass21.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗