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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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NASA NTRS2002

The Aeronautical Data Link: Taxonomy, Architectural Analysis, and Optimization

The future Communication, Navigation, and Surveillance/Air Traffic Management (CNS/ATM) System will rely on global satellite navigation, and ground-based and satellite based communications via Multi-Protocol Networks (e.g. combined Aeronautical Telecommunications Network (ATN)/Internet Protocol (IP)) to bring about needed improvements in efficiency and safety of operations to meet increasing levels of air traffic. This paper will discuss the development of an approach that completely describes optimal data link architecture configuration and behavior to meet the multiple conflicting objectives of concurrent and different operations functions. The practical application of the approach enables the design and assessment of configurations relative to airspace operations phases. The approach includes a formal taxonomic classification, an architectural analysis methodology, and optimization techniques. The formal taxonomic classification provides a multidimensional correlation of data link performance with data link service, information protocol, spectrum, and technology mode; and to flight operations phase and environment. The architectural analysis methodology assesses the impact of a specific architecture configuration and behavior on the local ATM system performance. Deterministic and stochastic optimization techniques maximize architectural design effectiveness while addressing operational, technology, and policy constraints.

Morris, A. Terry↗

NASA NTRS1993

WNN 92; Proceedings of the 3rd Workshop on Neural Networks: Academic/Industrial/NASA/Defense, Auburn Univ., AL, Feb. 10-12, 1992 and South Shore Harbour, TX, Nov. 4-6, 1992

The present conference discusses such neural networks (NN) related topics as their current development status, NN architectures, NN learning rules, NN optimization methods, NN temporal models, NN control methods, NN pattern recognition systems and applications, biological and biomedical applications of NNs, VLSI design techniques for NNs, NN systems simulation, fuzzy logic, and genetic algorithms. Attention is given to missileborne integrated NNs, adaptive-mixture NNs, implementable learning rules, an NN simulator for travelling salesman problem solutions, similarity-based forecasting, NN control of hypersonic aircraft takeoff, NN control of the Space Shuttle Arm, an adaptive NN robot manipulator controller, a synthetic approach to digital filtering, NNs for speech analysis, adaptive spline networks, an anticipatory fuzzy logic controller, and encoding operations for fuzzy associative memories.

Padgett, Mary L.↗

NASA NTRS2010

Multi-Stage System for Automatic Target Recognition

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an artificial neural network classifier. The multi-stage system allows tuning the detection sensitivity and the identification specificity individually in each stage. It is easier to achieve optimized ATR operation based on its specific goal. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar and video image datasets.

Chao, Tien-Hsin↗

NASA NTRS1987

Optimal service allocation among two heterogeneous traffic types with no queueing

Two communication traffic streams with Poisson statistics arrive at a network node. These are to be transmitted across a channel with a total bandwidth capacity of C slots. Messages not accepted at the node are assumed to be lost. Under the assumptions of exponential service time distributions, the problem of dynamic allocation of available channel bandwidth among the two traffic types is studied in order to minimize a weighted sum of blocking probabilities. Modeling the system as a two-dimensional Markov chain is studied to minimize a weighted sum of blocking probabilities. Modeling the system as a two-dimensional Markov chain, it is shown by an application of dynamic programming principles that the optimal policy has the form of a 'switching curve'.

Lambadaris, I.↗

NASA NTRS2003

Collectives for Multiple Resource Job Scheduling Across Heterogeneous Servers

Efficient management of large-scale, distributed data storage and processing systems is a major challenge for many computational applications. Many of these systems are characterized by multi-resource tasks processed across a heterogeneous network. Conventional approaches, such as load balancing, work well for centralized, single resource problems, but breakdown in the more general case. In addition, most approaches are often based on heuristics which do not directly attempt to optimize the world utility. In this paper, we propose an agent based control system using the theory of collectives. We configure the servers of our network with agents who make local job scheduling decisions. These decisions are based on local goals which are constructed to be aligned with the objective of optimizing the overall efficiency of the system. We demonstrate that multi-agent systems in which all the agents attempt to optimize the same global utility function (team game) only marginally outperform conventional load balancing. On the other hand, agents configured using collectives outperform both team games and load balancing (by up to four times for the latter), despite their distributed nature and their limited access to information.

Tumer, K.↗

NASA NTRS1984

Modification of epoxy-reinforced glass-cloth composites with a perfluorinated alkyl ether elastomer

A perfluorinated alkyl ether diacyl fluoride prepolymer (molecular weight about 1500) was coreacted with Epon 828 epoxy resin and diamino diphenyl sulfone to obtain an elastomer-toughened, glass-cloth composite. Improvements in flexural toughness, impact resistance, and water resistance, without loss of strength, modulus of elasticity or a lowering of the glass-transition temperature, were realized over those of the unmodified composite. Factors concerning optimization of the process are discussed. Results suggest that a simultaneously interpenetrating polymer network may be formed which gives rise to a measured improvement in composite mechanical properties.

Rosser, R. W.↗

NASA NTRS1988

Applications of concurrent neuromorphic algorithms for autonomous robots

This article provides an overview of studies at the Oak Ridge National Laboratory (ORNL) of neural networks running on parallel machines applied to the problems of autonomous robotics. The first section provides the motivation for our work in autonomous robotics and introduces the computational hardware in use. Section 2 presents two theorems concerning the storage capacity and stability of neural networks. Section 3 presents a novel load-balancing algorithm implemented with a neural network. Section 4 introduces the robotics test bed now in place. Section 5 concerns navigation issues in the test-bed system. Finally, Section 6 presents a frequency-coded network model and shows how Darwinian techniques are applied to issues of parameter optimization and on-line design.

Barhen, J.↗

NASA NTRS1990

Electronic Neural Networks

Viewgraphs on electronic neural networks for space station are presented. Topics covered include: electronic neural networks; electronic implementations; VLSI/thin film hybrid hardware for neurocomputing; computations with analog parallel processing; features of neuroprocessors; applications of neuroprocessors; neural network hardware for terrain trafficability determination; a dedicated processor for path planning; neural network system interface; neural network for robotic control; error backpropagation algorithm for learning; resource allocation matrix; global optimization neuroprocessor; and electrically programmable read only thin-film synaptic array.

Thakoor, Anil↗

NASA NTRS2007

F-15 837 IFCS Intelligent Flight Control System Project

This viewgraph presentation reviews the use of Intelligent Flight Control System (IFCS) for the F-15. The goals of the project are: (1) Demonstrate Revolutionary Control Approaches that can Efficiently Optimize Aircraft Performance in both Normal and Failure Conditions (2) Advance Neural Network-Based Flight Control Technology for New Aerospace Systems Designs. The motivation for the development are to reduce the chance and skill required for survival.

Bosworth, John T.↗

NASA NTRS2009

An Algorithm for Obtaining the Distribution of 1-Meter Lightning Channel Segment Altitudes for Application in Lightning NOx Production Estimation

An algorithm has been developed to estimate the altitude distribution of one-meter lightning channel segments. The algorithm is required as part of a broader objective that involves improving the lightning NOx emission inventories of both regional air quality and global chemistry/climate models. The algorithm was tested and applied to VHF signals detected by the North Alabama Lightning Mapping Array (NALMA). The accuracy of the algorithm was characterized by comparing algorithm output to the plots of individual discharges whose lengths were computed by hand; VHF source amplitude thresholding and smoothing were applied to optimize results. Several thousands of lightning flashes within 120 km of the NALMA network centroid were gathered from all four seasons, and were analyzed by the algorithm. The mean, standard deviation, and median statistics were obtained for all the flashes, the ground flashes, and the cloud flashes. One-meter channel segment altitude distributions were also obtained for the different seasons.

Peterson, Harold↗

NASA NTRS2023

Distributed Spacecraft Mission (DSM) Plume Design Reference Mission (DRM) Inter-Satellite Link Modeling, Analysis and Simulation

NASA Goddard Space Flight Center (GSFC) Radical Innovation Initiative (RI2) plans to focus intently on DSM capability advancements in FY22-24. A DSM mission involves multiple spacecraft, arranged in a constellation, to achieve one or more common goals via the use of inter-satellite links (ISL) between the satellites. Recently, the GSFC Internal Research & Development (IRAD) program established Enceladus as a design reference mission (DRM) for the current DSM effort to foster the conceptual development of communication architecture, requirements, and solutions for future DSM ISL, as well as being able to push other research areas of interest. Enceladus is an icy moon of the planet Saturn. The DRM Enceladus mission concept involves a constellation of 24 small satellites, orbiting Enceladus around 100 km altitude in 3 planes, as observing nodes for science measurement. The mission science data will be sent back to Earth through a relay orbiting Saturn, using the constellation’s inter-satellite links. A QualNet/STK simulation model of the Relay and constellation ISL optical and RF links is developed for the design and optimization of the link and orbital parameters, as well as the inter-networking protocols. Delay Tolerant Networking (DTN) is utilized in the application layer modeling. This paper describes the plume DRM mission concept of an Enceladus constellation to relay science data to Earth and includes the proposed communication architecture and operation concepts. We present details of the QualNet/STK engineering model for this communication scenario to simulate the end-to-end data traffic through multiple layers (physical, data link, networking, transport and application). A link analysis for the constellation’s ISL, constellation to Relay and Direct to Earth (DTE) optical link is provided and discussed. The results of end-to-end traffic simulation for the data throughout/latency evaluation and assessment of the communication architecture are presented. The investigation of the concept of optical multiple access (OMA) for the Plume DRM is discussed. The modeling and simulation methodology developed in this paper is applicable to other DSMs in near Earth and deep space such as Earth-Moon L1/L2 and Lunar regions.

Distributed Spacecraft Mission (DSM) Inter-satelli↗

NASA NTRS1993

Analysis of multigrid methods on massively parallel computers: Architectural implications

We study the potential performance of multigrid algorithms running on massively parallel computers with the intent of discovering whether presently envisioned machines will provide an efficient platform for such algorithms. We consider the domain parallel version of the standard V cycle algorithm on model problems, discretized using finite difference techniques in two and three dimensions on block structured grids of size 10(exp 6) and 10(exp 9), respectively. Our models of parallel computation were developed to reflect the computing characteristics of the current generation of massively parallel multicomputers. These models are based on an interconnection network of 256 to 16,384 message passing, 'workstation size' processors executing in an SPMD mode. The first model accomplishes interprocessor communications through a multistage permutation network. The communication cost is a logarithmic function which is similar to the costs in a variety of different topologies. The second model allows single stage communication costs only. Both models were designed with information provided by machine developers and utilize implementation derived parameters. With the medium grain parallelism of the current generation and the high fixed cost of an interprocessor communication, our analysis suggests an efficient implementation requires the machine to support the efficient transmission of long messages, (up to 1000 words) or the high initiation cost of a communication must be significantly reduced through an alternative optimization technique. Furthermore, with variable length message capability, our analysis suggests the low diameter multistage networks provide little or no advantage over a simple single stage communications network.

Matheson, Lesley R.↗

NASA NTRS1996

Distributed Large Data-Object Environments: End-to-End Performance Analysis of High Speed Distributed Storage Systems in Wide Area ATM Networks

We have developed and deployed a distributed-parallel storage system (DPSS) in several high speed asynchronous transfer mode (ATM) wide area networks (WAN) testbeds to support several different types of data-intensive applications. Architecturally, the DPSS is a network striped disk array, but is fairly unique in that its implementation allows applications complete freedom to determine optimal data layout, replication and/or coding redundancy strategy, security policy, and dynamic reconfiguration. In conjunction with the DPSS, we have developed a 'top-to-bottom, end-to-end' performance monitoring and analysis methodology that has allowed us to characterize all aspects of the DPSS operating in high speed ATM networks. In particular, we have run a variety of performance monitoring experiments involving the DPSS in the MAGIC testbed, which is a large scale, high speed, ATM network and we describe our experience using the monitoring methodology to identify and correct problems that limit the performance of high speed distributed applications. Finally, the DPSS is part of an overall architecture for using high speed, WAN's for enabling the routine, location independent use of large data-objects. Since this is part of the motivation for a distributed storage system, we describe this architecture.

Johnston, William↗

NASA NTRSDate not supplied

NASA's Efforts to Commercialize Communications Services for Mission in Near-Earth Space

The National Aeronautics and Space Administration (NASA) Space Communications and Navigation (SCaN)Program enables high speed, robust, secure and cost-effective space communications and navigation services to current and future science and exploration missions. Consistent with National Space Policy, NASA is pursuing the use of demonstrated commercial services for all its future near-Earth requirements through a flexible, multi-provider approach that minimizes risks to the user missions and ensures costs to user missions are reasonable. Progress toward this goal is advancing in multiple key areas including direct to Earth (DTE), space-based relay, technology investments, required spectrum regulatory changes and mission engagement and infusion. The transition to commercial DTE services is already underway, with a target for transition by 2024. The primary functions to execute SCaN’s DTE strategy include increasing commercial service allocations by leveraging current commercial network providers and enabling seamless onboarding of additional providers into the network. Furthermore, moving away from government DTE services will allow operational costs to be optimized. A more gradual approach is planned for the transition to commercial space-based relay services to allow for demonstration and operationalization of commercial services for future users by 2030. In June of 2022, six American SATCOM vendors were awarded a combined $278.5 million through Funded Space Act Agreements (FSAAs) for the first cycle of demonstration and validation activities. The end-to-end service capabilities being targeted are based on existing NASA mission operational needs. Accordingly, each company has proposed a technical approach to lower costs, increase flexibility, and improve performance for a broad range of missions. Successful user mission transition to commercial services, both DTE and space-based relay, are dependent on the technologies and capabilities that address gaps in commercial capability. NASA is investing in technology development and pursuing a new strategic approach to the creation or adoption of space communications standards to move the agency toward a commercial paradigm. Wideband and multi-lingual user terminals are being developed to bridge differences in industry services. Building on ground demonstrations completed in 2021, the Johns Hopkins Applied Physics Lab (APL) will be flight testing a multi-lingual wideband terminal (payload) and demonstrating connectivity to both government and commercial relay services. NASA holds a leadership role in multiple civil space standards bodies and international coordination groups to ensure that standards supporting interoperability are developed with defined functions, interfaces, and performance. However, to successfully meet commercialization objectives, NASA seeks to collaborate with industry, and as applicable adopt or adapt to commercially defined standards. As such, NASA joined the 3rd Generation Partnership Project (3GPP) as an official member in 2021 to advocate for the inclusion of space missions as a unique user segment in future 5G non-terrestrial networks, and to better understand the scope of 3GPP releases and implications for space users. Further, engagement in Spectrum regulatory bodies is being undertaken to augment existing space-Earth and inter-satellite frequency allocations available for both government and commercial space systems. This paper addresses the recent progress toward NASA’s commercial space communications transition objectives and how key challenges are being navigated.

Gregory W Heckler↗

NASA NTRS1991

Toughening of PMR composites by semi-interpenetrating networks

Polymerization of monomer reactants (PMR-15) type polyimide and RP46 prepregs were drum wound using IM-7 fibers. Prepregging and processing conditions were optimized to yield good quality laminates with fiber volume fractions of 60 percent (+/- 2 percent). Samples were fabricated and tested to determine comprehensive engineering properties of both systems. These included 0 deg flexure, short beam shear, transverse flexure and tension, 0 deg tension and compression, intralaminar shear, short block compression, mode 1 and 2 fracture toughness, and compression after impact properties. Semi-2-IPN (interpenetrating polymer networks) toughened PMR-15 and RP46 laminates were also fabricated and tested for the same properties.

Tiwari, S. N.↗

NASA NTRSDate not supplied

A NASA Perspective on Quantum Computing: Algorithmic Opportunities and Challenges

In the last couple of decades, the world has seen several stunning instances of quantum algorithms that provably outperform the best classical algorithms. For most problems, however, it is currently unknown whether quantum algorithms can provide an advantage, and if so how to design quantum algorithms that realize such advantages. Today, classical heuristics are used to solve many of the most challenging computational problems arising in the practical world, algorithms that have been shown to be effective empirically but have not been mathematically proven to outperform other approaches. With the advent of quantum advantage, the ability of current quantum hardware to do certain computations beyond the ability of even that largest supercomputers, we have an unprecedented opportunity to explore heuristic quantum algorithms. The next few years will be exciting as empirical testing of quantum heuristic algorithms becomes more and more feasible. The talk will begin overview of the NASA QuAIL team’s ongoing quantum computing investigations, and then focus on both near-term and longer term algorithms for optimization, including distributed algorithms.

quantum computing↗

NASA NTRSDate not supplied

Joint Spectrum Access and Power Control in Air-Air Communications - A Deep Reinforcement Learning Based Approach

This paper considers the dynamic spectrum access and power control problem in a single-hop point-to-point Air-Air Communication Network (AACN). Due to spectrum scarcity, we assume the number of Aircraft-to-Aircraft (A2A) communication links is greater than that of the available channels, such that some communication links need to share the same channel, causing co-channel interference. We formulate the joint channel selection and power control optimization problem to maximize the Weighted Sum Spectral Efficiency (WSSE). A distributed and dynamic deep Q learning-based algorithm is proposed to find the optimal solution. Specifically, we design two different policies that are trained by conducting a trial-and-error scheme. Each communication link can achieve the optimal policy by exploiting the local information from its neighbors, and this distributive approach make it scalable to large networks. Finally, our experimental results demonstrate the effectiveness of the proposed solution in various AACN scenarios.

Zhe Wang↗

NASA NTRSDate not supplied

Joint Spectrum Access and Power Control in Air-Air Communications - A Deep Reinforcement Learning Based Approach

Zhe Wang↗