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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Data communication network at the ASRM facility

This three-year project (February 1991 to February 1994) has involved analyzing and helping to design the communication network for the Advanced Solid Rocket Motor (ASRM) facility at Yellow Creek, near Iuka, MS. The principal concerns in the analysis were the bandwidth (both on average and in the worst case) and the expandability of the network. As the communication network was designed and modified, a careful evaluation of the bandwidth of the network, the capabilities of the protocol, and the requirements of the controllers and computers on the network was required. The overall network, which was heterogeneous in protocol and bandwidth, needed to be modeled, analyzed, and simulated to obtain some degree of confidence in its performance capabilities and in its performance under nominal and heavy loads. The results of our analysis did have an impact on the design and operation of the ASRM facility. During 1993 we analyzed many configurations of this basic network structure. The analyses are described in detail in Section 2 and 3 herein. Section 2 reports on an analysis of the whole network. The preliminary results of that research indicated that the most likely bottleneck as the network traffic increased would be the hubs. Thus a study of Cabletron hubs was initiated. The results of that study are in Section 3. Section 4 herein reports on the final network configuration analyzed. When the ASRM facility was mothballed in December of 1993, this was basically the planned and partially installed network. A briefing was held at NASA/MSFC on December 7, 1993, at which time our final analysis and conclusions were disseminated. This report contains a written record of most of the information disseminated at that briefing.

Moorhead, Robert J., III↗
NASA NTRS2004

Real-Time Adaptive Color Segmentation by Neural Networks

Artificial neural networks that would utilize the cascade error projection (CEP) algorithm have been proposed as means of autonomous, real-time, adaptive color segmentation of images that change with time. In the original intended application, such a neural network would be used to analyze digitized color video images of terrain on a remote planet as viewed from an uninhabited spacecraft approaching the planet. During descent toward the surface of the planet, information on the segmentation of the images into differently colored areas would be updated adaptively in real time to capture changes in contrast, brightness, and resolution, all in an effort to identify a safe and scientifically productive landing site and provide control feedback to steer the spacecraft toward that site. Potential terrestrial applications include monitoring images of crops to detect insect invasions and monitoring of buildings and other facilities to detect intruders. The CEP algorithm is reliable and is well suited to implementation in very-large-scale integrated (VLSI) circuitry. It was chosen over other neural-network learning algorithms because it is better suited to realtime learning: It provides a self-evolving neural-network structure, requires fewer iterations to converge and is more tolerant to low resolution (that is, fewer bits) in the quantization of neural-network synaptic weights. Consequently, a CEP neural network learns relatively quickly, and the circuitry needed to implement it is relatively simple. Like other neural networks, a CEP neural network includes an input layer, hidden units, and output units (see figure). As in other neural networks, a CEP network is presented with a succession of input training patterns, giving rise to a set of outputs that are compared with the desired outputs. Also as in other neural networks, the synaptic weights are updated iteratively in an effort to bring the outputs closer to target values. A distinctive feature of the CEP neural network and algorithm is that each update of synaptic weights takes place in conjunction with the addition of another hidden unit, which then remains in place as still other hidden units are added on subsequent iterations. For a given training pattern, the synaptic weight between (1) the inputs and the previously added hidden units and (2) the newly added hidden unit is updated by an amount proportional to the partial derivative of a quadratic error function with respect to the synaptic weight. The synaptic weight between the newly added hidden unit and each output unit is given by a more complex function that involves the errors between the outputs and their target values, the transfer functions (hyperbolic tangents) of the neural units, and the derivatives of the transfer functions.

Duong, Tuan A.↗
DOE OSTI2023

Deconvoluting Structures of Component Plant Biopolymers Using Deuterium Labeled Brassica oleracea Stems

Several Brassica species are cultivated globally for the production of seed oils as food, lubricants, and increasingly biofuels. The stem and leaf residues of these herbaceous dicotyledonous crops constitute another feedstock for biofuels and other products. Plant cell walls are complex, multipolymeric structures that consist primarily of polysaccharides and lignin. Cellulose chains coalesce to form crystalline microfibrils while the amorphous biopolymers, hemicellulose, and lignin form a network structure and fill the interstitial space. Neutron scattering has been used for the structural study of the assembly and deconstruction of the plant cell walls. However, similar neutron sensitivity of the different amorphous biopolymers has made structural association to individual component biopolymers nontrivial and ambiguous. To improve the association of structural features to specific biopolymer components, partial deuteration of the plant cell wall can be employed to increase the difference in the neutron scattering length density between amorphous carbohydrate and lignin plant polymers. Vegetative stems from partially deuterated Brassica oleracea acephala (kale) plants were obtained commercially, and the plant cell wall structures were studied by contrast-variation small-angle neutron scattering (CV-SANS) and Fourier-transform infrared spectroscopy (FTIR). FTIR results indicated that deuterium substitution for hydrogen in the carbohydrates was higher than that in lignin. By combining CV-SANS and FTIR results, the neutron scattering length density (nSLD) of the polysaccharides and lignin was determined to match nSLD of 65%:35% and 48%:52% D 2 O/H 2 O solvent mixtures, respectively. These nSLD values were higher than the nSLD values of polysaccharides and lignin for H 2 O grown biopolymers. The nSLD increase correlates to replacing about 42.5% of hydrogens present as both C–H and O–H groups in cellulose with deuterium atoms, while only 21% for lignin. In conclusion, this study lays the foundation to use partially deuterated plants to deconvolute structural features of the different component biopolymers, especially cellulose, hemicellulose, and lignin, of the plant cell wall without introducing unintended structural modifications due to the pretreatment extraction processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Inelastic relaxation processes in amorphous sodium silicates

During fracture amorphous oxides exhibit irreversible processes, including inelastic and nonrecoverable relaxation effects in the process zone surrounding the crack tip. Here, classical molecular dynamics simulations were used with a reactive forcefield to evaluate inelastic relaxation processes in five amorphous sodium silicate compositions. Overall, the 20% Na 2 O-SiO 2 (NS20) composition exhibited the most inelastic relaxation, followed by the 15% Na 2 O-SiO 2 (NS15) composition, the 25% Na 2 O-SiO 2 (NS25) composition, and finally the 10% (NS10) and 30% (NS30) Na 2 O-SiO 2 compositions. Coordination analysis of the Na + ions identified that during inelastic relaxation the Na+ ions were increasingly coordinated by nonbridging oxygens (NBOs) for the NS10 and NS15 compositions, which was supported by radial analysis of the O-Na-O bond angles surrounding the crack tip. Across the sodium silicate compositional range, two different inelastic relaxation mechanism were identified based on the amount of bridging oxygens (BOs) and NBOs in the Na+ ion coordination shell. At lower (NS10) and higher (NS30) sodium compositions, the entire structured relaxed toward the crack tip. In contrast at intermediate sodium concentrations (NS20) the Na + ion migrates toward the crack tip separately from the network structure. By developing a fundamental understanding of how modified silica systems respond to static stress fields, we will be able to predict how varying amorphous silicate systems exhibit slow crack growth.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Anomalously strong viscosity behavior in mixed oxy-sulfide Na 4 P 2 S 7-x O x invert glasses

In this paper, the first observations have been made of anomalously strong viscosity behavior and correspondingly strong bulk glass formation and resistance to crystallization in a melt quenched (MQ) prepared series of invert, modifier content greater than the glass former content, mixed oxy-sulfide Na 4 P 2 S 7-x O x , 0 ≤ x ≤ 5, (NaPSO) glasses. We find that these glasses even with 67 mole % modifier, Na 2 S, and only 33 mole% glass former P 2 S 5-x O x , exhibit a calorimetric fragility index, m cal , as small as 29 compared to typical values of ~ 60 to 80 for alkali silicate glasses with > 50 mole% SiO 2 and the theoretical minimum m cal of ~ 15. The m cal values were converted to kinetic viscosity fragility, m vis , values and used with the measured glass transition temperatures, T g s, to produce viscosity curves for the glasses using the Mauro-Yue-Ellison-Gupta-Allan (MYEGA) model. The viscosity of the glass with a minimum m cal value of x = 2.5 was then shown to exhibit a viscosity that was as strong as, and for some compositions stronger than, the viscosity of alkali aluminosilicate glasses which have three dimensional network structures compared to the one dimensional chain structures observed in these MOS invert glasses. Consistent with these small values of fragility indices and therefore predicted higher viscosity above the glass transition temperature, T g , in the supercooled liquid regime, these glasses are also particularly resistant to crystallization. For example, the x = 2.5 glass composition exhibits a crystallization temperature, T C , more than 150K above its T g . We find that the calorimetric fragility of these glasses varies systematically with the extent of network forming bridging oxygens (BOs) in the glasses. The structural change caused by incrementally replacing sulfur with oxygen has been found to have consistent, large effects on the thermal properties.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Learning Based Edge Computing in Air-to-Air Communication Network

This paper studies learning-based edge computing and communication in a dynamic Air-to-Air Ad-hoc Network (AAAN). Due to spectrum scarcity, we assume the number of Air-to-Air (A2A) communication links is greater than that of the available frequency channels, such that some communication links have to share the same channel, causing co-channel interference. We formulate the joint channel selection and power control optimization problem to maximize the aggregate spectrum utilization efficiency under resource and fairness constraints. A distributed deep Q learning-based edge computing and communication algorithm is proposed to find the optimal solution. In particular, we design two different neural network structures and each communication link can converge to the optimal operation by exploiting only the local information from its neighbors, making it scalable to large networks. Finally, experimental results demonstrate the effectiveness of the proposed solution in various AAAN scenarios.

Zhe Wang↗
DOE OSTI2023

Hemp fiber reinforced dual dynamic network vitrimer biocomposites with direct incorporation of amino silane

Natural fiber composites are inexpensive and renewable alternatives to traditional fiber reinforced polymers (FRPs). However, existing natural fiber composites primarily rely on petrochemical based thermosetting matrices, which are difficult to recycle due to their stable crosslinked network structures. To address this challenge, it is desirable to develop natural fiber composites with inherently recyclable biobased matrices. In this study, we developed a dual dynamic network vitrimer matrix from hempseed oil and limonene derivatives and demonstrated its application in hemp fiber reinforced composites. To improve the weak interface between hemp fiber and the polymer matrix, a common challenge in the realm of natural fiber composites, we directly incorporated amino silane into the vitrimer matrix. The amino silane participated in the polymer network, increasing the crosslink density and toughening the matrix, as evidenced by a significantly improved impact strength from 3.5 kJ/m 2 to 10.3 kJ/m 2 . Moreover, the incorporation of amino silane resulted in a lower water absorption by 11% in 7-day soaking for the composites, demonstrating improved fiber/matrix interfacial interaction. Furthermore, our biobased vitrimer matrix exhibits both imine and hydroxy-ester dynamic bonds, which enable the recycling of the biocomposite through a mild and cost-effective aminolysis process (100°C, 3h, ambient pressure). The decomposed polymer matrix was successfully reused as a polyol for polyurethane adhesives, and the surface morphology of recovered hemp fibers was analyzed and compared with that of the original fibers. Furthermore, these findings will help broaden the use of vitrimers for practical natural fiber composite applications, raise awareness of the problem of recycling natural fiber composite waste, and shed light on the interfacial challenge of natural fiber reinforced vitrimer composites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1990

A Mobile Satellite Experiment (MSAT-X) network definition

The network architecture development of the Mobile Satellite Experiment (MSAT-X) project for the past few years is described. The results and findings of the network research activities carried out under the MSAT-X project are summarized. A framework is presented upon which the Mobile Satellite Systems (MSSs) operator can design a commercial network. A sample network configuration and its capability are also included under the projected scenario. The Communication Interconnection aspect of the MSAT-X network is discussed. In the MSAT-X network structure two basic protocols are presented: the channel access protocol, and the link connection protocol. The error-control techniques used in the MSAT-X project and the packet structure are also discussed. A description of two testbeds developed for experimentally simulating the channel access protocol and link control protocol, respectively, is presented. A sample network configuration and some future network activities of the MSAT-X project are also presented.

Wang, Charles C.↗
NASA NTRSDate not supplied

SPIKE-Dx : A Low-Power High-Throughput Fault Diagnostics Tool using Spiking Neural Networks for Constrained Systems

Diagnostic systems are important for many aerospace systems, which are severely limited in available power, like cubesats or UAVs. Therefore, traditional diagnostics systems cannot be used due to their substantial footprint and constraints. In this paper, we present our very low power diagnostic tool SPIKE-DX to monitor critical systems with constrained computational and energy resources. This is made possible through spiking neural networks (SNNs), which are executable within optimized simulation environments and further implemented on on cutting-edge neuromorphic hardware. Based upon FMEA (Failure Mode and Effect Analysis) framework, Diagnostic Bayesian Networks (DBNs) can be constructed that provide powerful means for diagnostic reasoning. In this paper, we describe such DBNs and a method to automatically translate the DBN into highly structured networks of spiking neurons for execution in SPIKE-DX.

Spiking Neural Networks↗
NASA NTRS2000

The Evolution of Networks in Extreme and Isolated Environment

This article reports on the evolution of network structure as it relates to the formal and informal aspects of social roles in well bounded, isolated groups. Research was conducted at the Amundsen-Scott South Pole Station over a 3-year period. Data was collected on crewmembers' networks of social interaction and personal advice over each of the 8.5-month winters during a time of complete isolation. In addition, data was collected on informal social role structure (e.g., instrumental leadership, expressive leadership). It was hypothesized that development and maintenance of a cohesive group structure was related to the presence of and group consensus on various informal social roles. The study found that core-periphery structures (i.e., reflecting cohesion) in winter-over groups were associated with the presence of critically important informal social roles (e.g., expressive leadership) and high group consensus on such informal roles. On the other hand, the evolution of clique structures (i.e., lack of cohesion) were associated with the absence of critical roles and a lack of consensus on these roles, particularly the critically important role of instrumental leader.

Johnson, Jeffrey C.↗
DOE OSTI2025

B‐Staging and Crosslinking of Polycarbosilane at Room Temperature: Cure Mechanism and Properties

The viscosity of polycarbosilane (PCS) polymers is not advantageous for free forming. Various fillers and heat are used to obtain a formable paste. Due to the low yield stress, structures and preforms tend to slump or resin will flow out, especially during the curing of the polymer. B-staging of PCS allows for a more stable structure from room temperature until the full cure of the allyl groups occurs with heat. Additionally, hydrosilation is an effective means of crosslinking at room temperature and controlling viscosity. A network structure was formed in SMP-10 using silane and a vinyl-based crosslinker to bridge each polymer chain. Pt addition catalysts were added to enhance the increase in viscosity to make a lightly crosslinked gel to aid in thickening and forming and to improve the ceramic yield at 1000°C. In conclusion, this enables several options for controlling rheology and improving the properties of preceramic polymers to avoid slumping during curing.

inorganic polymers↗
DOE OSTI2026

Tuning the Mechanical Properties of Crosslinked Copolymers via Sequence and Solvent‐Selective Swelling for Vat Photopolymerization

Block copolymers (BCPs) offer distinct advantages for vat photopolymerization by enabling mechanically programmable network structures through microphase-separated morphologies that can be kinetically trapped during curing, yielding properties unattainable in homogeneous resins. However, the respective roles of repeat-unit sequence and solvent environment, together with their interplay in directing network formation and mechanical performance, remain unclear. Here, we synthesize a series of CO 2 -based polycarbonate copolymers comprising a crosslinkable glassy poly(vinyl cyclohexene carbonate) (PVCHC, A block) and a non-crosslinkable soft poly(propylene carbonate) (PPC, B block). The polymer sequence is systematically varied (ABA, BAB, and statistical), and solvent choice controls block-selective swelling to jointly control gelation behavior, microphase morphology, and mechanical response through changes in the accessibility and local environment of photocrosslinkable vinyl groups during network formation, as revealed by photorheology and small angle x-ray scattering. By tuning polymer sequence and curing solvent, we transform nominally identical formulations from brittle to highly ductile materials, achieving a three-orders-of-magnitude range in toughness (0.003 to 9.1 MJ m −3 ). These results establish clear structure–processing–property relationships and identify polymer sequence and selective solvation as powerful strategies for programming both printability and performance of block copolymer resins for additive manufacturing.

additive manufacturing↗
NASA NTRS2003

Social roles and the evolution of networks in extreme and isolated environments

This article reports on the evolution of network structure as it relates to formal and informal social roles in well-bounded, isolated groups. Research was conducted at the Amundsen-Scott South Pole Station. Data were collected on crewmembers' networks of social interaction over each of three winter-over periods, when the station is completely isolated. In addition, data were collected on the informal roles played by crewmembers (e.g., instrumental leadership, expressive leadership). The study found that globally coherent networks in winter-over groups were associated with group consensus on the presence of critically important informal social roles (e.g., expressive leadership) where global coherence is the extent to which a network forms a single group composed of a unitary core and periphery as opposed to being factionalized into two or more subgroups. Conversely, the evolution of multiple subgroups was associated with the absence of consensus on critical informal social roles, above all the critically important role of instrumental leader.

NASA Program Biomedical Research and Countermeasur↗
DOE OSTI2021

A TTL-based Approach for Content Placement in Edge Networks

Edge networks are promising to provide better services to users by provisioning computing and storage resources at the edge of networks. However, due to the uncertainty and diversity of user interests, content popularity, distributed network structure, cache sizes, it is challenging to decide where to place the content, and how long it should be cached. In this paper, we study the utility optimization of content placement at edge networks through timer-based (TTL) policies. We propose provably optimal distributed algorithms that operate at each network cache to maximize the overall network utility. Our TTL-based optimization model provides theoretical answers to how long each content must be cached, and where it should be placed in the edge network. Extensive evaluations show that our algorithm significantly outperforms path replication with conventional caching algorithms over some network topologies.

Panigrahy, Nitish K.↗
DOE OSTI2023

Sub-nanosecond RF synchronization for MIMO software defined radio sensor networks

This disclosure presents distributed and decentralized synchronization for wireless transceivers. The disclosed system, device, and method achieve sub-nanosecond synchronization using low-cost commercial off the shelf software defined radios. By providing a decentralized mechanism that does not rely on a hierarchical master-slave structure, networks constructed as disclosed are robust to sensor drop-out in contested or harsh environments. Such networks may be used to create phased array radars and communication systems without requiring wired connections to distribute a common clock or local oscillator reference.

Moghaddam, Mahta↗
DOE OSTI2020

International network of nuclear structure and decay data evaluators

Compilation, evaluation and dissemination of nuclear data are arduous tasks that rely on contributions from experts in both the basic and applied sciences communities whose efforts are coordinated by the International Atomic Energy Agency (IAEA). The Evaluated Nuclear Structure Data File (ENSDF) includes the most extensive and comprehensive set of nuclear structure and decay data evaluations performed by the international network of Nuclear Structure and Decay Data evaluators (NSDD) under the auspices of the IAEA. In this report we describe the recent NSDD activities supported by the IAEA and provide some future perspectives.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

A New Approach to Distributed Hypothesis Testing and Non-Bayesian Learning: Improved Learning Rate and Byzantine-Resilience

Here, we study a setting where a group of agents, each receiving partially informative private signals, seek to collaboratively learn the true underlying state of the world (from a finite set of hypotheses) that generates their joint observation profiles. To solve this problem, we propose a distributed learning rule that differs fundamentally from existing approaches, in that it does not employ any form of “belief-averaging”. Instead, agents update their beliefs based on a min-rule. Under standard assumptions on the observation model and the network structure, we establish that each agent learns the truth asymptotically almost surely. As our main contribution, we prove that with probability 1, each false hypothesis is ruled out by every agent exponentially fast, at a network-independent rate that is strictly larger than existing rates. We then develop a computationally-efficient variant of our learning rule that is provably resilient to agents who do not behave as expected (as represented by a Byzantine adversary model) and deliberately try to spread misinformation.

42 ENGINEERING↗
NASA NTRS1978

Photospheric models of solar active regions and the network based on the Mg II h and k line wings

From a comparison between observed and computed wings of the Mg II resonance lines, distributions of temperature versus mass column density for solar photospheric layers in plages and in the chromospheric network are derived. The theoretical profiles are computed assuming partial coherent scattering. In the active regions, temperatures exceed those in the quiet sun by up to 200 K near the temperature minimum and up to 400 K in deeper layers. In the observed network structure, the temperature is enhanced by 200 K at the temperature minimum but is the same as that in the quiet sun at greater depths. The difference in the slope of the temperature distribution between the network and plages is real, but may refer only to long elements of the network rather than to the brightest portions. Adjacent to the network is a region in which the temperatures are similar to those in the quiet sun, except immediately below the temperature minimum, where the temperatures are depressed by 150 K.

Morrison, N. D.↗