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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

VLBI: A Fascinating Technique for Geodesy and Astrometry

Since the 1970s Very Long Baseline Interferometry (VLBI) has proven to be a primary space-geodetic technique by determining precise coordinates on the Earth, by monitoring the variable Earth rotation and orientation with highest precision, and by deriving many other parameters of the Earth system. VLBI provides an important linkage to astronomy through, for instance, the determination of very precise coordinates of extragalactic radio sources. Additionally, it contributes to determining parameters of relativistic and cosmological models. After a short review of the history of geodetic VLBI and a summary of recent results, this paper describes future perspectives of this fascinating technique. The International VLBI Service for Geodesy and Astrometry (IVS), as a service of the International Association of Geodesy (IAG) and the International Astronomical Union (IAU), is well on its way to fully defining a next generation VLBI system, called VLBI2010. The goals of the new system are to achieve on scales up to the size of the Earth an accuracy of 1 mm in position and of 0.1 mm/year in velocity. Continuous observations shall be carried out 24 h per day 7 days per week in the future with initial results to be delivered within 24 h after taking the data. Special sessions, e.g. for monitoring the Earth rotation parameters, will provide the results in near real-time. These goals require a completely new technical and conceptual design of VLBI measurements. Based on extensive simulation studies, strategies have been developed by the IVS to significantly improve its product accuracy through the use of a network of small (approx 12 m) fast-slewing antennas. A new method for generating high precision delay measurements as well as improved methods for handling biases related to radio source structure, system electronics, and deformations of the antenna structures has been developed. Furthermore, as of January 2012, the construction of ten new VLBI2010 sites has been funded, with good prospects for one dozen more antennas, which will improve the geographical distribution of geodetic VLBI sites on Earth and provide an important step toward a global VLBI2010 network. Within this paper, the Global Geodetic Observing System (GGOS) of the IAG will also be introduced and the contribution of VLBI to GGOS will be described.

Geodesy↗
NASA NTRSDate not supplied

Refined Analysis of CO2 Emissions in Urban Air Mobility Networks

In this study, we examine the environmental impact of Urban Air Mobility (UAM) operations as measured via carbon dioxide (CO2) emissions by leveraging a computational model from previous studies that has been refined and expanded. Several scenarios are examined in which total transportation emissions for a representative day in a metro area are distributed differently among vehicle types and transportation modes. Specifically, we investigate the use of electric air vehicles in a UAM network; the increasing presence of electric ground vehicles for ground transportation; the impacts from implementing ridesharing in the UAM mode; and the effects of varying the electricity grid emissions. Results for a case study in the Chicago, IL metro area indicate that incorporating electric ground vehicles and UAM ridesharing can both lead to reduced CO2 emissions. These preliminary results indicate that carbon emissions from a UAM system leveraging ridesharing and all-electric aircraft may not be a practical operational limit on UAM, though further improvements to the modeling are warranted.

advanced air mobility↗
NASA NTRSDate not supplied

Refined Analysis of CO2 Emissions in Urban Air Mobility Networks

In this study, we examine the environmental impact of Urban Air Mobility (UAM) operations as measured via carbon dioxide (CO2) emissions by leveraging a computational model from previous studies that has been refined and expanded. Several scenarios are examined in which total transportation emissions for a representative day in a metro area are distributed differently among vehicle types and transportation modes. Specifically, we investigate the use of electric air vehicles in a UAM network; the increasing presence of electric ground vehicles for ground transportation; the impacts from implementing ridesharing in the UAM mode; and the effects of varying the electricity grid emissions. Results for a case study in the Chicago, IL metro area indicate that incorporating electric ground vehicles and UAM ridesharing can both lead to reduced CO2 emissions. These preliminary results indicate that carbon emissions from a UAM system leveraging ridesharing and all-electric aircraft may not be a practical operational limit on UAM, though further improvements to the modeling are warranted.

advanced air mobility↗
NASA NTRS1996

An Acoustic Emission and Acousto-Ultrasonic Analysis of Impact Damaged Composite Pressure Vessels

The research presented herein summarizes the development of acoustic emission (AE) and acousto-ultrasonic (AU) techniques for the nondestructive evaluation of filament wound composite pressure vessels. Vessels fabricated from both graphite and kevlar fibers with an epoxy matrix were examined prior to hydroburst using AU and during hydroburst using AE. A dead weight drop apparatus featuring both blunt and sharp impactor tips was utilized to produce a single known energy 'damage' level in each of the vessels so that the degree to which the effects of impact damage could be measured. The damage levels ranged from barely visible to obvious fiber breakage and delamination. Independent neural network burst pressure prediction models were developed from a sample of each fiber/resin material system. Here, the cumulative AE amplitude distribution data collected from low level proof test (25% of the expected burst for undamaged vessels) were used to measure the effects of the impact on the residual burst pressure of the vessels. The results of the AE/neural network model for the inert propellant filled graphite/epoxy vessels 'IM7/3501-6, IM7/977-2 and IM7/8553-45' demonstrated that burst pressures can be predicted from low level AE proof test data, yielding an average error of 5.0%. The trained network for the IM7/977-2 class vessels was also able to predict the expected burst pressure of taller vessels (three times longer hoop region length) constructed of the same material and using the same manufacturing technique, with an average error of 4.9%. To a lesser extent, the burst pressure prediction models could also measure the effects of impact damage to the kevlar/epoxy 'Kevlar 49/ DPL862' vessels. Here though, due to the higher attenuation of the material, an insufficient amount of AE amplitude information was collected to generate robust network models. Although, the worst case trial errors were less than 6%, when additional blind predictions were attempted, errors as high as 50% were produced. An acousto-ultrasonic robotic evaluation system (AURES) was developed for mapping the effects of damage on filament wound pressure vessels prior to hydroproof testing. The AURES injects a single broadband ultrasonic pulse into each vessel at preprogrammed positions and records the effects of the interaction of that pulse on the material volume with a broadband receiver. A stress wave factor in the form of the energy associated with the 750 to 1000 kHz and 1000 to 1250 kHz frequency bands were used to map the potential failure sites for each vessel. The energy map associated with the graphite/epoxy vessels was found to decrease in the region of the impact damage. The kevlar vessels showed the opposite trend, with the energy values increasing around the damage/failure sites.

Walker, James L.↗
NASA NTRS2011

Space Flight Middleware: Remote AMS over DTN for Delay-Tolerant Messaging

This paper describes a technique for implementing scalable, reliable, multi-source multipoint data distribution in space flight communications -- Delay-Tolerant Reliable Multicast (DTRM) -- that is fully supported by the "Remote AMS" (RAMS) protocol of the Asynchronous Message Service (AMS) proposed for standardization within the Consultative Committee for Space Data Systems (CCSDS). The DTRM architecture enables applications to easily "publish" messages that will be reliably and efficiently delivered to an arbitrary number of "subscribing" applications residing anywhere in the space network, whether in the same subnet or in a subnet on a remote planet or vehicle separated by many light minutes of interplanetary space. The architecture comprises multiple levels of protocol, each included for a specific purpose and allocated specific responsibilities: "application AMS" traffic performs end-system data introduction and delivery subject to access control; underlying "remote AMS" directs this application traffic to populations of recipients at remote locations in a multicast distribution tree, enabling the architecture to scale up to large networks; further underlying Delay-Tolerant Networking (DTN) Bundle Protocol (BP) advances RAMS protocol data units through the distribution tree using delay-tolerant storeand- forward methods; and further underlying reliable "convergence-layer" protocols ensure successful data transfer over each segment of the end-to-end route. The result is scalable, reliable, delay-tolerant multi-source multicast that is largely self-configuring.

Disruption Tolerant Networking (DTN)↗
NASA NTRS2008

Determination of a Limited Scope Network's Lightning Detection Efficiency

This paper outlines a modeling technique to map lightning detection efficiency variations over a region surveyed by a sparse array of ground based detectors. A reliable flash peak current distribution (PCD) for the region serves as the technique's base. This distribution is recast as an event probability distribution function. The technique then uses the PCD together with information regarding: site signal detection thresholds, type of solution algorithm used, and range attenuation; to formulate the probability that a flash at a specified location will yield a solution. Applying this technique to the full region produces detection efficiency contour maps specific to the parameters employed. These contours facilitate a comparative analysis of each parameter's effect on the network's detection efficiency. In an alternate application, this modeling technique gives an estimate of the number, strength, and distribution of events going undetected. This approach leads to a variety of event density contour maps. This application is also illustrated. The technique's base PCD can be empirical or analytical. A process for formulating an empirical PCD specific to the region and network being studied is presented. A new method for producing an analytical representation of the empirical PCD is also introduced.

Rompala, John T.↗
NASA NTRS1978

Cargo Logistics Airlift Systems Study (CLASS). Volume 3: Cross impact between the 1990 market and the air physical distribution systems, book 2

Book 2 of this volume is divided into the following sections: (1) commodities and system networks; (2) future mode choice decisions and commodity air eligibility; (3) comparative cargo transportation costs - air, truck, rail and water; (4) elasticities of demand; (5) operating cost; (6) operating profit, rate making, and returns; (7) importance of rate and service on future aircraft; (8) potential market demand for new aircraft; (9) scenario of events affecting system/market growth; and (10) future study and technology requirements.

Burby, R. J.↗
NASA NTRS1994

Design and Implementation of a Distributed Version of the NASA Engine Performance Program

Distributed NEPP is a new version of the NASA Engine Performance Program that runs in parallel on a collection of Unix workstations connected through a network. The program is fault-tolerant, efficient, and shows significant speed-up in a multi-user, heterogeneous environment. This report describes the issues involved in designing distributed NEPP, the algorithms the program uses, and the performance distributed NEPP achieves. It develops an analytical model to predict and measure the performance of the simple distribution, multiple distribution, and fault-tolerant distribution algorithms that distributed NEPP incorporates. Finally, the appendices explain how to use distributed NEPP and document the organization of the program's source code.

Cours, Jeffrey T.↗
NASA NTRSDate not supplied

Distributed Pressure Sensing for Enabling Self-Aware Autonomous Aerial Vehicles

Autonomous aerial transportation will be a fixture of future robotic societies, simultaneously requiring more stringent safety requirements and fewer resources for characterization than current commercial air transportation. More robust, adaptable, self-state estimation will be necessary to create such autonomous systems. We present a modular, scalable, distributed pressure sensing skin for aerodynamic state estimation of a large, flexible aerostructure. This skin used a network of 22 nodes that performed in-situ computation and communication of data collected from 74 pressure sensors, which were embedded into the skin panels of an ultra-lightweight 14-foot wingspan made from commutable, lattice-based subcomponents, and tested at NASA Langley Research Center's 14X22 wind tunnel. The density of the pressure sensors allowed for the use of a novel distributed algorithm to generate estimates of the wing lift contribution that were more accurate than the direct integration of the pressure distribution over the wing surface.

Daniel Cellucci↗
NASA NTRS1992

Mathematical modelling of flow distribution in the human cardiovascular system

The paper presents a detailed model of the entire human cardiovascular system which aims to study the changes in flow distribution caused by external stimuli, changes in internal parameters, or other factors. The arterial-venous network is represented by 325 interconnected elastic segments. The mathematical description of each segment is based on equations of hydrodynamics and those of stress/strain relationships in elastic materials. Appropriate input functions provide for the pumping of blood by the heart through the system. The analysis employs the finite-element technique which can accommodate any prescribed boundary conditions. Values of model parameters are from available data on physical and rheological properties of blood and blood vessels. As a representative example, simulation results on changes in flow distribution with changes in the elastic properties of blood vessels are discussed. They indicate that the errors in the calculated overall flow rates are not significant even in the extreme case of arteries and veins behaving as rigid tubes.

NASA Center JSC↗
NASA NTRS2019

Quantum Technologies for UAS (QTech)

Harness the power of quantum technologies to assure the availability of UAS communications against disruptions. Make use of quantum computing (e.g. quantum optimization) and quantum communication (e.g. quantum key distribution) to address the availability cybersecurity challenge. Our approach is three-fold: (1) Utilize quantum optimization algorithms to design robust network with routing redundancy that can respond adaptively to dynamically changing real-time environment and disruptions, (2) Utilize quantum optimization algorithms resource allocation for detection, localization, and tracking of mobile communication disruption agents, (3) Utilize quantum key distribution (QKD) to execute secure key sharing in high data rate optical communication and/or anti-jamming protocols for secure RF communication.

Quantum Computing↗
NASA NTRS1993

Mars Relays Satellite Orbit Design Considerations for Global Support of Robotic Surface Missions

This paper discusses orbit design considerations for Mars relay satellite (MRS)support of globally distributed robotic surface missions. The orbit results reported in this paper are derived from studies of MRS support for two types of Mars robotic surface missions: 1) the mars Environmental Survey (MESUR) mission, which in its current definition would deploy a global network of up to 16 small landers, and 2)a Small Mars Sample Return (SMSR) mission, which included four globally distributed landers, each with a return stage and one or two rovers, and up to four additional sets of lander/rover elements in an extended mission phase.

Robitics Mars↗
NASA NTRS1993

Space Station Freedom ground data system: Design and operations

Over the previous year the Space Station Freedom (SSF) Program (SSFP) ground data distribution system has become independent of a number of data systems that were to have been provided by other National Aeronautics and Space Administration (NASA) programs. Consequently, the SSFP has outlined the basic architecture of a new data system dedicated to supporting SSF requirements. This has been accomplished through a complete redesign of the ground network and a reallocation of selected functions. There are a number of aspects of the new ground data distribution system that are unique among NASA programs. These considerations make SSF ground data distribution one of the most extensive and complex data management challenges encountered in the arena of Space Operations. A description of this system comprises the main focus of the paper.

Dunning, Richard A., Jr.↗
NASA NTRS2003

Application of a data-mining method based on Bayesian networks to lesion-deficit analysis

Although lesion-deficit analysis (LDA) has provided extensive information about structure-function associations in the human brain, LDA has suffered from the difficulties inherent to the analysis of spatial data, i.e., there are many more variables than subjects, and data may be difficult to model using standard distributions, such as the normal distribution. We herein describe a Bayesian method for LDA; this method is based on data-mining techniques that employ Bayesian networks to represent structure-function associations. These methods are computationally tractable, and can represent complex, nonlinear structure-function associations. When applied to the evaluation of data obtained from a study of the psychiatric sequelae of traumatic brain injury in children, this method generates a Bayesian network that demonstrates complex, nonlinear associations among lesions in the left caudate, right globus pallidus, right side of the corpus callosum, right caudate, and left thalamus, and subsequent development of attention-deficit hyperactivity disorder, confirming and extending our previous statistical analysis of these data. Furthermore, analysis of simulated data indicates that methods based on Bayesian networks may be more sensitive and specific for detecting associations among categorical variables than methods based on chi-square and Fisher exact statistics.

NASA Discipline Neuroscience↗
NASA NTRS2004

Intelligent Systems Technologies and Utilization of Earth Observation Data

The addition of raw data and derived geophysical parameters from several Earth observing satellites over the last decade to the data held by NASA data centers has created a data rich environment for the Earth science research and applications communities. The data products are being distributed to a large and diverse community of users. Due to advances in computational hardware, networks and communications, information management and software technologies, significant progress has been made in the last decade in archiving and providing data to users. However, to realize the full potential of the growing data archives, further progress is necessary in the transformation of data into information, and information into knowledge that can be used in particular applications. Sponsored by NASA s Intelligent Systems Project within the Computing, Information and Communication Technology (CICT) Program, a conceptual architecture study has been conducted to examine ideas to improve data utilization through the addition of intelligence into the archives in the context of an overall knowledge building system (KBS). Potential Intelligent Archive concepts include: 1) Mining archived data holdings to improve metadata to facilitate data access and usability; 2) Building intelligence about transformations on data, information, knowledge, and accompanying services; 3) Recognizing the value of results, indexing and formatting them for easy access; 4) Interacting as a cooperative node in a web of distributed systems to perform knowledge building; and 5) Being aware of other nodes in the KBS, participating in open systems interfaces and protocols for virtualization, and achieving collaborative interoperability.

Ramapriyan, H. K.↗
NASA NTRS1999

A Study of Quality of Service Communication for High-Speed Packet-Switching Computer Sub-Networks

With the development of high-speed networking technology, computer networks, including local-area networks (LANs), wide-area networks (WANs) and the Internet, are extending their traditional roles of carrying computer data. They are being used for Internet telephony, multimedia applications such as conferencing and video on demand, distributed simulations, and other real-time applications. LANs are even used for distributed real-time process control and computing as a cost-effective approach. Differing from traditional data transfer, these new classes of high-speed network applications (video, audio, real-time process control, and others) are delay sensitive. The usefulness of data depends not only on the correctness of received data, but also the time that data are received. In other words, these new classes of applications require networks to provide guaranteed services or quality of service (QoS). Quality of service can be defined by a set of parameters and reflects a user's expectation about the underlying network's behavior. Traditionally, distinct services are provided by different kinds of networks. Voice services are provided by telephone networks, video services are provided by cable networks, and data transfer services are provided by computer networks. A single network providing different services is called an integrated-services network.

Cui, Zhenqian↗
NASA NTRS2012

Hybrid Collaborative Learning for Classification and Clustering in Sensor Networks

Traditionally, nodes in a sensor network simply collect data and then pass it on to a centralized node that archives, distributes, and possibly analyzes the data. However, analysis at the individual nodes could enable faster detection of anomalies or other interesting events as well as faster responses, such as sending out alerts or increasing the data collection rate. There is an additional opportunity for increased performance if learners at individual nodes can communicate with their neighbors. In previous work, methods were developed by which classification algorithms deployed at sensor nodes can communicate information about event labels to each other, building on prior work with co-training, self-training, and active learning. The idea of collaborative learning was extended to function for clustering algorithms as well, similar to ideas from penta-training and consensus clustering. However, collaboration between these learner types had not been explored. A new protocol was developed by which classifiers and clusterers can share key information about their observations and conclusions as they learn. This is an active collaboration in which learners of either type can query their neighbors for information that they then use to re-train or re-learn the concept they are studying. The protocol also supports broadcasts from the classifiers and clusterers to the rest of the network to announce new discoveries. Classifiers observe an event and assign it a label (type). Clusterers instead group observations into clusters without assigning them a label, and they collaborate in terms of pairwise constraints between two events [same-cluster (mustlink) or different-cluster (cannot-link)]. Fundamentally, these two learner types speak different languages. To bridge this gap, the new communication protocol provides four types of exchanges: hybrid queries for information, hybrid "broadcasts" of learned information, each specified for classifiers-to-clusterers, and clusterers-to-classifiers. The new capability has the potential to greatly expand the in situ analysis abilities of sensor networks. Classifiers seeking to categorize incoming data into different types of events can operate in tandem with clusterers that are sensitive to the occurrence of new kinds of events not known to the classifiers. In contrast to current approaches that treat these operations as independent components, a hybrid collaborative learning system can enable them to learn from each other.

Wagstaff, Kiri L.↗