Search NASA⌕ Search

SEARCH · Search NASA

Results for “NETWORK TECHNOLOGY”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 901 records · Page 50
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Modulation Classification of Satellite Communication Signals Using Cumulants and Neural Networks

National Aeronautics and Space Administration (NASA)'s future communication architecture is evaluating cognitive technologies and increased system intelligence. These technologies are expected to reduce the operational complexity of the network, increase science data return, and reduce interference to self and others. In order to increase situational awareness, signal classification algorithms could be applied to identify users and distinguish sources of interference. A significant amount of previous work has been done in the area of automatic signal classification for military and commercial applications. As a preliminary step, we seek to develop a system with the ability to discern signals typically encountered in satellite communication. Proposed is an automatic modulation classifier which utilizes higher order statistics (cumulants) and an estimate of the signal-to-noise ratio. These features are extracted from baseband symbols and then processed by a neural network for classification. The modulation types considered are phase-shift keying (PSK), amplitude and phase-shift keying (APSK),and quadrature amplitude modulation (QAM). Physical layer properties specific to the Digital Video Broadcasting - Satellite- Second Generation (DVB-S2) standard, such as pilots and variable ring ratios, are also considered. This paper will provide simulation results of a candidate modulation classifier, and performance will be evaluated over a range of signal-to-noise ratios, frequency offsets, and nonlinear amplifier distortions.

Signal Classification↗
DOE OSTI2013

Southeast Regional CO 2 Sequestration Technology Training Program (SECARB-Ed)

Carbon capture and storage (CCS) technologies have tremendous potential for reducing carbon dioxide (CO 2 ) emissions and mitigating global climate change. These technologies encourage economic growth and have manageable influence on energy use. Deploying these technologies on a commercial scale will require expanding the workforce, including geologists, engineers, scientists and technicians, trained in CCS specialties. In 2009, the U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) selected seven projects to help develop regional sequestration technology training centers in the United States. The “Southeast Regional CO 2 Sequestration Technology Training Program” (SECARB-Ed) was managed and administered by the Southern States Energy Board (SSEB) from November 16, 2009, to November 15, 2012. During this performance period, the SECARB-Ed partners were successful in achieving their primary objective of developing a self-sustaining regional CO 2 sequestration training program to facilitate the transfer of knowledge and technologies required for site development, operations and monitoring of commercial CCS projects. An experienced team of professionals participated in the SECARB-Ed program, with skills and competencies in geosciences, reservoir engineering and CCS related capture/separation, transportation, legal and regulatory disciplines. The SECARB-Ed Advisory Board included representatives from SSEB, Clemson University, GERALD R HILL PHD, Inc. (HILL), EnTech Strategies, LLC- Research Experience in Carbon Sequestration (RECS), Virginia Tech (VAT), Geological Survey of Alabama (GSA) at The University of Alabama and the Bureau of Economic Geology (BEG) at The University of Texas at Austin. The program encompasses fifteen of SSEB’s member states, including: Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, Missouri, North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia and West Virginia. The SECARB-Ed partners implemented an organized sponsorship development program, developed short courses on CCS technologies, participated in regional training and other activities through outreach and networking and performed internet-based and electronic regional/basin technology transfer services. The partners addressed the most promising sequestration options in the region; the mix of industry and power plant sources of CO 2 ; regional transportation infrastructure; and the legal, regulatory, and institutional frameworks that exist in the southeast. As a result, SECARB-Ed fostered the development of a future workforce with disciplines specific to applied engineering and CCS science and technologies and advance the United States in its position as the leader in addressing climate change, near-zero emissions technologies and geologic sequestration technologies. The educational and training opportunities detailed in this Final Report demonstrate an effective means of disseminating a broad base of such knowledge and skills to a variety of students and professionals who are interested in the area of CCS technologies. The efforts of the SECARB-Ed Advisory Board and partners have resulted in a total of 1,951 professional development hours (PDHs) awarded to 1,131 participants.

Baskin, Kathryn A.↗
DOE OSTI2023

Analyzing Insider Risk Threat to the Internet of Things (IoT)

Recent technological advancement has created a growing convergence of innovation. From machine learning to ubiquitous computing to wireless networks and automation, the world is seeing new technology increasingly capable of connecting with each other. Devices and systems use open communications networks to interact, process information, and react. This is called the Internet of Things (IoT) and is comprised of physical devices that exchange data over networks, creating revolutionary possibilities. The most common way most people interact with an IoT is through ‘smart home’ products like Amazon’s Alexa, which use microphones, speakers, and phones to control a variety of devices, from lights and thermostats, to cameras, to appliances and vacuum cleaners. But the open nature of IoT networks—necessary for their ability to communicate and operate—also introduces privacy and security concerns. At a personal level, this might mean a hack into a home to steal private information, but when applied in broader industries like healthcare, transportation, manufacturing, or the military, this vulnerability can have serious consequences. As IoT usage and interconnectivity increases, so too does the susceptibility to malicious actors. And the entire system is only as secure as its least secure member. This creates particular risk and vulnerability to radiological material industries, as a competent insider adversary could utilize the IoT to potentially steal or access classified or sensitive information about employees, sites, or systems; or simply sabotage security or maintenance from a more remote—and less secure—device. The IoT relies on a secure network across the entire system, especially in transport which may lack the security of more permanent locations; if one device fails, it can create a ripple effect and an insider threat may seek to exploit that connectivity. While IoT benefits drive increased innovation and usage, there are also vulnerabilities an insider threat could exploit; this risk of an IoT to radiological material must be addressed in any mitigation effort.

Kinney, Justin↗
DOE OSTI2024

T-Type Modular DC Circuit Breaker (T-Breaker) for Future DC Networks

The developed T-Type Modular DC Circuit Breaker (T-Breaker) technology offers an all-in-one solution to challenges in DC networks. This includes swift fault detection and protection, power transient stability, and power quality improvement, achieved through the utilization of wide bandgap (WBG) power semiconductors and energy storage devices. The T-Breaker not only facilitates rapid fault current detection and interruption but also implements fault current limiting through active insertion of storage devices or by operating WBG devices in the saturation region. Additionally, with the assistance of energy storage devices, potential overvoltage issues on power devices induced by control signal misalignment can be mitigated. The T-Breaker can be regulated to perform shunt current injection/absorption using the vertical arm and series voltage insertion via the horizontal arm, thereby enhancing DC system stability during voltage or load power fluctuation transients. The OSU team and Raytheon team actively worked together on designing, fabricating, assembling, and testing of two T-Breaker prototypes. The first prototype is rated at 1 kV, 500 A with half-bridge (unipolar) structure to validate the T-Breaker concept. The second prototype is rated at 20 kV, 50 A with full-bridge (bipolar) topology which can reach an efficiency of 99.977%, realize a power density of 60.2 MW/m3, and eliminate the 500-A fault current with a fault response time of around 20 µs. The prototypes show great feasibility of adopting this technology in multiple applications including electrified aircraft, super charging stations, data centers, etc.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1979

The critical satellite technical issues of future pervasive broadband low-cost communication networks

The critical technical issues of signal waveform design, projected spacecraft technology, satellite launch options, and satellite cost are discussed for future pervasive broadband communication networks. With DPCM video signal encoding, 32 Mb/s user-to-user data rate per channel, 10% overhead, two orthogonal polarizations, and crosstalk loss limited to 1 dB, TFM permits about 75 channels/GHz of frequency allocation. The BOM (beginning of mission) weight and power of a baseline 400-channel multibeam satellite is about 1800 kg and 5000 W. Each 35 Mb/s channel can support 1 to 10 video channels. The weight and power estimates assume hardened digital logic, composite materials for a multibeam antenna structure, high-efficiency solar cells, batteries, and amplifiers. Based on a cost model for large communication satellites, the total space segment cost of two active satellites and one spare would be about $485 M.

Harvey, R. L.↗
NASA NTRS2006

Comparison of Event Detection Methods for Centralized Sensor Networks

The development of an Integrated Vehicle Health Management (IVHM) for space vehicles has become a great concern. Smart Sensor Networks is one of the promising technologies that are catching a lot of attention. In this paper, we propose to a qualitative comparison of several local event (hot spot) detection algorithms in centralized redundant sensor networks. The algorithms are compared regarding their ability to locate and evaluate the event under noise and sensor failures. The purpose of this study is to check if the ratio performance/computational power of the Mote Fuzzy Validation and Fusion algorithm is relevant compare to simpler methods.

Sauvageon, Julien↗
DOE OSTI2023

Radionuclide measurements of the international monitoring system

The International Monitoring System (IMS) is a unique global network of sensors, tuned to measure various phenomenology, with the common goal of detecting a nuclear explosion anywhere in the world. One component of this network collects measurements of radioactive particulates and gases (collectively known as radionuclides) present in the atmosphere; through this, compliance with the Comprehensive Nuclear-Test-Ban Treaty (CTBT) can be verified. The radionuclide sub-network consists of 120 sensors across 80 locations, supported by 16 measurement laboratories. All radionuclide stations make use of a form of γ-ray spectroscopy to measure radionuclides from samples; this remains largely unchanged since the network was first established 25 years ago. Advances in sampling and spectroscopy systems can yield improvements to the sensitivity of the network to detect a nuclear explosion. This paper summarises the status of the IMS radionuclide network, the current suite of technology used and reviews new technology that could enhance future iterations, potentially improving the verification power of the IMS.

Goodwin, Matthew A.↗
DOE OSTI2013

Three-dimensional reconstruction and morphologic characteristics of porous metal fiber sintered sheet

This paper presents an approach to achieve morphological characterizing for complex porous materials based on micro X-ray tomography images, with an example of a novel porous metal fiber sheet produced through solid-state sintering method. The geometrical reconstruction was performed after selection of volume of interest and image processing of anisotropic diffusion smooth. The reconstructed gray level images were then transferred into binary images by adjusting binarization threshold according to the actual porosity. Taking into account the tubular structural feature of the fibers, skeleton extraction algorithm based on the distance transform function was applied and further improved by the scale axis transform method. The skeleton was later pruned and segmented according to the contact points to perform morphological characterizing. Compared with actual manufacturing parameters, the style, length, radius, orientation and tortuosity of fiber segments were discussed. The results show that our proposed method can well describe the actual geometrical and morphological characteristics, which will provide a promising method for the structural description of fibrous networks. - Highlights: • Micro-CT technology was used to achieve the 3D geometrical reconstruction. • Skeleton extraction algorithm was modified to get the medial skeleton. • Skeleton filter operation was adopted to deal with the segmented skeleton. • Useful morphological statistics was obtained through skeleton segments. • Relationship between structure and manufacturing processes was discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Label-free time- and space-resolved exometabolite sampling of growing plant roots through nanoporous interfaces

Abstract Spatial and temporal profiling of metabolites within and between living systems is vital to understanding how chemical signaling shapes the composition and function of these complex systems. Measurement of metabolites is challenging because they are often not amenable to extrinsic tags, are diverse in nature, and are present with a broad range of concentrations. Moreover, direct imaging by chemically informative tools can significantly compromise viability of the system of interest or lack adequate resolution. Here, we present a nano-enabled and label-free imaging technology using a microfluidic sampling network to track production and distribution of chemical information in the microenvironment of a living organism. We describe the integration of a polyester track-etched (PETE) nanofluidic interface to physically confine the biological sample within the model environment, while allowing fluidic access via an underlying microfluidic network. The nanoporous interface enables sampling of the microenvironment above in a time-dependent and spatially-resolved manner. For demonstration, the diffusional flux through the PETE membrane was characterized to understand membrane performance, and exometabolites from a growing plant root were successfully profiled in a space- and time-resolved manner. This method and device provide a frame-by-frame description of the chemical environment that maps to the physical and biological characteristics of the sample.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Sensor Placement Optimization Software Applied to Site-Scale Methane-Emissions Monitoring

Advances in sensor technology have increased our ability to monitor a wide range of environments. However, even as the cost of sensors decline, only a limited number of sensors can be installed at any given site. The physical placement of sensors, along with the sensor technology and operating conditions, can have a large impact on our ability to adequately monitor environmental change. This paper introduces a new open-source Python package, called Chama, that determines optimal sensor placement and technology to improve a sensor network’s detection capabilities. Additionally, the methods are demonstrated using site-specific methane emission scenarios that capture uncertainty in wind conditions and emission characteristics. Mixed-integer linear programming formulations are used to determine sensor locations and detection thresholds that maximize detection of the emission scenarios. The optimized sensor networks consistently increase the ability to detect leaks, as compared to sensors placed near each potential emission source or along the perimeter of the site.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Kernelized Generalized Likelihood Ratio Test for Spectrum Sensing in Cognitive Radio

Spectrum sensing in next-generation wireless radio networks is considered a key technology to overcome the problem of spectrum scarcity. Unfortunately, many approaches to spectrum sensing do not work well in low signal-to-noise ratio (SNR) environments. This paper proposes and analyzes a new algorithm named kernelized generalized likelihood ratio test (KGLRT) for spectrum sensing in cognitive radio systems to overcome this problem. Effectively, KGLRT uses a nonlinear kernel to map input data onto a high-dimensional feature space; then, the widely accepted (linear) generalized likelihood ratio test is used for hypothesis testing. This new algorithm gives a gain of 4 dB in SNR over its linear counterpart. A theoretical analysis for this algorithm is given for the first time and is shown analogous to algorithms used in image signal processing. The detection metrics are found to be concentrated random variables; furthermore, the probability distributions of the detection metrics are proved to follow the F -distributions, which agree with the results obtained using the concentration inequality. The analytical thresholds are derived for target false-alarm probabilities. Here, the thresholds are independent of noise power; thus, the proposed algorithm can overcome noise uncertainty issues at very low SNR levels. Simulations validate the theoretical results.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Fit Fly: A Case Study of Interconnect Innovation through Parallel Simulation

To meet the demand for exascale-level performance from high-performance computing (HPC) interconnects, many system architects are turning to simulation results for accurate and reliable predictions of the performance of prospective technologies. Testing full-scale networks with a variety of benchmarking tools, including synthetic workloads and application traces, can give crucial insight into what ideas are most promising without needing to physically construct a test network. While flexible, however, this approach is extremely compute time intensive. We address this time complexity challenge through the use of large-scale, optimistic parallel simulation that ultimately leads to faster HPC network architecture innovations. In this paper we demonstrate this innovation capability through a real-world network design case study. Specifically, we have simulated and compared four extreme-scale interconnects: Dragonfly, Megafly, Slim Fly, and a new dual-rail-dual-plane variation of the Slim Fly network topology. We present this new variant of Slim Fly, dubbed Fit Fly, to show how interconnect innovation and evaluation-beyond what is possible through analytic methods-can be achieved through parallel simulation. We validate and compare the model with various network designs using the CODES interconnect simulation framework. By running large-scale simulations in a parallel environment, we are able to quickly generate reliable performance results that can help network designers break ground on the next generation of high-performance network designs.

High Performance Computing↗
DOE OSTI2023

Ameliorating Global Challenges: Globalization, Geopolitics, Basic & Applied Research, and Research Security

We are confronted with a myriad of global challenges, from extreme weather events, occurring at higher frequencies than at any point in history, to pollution, food insecurity, clean water shortages, and fundamentally limited natural resources and materials. The largest number of people inhabit our planet today and enjoy the highest standard of living - though not equally distributed across the world - compared to any prior moment in history. To sustain this quality of life, we are largely reliant on fossil fuel sources, which are responsible for more greenhouse gas emissions by weight each day than the collective weight of all humans that inhabit the planet. Ameliorating these global challenges will require elements of solutions that include advances in basic and applied research, innovative global engineering, materials discovery, new technologies, manufacturing at scale, resilient and adaptable infrastructure, carbon-free energy sources and storage technologies, and new supply chain networks and markets. Success will require constructive collaborative efforts between researchers in countries located in every continent of this planet. For any of these goals to be realized in a timely fashion, geopolitical leaders must become better educated about this existential challenge and incentivized to act.

applied research↗
DOE OSTI2019

An Overview of Technologies for Individual Trip History Collection: Mobility Decision Science Pillar SMART Mobility Consortium

WholeTraveler is a project of the Department of Energy's Smart Mobility consortium that explores how an individual's attitudes and lifestyle characteristics are embodied in transportation behaviors throughout one's life trajectory. As a study at the nexus of decision science and urban systems analysis, fine-grained location data (FGLD), or records of an individual's location collected at a resolution sufficient to determine both the unique destinations a traveler visits each day and the modes used to travel between them, underlie high quality results. Moreover, the methods for collecting FGLD and the means through which they are associated with a traveler's personal attributes have significant implications for the burden on research participants, the cost and complexity of the study, as well as the confidence with which hypotheses can be validated. This paper provides a broad overview of existing technologies for FGLD collection and is intended to provide a literature review for researcher exploring similar domain areas. Technologies are categorized as either network or onboard approaches. An onboard system, such as smartphone or GPS device, sends signals to external networks to capture its own location. Conversely, network systems, such as cell towers, are comprised of sensing nodes with known locations that record when individually identifiable assets come within their range of detection. Our analysis indicates that the most sensible approach to FGLD collection, for the purposes of WholeTraveler, is to leverage onboard devices, and in particular the existing Moves or Google Maps applications for Android and iOS smartphones. Dedicated GPS devices have been widely implemented by the transportation research community and pose an alternatively acceptable form of FGLD collection. Independently developing a custom smartphone application is not recommended because of the notable challenges in establishing minimal viable functionality, as well as in ensuring compatibility across an ever-growing combination of hardware devices and software versions. No matter the technical means of data collection, the secure handling of FGLD is of critical importance.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Single Photon Emitters Coupled to Photonic Wire bonds

This project will test the coupling of light emitted from silicon vacancy and nitrogen vacancy defects in diamond into additively manufactured photonic wire bonds toward integration into an "on-chip quantum photonics platform". These defects offer a room-temperature solid state solution for quantum information technologies but suffer from issues such as low activation rate and variable local environments. Photonic wire bonding will allow entanglement of pre-selected solid-state defects alleviating some of these issues and enable simplified integration with other photonic devices. These developments could prove to be key technologies to realize quantum secured networks for national security applications.

42 ENGINEERING↗
DOE OSTI2021

Kennesaw State University Scientific Deep Dive

EPOC uses the Deep Dive process to discuss and analyze current and planned science, research, or education activities and the anticipated data output of a particular use case, site, or project to help inform the strategic planning of a campus or regional networking environment. This includes understanding future needs related to network operations, network capacity upgrades, and other technological service investments. A Deep Dive comprehensively surveys major research stakeholders’ plans and processes in order to investigate data management requirements over the next 5–10 years. Between August 2021 and October 2021, staff members from the Engagement and Performance Operations Center (EPOC) met with researchers and staff from Kennesaw State University (KSU) for the purpose of a Deep Dive into scientific and research drivers. The goal of this activity was to help characterize the requirements for a number of campus use cases, and to enable cyberinfrastructure support staff to better understand the needs of the researchers within the KSU community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Shared Mobility Data Availability and Usage Trends

In this report, we summarize data availability of new shared mobility technologies by mobility type and region and analyze how shared mobility usage varies by time and by demographic factors in the United States. The shared mobility technologies include ridehailing from transportation network companies (TNC), bikeshare, and scooter share. There is a wide range in shared mobility usage per capita across the country, even within urban areas. We observe that there was steady growth of new shared mobility usage from 2015 to early 2020, before COVID-19 reduced overall ridership. An analysis focused on Chicago shows that despite the availability of good public transportation, high usage of new shared mobility modes is centered in high income communities, especially by households who own less vehicles. However, we find that TNC is used for first-mile and last-mile in lower income communities. Analysis on the bikeshare usage also shows that household income is shown to not be a statistically significant factor when accounting for other factors including employment density, population density, percentage of college graduates, and bike-lane proximity.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Midland College Requirements Analysis Report

EPOC uses the Deep Dive process to discuss and analyze current and planned science, research, or education activities and the anticipated data output of a particular use case, site, or project to help inform the strategic planning of a campus or regional networking environment. This includes understanding future needs related to network operations, network capacity upgrades, and other technological service investments. A Deep Dive comprehensively surveys major research stakeholders’ plans and processes in order to investigate data management requirements over the next 5–10 years. In April of 2022, staff members from the Engagement and Performance Operations Center (EPOC) met with researchers and staff from LEARN and Midland College for the purpose of a Deep Dive into scientific and research drivers. The goal of this activity was to help characterize the requirements for a number of campus use cases, and to enable cyberinfrastructure support staff to better understand the needs of the researchers within the community.

97 MATHEMATICS AND COMPUTING↗