Space programs summary no. 37-60, volume 2, for the period 1 September to 31 October 1969. The deep space network
Telemetry and ground support equipment design and developments for Deep Space Network
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Electro-optic network analyzer
The bandwidth of frequency domain measurement methods of electrical signals has usually been far greater than the bandwidth of time domain methods. The primary limits of the time domain approach have been the 20 to 30 GHz bandwidth limit for electronic waveform acquisition instrumentation, and the lack of usable electrical pulse generators for excitation of a test device. The bandwidth of frequency domain network analysis appears to have reached a plateau of between 100 to 200 GHz, while time domain measurement have improved markedly in both bandwidth and sensitivity with the introduction of the pulsed laser based electro-optic sampling approach. Network analysis or the measurement of device scattering parameters provides information necessary to the design of electronic network such as high frequency amplifiers, mixers, and phase shifter. The bandwidth of frequency domain network analysis is currently being exceeded by the next generations of high frequency transistors and devices. Thus the electro-optic approach is a natural means of extending network analysis into the range above 100 GHz by employing time domain methods. In this approach, a suitable electrical excitation pulse is generated and propagated along a transmission line toward a test device. In the picosecond domain, laser driven photoconductive switches provide a unique method of generating electrical transients. Several materials were studied for generating short electrical pulses using photoconductive switches. The various semiconductive materials tested for photoconductive switching, and the electro-optic measurement technique used to characterize the material performance are described.
Jackson, Todd A.↗
The Cable and Wireless approach to network synchronization
The philosophy adopted by Cable and Wireless for the synchronization of its world-wide network is presented. The architectures of some clock systems already deployed and how network synchronization had been implemented at selected locations are discussed. This includes some innovative designs as the network spans both first and third world countries with a combination of North Amercan and European hierarchy equipment. Different parts of the global network are linked together by a combination of terrestrial microwave, submarine cable and satellite technology. The impact of synchronization on Intelsat Intermediate Data Rate (IDR) operation and the restoration of submarine cable systems are addressed.
Calvert, Robert D.↗
BSTC: A Novel Binarized-Soft-Tensor-Core Design for Accelerating Bit-Based Approximated Neural Nets
Binarized neural network (or BNN) promises tremendous performance improvement over traditional DNNs through simplified bit-level computation and significantly reduced memory access/storage cost. In addition, it has other advantages of low-cost, low-energy and high-robustness, showing great utilization potential in resources-constrained, volatile and latency-critical applications, which are critical for future HPC execution. However, the promised significant performance gain of BNN inference has never been fully demonstrated on general-purpose processors, particularly on GPUs, due to: (i) the challenge to extract and leverage sufficient fine-grained bit-level-parallelism to saturate GPU cores when batch is small; (ii) the fundamental design conflict between bit-based BNN algorithm and underlying word-based architecture; (iii) architecture \& performance unfriendly BNN network design. To address (i) and (ii), we propose binarized-soft-tensor-core as a software-hardware codesign approach to construct bit-manipulation capability for modern GPUs to effectively harvest the emerging bit-level-parallelism. To tackle (iii), we propose intra- and inter-layer fusion techniques so that the entire BNN inference can be packed into a single GPU kernel, to avoid high-cost frequent launching. Experiments demonstrate that our design can achieve over 1000x speedup for raw inference latency and 10x for inference throughput over the state-of-the-art full-precision simulated BNN inference for AlexNet on ImageNet.
Li, Ang↗
Design of a Channel Error Simulator using Virtual Instrument Techniques for the Initial Testing of TCP/IP and SCPS Protocols
There exists a need for designers and developers to have a method to conveniently test a variety of communications parameters for an overall system design. This is no different when testing network protocols as when testing modulation formats. In this report, we discuss a means of providing a networking test device specifically designed to be used for space communications. This test device is a PC-based Virtual Instrument (VI) programmed using the LabVIEW(TM) version 5 software suite developed by National Instruments(TM)TM. This instrument was designed to be portable and usable by others without special, additional equipment. The programming was designed to replicate a VME-based hardware module developed earlier at New Mexico State University (NMSU) and to provide expanded capabilities exceeding the baseline configuration existing in that module. This report describes the design goals for the VI module in the next section and follows that with a description of the design of the VI instrument. This is followed with a description of the validation tests run on the VI. An application of the error-generating VI to networking protocols is then given.
Horan, Stephen↗
Compliance and Functional Testing of IEEE 1451.1 for NCAP-to-NCAP Communications in a Sensor Network
Distributed control in a networked environment is an irreplaceable feature in systems with remote sensors and actuators. Although distributed control was not originally designed to be networked, usage of off-the-shelf networking technologies has become so prevalent that control systems are desired to have access mechanisms similar to computer networks. However, proprietary transducer interfaces for network communications and distributed control overwhelmingly dominate this industry. Unless the lack of compatibility and interoperability among transducers is resolved, the mature level of access (that computer networking can deliver) will not be achieved in such networked distributed control systems. Standardization of networked transducer interfaces will enable devices from different manufacturers to talk to each other and ensure their plug-and-play capability. One such standard is the suite of IEEE 1451 for sensor network communication and transducer interfaces. The suite not only provides a standard interface for smart transducers, but also outlines the connection of an NCAP (network capable application processor) and transducers (through a transducer interface module TIM). This paper presents the design of the compliance testing of IEEE 1451.1 (referred to as Dot1) compatible NCAP-to-NCAP communications on a link-layer independent medium. The paper also represents the first demonstration of NCAP-to-NCAP communications with Dot1 compatibility: a tester NCAP and an NCAP under test (NUT).
Figueroa, Jorge↗
Convolutional networks for vehicle track segmentation
Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are unable to capture natural track features such as continuity and parallelism. More powerful, but computationally expensive models can be used in offline settings. We present an approach that uses dilated convolutional networks consisting of a series of 3-by-3 convolutions to segment vehicle tracks. The design of our networks considers the fact that remote sensing applications tend to operate in low power and have limited training data. As a result, we aim for small, efficient networks that can be trained end-to-end to learn natural track features entirely from limited training data. We demonstrate that our 6-layer network, trained on just 90 images, is computationally efficient and improves the F-score on a standard dataset to 0.992, up from 0.959 obtained by the current state-of-the-art method.
47 OTHER INSTRUMENTATION↗
Telecommunications network optimization
Analysis discusses STACOM (state criminal justic communication) network topology program used to design and evaluate digital telecommunications networks STACOM employs ESAU-WILLIAMS technique to search for direct links between system terminations and regional switching center. Inputs include traffic data, terminal locations, and functional requirements.
Lee, J.↗
Remote Sensor Design for Visual Recognition with Convolutional Neural Networks
While deep learning technologies for computer vision have developed rapidly since 2012, modeling of remote sensing systems has remained focused around human vision. In particular, remote sensing systems are usually constructed to optimize sensing cost-quality trade-offs with respect to human image interpretability. While some recent studies have explored remote sensing system design as a function of simple computer vision algorithm performance, there has been little work relating this design to the state-of-the-art in computer vision: deep learning with convolutional neural networks. We develop experimental systems to conduct this analysis, showing results with modern deep learning algorithms and recent overhead image data. Our results are compared to standard image quality measurements based on human visual perception, and we conclude not only that machine and human interpretability differ significantly, but that computer vision performance is largely self-consistent across a range of disparate conditions. This repository contains all the code required to replicate the results of our research paper, and the corresponding docker environment in which that code can be executed. All code is written in Python3 and utilizes the PyTorch library (v1.0) for neural network model training and evaluation. Jupyter notebooks are used to visualize images transformed with our code, in addition to plotting experimental results. We also include the specific parameter files used to execute our experiments, with the intent that these experiments can be replicated.
Zelinski, michaelE.↗
Symmetry-Based Structured Matrices for Efficient Approximately Equivariant Networks
There has been much recent interest in designing symmetry-aware neural networks (NNs) exhibiting relaxed equivariance. Such NNs aim to interpolate between being exactly equivariant and being fully flexible, affording consistent performance benefits. In a separate line of work, certain structured parameter matrices -- those with displacement structure, characterized by low displacement rank (LDR) -- have been used to design small-footprint NNs. Displacement structure enables fast function and gradient evaluation, but permits accurate approximations via compression primarily to classical convolutional neural networks (CNNs). In this work, we propose a general framework -- based on a novel construction of symmetry-based structured matrices -- to build approximately equivariant NNs with significantly reduced parameter counts. Our framework integrates the two aforementioned lines of work via the use of so-called Group Matrices (GMs), a forgotten precursor to the modern notion of regular representations of finite groups. GMs allow the design of structured matrices -- resembling LDR matrices -- which generalize the linear operations of a classical CNN from cyclic groups to general finite groups and their homogeneous spaces. We show that GMs can be employed to extend all the elementary operations of CNNs to general discrete groups. Further, the theory of structured matrices based on GMs provides a generalization of LDR theory focussed on matrices with cyclic structure, providing a tool for implementing approximate equivariance for discrete groups. We test GM-based architectures on a variety of tasks in the presence of relaxed symmetry. We report that our framework consistently performs competitively compared to approximately equivariant NNs, and other structured matrix-based compression frameworks, sometimes with a one or two orders of magnitude lower parameter count.
Samudre, Ashwin↗
In-Space Networking On NASA's SCaN Testbed
The NASA Space Communications and Navigation (SCaN) Testbed, an external payload onboard the International Space Station, is equipped with three software defined radios (SDRs) and a programmable flight computer. The purpose of the Testbed is to conduct inspace research in the areas of communication, navigation, and networking in support of NASA missions and communication infrastructure. Multiple reprogrammable elements in the end to end system, along with several communication paths and a semi-operational environment, provides a unique opportunity to explore networking concepts and protocols envisioned for the future Solar System Internet (SSI). This paper will provide a general description of the system's design and the networking protocols implemented and characterized on the testbed, including Encapsulation, IP over CCSDS, and Delay-Tolerant Networking (DTN). Due to the research nature of the implementation, flexibility and robustness are considered in the design to enable expansion for future adaptive and cognitive techniques. Following a detailed design discussion, lessons learned and suggestions for future missions and communication infrastructure elements will be provided. Plans for the evolving research on SCaN Testbed as it moves towards a more adaptive, autonomous system will be discussed.
space networks↗
Interior Athabascan Energy Capacity Building Network (Final Report)
Tanana Chiefs Conference (TCC) is the traditional tribal consortium for the 37 federally recognized Tribes and villages of Interior Alaska. TCC is based on a belief in tribal self-determination and the need for regional Native unity. TCC is a nonprofit organization that works toward meeting the needs and challenges for more than 10,000 Alaska Natives (mostly Alaskan Athabaskans) in Interior Alaska. With support from DOE-OIE’s Inter-Tribal Technical Assistance grant, TCC’s goal was to expand and build on the solid foundation of work that the existing TCC Energy Program established through the creation of the Interior Athabascan Energy Network (IAEN). More specifically, the IAEN was designed to create a network of village-based energy champions across the interior and hold quarterly teleconferences and annual inperson meetings. Among the greatest impacts of the IAEN were the creation and support of realistic, communitybased energy projects that produced tangible results such as fuel savings and skills and capacity development among local staff as well as establishment of an energy team that included TCC staff, Tribal participants, technical consultants, and support agencies. The DOE-TA funding allowed us to provide technical assistance to our Tribal communities to develop energy projects, and to foster a network consisting of Tribal community members and energy experts that has strengthened the ability in the region to troubleshoot energy issues, develop meaningful projects, envision a clean energy future, and to share project successes and challenges. The funding from DOE was a catalyst for growth, has created opportunities for learning and knowledge sharing, and has led to the development of cost saving energy projects. Most importantly, the DOE project allowed energy champions around the region to share their knowledge, experiences, and expertise to create place-based solutions and has forged inter-Tribal relationships that will continue to be an asset for years to come. Through information exchange that occurred at out IAEN annual meetings and other events, this technical assistance grant award has spurred a spinoff project that is focused on establishing a collaborative of independent utilities that work together to solve energy problems and share services to operate and maintain their electric utilities. We have indentified at least 10 and possibly 12 communities that are interested in collaborating in managing their utilities to reduce costs and increase reliability. As well, by identifying and supporting Community Energy Champions in the Interior villages and adding capacity to the TCC Energy Program, we were able to create actionable community energy plans, develop specific projects, and increase local capacity, skills, and literacy around clean energy initiatives.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
3D polycatenated architected materials
Architected materials derive their properties from the geometric arrangement of their internal structural elements. Their designs rely on continuous networks of members to control the global mechanical behavior of the bulk. Here, in this study, we introduce a class of materials that consist of discrete concatenated rings or cage particles interlocked in three-dimensional networks, forming polycatenated architected materials (PAMs). We propose a general design framework that translates arbitrary crystalline networks into particle concatenations and geometries. In response to small external loads, PAMs behave like non-Newtonian fluids, showing both shear-thinning and shear-thickening responses, which can be controlled by their catenation topologies. At larger strains, PAMs behave like lattices and foams, with a nonlinear stress-strain relation. At microscale, we demonstrate that PAMs can change their shapes in response to applied electrostatic charges. The distinctive properties of PAMs pave the path for developing stimuli-responsive materials, energy-absorbing systems, and morphing architectures.
36 MATERIALS SCIENCE↗
Self-organization in neural networks - Applications in structural optimization
The present paper discusses the applicability of ART (Adaptive Resonance Theory) networks, and the Hopfield and Elastic networks, in problems of structural analysis and design. A characteristic of these network architectures is the ability to classify patterns presented as inputs into specific categories. The categories may themselves represent distinct procedural solution strategies. The paper shows how this property can be adapted in the structural analysis and design problem. A second application is the use of Hopfield and Elastic networks in optimization problems. Of particular interest are problems characterized by the presence of discrete and integer design variables. The parallel computing architecture that is typical of neural networks is shown to be effective in such problems. Results of preliminary implementations in structural design problems are also included in the paper.
Hajela, Prabhat↗
The GPS based precision orbit determination experiment on TOPEX
The objectives of the GPS-based precision orbit determination (POD) experiment on TOPEX are discussed. Problems facing this experiment include the careful design of all network receivers to control uncalibrated systematic group-delay biases and delay variations between channels, and the careful design of both the GPS-antenna-TOPEX satellite interface and the ground antennas to mimimize multipath. Questions of reference frames, geoid recovery, and the application of innovative orbit determination strategies must also be addressed.
Melbourne, William G.↗
Real-Time Dispatcher for a Distributed Energy Resource Power Plant to Provide Grid Services [SWR-25-17]
This software dispatches the aggregated power of a distributed energy resource (DER) plant located on an electrical distribution network. It is designed to provide the following services to the grid in real-time: (i) voltage support of the distribution network, (ii) virtual power plant at the substation with power factor support, and (iii) operating reserves for automatic generator control for the transmission system. This dispatcher integrates with the local power plant controller and utilizes the battery energy storage system (BESS) to smooth the volatile net power output from the DERs. It can also integrate with a day-ahead scheduler to strategically charge and discharge.
Comden, Joshua [National Renewable Energy Laborato↗
5G Zero Trust Architecture: A Testable and Phased Approach
With the emphasis being placed on Zero Trust Architecture in technology and by Executive Order (Executive Order on Improving the Nation’s Cybersecurity ), an investigation was performed as to the feasibility of implementing this approach into 5G. Reference documents include NIST Special Publication 800-207 and Department of Defense (DoD) Zero Trust Reference Architecture , and these provided guidance as to the overall approach. Progress is being made within 5G to address the lack of Zero Trust Architecture; a June 2021 DoD press release indicated that “The prototype 5G network is built on the next generation of Open Radio Network standards and designed to comply with DOD specifications for zero-trust architecture for native security and secure connectivity with other networks.”
5G↗
Resilience and economics of microgrids with PV, battery storage, and networked diesel generators
Current designs and assessments of microgrids have ignored component reliability, leading to significant errors in predicting a microgrid’s performance while islanded. Existing life cycle cost studies on hybrid microgrids—which combine photovoltaics (PV), battery storage and networked emergency diesel generators—also have not identified all the potential economic opportunities. Reducing the number of emergency diesel generators through reliance on PV and battery, retail bill savings, and demand response and wholesale market revenue streams are all important. This paper provides a new statistical methodology that calculates the impact of distributed energy reliability and variability on a microgrid’s performance and a novel use of the optimization platform REopt to explore multiple cost savings and revenue streams. We examine the impacts for microgrids in California, Maryland, and New Mexico and show that a hybrid microgrid is a more resilient and cost-effective solution than a diesel-only system. Under realistic conditions, a hybrid microgrid can provide higher system reliability when islanded and have a lower life cycle cost under multiple market conditions than a traditional diesel generator-based system. The improved performance of the hybrid system is resilient to conditions experienced over the last 20 years in solar irradiance and sees little degradation in performance immediately after a hurricane. The cost savings to provide this more resilient backup power system as compared to a diesel-only microgrid are significant. The net present cost for a hybrid microgrid is 19% lower in New Mexico and 35% lower in Maryland than a diesel-only microgrid. In California, the net present cost of the hybrid microgrid is negative because, unlike a diesel-only microgrid, a hybrid microgrid has lower life cycle costs than the power costs without a microgrid.
25 ENERGY STORAGE↗