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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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Digital system can accommodate sixteen or more telephone or data units and eight, simultaneous two-way conversations through only four interconnecting wires. It uses fewer circuit components, is not bulky or complex, and requires no central exchange control.
An approach to the fault analysis of digital systems is proposed which combines faults, hardware, and software into one overall model. The model is useful for the consideration of intermittent/transient faults, and supports a new method, based on the concept of a containment set, for realizing transient fault tolerance without massive redundancy. The model also serves as the basis for a new approach to system fault tolerance evaluation and validation using a transition matrix defined in terms of the containment set. The application of upset theory to the design of transient fault-tolerant microprocessor controllers is discussed.
Hardware description languages are valuable tools in such applications as hardware design, system documentation, and logic design training. DDL is convenient medium for inputting design details into hardware-design automation system. It is suitable for describing digital systems at gate, register transfer, and major combinational block level.
Computer-aided optimization using Monte Carlo techniques for digital systems timing
For NASA's Advanced Information Systems Technology (AIST) Program, an Earth System Digital Twin (ESDT) is defined as an interactive and integrated multidomain, multiscale, digital replica of the state and temporal evolution of Earth systems. It dynamically integrates: relevant Earth system models and simulations; other relevant models (e.g., related to the world's infrastructure); continuous and timely (including near real time and direct readout) observations (e.g., space, air, ground, over/underwater, Internet of Things (IoT), socioeconomic); long-time records; as well as analytics and artificial intelligence tools. Effective ESDTs enable users to run hypothetical scenarios to improve the understanding, prediction of and mitigation/response to Earth system processes, natural phenomena and human activities as well as their many interactions. An ESDT is a type of integrated information system that, for example, enables continuous assessment of impact from naturally occurring and/or human activities on physical and natural environments. AIST ESDT strategic goals are to: 1. Develop information system frameworks to provide continuous and accurate representations of systems as they change over time; 2. Mirror various Earth Science systems and utilize the combination of Data Analytics, Artificial Intelligence, Digital Thread, and state-of-the-art models to help predict the Earth’s response to various phenomena; 3. Provide the tools to conduct "what if" investigations that can result in actionable predictions. The AIST ESDT thrust is developing capabilities toward the development of future digital twins of the Earth or of subcomponents of the Earth. This will enable the development of an overarching framework that will integrate New Observing Strategies (NOS) to enable new observation measurements, i.e., multi-source, coordinated, dynamic and responsive to needs and requests defined by Analytic Collaborative Frameworks (ACF) that enable agile science investigations fusing and analyzing very large amounts of diverse data. NOS and ACF capabilities along with open access to various science, infrastructure and human data, interconnected modeling, data assimilation, simulations, surrogate modeling, high-performance computing and advanced visualization, will define a powerful framework that could be utilized for local, regional or global and/or thematic digital twins. This presentation will describe a general overview of the AIST ESDT vision including prior work done in the areas of NOS and ACF as well as current and upcoming ESDT projects.
Parse-implement approach to digital systems design, combining systems level /conceptual/ and engineering environmental level /physical/ viewpoints
On June 23, 2023, the Advanced Information Systems Technology (AIST) program conducted grouped annual reviews of all its Earth System Digital Twins (ESDT) projects. This report regroups all these technical presentations.
Digital system for accurate time sector division of spin stabilized vehicle as used on Pioneer space probes
"The Earth Science Information Partners (ESIP) is hosting an Earth System Digital Twins (ESDT) workshop in collaboration with NASA’s Advanced Information Systems Technology (AIST) Program. The event will bring together science and technology communities to explore the use and benefits of ESDT and their enabling technologies. This workshop is one of the first steps in developing ESDT reference use cases and corresponding technology needs to guide the development of ESDT technologies that will be needed by NASA Earth Science within the next five to ten years. The workshop goals are to: • identify driving Earth science use cases that will benefit from unique ESDT capabilities • identify emerging technologies that will enable such ESDT systems within the next five to ten years • understand opportunities and technologies for federating ESDTs and creating more capable systems"
The use of digital transmission with narrow light pulses appears attractive for data communications, but carries with it a stringent requirement on system bit timing. The effects of imperfect timing in direct-detection (noncoherent) optical binary systems are investigated using both pulse-position modulation and on-off keying for bit transmission. Particular emphasis is placed on specification of timing accuracy and an examination of system degradation when this accuracy is not attained. Bit error probabilities are shown as a function of timing errors from which average error probabilities can be computed for specific synchronization methods. Of significance is the presence of a residual or irreducible error probability in both systems, due entirely to the timing system, which cannot be overcome by the data channel.
Coherent digital communication systems optimal design based on unified theory, discussing tradeoffs between error rates, Doppler tracking capability and time and frequency division multiplexing
Design and reliability of digital systems for hard cores of fault tolerant computers /hybrid- redundant systems/, discussing advantages over multiplexed systems
Mass spectrometer-spectrum digitizer system for rapid gas analysis
Methods of modeling the detection time or latency period of a hardware fault in a digital system are proposed that explain how a computer detects faults in a computational mode. The objectives were to study how software reacts to a fault, to account for as many variables as possible affecting detection and to forecast a given program's detecting ability prior to computation. A series of experiments were conducted on a small emulated microprocessor with fault injection capability. Results indicate that the detecting capability of a program largely depends on the instruction subset used during computation and the frequency of its use and has little direct dependence on such variables as fault mode, number set, degree of branching and program length. A model is discussed which employs an analog with balls in an urn to explain the rate of which subsequent repetitions of an instruction or instruction set detect a given fault.
IEEE SIgnal Processing Society (SPS) and Women in Signal Processing (WiSP) Webinar (https://signalprocessingsociety.org/blog/webinar-wisp-blood-platelets-classification-earth-system-digital-twins-career-computer-vision): Join us for an interactive session with Dr. Jacqueline Le Moigne, Manager of the NASA Science Mission Directorate Earth Science Technology Office’s Advanced Information Systems Technology Program. In this webinar, Dr. Le Moigne will share her journey through academia, the private sector, and her pivotal roles at NASA, emphasizing her work in signal processing, computer vision, and related technologies. The webinar will conclude with an interactive Q&A session, providing attendees the opportunity to engage directly with Dr. Le Moigne about her experiences and insights. Dr. Jacqueline Le Moigne manages NASA's Advanced Information Systems Technology Program, focusing on novel technologies that support Earth Science missions. She previously held roles at NASA Goddard, including Assistant Chief for Technology, and has worked on NASA's Space Technology Research Grants Program and Technology Roadmaps. Before NASA, she was a Research Scientist at the University of Maryland's Computer Vision Laboratory and also gained experience in the private sector. Jacqueline earned her Ph.D. in Computer Science from the University Pierre and Marie Curie in Paris. Her research interests include Image Registration, Computer Vision, Artificial Intelligence, Autonomous Systems, Distributed Spacecraft Missions (DSM), and Earth System Digital Twins (ESDT), as well as high-performance and onboard computing. She has authored over 180 publications, including books and patents, and has received multiple awards, including the NASA Exceptional Service Medal and the Goddard Information Science and Technology Award in 2012.
The term “Digital Twin” was first used in 2002 for product lifecycle management. Since then, Digital Twin concepts have been proposed in various domains until very recently for Earth Science. For NASA’s Advanced Information Systems Technology (AIST) Program, an Earth System Digital Twin (ESDT) is defined as composed of three components: 1. A Digital Replica, i.e., an integrated picture of the past and current states of Earth systems 2. Forecasting capabilities, providing an integrated picture of how Earth systems will evolve in the future from the current state 3. Impact Assessment capabilities, providing an integrated picture of how Earth systems could evolve under different hypothetical what-if scenarios. Developing such a vision will require technologies related to: integrating continuous observations from various disparate sources; developing frameworks that builds on inter-connected models; improving the speed and accuracy of integrated prediction, analysis and visualization capabilities (e.g., by using machine learning); and utilizing causality and uncertainty quantification to improve our understanding of the evolution of Earth Science systems as a function of their interactions with other Earth and human systems. In addition, AIST is also investigating interoperability standards to federate multiple Digital Twins, as well as computational resources required by those systems.
Design and testing of majority logic redundancy for spaceborne and GSE digital systems
Diagnosability and recovery from massive faults in digital systems