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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Deep Space Network information system architecture study

The purpose of this article is to describe an architecture for the Deep Space Network (DSN) information system in the years 2000-2010 and to provide guidelines for its evolution during the 1990s. The study scope is defined to be from the front-end areas at the antennas to the end users (spacecraft teams, principal investigators, archival storage systems, and non-NASA partners). The architectural vision provides guidance for major DSN implementation efforts during the next decade. A strong motivation for the study is an expected dramatic improvement in information-systems technologies, such as the following: computer processing, automation technology (including knowledge-based systems), networking and data transport, software and hardware engineering, and human-interface technology. The proposed Ground Information System has the following major features: unified architecture from the front-end area to the end user; open-systems standards to achieve interoperability; DSN production of level 0 data; delivery of level 0 data from the Deep Space Communications Complex, if desired; dedicated telemetry processors for each receiver; security against unauthorized access and errors; and highly automated monitor and control.

Beswick, C. A.↗
NASA NTRS2008

Modeling Bird Migration in Changing Habitats: Space-based Ornithology using Satellites and GIS

Understanding bird migration and avian biodiversity is one of the most compelling and challenging problems of modern biology with major implications for human health and conservation biology. Migration and conservation efforts cross national boundaries and are subject to numerous international agreements and treaties presenting challenges in both geographic space and time. Space based technology, coupled with geographic information systems, yields new opportunities to shed light on the distribution and movement of organisms on the planet and their sensitivity to human disturbances and environmental changes. At NASA, we are creating ecological forecasting tools for science and application users to address the consequences of loss of wetlands, flooding, drought or other natural disasters such as hurricanes on avian biodiversity and bird migration. In our work, we use individual organism biophysical models and drive these models with satellite observations and numerical weather predictions of the spatio-temporal gradients in climate and habitat. Geographic information system technology comprises one component of our overall simulation framework, especially for characterizing the changing habitats and conditions encountered by en-route migratory birds. Simulation provides a tool for studying bird migration across multiple scales and can be linked to mechanistic processes describing the time and energy budget states of migrating birds. Such models yield an understanding of how a migratory flyway and its component habitats function as a whole and link stop-over ecology with biological conservation and management. We present examples of our simulation of shorebirds, principally, pectoral sandpipers, along the central flyways of the United States and Canada from the Gulf of Mexico to Alaska.

Smith, James A.↗
NASA NTRS2015

Real-Time On-Board Airborne Demonstration of High-Speed On-Board Data Processing for Science Instruments (HOPS)

The project called High-Speed On-Board Data Processing for Science Instruments (HOPS) has been funded by NASA Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) program since April, 2012. The HOPS team recently completed two flight campaigns during the summer of 2014 on two different aircrafts with two different science instruments. The first flight campaign was in July, 2014 based at NASA Langley Research Center (LaRC) in Hampton, VA on the NASA's HU-25 aircraft. The science instrument that flew with HOPS was Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) CarbonHawk Experiment Simulator (ACES) funded by NASA's Instrument Incubator Program (IIP). The second campaign was in August, 2014 based at NASA Armstrong Flight Research Center (AFRC) in Palmdale, CA on the NASA's DC-8 aircraft. HOPS flew with the Multifunctional Fiber Laser Lidar (MFLL) instrument developed by Excelis Inc. The goal of the campaigns was to perform an end-to-end demonstration of the capabilities of the HOPS prototype system (HOPS COTS) while running the most computationally intensive part of the ASCENDS algorithm real-time on-board. The comparison of the two flight campaigns and the results of the functionality tests of the HOPS COTS are presented in this paper.

Beyon, Jeffrey Y.↗
NASA NTRS2015

High-Speed On-Board Data Processing for Science Instruments: HOPS

The project called High-Speed On-Board Data Processing for Science Instruments (HOPS) has been funded by NASA Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST) program during April, 2012 â€" April, 2015. HOPS is an enabler for science missions with extremely high data processing rates. In this three-year effort of HOPS, Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) and 3-D Winds were of interest in particular. As for ASCENDS, HOPS replaces time domain data processing with frequency domain processing while making the real-time on-board data processing possible. As for 3-D Winds, HOPS offers real-time high-resolution wind profiling with 4,096-point fast Fourier transform (FFT). HOPS is adaptable with quick turn-around time. Since HOPS offers reusable user-friendly computational elements, its FPGA IP Core can be modified for a shorter development period if the algorithm changes. The FPGA and memory bandwidth of HOPS is 20 GB/sec while the typical maximum processor-to-SDRAM bandwidth of the commercial radiation tolerant high-end processors is about 130-150 MB/sec. The inter-board communication bandwidth of HOPS is 4 GB/sec while the effective processor-to-cPCI bandwidth of commercial radiation tolerant high-end boards is about 50-75 MB/sec. Also, HOPS offers VHDL cores for the easy and efficient implementation of ASCENDS and 3-D Winds, and other similar algorithms. A general overview of the 3-year development of HOPS is the goal of this presentation.

Beyon, Jeffrey↗
NASA NTRS2017

NeMO-Net: The Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 percent error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets. We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

NeMO-Net↗
NASA NTRS2017

NeMO-Net The Neural Multi-Modal Observation Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets.We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

Remote Sensin↗
NASA NTRS2015

An Overview of Technology Investments in the NASA Entry Systems Modeling Project

ESM was created with two primary technical areas: Aerosciences and Materials. One of the first project deliverables, in both technology areas, was the development of Key Performance Parameters (KPPs), which are used to gauge the rate of progress in technology maturation, and to inform eventual technology downselects. In addition, the project was tasked to identify stakeholders or customers for proposed technology investments. While pull technologies are permitted within STMD, those capabilities that have strong customer support and a clear infusion plan are given higher priority. The current investment portfolio and achievements will be summarized in this paper.

Wright, Michael J.↗
NASA NTRS2023

Space Trusted Autonomy Readiness Levels

Technology Readiness Levels are a mainstay for organizations that fund, develop, test, acquire, or use technologies. Technology Readiness Levels provide a standardized assessment of a technology’s maturity and enable consistent comparison among technologies. They inform decisions throughout a technology’s development life cycle, from concept, through development, to use. A variety of alternative Readiness Levels have been developed, including Algorithm Readiness Levels, manufacturing Readiness Levels, Human Readiness Levels, Commercialization Readiness Levels, Machine Learning Readiness Levels, and Technology Commitment Levels. However, while Technology Readiness Levels have been increasingly applied to emerging disciplines, there are unique challenges to assessing the rapidly developing capabilities of autonomy. This paper adopts the moniker of Space Trusted Autonomy Readiness Levels to identify a two-dimensional scale of readiness and trust appropriate for the special challenges of assessing autonomy technologies that seek space use. It draws inspiration from other readiness levels’ definitions, and from the rich field of trust and trustworthiness. The Space Trusted Autonomy Readiness Levels were developed by a collaborative Space Trusted Autonomy subgroup, which was created from The Space Science and Technology Partnership Forum between the United States Space Force, the National Aeronautics and Space Administration, and the National Reconnaissance Office.

Kerianne L Hobbs↗
NASA NTRS1992

NASA technology transfer network communications and information system: TUNS user survey

Applied Expertise surveyed the users of the deployed Technology Utilization Network System (TUNS) and surveyed prospective new users in order to gather background information for developing the Concept Document of the system that will upgrade and replace TUNS. Survey participants broadly agree that automated mechanisms for acquiring, managing, and disseminating new technology and spinoff benefits information can and should play an important role in meeting NASA technology utilization goals. However, TUNS does not meet this need for most users. The survey describes a number of systematic improvements that will make it easier to use the technology transfer mechanism, and thus expedite the collection and dissemination of technology information. The survey identified 26 suggestions for enhancing the technology transfer system and related processes.

Source record↗
DOE OSTI2021

Scalable Technologies Achieving Risk-Informed Condition-Based Predictive Maintenance Enhancing the Economic Performance of Operating Nuclear Power Plants

The primary objective of the research presented in this report is to develop scalable technologies that are deployable across plant assets and across the nuclear fleet to achieve risk-informed predictive maintenance (PdM) strategies at commercial nuclear power plants (NPPs). Over the years, the nuclear fleet has relied on labor-intensive and time-consuming preventive maintenance (PM) programs, driving up operation and maintenance (O&M) costs to achieve high capacity factors. A well-constructed risk-informed PdM approach for an identified plant asset has been developed in this research, taking advantage of advancements in data analytics, machine learning (ML), artificial intelligence (AI), physics-informed modeling, and visualization. These technologies would allow commercial NPPs to reliably transition from current labor-intensive PM programs to a technology driven PdM program, eliminating unnecessary O&M costs. The work presented in the report is being developed as part of a collaborative research effort between Idaho National Laboratory and Public Service Enterprise Group Nuclear, LLC. This report (1) reflects the results of work by LWRS Program researchers with PSEG, Nuclear LLC-owned Salem and Hope Creek Nuclear Power Plants; (2) presents utilization of circulating water system (CWS) heterogeneous data and fault modes from both the Salem and Hope Creek nuclear power plant sites to develop salient fault signatures associated with each fault mode; (3) describes the integration of component-level predictive models into a robust system-level model enabled by the federated-transfer learning; (4) describes the development of physics-informed model of circulating water pump and motor; (5) develops a scalable risk and economic model; and (6) outlines the development of a user-centric visualization application. The outcomes presented in this report lays the foundation and provides a much-needed technical basis to focus on explainability and trustworthiness of ML and AI-based technologies, as part of future research.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

Advanced Instrumentation, Information, and Control Systems Technologies Pathway: FY 2016 External Review

This report describes an External Review conducted by the LWRS Program Advanced Instrumentation, Information, and Control (II&C) Systems Technologies Pathway to solicit feedback on the topics and results of the ongoing II&C research program. This review was held in conjunction with the Nuclear Energy Institute (NEI) Digital I&C Working Group meeting that was held at Idaho National Laboratory (INL) on August 9-10, 2016. Given the opportunity to visit INL and see the pathway research projects, NEI agreed that the Working Group would serve as the External Review panel for the purpose of obtaining expert input on the value and timing of the research projects. This consisted of demonstrations in the Human Systems Simulation Laboratory followed by presentations on the II&C research program in general as well as the five technology development areas. Following the meeting, the presentations were sent to each of the attendees so they could review them in more detail and refer to them in completing the feedback form. Follow-up activities were conducted with the attendees following the meeting to obtain the completed feedback forms. A total of 13 forms were returned. The feedback forms were reviewed by the pathway to compile the data and comments received, which are documented in the report. In all, the feedback provided by the External Review participants is taken to be a strong endorsement of the types of projects being conducted by the pathway, the value they hold for the nuclear plants, and the general timing of need. The feedback aligns well with the priorities, levels of efforts allocated for the research projects, and project schedules. The feedback also represents realistic observations on the practicality of some aspects of implementing these technologies. In some cases, the participants provided thoughtful challenges to certain assumptions in the formulation of the technologies or in deployment plans. These deserve further review and revision of plans if warranted. The pathway will take all of the feedback and address the open issues that have been identified by the participants. This includes 11 actionable items for follow up by the II&C Pathway.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Leveraging Pre-Built Catalogs and Object-Level Scheduling to Eliminate I/O Bottlenecks in HPC Environments

Modern High-Performance Computing (HPC) environments face mounting challenges due to the shift from large to small file datasets, along with an increasing number of users and parallelized applications. As HPC systems rely on Parallel File Systems (PFS), such as Lustre for data processing, performance bottlenecks stemming from Object Storage Target (OST) contention have become a significant concern. Existing solutions, such as LADS with its object-level scheduling approach, fall short in large-scale HPC environments due to their inability to effectively address metadata I/O bottlenecks and the growing number of I/O processes. This study highlights the pressing need for a comprehensive solution that tackles both OST contention and metadata I/O challenges in diverse HPC workloads. To address these challenges, we propose SwiftLoad, an object-level I/O scheduling framework that leverages a metadata catalog to enhance the performance and efficiency of parallel HPC utilities. The adoption of the metadata catalog mitigates the metadata I/O bottlenecks that commonly occur in HPC utilities, a challenge that is particularly pronounced in object-level I/O scheduling. SwiftLoad addresses OST contention and the uneven distribution of I/O processes across different OSTs through mathematical modeling and incorporates a Loader Configuration Module to regulate the number of I/O processes. Evaluated with two representative utilities—data deduplication profiling and data augmentation—SwiftLoad achieved performance improvements of up to 5.63x and 11.0x, respectively, on a production supercomputer.

HPC↗
DOE OSTI2025

Obstacles to Practical Digital Supply Chain Risk Management in the Energy Sector

Cyber supply chain risk management (C-SCRM) programs must consider operations that depend on the lifecycles of digital components such as hardware, firmware, software, and services. We integrate academic literature, historical incidents, and existing standards to identify obstacles faced by C-SCRM programs.

Business Process Management & Integration↗
NASA NTRS2021

NASA Strategy for Technology Development

The National Aeronautics and Space Administration (NASA) Office of the Chief Technologist (OCT) provides the strategy and leadership that integrates NASA’s technology development and open innovation activities to advance American aeronautic, science, and space exploration objectives. OCT performs an agency-level technology coordination role, coordinating with the NASA Mission Directorates, field centers, and other government agencies to align the agency’s technology investments to meet mission requirements while filling gaps, anticipating future needs, and minimizing duplication of effort. OCT provides the strategy and coordination that guide NASA's technology and innovation activities through Strategic Technology Integration, Digital Transformation, the Science and Technology Partnership Forum, and Innovation. The Strategic Technology Integration team informs policy, requirements, and strategy for NASA’s technology development activities in support of the Chief Technologist by coordinating with NASA mission directorates, other government agencies, and external organizations. As part of these efforts, OCT develops the NASA Technology Taxonomy and the NASA Strategic Space Technology Investment Plan. Digital Transformation will increasingly change the way NASA operates and will enable the agency’s missions to be completed more efficiently and effectively. It will allow current and future employees to use their talents in more innovative ways. The Science and Technology Partnership Forum is a strategic forum, with principal partners at the United States Space Force and the National Reconnaissance Office. It was established to identify synergistic efforts and technologies in order to leverage those synergies and influence portfolios across space agencies in areas deemed pervasive and ready for collaboration. NASA's Innovation efforts are designed to transform diverse ideas into value and are guided by a framework that is focused on the agency’s people, processes, partnerships and portfolio. The innovation framework is used to connect the workforce to tools, strategies and activities to increase the pace of innovation. OCT translates National space policies into NASA technology strategies and coordination across the agency and interagency communities to guide NASA's technology and innovation activities to achieve capabilities needed for future missions. This chapter provides insight into the value of analyzing future states to inform technology developments to plot the strategic direction of NASA’s space technology program.

Erica Rodgers↗
DOE OSTI2017

Light Water Reactor Sustainability Program Advanced Instrumentation, Information, and Control Systems Technologies Technical Program Plan for FY 2018

This report presents the Technical Program Plan for FY 2018 for the Department of Energy Light Water Reactor Sustainability Program – Advanced Instrumentation, Information, and Control (II&C) Systems Technologies research pathway. A summary of the vision and strategy is provided to explain how this program addresses key issues and barriers for implementing digital instrumentation and control technologies in domestic nuclear power plants. The report describes 20 pilot projects that have been formulated to develop and validate enabling technologies over a 16 year period that will result in digital alternatives to the legacy analog II&C systems in place today. This will allow much needed modernization of these systems to address reliability and obsolescence problems, as well as serve as a platform for substantial operational improvement. The report further describes key project resources and cooperative relationships, including the Electric Power Research Institute, the Nuclear Energy Institute (NEI), the Institute of Nuclear Power Operations (INPO)the Nuclear Energy Institute )NEI), the Institute of Nuclear Power Operations (INPO), the IFE Halden Reactor Project, the Nuclear Regulatory Commission, and industry suppliers, that are instrumental to the success of the program. The report also lists the schedule for all program products, including the titles and report numbers for all published reports under this program.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1993

Multiple degree-of-freedom force and moment measurement for static propulsion testing using magnetic suspension technology

Innovative Information Systems (IIS), Inc. is in the process of designing and fabricating a high bandwidth force and moment measuring device (i.e. the Magnetic Thruster Test Stand). This device will use active magnetic suspension to allow direct measurements of the forces and torques generated by the rocket engines of the missile under test. The principle of operation of the Magnetic Thruster Test Stand (MTTS) is based on the ability to perform very precise, high bandwidth force and position measurements on an object suspended in a magnetic field. This ability exists due to the fact that the digital servo control mechanism that performs the magnetic suspension uses high bandwidth (10 kHz) position data (via an eddy-current proximity sensor) to determine the amount of force required to maintain stable suspension at a particular point. This force is converted into required electromagnet coil current, which is then output to a current amplifier driving the coils. A discussion of how the coil current and magnetic gap distance (the distance between the electromagnet and the object being suspended) is used to determine the forces being applied from the suspended assembly is presented.

Stuart, Keith↗