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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Advanced concepts for telemetry data systems

The Consultative Committee for Space Data Standards (CCSDS) has defined Advanced Orbiting System (AOS) standards for the overall architectural framework of future packet telemetry systems. The standards encompass a CCSDS principal network covering the onboard space-link and ground systems, and furnishes an asynchronous (telemetry/internetworking) and isochronous (audio and video) data-transport services employing CCSDS packets and virtual channels. Attention is given to changes envisioned in ground telemetry processing systems currently in use, as well as to the application of CCSDS standards to future systems.

Pritchard, James A.↗
NASA NTRS1993

Space Station technology testbed: 2010 deep space transport

A space station in a crew-tended or permanently crewed configuration will provide major R&D opportunities for innovative, technology and materials development and advanced space systems testing. A space station should be designed with the basic infrastructure elements required to grow into a major systems technology testbed. This space-based technology testbed can and should be used to support the development of technologies required to expand our utilization of near-Earth space, the Moon and the Earth-to-Jupiter region of the Solar System. Space station support of advanced technology and materials development will result in new techniques for high priority scientific research and the knowledge and R&D base needed for the development of major, new commercial product thrusts. To illustrate the technology testbed potential of a space station and to point the way to a bold, innovative approach to advanced space systems' development, a hypothetical deep space transport development and test plan is described. Key deep space transport R&D activities are described would lead to the readiness certification of an advanced, reusable interplanetary transport capable of supporting eight crewmembers or more. With the support of a focused and highly motivated, multi-agency ground R&D program, a deep space transport of this type could be assembled and tested by 2010. Key R&D activities on a space station would include: (1) experimental research investigating the microgravity assisted, restructuring of micro-engineered, materials (to develop and verify the in-space and in-situ 'tuning' of materials for use in debris and radiation shielding and other protective systems), (2) exposure of microengineered materials to the space environment for passive and operational performance tests (to develop in-situ maintenance and repair techniques and to support the development, enhancement, and implementation of protective systems, data and bio-processing systems, and virtual reality and telepresence/kinetic processes), (3) subsystem tests of advanced nuclear power, nuclear propulsion and communication systems (using boom extensions, remote station-keeping platforms and mobile EVA crew and robots), and (4) logistics support (crew and equipment) and command and control of deep space transport assembly, maintenance, and refueling (using a station-keeping platform).

Holt, Alan C.↗
NASA NTRS1994

A heterogeneous computing environment for simulating astrophysical fluid flows

In the Concurrent Computing Laboratory in the Department of Physics and Astronomy at Louisiana State University we have constructed a heterogeneous computing environment that permits us to routinely simulate complicated three-dimensional fluid flows and to readily visualize the results of each simulation via three-dimensional animation sequences. An 8192-node MasPar MP-1 computer with 0.5 GBytes of RAM provides 250 MFlops of execution speed for our fluid flow simulations. Utilizing the parallel virtual machine (PVM) language, at periodic intervals data is automatically transferred from the MP-1 to a cluster of workstations where individual three-dimensional images are rendered for inclusion in a single animation sequence. Work is underway to replace executions on the MP-1 with simulations performed on the 512-node CM-5 at NCSA and to simultaneously gain access to more potent volume rendering workstations.

Cazes, J.↗
NASA NTRS1995

Infrared/Ultrasonic Position-Measuring System

System for measuring positions of sensors at designated points on body suit developed. Measuring system, body suit, and sensors incorporated into interactive virtual-reality system, wherein they provide feedback data on positions and orientations of various parts of wearer's body. Based on straightforward concept of computating three-dimensional coordinates of sensor from simultaneous measurements of distances of sensor from three locations, coordinates of which known.

Roberson, Ricky J.↗
NASA NTRS1998

How Human Factors Drove the Design and Implementation of the Virtual Windtunnel

This viewgraph presentation describes decisions made at the NASA Ames Research Center during its development of a virtual windtunnel to assist humans in visualizing computational fluid dynamics simulations. User requirements for the system include the simulation of vortical structure, pressure distribution, and overall sense of flow. In addition, the system needs to support a variety of interfaces, excluding head mounts, and needs to use an object oriented approach. Direct manipulation of the system is most user-friendly when limited to only grab and point gestures. 'Visualization control tools' (vtools) improve the realism of the system. The necessary object oriented programming is in C++ and openGL. Users interact with objects called 'tools', which include vtools and tools which control the virtual wind tunnel environment. Other objects include data objects accessed by the visualizations. Visualizations can be added to the system by the user. The presentation includes a discussion of run-time architecture, and issues related to computation and implementation.

Bryson, Steve↗
NASA NTRS2014

Simulating Wake Vortex Detection with the Sensivu Doppler Wind Lidar Simulator

In support of NASA's Atmospheric Environment Safety Technologies NRA research topic on Wake Vortex Hazard Investigation, Aerospace Innovations (AI) investigated a set of techniques for detecting wake vortex hazards from arbitrary viewing angles, including axial perspectives. This technical report describes an approach to this problem and presents results from its implementation in a virtual lidar simulator developed at AI. Threedimensional data volumes from NASA's Terminal Area Simulation System (TASS) containing strong turbulent vortices were used as the atmospheric domain for these studies, in addition to an analytical vortex model in 3-D space. By incorporating a third-party radiative transfer code (BACKSCAT 4), user-defined aerosol layers can be incorporated into atmospheric models, simulating attenuation and backscatter in different environmental conditions and altitudes. A hazard detection algorithm is described that uses a twocomponent spectral model to identify vortex signatures observable from arbitrary angles.

Ramsey, Dan↗
NASA NTRS2018

Evolving Storage and Cyber Infrastructure at the NASA Center for Climate Simulation

This talk will describe recent developments at the NASA Center for Climate Simulation, which is funded by NASAs Science Mission Directorate, and supports the specialized data storage and computational needs of weather, ocean, and climate researchers, as well as astrophysicists, heliophysicists, and planetary scientists. To meet requirements for higher-resolution, higher-fidelity simulations, the NCCS augments its High Performance Computing (HPC) and storage retrieval environment. As the petabytes of model and observational data grow, the NCCS is broadening data services offerings and deploying and expanding virtualization resources for high performance analytics.

Cyberinfrastructure↗
NASA NTRSDate not supplied

Notional Habitat Science Outfitting for a Lunar Surface Habitat or Mars Transit Habitat

Science outfitting is often given insufficient treatment in the development of early conceptual studies for lunar surface habitats. In some cases, only control masses and volumes are used as placeholders. In others, one science discipline may be given detailed treatment while others are largely ignored. It is not unheard of for science outfitting to be entirely forgotten in initial concept layouts. This is exacerbated by the reality that spacecraft design studies are often initiated long before science objectives have been established for any given human spaceflight destination. When those objectives later emerge, they can be difficult to accommodate if sizing studies did not allocate sufficient resources for them. A notional science outfitting can be created for virtually any human exploration habitat, however, utilizing data created by the International Space Station and Constellation programs. Biology, human research, physics, and geology science laboratories and a general-purpose work area for a lunar surface habitat will be derived using equipment identified by the Constellation-era Optimizing Science and Exploration Working Group (OSEWG) or flown on the International Space Station. Early science outfitting definition and inclusion in surface habitat sizing is critical for developing an exploration architecture that meets science needs. The mass, volume, power, and use cases associated with these notional laboratories impacts all of the habitat subsystems, habitat dimensions, hatch dimensions, logistics operations, launch vehicles and landers.

Lunar Habitat↗
DOE OSTI2023

Simulating the metabolic pathway dynamics of an organism

Disclosed herein are systems and methods for determining metabolic pathway dynamics using time series multiomics data. In one example, after receiving time series multiomics data comprising time-series metabolomics data associated a metabolic pathway and time-series proteomics data associated with the metabolic pathway, derivatives of the time series multiomics data can be determined. A machine learning model, representing a metabolic pathway dynamics model, can be trained using the time series multiomics data and the derivatives of the time series multiomics data, wherein the metabolic pathway dynamics model relates the time-series metabolomics data and time-series proteomics data to the derivatives of the time series multiomics data. The method can include simulating a virtual strain of the organism using the metabolic pathway dynamics model.

Costello, Zachary↗
DOE OSTI2023

Automated platform to assess commercial off the shelf (COTS) software assurance

A computer-implemented method of verifying software is provided. The method comprises creating a number of virtual machines that simulate computing environments and running a number of software program on the virtual machines. The software programs have full access to the simulated computing environments, but the source code of the software program is unavailable. A hypervisor performs virtual machine introspection as the software programs run on the virtual machines, wherein the virtual machines and software programs are unaware the virtual machine introspection is being performed. Telemetry data is collected about the software programs, including any identified threats posed by the software programs to the simulated computing environments, and presented to a user via an interface.

Urias, Vincent↗
DOE OSTI2025

Enhancing Security and Resiliency in Operational Technology Environments Through Network Slicing and Federated Learning

The growing convergence of Information Technology (IT) and Operational Technology (OT) within Industry 4.0 environments has introduced new demands on industrial network infrastructure. As cyber-physical systems become increasingly interconnected, ensuring the secure, timely, and efficient exchange of critical data is essential. This thesis explores how network slicing, a method of creating isolated virtual network segments, can be applied within OT environments to address challenges such as latency, security, and resource allocation. The first research question addressed in this thesis is: How can OT networks take advantage of NFV and SDN technology to become cyber resilient? This study examines the operational, security, and architectural implications of introducing network slicing into traditionally static OT infrastructures such as Industrial Control Systems (ICS) and SCADA. Through simulated deployments and case studies, the research demonstrates how slicing enables better isolation between critical and non-critical services, thereby improving response time, throughput, and security in sensitive environments. The second question considers: How to dynamically implement network slicing and take advantage of network resources towards integrating decentralized machine learning? In response, this thesis proposes a framework that combines Software-Defined Networking (SDN), Network Function Virtualization (NFV), and Federated Learning (FL) to enable real-time analytics while maintaining data locality. The proposed approach reduces the burden on centralized infrastructure and minimizes privacy risks by supporting on-site training of models across distributed OT nodes, coordinated through dynamically allocated network slices. The third focus explores: How slicing helps to increase the resiliency of OT networks through the orchestration of a dynamic DMZ? To answer this, the thesis presents a method for creating and managing Dynamic Demilitarized Zones (DMZs) using network slicing. This enables flexible and automated isolation of sensitive subsystems during threat scenarios or high-risk operations. Coupled with intelligent orchestration and containerized security services, the dynamic DMZ significantly enhances the system's ability to respond to cyber incidents without halting production. Ultimately, this thesis contributes a comprehensive architecture that blends network slicing with machine learning, secure segmentation, and automation, paving the way for resilient, adaptive, and intelligent OT environments. Performance evaluations across multiple scenarios show improvements in system reliability, threat response time, model accuracy, and resource utilization, providing a strong foundation for future industrial automation systems.

Rodiles Delgado, Brian G↗
DOE OSTI2024

Photovoltaic Analysis and Response Support (PARS) Platform for Solar Situational Awareness and Resiliency Services

The project's primary objective is to develop a digital-twin based Photovoltaic (PV) Analysis and Response Support (PARS) platform, which aims to provide real-time situational awareness and optimal response plans. This platform is designed to enhance the performance of hybrid PV systems, making them competitive with or even superior to conventional generation resources. The PARS platform enabled the project team to develop and evaluate an extensive suite of grid support functionalities for the hybrid PV systems to enhance grid performance, across key areas including visibility, dispatchability, security, resilience, and reliability. Given the global push toward achieving 100% clean energy by 2035, there is a significant increase in the integration of inverter-based resources (IBRs) throughout the energy grid. Effectively managing the inherent variability and uncertainty associated with IBRs is crucial for ensuring cost-effectiveness, reliability, and security in both the main grid and islanded microgrids. Constrained to a limited array of IEEE test systems or standard feeder models, traditional IBR modeling struggles to assimilate new field data, accurately reflect system dynamics, and adapt to the evolving energy landscape. In our project, we embraced a Digital Twin (DT) strategy for crafting the PARS platform. A digital twin acts as a precise virtual counterpart of a physical system, built on historical data and continuously honed with real-time insights. This enables the high-fidelity DT to accurately mirror current system operations and forecast future scenarios. Consequently, the PARS platform becomes an ideal environment for testing and refining monitoring, control, power, and energy management algorithms designed to boost hybrid PV system performance. The defining feature of the PARS platform, distinguishing it from other advanced simulation tools, is its exceptional adaptability. This is achieved by employing actual network topologies and utilizing real-time field data for fine-tuning and calibration, ensuring a close emulation of real-world conditions. The project deliverables include: 1) High-fidelity IBR models and tools for real-time parameterization, utilizing real-time field measurements to refine IBR models for enhanced accuracy and performance; 2) Grid-forming and Grid-following capabilities to deliver resilience services, including blackstart, voltage and frequency support, cold-load pick-up, power reserves, and three-phase load balancing across grid-connected and microgrid settings; 3) Machine learning-based forecasting tools and methods for generating synthetic data and topologies, creating diverse and realistic simulation environments for evaluating varied operational scenarios; 4) Advanced microgrid power and energy management algorithms for optimizing the integration and operation of PV, storage, and demand response resources within both feeder and community scales. The power grid data sets are provided by four utility companies in North Carolina and the New York Power Administration. Acting as industry advisors, our industry partners communicated stakeholder needs and regulatory standards to the research teams, aiding technology transfer by incorporating the developed methodologies into their daily operations. This collaboration ensures that the PARS platform, functioning as a power system digital twin, enhances our understanding of IBR dynamic behaviors and enables the development and evaluation of IBR control functions that match or exceed the capabilities of conventional synchronous generators.

14 SOLAR ENERGY↗
NASA NTRS2018

Live Aircraft Encounter Visualization at FutureFlight Central

Researchers at the National Aeronautics and Space Administration (NASA) have developed an aircraft data streaming capability that can be used to visualize live aircraft in near real-time. During a joint Federal Aviation Administration (FAA)/NASA Airborne Collision Avoidance System flight series, test sorties between unmanned aircraft and manned intruder aircraft were shown in real-time at NASA Ames' FutureFlight Central tower facility as a virtual representation of the encounter. This capability leveraged existing live surveillance, video, and audio data streams distributed through a Live, Virtual, Constructive test environment, then depicted the encounter from the point of view of any aircraft in the system showing the proximity of the other aircraft. For the demonstration, position report data were sent to the ground from on-board sensors on the unmanned aircraft. The point of view can be change dynamically, allowing encounters from all angles to be observed. Visualizing the encounters in real-time provides a safe and effective method for observation of live flight testing and a strong alternative to travel to the remote test range.

Video Streaming↗
NASA NTRS1984

Global Hydrologic Cycle

One of the major scientific questions in hydrology is: Can remote sensing data be used effectively with models to improve our understanding of hydrologic processes? Virtually all hydrologic models, with only a few exceptions, were designed to interface with conventional point data. These models must be modified or new ones developed to be compatible with remote sensing capabilities (areal coverage, high spatial resolution, repetitiveness, etc.). A comprehensive program of development and testing of these models at various application scales ranging from flash flood modeling and small tributary streams to continental size general circulation models must be carried out.

Rango, A.↗
NASA NTRS2001

Legato: Personal Computer Software for Analyzing Pressure-Sensitive Paint Data

'Legato' is personal computer software for analyzing radiometric pressure-sensitive paint (PSP) data. The software is written in the C programming language and executes under Windows 95/98/NT operating systems. It includes all operations normally required to convert pressure-paint image intensities to normalized pressure distributions mapped to physical coordinates of the test article. The program can analyze data from both single- and bi-luminophore paints and provides for both in situ and a priori paint calibration. In addition, there are functions for determining paint calibration coefficients from calibration-chamber data. The software is designed as a self-contained, interactive research tool that requires as input only the bare minimum of information needed to accomplish each function, e.g., images, model geometry, and paint calibration coefficients (for a priori calibration) or pressure-tap data (for in situ calibration). The program includes functions that can be used to generate needed model geometry files for simple model geometries (e.g., airfoils, trapezoidal wings, rotor blades) based on the model planform and airfoil section. All data files except images are in ASCII format and thus are easily created, read, and edited. The program does not use database files. This simplifies setup but makes the program inappropriate for analyzing massive amounts of data from production wind tunnels. Program output consists of Cartesian plots, false-colored real and virtual images, pressure distributions mapped to the surface of the model, assorted ASCII data files, and a text file of tabulated results. Graphical output is displayed on the computer screen and can be saved as publication-quality (PostScript) files.

Schairer, Edward T.↗
NASA NTRSDate not supplied

OpenNEX: An open collaboration platform for the earth science community

Satellite data from the past several decades provide the most consistent record of land-surface processes that form the basis for scientific assessments of the impacts of climate variations and changes on the environment and human social-economical activities. During this time, scientific research on the characterization and assessment of environmental changes had tended to focus on large-scale land-surface changes with significant social-economic impacts. Increasingly, attention is shifting toward changes that occur more locally and that most directly relate to the everyday life of the majority of the population. In addition, there has been needs to develop management and policy decision support systems that are based on local environmental information. Almost at the same time, the advancement in sensor technology has allowed us to collect an unprecedented volume of environmental data. These data must be curated and analyzed to extract useful information for research and decision support purposes. Established in 2013 and funded by NASA, the Open NASA Earth eXchange (OpenNEX; https://opennex.org/ , Jia et al., 2019 ) project partnered with Amazon Web Services (AWS) to make available a large amount of Earth observing data, modeling results, and analysis tools on the AWS. OpenNEX provides researchers, developers, educators, and ordinary users with easy access to an integrated Earth science computational and data platform, enabling citizen scientists and application developers to realize the full value of NASA data assets and software tools. To encourage the public's engagement in this project, NASA ran virtual workshops and prize competitions. The virtual workshops provided online lectures and tutorials about how prominent scientists used the data in their research and the tutorials gave examples how to use the tools to interrogate the data in the Amazon cloud. Finally, the prize competitions allowed much wider participation in the OpenNEX project and enable testing the non-traditional projects and out-of-box ideas. OpenNEX has continued to evolve and mature. Here, we highlight new features and functionalities available to the community.

Jian Zhang↗