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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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The following research work is reported: (1) vestibular-visual interactions; (2) flight management and crew system interactions; (3) peripheral cue utilization in simulation technology; (4) control of signs and symptoms of motion sickness; (5) auditory cue utilization in flight simulators, and (6) vestibular function: Animal experiments.
The results of a NASA sponsored study, performed in order to establish the feasibility of remotely manipulated or unmanned welding fabrication systems for space construction, are presented. Possible space welding fabrication tasks and operational modes are classified and the capabilities and limitations of human operators and machines are outlined. Human performance in remote welding tasks was experimentally tested under the sensing and actuation constraints imposed by remote manipulation in outer space environments. Proposals for the development of space welding technology are made and necessary future R&D efforts are identified. The development of improved visual sensing strategies and computer encoding of the human welding engineering expertise are identified as essential, both for human operator assistance and for autonomous operation in all phases of welding fabrication. Novel uses of machine vision for the determination of the weld joint and bead geometry are proposed, and a prototype of a rule-based expert system is described for the interpretation of the visually detected weld features and defects.
In low speed wind tunnels it is often desirable to visualize airflow to augment observations made with instruments such as strain and pressure gages. Current technology devices for delivery of a vapor are bulky and thus disrupt local airflow. It is the object of this invention to provide a device capable of delivering a stream of vapor with a minimal effect on local airflow. The present invention achieves this object by utilizing a narrow tube as a heating device for producing the vapor. Running an electrical current through the tube provides resistive heating to a liquid which produces a vapor when boiled. As the entire heating and delivery portion of the device is simply a small cylinder the disruption to airflow within the tunnel is minimized. this allows an experimenter to place the source of vapor fairly close to a model without causing too much change to the model data. The novelty of the present invention lies in reducing the bulk of current technology devices by combining the acts of heating and delivery.
Recent research in Synthetic/Enhanced Vision technology is analyzed with respect to existing Category II/III performance and certification guidance. The goal is to start the development of performance-based vision systems technology requirements to support future all-weather operations and the NextGen goal of Equivalent Visual Operations. This work shows that existing criteria to operate in Category III weather and visibility are not directly applicable since, unlike today, the primary reference for maneuvering the airplane is based on what the pilot sees visually through the "vision system." New criteria are consequently needed. Several possible criteria are discussed, but more importantly, the factors associated with landing system performance using automatic and manual landings are delineated.
As NASA focuses on the Moon to Mars (M2M) efforts, an environment-tolerable spacesuit design will be needed. NASA has traditionally used Roadmaps to strategize technology development and lay the foundation for the Exploration EMU (xEMU) spacesuit prototype. The Roadmaps visualize an actionable plan to realize EVA capabilities needed for Mars exploration.
Historically, there have been a limited number of studies involving Transitional Shock-Wave/Boundary-Layer Interactions (XSWBLI) in hypersonic flows, the majority of which have been performed at Mach Numbers of 7.5 and below. Additionally, there have been even fewer such experiments which incorporate non-intrusive and optical diagnostics. NASA Langley Research Center (NASA LaRC), in collaboration with The University of Texas at San Antonio (UTSA) and The University of Tennessee Space Institute (UTSI), is currently planning and preparing for a series of experimental aerodynamic tests using the NASA LaRC 31-inch Mach 10 Air Tunnel. The experiments will primarily focus on studying the dynamics of Shock-Wave/Boundary-Layer Interactions (SWBLI) in the presence of transition (XSWBLI) and turbulence (SWTBLI) on a large, flat plate model at a freestream Mach number of 10. Besides continued interest in understanding the flow at high Mach numbers, executing such tests at Mach 10 avoids some known concerns and will aid in solving new problems. XSWBLI are a highly unsteady phenomena and the generation of XSWBLI at lower Mach numbers can prove to be a significant challenge. This concern will be somewhat mitigated in the Mach 10 flow, as boundary layers become increasingly stabilized, but some difficulty in achieving transition is still expected. Modelling SWBLI in the presence of transitional and turbulent boundary layers has also proven to be difficult, so a high-Mach number experiment which applies non-intrusive and optical diagnostics will aid in solving a unique problem as well as advancing the understanding and characterization of an aerodynamic surface at Mach 10.The NASA LaRC 31-inch Wind Tunnel incorporates a test section having a cross-section of 31-inches × 31-inches and provides optical access to the test section via three (3) ultra-violet (UV) transmitting windows on the top, side, and bottom. The Mach 10 operating conditions will consist of pressures (P0) ranging from 2.4 to 10MPa (348 to 1,450 psi) at a temperature (T0) of 1,000 K (1,800 °R). The NASA LaRC 31-inch wind tunnel will deliver 1-minute blow-down runs, of which 30-45 seconds will be consumed to reach the aforementioned test conditions. The pump down time between runs will be approximately 45-60 minutes, which will provide for 6-10 test runs per day over the course of a weeklong entry. The proposed flat plate model will be constructed of stainless steel with geometry consisting of a10-inch × 30-inch upper surface and a 2-inch thickness. The model will be designed to support multiple leading-edge inserts in order to examine blunt, round, and sharp leading edges at Mach 10. Adjustments will be made to manage boundary layer thickness as well as the strength and size of the shock interaction region for each test. Measurements and diagnostics will be performed though high-speed Schlieren, on-body high-speed pressure transducers, IR thermography, and oil flow visualization. Hypersonic vehicle applications have and will continue to emerge at the forefront of aerospace. The NASA-UTSA-UTSI team realizes the value of characterizing SWBLI, XSWBLI, and SWTBLI behaviors well beyond single-digit hypersonic Mach numbers. As hypersonic vehicle speed capabilities continue to increase, measurement and diagnostic methods for Mach numbers of 10 and beyond will provide the foundation for a firm understanding of flow field behavior which will directly influence the advancement of technologies towards the design and manufacturing of high-speed aerodynamic surfaces, controls, thermal protection systems, acoustic treatments, and structural components. The use of non-intrusive and optical diagnostic methods in such experimentation is pivotal in developing the visualization and empirical data necessary to advance the aforementioned technology areas.
The goal of this internship was to improve and create virtual reality simulations and visualizations for use in parallel with the design, fabrication, and analysis of flight ready hardware for areas like the Environmental Control and Life Support Systems (ECLSS) and also Space Systems. Specifically, my work was done in the XRSpace lab at Marshall Space Flight Center (MSFC) with assistance directly and indirectly from workers at KSC, JSC and LaRC. Led by David Reynolds, the XRSpace lab develops products for various entities at NASA. The work done in the XRSpace lab focuses on Extended Reality (XR) solutions for both simulations and visualization capabilities. The goal of the lab is to support the larger systems of NASA and to help find ways that XR technologies can streamline and optimize the design process. Extended Reality is an umbrella term that encompasses Mixed Reality, Augmented Reality, and Virtual Reality. In this capacity, I was able to complete several elements in the design, building, testing, and deployment for a variety of immersive experiences, including a VR procedure simulation, visualization aids, and a 360-image capture tool.
An in depth look at the Earth Science datasets used in the Etheater Visualizations will be presented. This will include the satellite orbits, platforms, scan patterns, the size, temporal and spatial resolution, and compositing techniques used to obtain the datasets as well as the spectral bands utilized.
Pursuit and perception both require accurate information about the motion of objects. Recovering the motion of objects by integrating the motion of their components is a difficult visual task. Successful integration produces coherent global object motion, while a failure to integrate leaves the incoherent local motions of the components unlinked. We compared the ability of perception and pursuit to perform motion integration by measuring direction judgments and the concomitant eye-movement responses to line-figure parallelograms moving behind stationary rectangular apertures. The apertures were constructed such that only the line segments corresponding to the parallelogram's sides were visible; thus, recovering global motion required the integration of the local segment motion. We investigated several potential motion-integration rules by using stimuli with different object, vector-average, and line-segment terminator-motion directions. We used an oculometric decision rule to directly compare direction discrimination for pursuit and perception. For visible apertures, the percept was a coherent object, and both the pursuit and perceptual performance were close to the object-motion prediction. For invisible apertures, the percept was incoherently moving segments, and both the pursuit and perceptual performance were close to the terminator-motion prediction. Furthermore, both psychometric and oculometric direction thresholds were much higher for invisible apertures than for visible apertures. We constructed a model in which both perception and pursuit are driven by a shared motion-processing stage, with perception having an additional input from an independent static-processing stage. Model simulations were consistent with our perceptual and oculomotor data. Based on these results, we propose the use of pursuit as an objective and continuous measure of perceptual coherence. Our results support the view that pursuit and perception share a common motion-integration stage, perhaps within areas MT or MST.
The state of the art for many Earth-to-orbit trajectory analysis toolsets used at NASA is somewhat dated in terms of the languages they are written in and their user interfaces. Many of these programs are written in languages like Fortran or C that are no longer considered modern in the technology industry, and are command-line based without any means of interpreting the data outputs. This presentation is meant to demonstrate a specific use case for a newly developed web app that visualizes the output data for one of these tools. Specifically, one key usage is to investigate and validate launches for notional multi-stage vehicle concepts to various non-standard high-inclination orbits. Some NASA requirements dictate that trajectories be designed such that no surviving debris lands closer than 200 nautical miles (nm) from foreign landmasses or 27 nm from the continental United States, therefore validating re-entry locations of spent stages is an integral part of the launch planning process. In addition, at programmatic levels it can prove insightful and clarifying for the decision-making process to enhance the technical results of numerical simulations with visualizations. The intent with this tool is to provide the mission analyst and program level management with an intuitive and clear grasp of key information on possible mission scenarios either departing from or arriving at Earth, and in the future, the moon or Mars as well. The software tool was developed with an agile development approach and utilizes the latest frameworks and technologies. The front end uses the React JavaScript library for making a state of the art frontend and a backend based on the Django Python framework for handling data using Python’s powerful and free scientific libraries. In addition, the CesiumJS open-source library is key for visualizing these end-to-end trajectories on a high-resolution Earth model. The presentation will demonstrate the current capability and tested use cases.
There is an urgent need to increase the capacity of developing countries to take part in the study and monitoring of their environments through remote sensing and space-based Earth observation technologies. The Open Data Cube (ODC) provides a mechanism for efficient storage and a powerful framework for processing and analyzing satellite data. While this is ideal for scientific research, the expansive feature space can also be daunting for end-users and decision-makers who simply require a solution which provides easy exploration, analysis, and visualization of Analysis Ready Data (ARD). Utilizing innovative web-design and a modular architecture, the Committee on Earth Observation Satellites (CEOS) has created a web-based user interface (UI) which harnesses the power of the ODC yet provides a simple and familiar user experience: the CEOS Data Cube (CDC). This paper presents an overview of the CDC architecture and the salient features of the UI. In order to provide adaptability, flexibility, scalability, and robustness, we leverage widely-adopted and well-supported technologies such as the Django web framework and the AWS Cloud platform. The fully-customizable source code of the UI is available at our public repository. Interested parties can download the source and build their own UIs. The UI empowers users by providing features that assist with streamlining data preparation, data processing, data visualization, and sub-setting ARD products in order to achieve a wide variety of Earth imaging objectives through an easy to use web interface.
With the upcoming shift to extra‐long duration missions (1 year) aboard the ISS, sensorimotor adaptations during transitory periods in‐and‐out of microgravity are more important to understand and prepare for. Advances in virtual reality technology enables everyday adoption of these tools for entertainment and use in training. Experiencing virtual environments (VE) allows for the manipulation of visual flow to elicit automatic motor behavior and produce sensorimotor adaptation (SA). Recently, the ability to train individuals using repeatable and varied exposures to SA challenges has shown success by improving performance during exposure to a novel environment (Batson 2011). This capacity to 'learn to learn' is referred to as sensorimotor adaptive generalizability and, through the use of treadmill training, represents an untapped potential for individualized countermeasures. The goal of this study is to determine the feasibility of present head mounted displays (HMDs) to produce compelling visual flow information and the expected adaptations for use in future SA treadmill‐based countermeasures. Participants experience infinite hallways providing congruent (baseline) or incongruent visual information (half or double speed) via HMD while walking on an instrumented treadmill at 1.1m/s. As gait performance approaches baseline levels, an adaptation time constant is derived to establish individual time‐to‐adapt (TTA). It is hypothesized that decreasing the TTA through SA treadmill training will facilitate sensorimotor adaptation during gravitational transitions. In this way, HMD technology represents a novel platform for SA training using off‐the‐shelf consumer products for greater training flexibility in astronaut and terrestrial applications alike.
Ground-based flight simulation contributes greatly to the development of new aircraft and flight management systems and will be especially important in improving the performance, safety, and environmental characteristics of future civil and military V/STOL aircraft. This paper describes existing simulation facilities at Ames Research Center and discusses their capabilities and limitations for V/STOL aircraft investigations. Simulation requirements for NASA research and support of DOD programs are also discussed, including technology development for advanced rotorcraft and civil and military V/STOL aircraft. Current efforts and future plans are described for the upgrading of Ames simulation facilities to meet those requirements. Recent advances in equipment technology and operational methodology are shown to provide significantly improved simulation fidelity through better motion and visual cues and faster system response to pilot inputs.
The problems associated with assessing visual performance during translation and rotation in a virtual world are presented. Two studies are summarized that highlight the difficulties in defining and measuring the optical and visual variables that pilots use during the control of a craft in simulated flight. The analysis suggests that gaze line-of-sight (LOS), based on craft orientation, should be used to describe the visual information available to an observer. Head-mounted displays that utilize a headtracker provide a technology that can be used for determining an observer's LOS and generating a virtual world display. Such head-mounted displays put observers in a graphical world that exists no matter where they look.
The National Aeronautics and Space Administration is addressing airport capacity enhancements during instrument meteorological conditions though the Terminal Area Productivity (TAP) program. The major goal of the TAP program is to develop the technology that will allow air traffic levels during instrument meteorological condition to approach those achieved during visual operations. The Reduced Spacing Operations (RSO) subelement of TAP at the NASA Langley Research Center (LaRC) will develop the Aircraft Vortex Spacing System (AVOSS). The purpose of the AVOSS is to integrate current and predicted weather conditions, wake vortex transport and decay knowledge, wake vortex sensor data, and operational definitions of acceptable strengths for vortex encounters to produce dynamic wake vortex separation criteria. The proposed research is in support of the wake vortex hazard definition component of the LaRC AVOSS development research. The research program described in the next section provided an analysis of the static test data and uses this data to evaluate the accuracy vortex/wake-encounter models. The accuracy of these models has not before been evaluated using experimental data. The research results also presented the first analysis of the forces and moments imparted on an airplane during a wake vortex encounter using actual flight test data.
NASA's Advanced Information Systems Technology (AIST) Program is one of several Technology programs managed by the Earth Science Technology Office (ESTO) in the Earth Science Division (ESD). The AIST Program focuses on advanced information systems and novel computer science technologies that will be needed by NASA Earth Science in the next 5 to 10 years. The three main thrusts of the AIST Program deal with Novel Observing Strategies (NOS), Analytic Collaborative Frameworks (ACF) and Earth System Digital Twins (ESDT). For all these thrusts, Machine Learning (ML) is increasingly being used in multiple aspects of Earth science systems, e.g., for onboard autonomy and decision making, for the analysis of massive and diverse datasets as well as more recently for developing surrogate models that will represent one of the main components of future Digital Twins of the Earth. Particularly, ESDT technologies developed by the AIST Program will allow to develop integrated Earth Science frameworks that will mirror the Earth with state-of-the-art models (Earth system models and others), timely and relevant observations, and analytic tools. These information systems will be used for supporting near- and long-term science and policy decisions. ESDT frameworks will build on previously developed AIST capabilities and technologies to integrate interconnected models with continuous streams of observations, data analytics, data assimilation, simulations, advanced visualizations and the ability to conduct "what-if" scenarios. This talk will describe the three thrusts of the AIST Program with a special focus on Machine Learning and how it is being used at all steps of the Earth Science data lifecycle.
The purpose of this article is to discuss several different types of software tools the Jet Propulsion Laboratory's (JPL) Measurement Technology Center (MTC) has used to develop such systems.
Ambient air pollution is the largest environmental health risk factor, leading to several million premature deaths globally per year. The challenge of combating poor air quality is exacerbated by growing urban populations, changing emissions, and a warming climate. While there have been many advances monitoring and modeling of atmospheric composition, reflected in the dramatic increase in archived Earth Observations, there is no single measurement or method that alone can provide an accurate depiction of the entire atmosphere. The rapidly growing collections of observational and modeling data require us to be smarter about what data to include, and how such data is used. In recent years, NASA has invested significantly in advancing the concepts for Analytics Collaborative Framework (ACF) [5] and New Observing Strategies (NOS) [4] to tackle our software infrastructure need for harmonized data management and dynamic acquisition of diverse measurements for on-demand, interactive, multivariate analysis, and access [3]. It is not enough to have a big data, standalone analytics solution; it is critical that we start integrating data from remote sensing, modeling, and in-situ networks in a harmonized manner that enables timely and data-driven decision-making for air quality management. This work presents the design and development of an Air Quality Analytics Collaborative Framework (AQ ACF), as part of NASA’s Advanced Information Systems Technology (AIST) effort, to establish a data, machine-learning, and numerically driven platform for air quality analysis, visualization, and prediction.