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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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NASA NTRS2019

Laser Light Sheet Flow Visualization of the Space Launch System Booster Separation Test

Planar flow visualizations were obtained in a wind tunnel test in the NASA Langley Research Center’s Unitary Plan Wind Tunnel using the laser-light-sheet method. This method uses a laser to illuminate fine particles generated in the wind tunnel to visualize flow structures. The test article was designed to simulate the separation of the two solid rocket boosters (SRBs) from the core stage of the NASA Space Launch System (SLS) at Mach 4 using a scale model. The test was run on of the SLS Block 1B Cargo (27005) configuration and the SLS Block 1B Crew (28005) configuration. Planar flow visualization was obtained only on the crew configuration. Air at pressures up to 1500 psi was used to simulate plumes from the booster separation motors (BSMs) located at the nose, and aft skirt of the two boosters. The facility free stream was seeded with water vapor, which condensed and froze into small ice crystals in the tunnel nozzle expansion. A continuous wave green (532 nm) laser sheet was used to illuminate the ice crystals, and the resulting Mie-scattered light was collected with a camera. The resulting images clearly identify shock waves and other flow features including BSM plume shapes. Measurements were acquired for different BSM pressures and booster separation locations.

Danehy, Paul M.↗
NASA NTRSDate not supplied

Demonstration of Two Extended Visual Line of Sight Methods for Urban UAV Operations

This report describes two extended visual line of sight (EVLOS) methods developed and utilized during two flight campaigns over the campus of NASA Langley Research Center (LaRC): a chase vehicle method and a radio controlled (RC) pilot handoff method. These campaigns were performed to (a) evaluate small unmanned aerial system (sUAS) flight beyond the visual line of sight (BVLOS) of the ground control station operator and (b) test technologies under development to enable a transition from EVLOS to BVLOS operations. While an autonomous waypoint-based operational approach enabled minimal pilot intervention in both methods, range containment was enforced (a) manually via continual pilot visual monitoring and (b) autonomously via on-board contingency landing autonomy triggerable at the boundary of stay-in geofences. In the thirty-nine flights which utilized the chase vehicle, the pilot followed the sUAS flying a 1.2 km path at 40m altitude over urban streets. In the fifteen flights which utilized pilot handoff, a pilot at one end of a 1.5 km path initiated the flight at 120m altitude over buildings and trees, and at the midway point of the path transferred radio control to a pilot at the other end. In comparison, the chase vehicle method requires less ground crew and simpler avionics, while the pilot handoff method avoids schedule risk arising from street traffic congestion but better replicates actual direct routing for BVLOS flights. Collision risk with another aircraft was introduced in both campaigns and mitigated with the same manual and autonomous methods. Results from these campaigns serve as a basis for planned BVLOS operations at NASA LaRC.

Nicholas Rymer↗
NASA NTRSDate not supplied

GeneLab: The NASA Systems Biology Platform for Space Omics Repository, Analysis and Visualization

The NASA GeneLab project capitalizes on multi-omic technologies to maximize the return on spaceflight experiments. To do this, GeneLab maintains a publicly accessible database (GLDS) that houses spaceflight and spaceflight relevant multi-omics dataand collaborates with NASA principal investigators and projects to generate additional omics data. GeneLab houses more than 220 transcriptomic, proteomic, metabolomic and epigenomic datasets from plant, animal and microbial experiments, with a growing number of these having been produced by the GeneLab sample processing lab. The GLDS contains rich metadata about each experiment and has recently integrated radiation dosimetery data from experiments flown on the Space Shuttle. GeneLab has also recently implemented an effort to present processed data in the GLDS in addition to the raw omics data. The processed data will enable interpretationof the data by a larger group of students, scientists and the general public. Standard pipelines for the transformation of raw data into visualizations were developed by four GeneLab Analysis Working Groups (animals, plants, microbes, multi-omics) comprised of over 120 scientists from NASA, industry, and academia. To explore the data, the GLDS provides users various tools for data analysis, collaborative workspace for file storage and sharing, and a visualization portal. The analysis platform built using the Galaxy toolshed provides access to a broad variety of users including those with limited bioinformatics experience and students to learn how to analyze spaceflight omics data. The visualization portal takes GeneLab one step closer to data democratization by removing all bioinformatics requisites to interpret transcriptomics data hosted in the repository. Discoveries made using GeneLabhave begunand will continue to deepen our understanding of biology, advance the field of genomics, and help to discover cures for diseases, create better diagnostic tools, and ultimately allow astronauts to better withstand the rigors of long-duration spaceflight.

Samrawit Getachew Gebre↗
NASA NTRSDate not supplied

GeneLab: The NASA Systems Biology Platform for Space Omics Repository, Analysis and Visualization

The NASA GeneLab project capitalizes on multi-omic technologies to maximize the return on spaceflight experiments. To do this, GeneLab maintains a publicly accessible database (GLDS) that houses spaceflight and spaceflight relevant multi-omics data, and collaborates with NASA principal investigators and projects to generate additional omics data. GeneLab houses more than 220 transcriptomic, proteomic, metabolomic and epigenomic datasets from plant, animal and microbial experiments, with a growing number of these having been produced by the GeneLab sample processing lab. The GLDS contains rich metadata about each experiment and has recently integrated radiation dosimetery data from experiments flown on the Space Shuttle. GeneLab has also recently implemented an effort to present processed data in the GLDS in addition to the raw omics data. The processed data will enable interpretation of the data by a larger group of students, scientists and the general public. Standard pipelines for the transformation of raw data into visualizations were developed by four GeneLab Analysis Working Groups (animals, plants, microbes, multi-omics) comprised of over 120 scientists from NASA, industry, and academia. To explore the data, the GLDS provides users various tools for data analysis, collaborative workspace for file storage and sharing, and a visualization portal. The analysis platform built using the Galaxy toolshed provides access to a broad variety of users including those with limited bioinformatics experience and students to learn how to analyze spaceflight omics data. The visualization portal takes GeneLab one step closer to data democratization by removing all bioinformatics requisites to interpret transcriptomics data hosted in the repository. Discoveries made using GeneLab have begun and will continue to deepen our understanding of biology, advance the field of genomics, and help to discover cures for diseases, create better diagnostic tools, and ultimately allow astronauts to better withstand the rigors of long-duration spaceflight.

Samrawit Gebre↗
NASA NTRSDate not supplied

Visualizations to Aid Decision-Making in the ACCP Value Framework

NASA’s priorities for Earth Science are informed by the 2017-2027 Decadal Survey for Earth Science and Applications from Space of the National Academies of Sciences, Engineering and Medicine. In that document, five Designated Observables are identified as priorities for research, two of which are Aerosols, and Clouds, Convection, and Precipitation. NASA is addressing these two Designated Observables by a combined study (the Aerosols, Clouds, Convection, and Precipitation, or ACCP, study). In this context of the ACCP study’s multiple objectives and multiple stakeholders, heuristic-based approaches are insufficient to assess candidate observing system concepts due to the complexity of the decision problem. For the ACCP study, this complexity in assessment is such that absent a structured approach that permits understanding of the steps leading to a decision, the decision risks being made on an incomplete basis. While prose and numeric data both have their place in effective communication, visualizations play an important part not only in presenting information, but also in structuring conversations around that information. Each of the visualizations developed for the ACCP Value Framework serve at least one of several functions: it structures communication about a method or process, it facilitates the elicitation and aggregation of data, or it summarizes complex information to enable analysis. Thus, these visualizations can present information, structure conversations, or do both.

Christopher A Jones↗
NASA NTRSDate not supplied

Splashdown Visualization of Spent Stages

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.

Jack Agolli↗
NASA NTRSDate not supplied

Entwine Point Tiles for 3D Visualization and Querying of ICESat-2

Point Cloud data from non-optical sensors present challenges in scientific computing in both volume of data and files, even for cloud services environments. As part of the Multi-Mission Algorithm and Analysis Platform (MAAP), a joint open science platform for global biomass modelling, we’ve developed a cloud optimized workflow for using ATL08 (ICESat-2) data as a point cloud. For MAAP, the ATL08 data product is published as Entwine Point Tiles (EPT), allowing users to visualize and query the full extent of this collection interactively without pre-downloading, or preprocessing. The EPT format is a cloud-optimized point cloud data format which re-organizes points into a cloud friendly spatially indexed data structure. MAAP uses AWS S3 to store these point clouds and serves them over OGC specified APIs, 3DTiles for visualization, and WFS for querying. This workflow allows for interactive 3D visualizations in a web browser, including notebook environments and facilitates on the fly subsetting for interactive data exploration, all of which can be applied to other similar sensors.

Alex Mandel↗
NASA NTRS2004

Path following using visual odometry for Mars Rover in high-slip environments.

An architecture for autonomous operation of Mars rovers in high slip environments has been designed, implemented, and tested. This architecture is composed of several key technologies that enable the rover to accurately follow a designated path, compensate for slippage, and reach intended goals independent of the terrain over which it is traversing (within the mechanical constraints of the mobility system). These technologies include: visual odometry, full vehicle kinematics, a Kalman filter, and a slop compensation/path follower. Visual odometry tracks distinctive scene features in stereo imagery to estimate rover motion between successively acquired stereo image pairs using a maximum likelihood motion estimation algorithm. The full vehicle kinematics for a rocker-bogie suspension system estimates motion, with a no-slip assumption, by measuring wheel, rates, and rocker, bogie, and steering angles. The Kalman filter merges data from an Inertial Measurement Unit (IMU) and visual odometry. This merged estimate is then compared to the kinematic estimate to determining (tracking into account estimate uncertainties) if and how much slippage has occurred then a slip vector is calculated by differencing the current Kalman filter estimate from the kinematic estimate. This slip vector is then used, in conjunction with the inverse kinematics, to determine the necessary wheel velocities and steering angles to compensate for slip and follow the desired path.

Roumeliotis, Stergios I.↗
NASA NTRS2019

Supporting automation in spacecraft activity planning with simulation and visualization

Automation is gaining momentum in spacecraft operations, however, at a much slower pace than comparable application domains. The reasons behind slow adoption is (1) the need for high reliability and (2) the limited interaction between human operators and the automated systems. For automated systems to be adopted and trusted by humans, humans need to gain intuition about the decision making process of the automated system and trust in its execution [1]. In this paper, we present how simulation and visualization can enhance adoption of an automated on-board activity scheduling system, specifically in the context of Mars2020 rover mission[2]. The visualization aims to communicate to the users degree of variance and uncertainty in possible schedule execution. Our preliminary validation results suggest that the proposed visualization increases operators’ confidence in—and likelihood of adopting—the automated scheduling system.

Chien, Steve↗
NASA NTRS2021

Teleoperation and Visualization Interfaces for Remote Intervention in Space

Approaches to robotic manufacturing, assembly, and servicing of in-space assets range from autonomous operation to direct teleoperation, with many forms of semi-autonomous teleoperation in between. Because most approaches require one or more human operators at some level, it is important to explore the control and visualization interfaces available to those operators, taking into account the challenges due to significant telemetry time delay. We consider one motivating application of remote teleoperation, which is ground-based control of a robot on-orbit for satellite servicing. This paper presents a model-based architecture that: 1) improves visualization and situation awareness, 2) enables more effective human/robot interaction and control, and 3) detects task failures based on anomalous sensor feedback. We illustrate elements of the architecture by drawing on 10 years of our research in this area. The paper further reports the results of several multi-user experiments to evaluate the model-based architecture, on ground-based test platforms, for satellite servicing tasks subject to round-trip communication latencies of several seconds. The most significant performance gains were obtained by enhancing the operators’ situation awareness via improved visualization and by enabling them to precisely specify intended motion. In contrast, changes to the control interface, including model-mediated control or an immersive 3D environment, often reduced the reported task load but did not significantly improve task performance. Considering the challenges of fully autonomous intervention, we expect that some form of teleoperation will continue to be necessary for robotic in-situ servicing, assembly, and manufacturing tasks for the foreseeable future. We propose that effective teleoperation can be enabled by modeling the remote environment, providing operators with a fused view of the real environment and virtual model, and incorporating interfaces and control strategies that enable interactive planning, precise operation, and prompt detection of errors.

space robotics↗
NASA NTRS2021

Mid-Air Range-Visual-Inertial Estimator Initialization for Micro Air Vehicles

Monocular Visual-Inertial Odometry (VIO) has become ubiquitous for navigation of autonomous Micro Air Vehicles (MAVs). Yet, state-of-the-art VIO is still very failure- prone, which can have dramatic consequences. To prevent this, VIO must be able to re-initialize in mid-air, either during a free fall or on a constant horizontal velocity trajectory after attitude control has been re-established. However, for both of these trajectories, the visual scale cannot be observed with VIO batch initializers because of the absence of acceleration change. We propose to use a small and lightweight laser range finder and a scene facet model to initialize vision-based navigation at the right scale under any motion condition and over any scene structure. This new range constraint is integrated into a visual-inertial bundle adjustment initializer. We demonstrate in simulation and real data how this approach can address mid-air state estimation failure in real-time and analyze the sensitivity of estimators to initial state errors.

Brockers, Roland↗
NASA NTRS2022

Flow Visualization to Complement Modern Wing Tunnel Testing

In recent times, wind tunnel testing at the NASA Ames Unitary Plan Wind Tunnel (UPWT) seeks to validate computational fluid dynamics (CFD) tools. To that end, we find that now more than ever, flow visualization is a powerful capability that provides context to the experimental results bringing real-time insight to the researcher. It enables us to answer questions like: “Why does this drag polar look different?” or “What is the source of this tone in the microphone data?”. Flow visualization can verify that assumptions made in the CFD model are correct, addressing questions like: “Are our trip dots the correct size and location?” or “Does the position of this shock match our prediction?”. Techniques such as infrared flow visualization and schlieren / shadowgraph are powerful capabilities that when taken together can provide results as to the nature of the fluid structure interaction at a test condition in a format that pairs well with computational results. When properly integrated these measurements can be taken with no impact on the productivity of the test program, supplementing traditional measurements and often discovering something unforeseen, helping the researcher to answer those slippery aerodynamic questions and ultimately build confidence in the accuracy of a model.

wind tunnel↗
NASA NTRSDate not supplied

Developing an Earth-Fixed Visual Reference to Aid Stability, Readaptation, and Egress After A Water Landing

Water landings present the worst possible sensory conditions for crews trying to orient and stabilize themselves immediately after long-duration spaceflight. Of the three sensory feedback systems involved in maintaining stability (i.e., proprioceptive, vestibular, and visual), none will provide reliable orientation information under the current water landing scenarios. The proprioceptive and vestibular systems are affected during spaceflight by disuse and adaptation to microgravity. Vision may not suffer the same degradation, but the visual environment within the enclosed space of a capsule, or interior room of a recovery ship, induces instability during wave motion. In addition to an increased fall risk, sensory readaptation is delayed until inputs from the three sensory systems can be synchronized with one another and aligned with Earth’s gravity. An Earth-fixed visual reference (EFVR) can be provided to increase crewmember stability and allow for earlier readaptation initiation.

B.T. Peters↗
NASA NTRS2023

Safety Case for Small Uncrewed Aircraft Systems (sUAS) Beyond Visual Line of Sight (BVLOS) Operations at NASA Langley Research Center

This Technical Memorandum (TM) is written to provide for dissemination of the methods and safety considerations for operations of small Uncrewed Aerial Systems (sUAS) Beyond Visual Line-of-Sight (BVLOS)at NASA Langley Research Center. It includes the Safety Case used to acquire a BVLOS Certificate of Authorization (COA) from the FAA and is being published to enable others to benefit from this work. The intended operations, subject to approval from the Federal Aviation Administration (FAA) and the National Aeronautics and Space Administration (NASA), will include a combination of Within Visual Line of Sight (WVLOS) and Beyond Visual Line of Sight (BVLOS) flights, comprising of at most five sUAS operating concurrently, with no more than three operating BVLOS. Flights will occur in a subset of the Langley Air Force Base (LAFB) Class D airspace (KLFI) at a maximum altitude of 400 ft AGL. Most operations within this subset will take place in the City Environment Range Testing for Autonomous Integrated Navigation (CERTAIN) Range. The CERTAIN Range includes airspace inside the borders of NASA Langley Research Center (LaRC). Additional airspace over the northern section of CERTAIN will be requested as part of the Certificate of Authorization (COA). NASA LaRC BVLOS operations on the CERTAIN Range can be broken down into five critical components needed to meet the 14 CFR § 91.113 see and avoid requirement: 1) procedural deconfliction with LAFB for UAS operations at or below 400 ft and manned aircraft at or above 900’ AGL; 2) ground equipment for detection of intruder aircraft and to support communications between crewmembers ; 3) sUAS vehicles with advanced onboard automation capable of autonomously maintaining safe separation; 4) BVLOS standardized operating procedures (SOPs); 5) and personnel to execute the flight operations in accordance with the SOPs and respond to airborne contingencies. The introduction of new ground equipment includes the use of the Remote Operations for Autonomous Missions (ROAM) UAS Operations Center, development and use of an Integrated Airspace Display (IAD), use of the L-STAR and GA-9120 radars, and the incorporation of standardized Vertiports. The ROAM Operations Center will be the central point for all BVLOS sUAS operations. All command and control (C2), voice communications and airspace awareness displays will reside inside ROAM. The IAD will provide raw data from ADS-B, FLARM, radar tracks and telemetered GPS vehicle positions for interpretation by an Airspace Monitor. The radars will search the class D airspace around the CERTAIN Range and serve as a backup to procedural deconfliction procedures coordinated with LAFB. In the event of a procedural deconfliction breakdown, radar detections of non-participating aircraft will be available so that the 91.113 see and avoid requirement can still be safely met. Finally, the incorporation of Vertiports will have video and network connectivity that enables large numbers of sUAS launches and recoveries from a single location. This is a continuation of the remote command and control of unpiloted aircraft component focused on evaluating unpiloted aircraft flight crew roles and responsibilities, control interfaces and the associated data links needed to operate a fleet of aircraft within a UAM Ecosystem. This work supports the development of future aviation operational concepts based on an Urban Air Mobility Maturity Level (UML) 4 environment (Patterson, 2020). It is assumed that future airspace will include hundreds of simultaneous aircraft operations within the airspace, therefore scalable operations are essential for enabling this future airspace to become a reality. Follow on work includes envisioned flights that expand operations beyond the CERTAIN range and lead to an effective Maritime Surveillance capability.

Matthew W Coldsnow↗
NASA NTRSDate not supplied

VEDA: Visualization, Exploration, & Data Analysis

NASA's Visualization, Exploration, and Data Analysis (VEDA) project is an open-source science cyberinfrastructure for data processing, visualization, exploration, and geographic information systems (GIS) capabilities. Developed collaboratively and mostly reusing existing open-source components, VEDA consolidates GIS delivery mechanisms, processing platforms, analysis services, and visualization tools and provides an ecosystem of open tools for addressing Earth science research and application needs through the public-facing VEDA Dashboard. In this presentation, Dr. Freitag will provide an overview of VEDA and how it can potentially serve the AOS community.

Brian Freitag↗
NASA NTRSDate not supplied

Flow Visualization of Intrusive and Non-Intrusive Configurations for Lunar- and Martian-Relevant Plume-Surface Interaction

Flow visualization of a heated, inert-gas plume impinging onto a rigid surface was performed in lunar- and Martian-relevant pressure conditions. The experimental campaign was part of a broader effort to improve predictive models and capabilities for plume-surface interactions in spacecraft landing environments relevant to the Moon and Mars. The experiments used the planar laser induced fluorescence (PLIF) technique to visualize the flow of the jet over both a full-plane configuration using a flat impingement plate and a half-plane configuration where the jet flow was bisected by a splitter edge mounted to the impingement plate. The latter configuration has been previously used to study erosion mechanisms in plume-surface interactions because the technique enables cross-sectional optical access for visualizing the plume-induced crater. However, this approach has some uncertainty regarding the influence of the splitter edge on the flow field. The present work evaluates the differences in flow structures and characteristics between the flat plate and splitter plate experimental configurations at eight unique test conditions with and without the splitter edge where the vacuum chamber pressure, nozzle mass flow rate, and height of the nozzle were varied. Several features are identified which differ between the flat plate and splitter plate comparison cases, and these are summarized in this paper. The results presented provide insights to the differences between intrusive and non-intrusive experimental configurations for plume-surface interaction studies that can be used to further validate predictive models and inform future ground and flight test results.

PLIF↗
NASA NTRSDate not supplied

Improving Data Discovery, Analysis, and Visualizations With Cloud-Based User Services

The Global Hydrometeorology Resource Center (GHRC) Distributed Active Archive Center (DAAC) is one of 12 DAACs managed by the United States National Aeronautics and Space Administration (NASA) Earth Science Data and Information System (ESDIS) project [1]. GHRC and the other DAACs are designed to process, archive, document, and distribute NASA Earth-observing data, ranging from satellite missions to field campaigns [2]. A major goal of the DAACs is to enable science with these data. Science enabling can be difficult as datasets can be very large, use multiple formats, come from numerous platforms, and require three-dimensional visualization. GHRC is using its expertise with cloud-based technologies to develop open source and open science tools to empower users to explore, coincidentally visualize, and analyze multiple datasets. Being open source, the user community can develop visualizations for their own datasets. This presentation will expand on this objective and highlight the capabilities available to the international community now.

GHRC↗
NASA NTRSDate not supplied

Flow Visualization of Intrusive and Non-Intrusive Configurations for Lunar- and Martian-Relevant Plume-Surface Interaction

Flow visualization of a heated, inert-gas plume impinging onto a rigid surface was performed in lunar- and Martian-relevant pressure conditions. The experimental campaign was part of a broader effort to improve predictive models and capabilities for plume-surface interactions in spacecraft landing environments relevant to the Moon and Mars. The experiments used the planar laser-induced fluorescence (PLIF) technique to visualize the flow of the jet over both a full-space configuration using a flat impingement plate and a half-space configuration where the jet flow was bisected by a splitter edge mounted to the impingement plate. The latter configuration has been previously used to study erosion mechanisms in plume-surface interactions because the technique enables cross-sectional optical access for visualizing the plume-induced crater. However, this approach has some uncertainty regarding the influence of the splitter edge on the flow field. The present work evaluates the differences in flow structures and characteristics between the flat plate and splitter plate experimental configurations at eight unique test conditions with and without the splitter edge where the vacuum chamber pressure, nozzle mass flow rate, and height of the nozzle were varied. Several features are identified which differ between the flat plate and splitter plate comparison cases, and these are summarized in this paper. The results presented provide insights to the differences between intrusive and non-intrusive experimental configurations for plume-surface interaction studies that can be used to further validate predictive models and inform future ground and flight test results.

PLIF↗