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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Virtually Out of This World!

Ames Research Center granted Reality Capture Technologies (RCT), Inc., a license to further develop NASA's Mars Map software platform. The company incorporated NASA#s innovation into software that uses the Virtual Plant Model (VPM)(TM) to structure, modify, and implement the construction sites of industrial facilities, as well as develop, validate, and train operators on procedures. The VPM orchestrates the exchange of information between engineering, production, and business transaction systems. This enables users to simulate, control, and optimize work processes while increasing the reliability of critical business decisions. Engineers can complete the construction process and test various aspects of it in virtual reality before building the actual structure. With virtual access to and simulation of the construction site, project personnel can manage, access control, and respond to changes on complex constructions more effectively. Engineers can also create operating procedures, training, and documentation. Virtual Plant Model(TM) is a trademark of Reality Capture Technologies, Inc.

Source record↗
NASA NTRS1991

Virtual reality applications to automated rendezvous and capture

Virtual Reality (VR) is a rapidly developing Human/Computer Interface (HCI) technology. The evolution of high-speed graphics processors and development of specialized anthropomorphic user interface devices, that more fully involve the human senses, have enabled VR technology. Recently, the maturity of this technology has reached a level where it can be used as a tool in a variety of applications. This paper provides an overview of: VR technology, VR activities at Marshall Space Flight Center (MSFC), applications of VR to Automated Rendezvous and Capture (AR&C), and identifies areas of VR technology that requires further development.

Hale, Joseph↗
NASA NTRS2000

Visualizing Progress

Reality Capture Technologies, Inc. is a spinoff company from Ames Research Center. Offering e-business solutions for optimizing management, design and production processes, RCT uses visual collaboration environments (VCEs) such as those used to prepare the Mars Pathfinder mission.The product, 4-D Reality Framework, allows multiple users from different locations to manage and share data. The insurance industry is one targeted commercial application for this technology.

Source record↗
NASA NTRS2019

Using Virtual Reality and Motion Capture as tools for Human Factors Engineering at NASA Marshall Space Flight Center

NASA Marshall Space Flight Center (MSFC) Human Factors Engineering (HFE) Team is implementing virtual reality (VR) and motion capture (MoCap) into HFE analyses of various projects through its Virtual Environments Lab (VEL). VR allows for multiple analyses early in the design process and more opportunities to give design feedback. This tool can be used by engineers in most disciplines to compare design alternatives and is particularly valuable to HFE to give early input during these evaluations. These techniques are being implemented for concept development of Deep Space Habitats (DSH), and work is being done to implement VR for design aspects of the Space Launch System (SLS). VR utilization in the VEL will push the design to be better formulated before mockups are constructed, saving budget and time. The MSFC VEL will continue forward leaning implementation with VR technologies in these and other projects for better models earlier in the design process.

Andrews, Tanya↗
NASA NTRS2019

Using Virtual Reality and Motion Capture as tools for Human Factors Engineering at NASA Marshall Space Flight Center

NASA Marshall Space Flight Center (MSFC) Human Factors Engineering (HFE) Team is implementing virtual reality (VR) and motion capture (MoCap) into HFE analyses of various projects through its Virtual Environments Lab (VEL). These techniques are being implemented for concept of development of Deep Space Habitats (DSH) and design and analyses for NASA’s Space Launch System (SLS). VR utilization in the VEL will push the design to be better formulated before mockups are constructed, saving budget and time.

Andrews, Tanya↗
NASA NTRS2019

Using Virtual Reality and Motion Capture as Tools for Human Factors Engineering at Nasa Marshall Space Flight Center

MSFC’s Human Factors Engineering (HFE) team is responsible for all worksite analyses performed for the SLS pre-launch integration activities at Kennedy Space Center (KSC). There is a wide variety of tasks associated with pre-launch integration activities and it is important to verify that vehicle integration will be successful early in the design process. The VR work performed by the HFE team at MSFC has allowed fast changing layouts to be analyzed by various departments with minimal impact to cost or schedule. Implementing these methods for SLS allows for VR use in early design cycles, saving time and budget. Utilizing the resulting HFE analyses improves usability and safety. Ultimately, the goal is to provide a safe environment for the technicians assembling the vehicle and the astronaut crew at launch.

Andrews, Tanya↗
NASA NTRSDate not supplied

Artificial Intelligence Enhancements to Imagery for Space Operations

Philosophy classes still ponder the question asked by Dr. George Berkely, an Anglican Bishop and philosopher in the 1600’s-- “If a tree falls in a forest and no one is around to hear it, does it make a sound?” With that in mind, I ask the following—If a still image or motion imagery from a space mission cannot be found during a search, does it exist? Since the beginning of spaceflight, imagery has been a key form of data collected. Whether for mere curiosity (what does Earth look like from Space?), or for operational reasons (did the solar panel deploy?), or for engineering purposes (what was that object that floated away from the spacecraft?), imagery has been included in space missions. To be useful, though, the image or motion imagery must be accessible and accessed when needed. During the analog era, that typically meant captions and numbers associated with the physical media. With “born digital” imagery, it is possible to add metadata to the image data file. This metadata might include the date and time of capture, mission, camera, exposure data, and similar data fields. Many modern cameras embed some basic metadata into the image file at the moment of capture. The reality, though, is even with today’s born-digital enhancements with embedded metadata at the time of capture, reviewing and cataloging still and motion imagery is very labor intensive. Humans review the imagery for sensitive content (privacy concerns, imagery containing proprietary data/subject matter), and to identify imagery containing crew members or imagery that should be reviewed for engineering or scientific reasons. All this review and manual data entry is very time-consuming. Many improvements in Artificial Intelligence (AI), Machine Learning, and processing power now make it possible to identify persons, objects, motion, color, audio with sensitive content, and other details after or while the imagery is captured.

Rodney Grubbs↗
NASA NTRS2018

(GO)2-SIM: a GCM-Oriented Ground-Observation Forward-Simulator Framework for Objective Evaluation of Cloud and Precipitation Phase

General circulation model (GCM) evaluation using ground-based observations is complicated by inconsistencies in hydrometeor and phase definitions. Here we describe (GO)2-SIM, a forward simulator designed for objective hydrometeor-phase evaluation, and assess its performance over the North Slope of Alaska using a 1-year GCM simulation. For uncertainty assessment, 18 empirical relationships are used to convert model grid-average hydrometeor (liquid and ice, cloud, and precipitation) water contents to zenith polarimetric micropulse lidar and Ka-band Doppler radar measurements, producing an ensemble of 576 forward-simulation realizations. Sensor limitations are represented in forward space to objectively remove from consideration model grid cells with undetectable hydrometeor mixing ratios, some of which may correspond to numerical noise.Phase classification in forward space is complicated by the inability of sensors to measure ice and liquid signals distinctly. However, signatures exist in lidar–radar space such that thresholds on observables can be objectively estimated and related to hydrometeor phase. The proposed phase-classification technique leads to misclassification in fewer than 8% of hydrometeor-containing grid cells. Such misclassifications arise because, while the radar is capable of detecting mixed-phase conditions, it can mistake water- for ice-dominated layers. However, applying the same classification algorithm to forward-simulated and observed fields should generate hydrometeor-phase statistics with similar uncertainty. Alternatively, choosing to disregard how sensors define hydrometeor phase leads to frequency of occurrence discrepancies of up to 40%. So, while hydrometeor-phase maps determined in forward space are very different from model "reality" they capture the information sensors can provide and thereby enable objective model evaluation.

Lamer, K.↗
NASA NTRS2017

Human Factors Virtual Analysis Techniques for NASA's Space Launch System Ground Support using MSFC's Virtual Environments Lab (VEL)

Using virtual environments to assess complex large scale human tasks provides timely and cost effective results to evaluate designs and to reduce operational risks during assembly and integration of the Space Launch System (SLS). NASA's Marshall Space Flight Center (MSFC) uses a suite of tools to conduct integrated virtual analysis during the design phase of the SLS Program. Siemens Jack is a simulation tool that allows engineers to analyze human interaction with CAD designs by placing a digital human model into the environment to test different scenarios and assess the design's compliance to human factors requirements. Engineers at MSFC are using Jack in conjunction with motion capture and virtual reality systems in MSFC's Virtual Environments Lab (VEL). The VEL provides additional capability beyond standalone Jack to record and analyze a person performing a planned task to assemble the SLS at Kennedy Space Center (KSC). The VEL integrates Vicon Blade motion capture system, Siemens Jack, Oculus Rift, and other virtual tools to perform human factors assessments. By using motion capture and virtual reality, a more accurate breakdown and understanding of how an operator will perform a task can be gained. By virtual analysis, engineers are able to determine if a specific task is capable of being safely performed by both a 5% (approx. 5ft) female and a 95% (approx. 6'1) male. In addition, the analysis will help identify any tools or other accommodations that may to help complete the task. These assessments are critical for the safety of ground support engineers and keeping launch operations on schedule. Motion capture allows engineers to save and examine human movements on a frame by frame basis, while virtual reality gives the actor (person performing a task in the VEL) an immersive view of the task environment. This presentation will discuss the need of human factors for SLS and the benefits of analyzing tasks in NASA MSFC's VEL.

Searcy, Brittani↗
NASA NTRS2019

NASA Marshall Space Flight Center Tools for Human Factors Engineering Assessments for Safe Sls Worksites

NASA Marshall Space Flight Center (MSFC) Human Factors Engineering (HFE) Team is implementing mockup fabrication, virtual reality (VR) and motion capture (MoCap) into HFE analyses of SLS worksites through its Virtual Environments Lab (VEL). MSFC HFE Team is responsible for the Space Launch System (SLS) worksite analyses of the integration activities performed at the Kennedy Space Center (KSC). With a wide variety of tasks, it is important to verify that SLS can be safely integrated at KSC early in the design process. If the ground support crew cannot safely complete the tasks, redesign efforts must be implemented. MSFC HFE is responsible for verification through methods such as drawing inspection, observation of tasks performed, and building physical mockups. There is a need, however, for a faster analysis early in the process that can impact design safety before drawings are finalized. This need is addressed through MSFC’s VEL.

Andrews, Tanya↗
NASA NTRS2019

Using Virtual Reality for Worksite Analysis

NASA Marshall Space Flight Center (MSFC) Human Factors Engineering (HFE) Team is implementing virtual reality (VR) and motion capture (MoCap) into HFE analyses of various projects through its Virtual Environments Lab (VEL). This complements the long history of analyses completed using mockups. These techniques are being implemented for; (1) Concept of development of Deep Space Habitats (DSH), (2) Design and analyses for NASA’s Space Launch System (SLS). VR utilization in the VEL will push the design to be better formulated before mockups are constructed, saving budget and time.

Andrews, Tanya↗
NASA NTRS2010

Towards Global Simulation of Irrigation in a Land Surface Model: Multiple Cropping and Rice Paddy in Southeast Asia

Agricultural land use significantly influences the surface water and energy balances. Effects of irrigation on land surface states and fluxes include repartitioning of latent and sensible heat fluxes, an increase in net radiation, and an increase in soil moisture and runoff. We are working on representing irrigation practices in continental- to global-scale land surface simulation in NASA's Global Land Data Assimilation System (GLDAS). Because agricultural practices across the nations are diverse, and complex, we are attempting to capture the first-order reality of the regional practices before achieving a global implementation. This study focuses on two issues in Southeast Asia: multiple cropping and rice paddy irrigation systems. We first characterize agricultural practices in the region (i.e., crop types, growing seasons, and irrigation) using the Global data set of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000) dataset. Rice paddy extent is identified using remote sensing products. Whether irrigated or rainfed, flooded fields need to be represented and treated explicitly. By incorporating these properties and processes into a physically based land surface model, we are able to quantify the impacts on the simulated states and fluxes.

Beaudoing, Hiroko Kato↗
NASA NTRS2014

Robonaut 2 - IVA Experiments On-Board ISS and Development Towards EVA Capability

Robonaut 2 (R2) has completed its fixed base activities on-board the ISS and is scheduled to receive its climbing legs in early 2014. In its continuing line of firsts, the R2 torso finished up its on-orbit activities on its stanchion with the manipulation of space blanket materials and performed multiple tasks under teleoperation control by IVA astronauts. The successful completion of these two IVA experiments is a key step in Robonaut's progression towards an EVA capability. Integration with the legs and climbing inside the ISS will provide another important part of the experience that R2 will need prior to performing tasks on the outside of ISS. In support of these on-orbit activities, R2 has been traversing across handrails in simulated zero-g environments and working with EVA tools and equipment on the ground to determine manipulation strategies for an EVA Robonaut. R2 made significant advances in robotic manipulation of deformable materials in space while working with its softgoods task panel. This panel features quarter turn latches that secure a space blanket to the task panel structure. The space blanket covers two cloth cubes that are attached with Velcro to the structure. R2 was able to open and close the latches, pull back the blanket, and remove the cube underneath. R2 simulated cleaning up an EVA worksite as well, by replacing the cube and reattaching the blanket. In order to interact with the softgoods panel, R2 has both autonomously and with a human in the loop identified and localized these deformable objects. Using stereo color cameras, R2 identified characteristic elements on the softgoods panel then extracted the location and orientation of the object in its field of view using stereo disparity and kinematic transforms. R2 used both vision processing and supervisory control to successfully accomplish this important task. Teleoperation is a key capability for Robonaut's effectiveness as an EVA system. To build proficiency, crewmembers have attempted increasingly difficult tasks using R2 inside the Station. After donning motion capture equipment and a virtual reality visor, Expedition 34/35 flight engineer Tom Marshburn began operations with simple hand movements. Having gained confidence, Marshburn guided R2's arms in a leader-follower exercise with crewmate Chris Cassidy. He was also able to use the hand to grab a tumbling roll of tape, a task only demonstrable in microgravity. Later efforts saw Cassidy handle softgoods through shared control with ground operators, mimicking an activity previously achieved using only autonomy. Robotic climbing through the ISS on handrails requires both precision motion and compliant grasps in order to both position grippers on handrails/seat track and prevent large internal forces. R2 climbs using actively controlled compliance and torque limiting to meet both the precision and softness requirements. During a step, the attached leg is controlled to be strong and stiff in order to maintain precision trajectory tracking. The swing leg is controlled to be stiff but weak to minimize unintentional impact forces while maintaining precision. During a simulated dual limb grasp (as shown in Figure 1), the R2 controller maintains one limb rigid and one limb soft to prevent large internal forces from building up. R2's grippers also use a form of force control to limit grip force while not fully closed on either a handrail or seat track thus limiting unintentional forces on cables/objects that may be present in R2's translational path. The on-board torso R2 safety system relies on a single end-effector velocity limit to prevent potential impact forces from exceeding Station maximum load requirements. R2's mobile configuration required modifications to the velocity limiting safety function due to its large, dynamic inertia. R2's legs maneuver the robot's mass creating configuration dependent, joint-relative inertias. A single all-encompassing velocity limit to cover worst case inertia is prohibitively low. The upgraded R2 control and safety systems solve this problem using momentum limiting, momentum control, and kinetic energy minimization. Momentum and kinetic energy take the robot mass into account relieving low velocity restrictions on low inertia end-effectors while ensuring that the overall mass of R2 is limited from hazardous velocities. The momentum of R2's five safety nodes (each of the four end-effectors and the body) is monitored and compared to a single momentum limit. If any of the five nodes exceeds the safety limit, the motor power is removed and the robot comes to a stop. Momentum control/limiting also provides a simple, reliable method to integrate hand held tools into the safety system by providing the tool mass to the control system thus automatically reducing the allowable velocity of the end-effector with the tool. Work on the ground continues to build the skill set for an EVA Robonaut. Recent experiments (Figure 2) demonstrate how a teleoperator can use R2 to manipulate a tether hook, an important safety precaution on spacewalks. Another task displayed Robonaut's ability to pull back a protective jacket over a hose and search for damage, as well as inspect a quick-disconnect fitting for debris. Demonstrations such as these are indicative of EVA work done on ISS, specifically seen during a series of spacewalks over 2012 and 2013 where astronauts searched for an ammonia leak in one of the external cooling loops. Through experiments both on ISS and on the ground, R2 is evolving and providing the information needed to plan out the upgrades that will make an EVA Robonaut an effective tool. With the addition of legs, R2 will start climbing inside the space station and supply invaluable information on how the climbing strategies and task stabilization techniques must be refined. Ground R2 systems will continue to work with additional EVA tools and equipment in preparation for onboard IVA testing and future EVA applications.

Diftler, Myron↗
NASA NTRSDate not supplied

Lunar Surface Mixed Reality and ARGOS Trainer

This Artemis focused Mixed Reality (MR) and ARGOS project extends the current VR/ARGOS CIF project to enhance and add VR/MR capabilities to support analysis, training and risk reduction for lunar surface EVA operations in the extreme South Pole lunar environment. This third year focused on establishing a functional trainer for crew that supports the ingress/egress of a lander as well as surface tasks such as sample collection and tool deployment and operation. Completed enhancements include improving hand tracking, the addition of supporting mixed reality surface operations, and the implementation of a higher fidelity body tracking capability through a motion capture system.

Lunar↗
NASA NTRS2018

Research and Development of The Immersive Simulations and Engineering Environment

March of 2018 marked the conclusion of the primary updates to the immersive Simulations and Engineering Environment (iSEE) at Kennedy Space Center (KSC). Many of the problems that had arisen during the previous semester have been addressed and rectified. These included the malfunction to one of the lab's primary routers, the inefficiency of the capture environment, and various interface issues in the analysis software, Jack. This semester was primarily research and development oriented with some focus on implementation of the new hardware and software that was received last semester. The new computers and cameras that arrived sometime during the winter were installed, and the lab received its second operation opportunity. The second operation was a major milestone for the lab, both in terms of what the abilities were and what can be learned from its use. The operation performed was a virtual simulation of a critical task that would occur, if it should be needed, in the Multi Payload Processing Facility. It was done to gather human factors data on its safety and process controls. The technicians were able to come to a number of conclusions about how to perform their task as a result of utilizing iSEE. Another key breakthrough this semester was the introduction to Jack Script, a scripting language built into our analysis software that further extend Jack capabilities. In addition to the aforementioned, many preparations were made for family day, an exposition for KSC families to come out and tour the spaceport. Due to family day being moved to the spring, the video made last fall had to be updated with recent environment changes in preparation for the Family Day demonstrations.

Motion Capture↗
NASA NTRS2019

The Implementation of Maximum Likelihood Estimation in Space Launch System Vehicle Design

As NASA’s Space Launch System (SLS) approaches first launch, the design has matured to a point where the manufacturing uncertainty has decreased now that many of the components of the launch vehicle have been manufactured and the flight engines have been successfully tested. Prior to this point, a method was required to qualify and capture the impact of the differences between simulation and reality, as well as any uncertainties in the SLS design. Two primary categories of uncertainty arise during the launch vehicle design process. The first represents flight-day uncertainties including dispersions due to winds and temperatures. These are typically examined by performing a Monte Carlo on 6 Degree of Freedom (6-DOF) simulations. The second category of uncertainties represents any manufacturing variations that are present at the individual component level of the launch vehicle design. These variations are constructed using statistical masses and tend to become better understood and refined as the design cycle matures, finally resulting in the launch vehicle as constructed and tested.

Stein, W. B.↗
NASA NTRS1996

Integrated Design Systems -Capturing, Reusing and Optimizing Design Methods in New Millenium

An important goal of New Millenium is to research new methods of performing spacecraft and mission design. We have completed the first phase of our effort on how to make design tools such as analysis programs more available. We are now embarking with Stanford University on discovering methods to allow more project history and knowledge to be automatically captured and reused with Ames Research Center on how to use virtual reality to enhance the visualization of new missions before any hardware exists.

New↗