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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 NTRS1981

The design, fabrication and installation of cable routing mockups in support of Spacelab 2

From flight and mockup drawings of Spacelab 2 (SL 2) experiments and hardware, shop ready mockup drawings were produced. Floor panels were the first items considered for fabrication. Cold plate and orthogrid mockups were designed and fabricated. Experiment and other hardware mockups were fabricated of aluminum or plywood, depending on size and configuration. Eighty-three cable routing bracket mockups were fabricated of aluminum and delivered for painting.

Source record↗
NASA NTRSDate not supplied

Robotic Software Architecture for in-Space Outfitting Operations

Space exploration is expanding into longer missions, larger payloads, and more complex operations. To make these larger scale missions a reality, it is necessary to perform assembly, construction, and maintenance tasks via a robotic workforce in addition to crewed operations. While there has been significant research into in-space assembly and manufacturing, it is primarily focused on rigid structural elements, such as ISRU printing or truss construction. Outfitting tasks, such as cable routing, are a critical step to a fully operational in-space facility. This paper seeks to provide a reduced order state model and an optimized combination of state-of-the-art robotics algorithms applied to a cable routing scenario. Simulation results are expected to advance approaches to online autonomous robotic manipulation of non-rigid elements.

Amy M Quartaro↗
NASA NTRSDate not supplied

Robotic Software Architecture for In-Space Outfitting Operations

Space exploration is expanding into longer missions, larger payloads, and more complex operations. To make these larger scale missions a reality, it is necessary to perform assembly, construction, and maintenance tasks via a robotic workforce in addition to crewed operations. While there has been significant research into in-space assembly and manufacturing, it is primarily focused on rigid structural elements, such as ISRU printing or truss construction. Outfitting tasks, such as cable routing, are a critical step to a fully operational in-space facility. This paper seeks to provide a reduced order state model and an optimized combination of state-of-the-art robotics algorithms applied to a cable routing scenario. Simulation results are expected to advance approaches to online autonomous robotic manipulation of non-rigid elements.

Amy Quartaro↗
NASA NTRS2003

Improved Testing Capability and Adaptability Through the Use of Wireless Sensors

From the first Saturn V rocket booster (S-II-T) testing in 1966 and the routine Space Shuttle Main Engine (SSME) testing beginning in 1975, to more recent test programs such as the X-33 Aerospike Engine, the Integrated Powerhead Development (IPD) program, and the Hybrid Sounding Rocket (HYSR), Stennis Space Center (SSC) continues to be a premier location for conducting large-scale testing. Central to each test program is the capability for sensor systems to deliver reliable measurements and high quality data, while also providing a means to monitor the test stand area to the highest degree of safety and sustainability. Sensor wiring is routed along piping and through cable trenches, making its way from the engine test area, through the test stand area and to the signal conditioning building before final transfer to the test control center. When sensor requirements lie outside the reach of the routine sensor cable routing, the use of wireless sensor networks becomes particularly attractive due to their versatility and ease of installation. As part of an on-going effort to enhance the testing capabilities of Stennis Space Center, the Test Technology and Development group has found numerous applications for its sensor-adaptable wireless sensor suite. While not intended for critical engine measurements or control loops, in-house hardware and software development of the sensor suite can provide improved testing capability for a range of applications including the safety monitoring of propellant storage barrels and as an experimental test-bed for embedded health monitoring paradigms.

Solano, Wanda M.↗
NASA NTRSDate not supplied

Autonomous Stabilization and Orientation Control of Hoisted Payloads

An orientation control system prototype has been developed for hoisted payloads. This system will allow payloads to be lifted off inclined surfaces while maintaining orientation control, allowing removal of tightly packed payloads without colliding with adjacent objects. For this concept, the payload is hoisted with a crane using a rigging system composed of a cable routed through two capstans and three or four attachment points on the payload. Motors rotate the capstans to adjust the cable lengths to the payload, and thereby control the orientation of the payload. Initial testing of the prototype was completed using manual control, however the algorithms necessary to fully automate the system are presented in this paper.

control↗
NASA NTRS1984

Cryogenic Pressure Seal for Wires

High-pressure-seal formed by forcing polyurethane into space surrounding wire or cable in special fitting. Wire or cable routed through fitting then through a tightly fitting cap. Wire insulation left intact. Cap filled with sealant and forced onto the fitting: this pushes sealant into fitting so it seals wire or cable in fitting as well as in cap.

Ciana, J. J.↗
NASA NTRSDate not supplied

Modeling Deformable Linear Objects for Autonomous Robotic Outfitting of Lunar Surface Systems

This paper presents structural models of deformable linear objects (DLOs). DLOs are a subclass of deformable objects that encompasses common outfitting elements such as cables and ropes. Models are validated through hardware experiments, and integration in a robotic autonomy architecture for space environments is discussed. A persistent human presence on the lunar surface is one of the next major milestones in space exploration. This requires the development of robust extraplanetary construction technologies including structures and materials modeling and robotic systems. Previous robotic construction technology development has primarily focused on structural assembly, with significantly less focus on robotically performed outfitting tasks to instantiate subsystems providing power, data, life support, etc. These tasks involve manipulation of highly flexible elements, which are difficult to model, such as cable harnesses, ropes, and hoses. Robotic manipulation of DLOs, especially cable harnesses, is an active area of research as cable harnesses are essential for providing power and data to space assets. DLO models that can be used for robot manipulator trajectory generation are necessary for autonomous operation of lunar infrastructure. There are many proposed methods for modeling DLOs, and they primarily fall into three types: 1) discrete model-based, 2) continuum model-based, and 3) Neural Network-based. These types each have pros and cons, and the tradeoff between model accuracy and computational speed informs which type should be used. An understanding of this trade-off is imperative for real-time control of autonomous systems. High computational requirements reduce the speed of the model, making real-time control difficult, while accuracy is critical to preventing collisions. Discrete models, such as a mass-spring multibody representation, require relatively few calculations, and accuracy is directly tied to the step size of the discretization. Continuum models, such as a B-spline representation or a Cosserat rod model (a mix of continuous and discrete), are more informed of the structural properties of the cable and are much more accurate than a rigid body mass-spring model, but at significant computational cost. A Neural Network approach can provide an online solution with very few computational steps, but properly generating training data can be difficult and validation for an in-space application is not trivial. This paper explores the trade-off between different modeling approaches and compares accuracy and computational speed/complexity of the three types mentioned above. Model accuracy is evaluated using a cable in a static configuration. True cable shape is obtained using a depth camera for RGB images and point-cloud segmentation. The purpose of this experiment is to evaluate the trade-offs of different approaches to the DLO modeling problem. Understanding the tradeoffs between different cable modeling techniques paves the way for developing robotic control and planning architectures necessary for real-time manipulation of DLOs for lunar infrastructure outfitting. Real-time control is required for robotic systems to be able to actively manipulate a cable in a harsh environment where model and sensor errors compound, and environmental conditions can cause significant disturbances. Cable routing must be performed in areas with high density of objects/obstacles: through truss structures, near solar panels or mirror arrays, next to bundles of electrical equipment. Understanding the best way to plan and manipulate a cable without disrupting the environment or damaging the cable is imperative to robotic outfitting operations on the lunar surface.

Amy M Quartaro↗
NASA NTRS1994

Space Station Freedom secondary power wiring requirements

Secondary power is produced by DDCU's (direct current to direct current converter units) and routed to and through secondary power distribution assemblies (SPDA's) to loads or tertiary distribution assemblies. This presentation outlines requirements of Space Station Freedom (SSF) EEE (electrical, electronic, and electromechanical) parts wire and the approved electrical wire and cable. The SSF PDRD (Program Definition and Requirements Document) language problems and resolution are reviewed. The cable routing to and from the SPDA's is presented as diagrams and the wire recommendations and characteristics are given.

Sawyer, C. R.↗
NASA NTRS1986

The design and fabrication of the Centaur neutral buoyancy trainer and related hardware

Two full scale mockups of the Centaur upper stage were designed, fabricated and delivered to NASA. One was the Centaur Weightless Environment Training Facility (WETF) trainer and the other was the Centaur 1-G mockup. The Centaur upper stage booster is designed to carry the spacecraft Galileo to Jupiter, and the spacecraft Ulysses to an orbit around the Sun after launch from the Space Shuttle. The flight vehicle has several Extravehicular Activity (EVA) contingency tasks that require crew training. This need for crew training generated the requirement for the Centaur WETF crew trainer, which is high fidelity in areas of expected crew interface. During the production of the Centaur WETF crew trainer, the need for a jumper cable from Centaur to the Orbiter was identified. This EVA contingency task would be the installation of a cable from the Orbiter cargo bay sill to various command data boxes on Centaur to allow crew control deployment should a failure occur. This task required the upgrading of volumetric boxes on the trainer to a high fidelity configuration including electrical connector installation and cable routing.

Ware, Alan S.↗
NASA NTRS1993

Layout and cabling considerations for a large communications antenna array

Layout considerations for a large deep space communications antenna array are discussed. A fractal geometry for the antenna layout is described that provides optimal packing of antenna elements, efficient cable routing, and logical division of the array into identical sub-arrays.

Logan, R. T., Jr.↗
NASA NTRS2008

Cammp Team

The International Space Station (ISS) Configuration Analysis Modeling and Mass Properties (CAMMP) Team is presenting a demo of certain CAMMP capabilities at a Booz Allen Hamilton conference in San Antonio. The team will be showing pictures of low fidelity, simplified ISS models, but no dimensions or technical data. The presentation will include a brief description of the contract and task, description and picture of the Topology, description of Generic Ground Rules and Constraints (GGR&C), description of Stage Analysis with constraints applied, and wrap up with description of other tasks such as Special Studies, Cable Routing, etc. The models include conceptual Crew Exploration Vehicle (CEV) and Lunar Lander images and animations created for promotional purposes, which are based entirely on public domain conceptual images from public NASA web sites and publicly available magazine articles and are not based on any actual designs, measurements, or 3D models. Conceptual Mars rover and lander are completely conceptual and are not based on any NASA designs or data. The demonstration includes High Fidelity Computer Aided Design (CAD) models of ISS provided by the ISS 3D CAD Team which will be used in a visual display to demonstrate the capabilities of the Teamcenter Visualization software. The demonstration will include 3D views of the CAD models including random measurements that will be taken to demonstrate the measurement tool. A 3D PDF file will be demonstrated of the Blue Book fidelity assembly complete model with no vehicles attached. The 3D zoom and rotation will be displayed as well as random measurements from the measurement tool. The External Configuration Analysis and Tracking Tool (ExCATT) Microsoft Access Database will be demonstrated to show its capabilities to organize and track hardware on ISS. The data included will be part numbers, serial numbers, historical, current, and future locations, of external hardware components on station. It includes dates of all external ISS events and flights and the associated hardware changes for each event. The hardware location information does not always reveal the exact location of the hardware, only the general location. In some cases the location is a module or carrier, in other cases it is a WIF socket, handrail, or attach point. Only small portions of the data will be displayed for demonstration purposes.

Evertt, Shonn F.↗
NASA NTRS2009

Miniature Six-Axis Load Sensor for Robotic Fingertip

A miniature load sensor has been developed as a prototype of tactile sensors that could fit within fingertips of anthropomorphic robot hands. The sensor includes a force-and-torque transducer in the form of a spring instrumented with at least six semiconductor strain gauges. The strain-gauge wires are secured to one side of an interface circuit board mounted at the base of the spring. This board protects the strain-gauge wires from damage that could otherwise occur as a result of finger motions. On the opposite side of the interface board, cables routed along the neutral axis of the finger route the strain-gauge output voltages to an analog-to-digital converter (A/D) board. The A/D board is mounted as close as possible to the strain gauges to minimize electromagnetic noise and other interference effects. The outputs of the A/D board are fed to a controller, wherein, by means of a predetermined calibration matrix, the digitized strain-gauge output voltages are converted to three vector components of force and three of torque exerted by or on the fingertip.

Diftler, Myron A.↗
NASA NTRS2010

Operational Lessons Learned from the Ares I-X Flight Test

The Ares I-X flight test, launched in 2009, is the first test of the Ares I crew launch vehicle. This development flight test evaluated the flight dynamics, roll control, and separation events, but also provided early insights into logistical, stacking, launch, and recovery operations for Ares I. Operational lessons will be especially important for NASA as the agency makes the transition from the Space Shuttle to the Constellation Program, which is designed to be less labor-intensive. The mission team itself comprised only 700 individuals over the life of the project compared to the thousands involved in Shuttle and Apollo missions; while missions to and beyond low-Earth orbit obviously will require additional personnel, this lean approach will serve as a model for future Constellation missions. To prepare for Ares I-X, vehicle stacking and launch infrastructure had to be modified at Kennedy Space Center's Vehicle Assembly Building (VAB) as well as Launch Complex (LC) 39B. In the VAB, several platforms and other structures designed for the Shuttle s configuration had to be removed to accommodate the in-line, much taller Ares I-X. Vehicle preparation activities resulted in delays, but also in lessons learned for ground operations personnel, including hardware deliveries, cable routing, transferred work and custodial paperwork. Ares I-X also proved to be a resource challenge, as individuals and ground service equipment (GSE) supporting the mission also were required for Shuttle or Atlas V operations at LC 40/41 at Cape Canaveral Air Force Station. At LC 39B, several Shuttle-specific access arms were removed and others were added to accommodate the in-line Ares vehicle. Ground command, control, and communication (GC3) hardware was incorporated into the Mobile Launcher Platform (MLP). The lightning protection system at LC 39B was replaced by a trio of 600-foot-tall towers connected by a catenary wire to account for the much greater height of the vehicle. Like Shuttle, Ares I-X will be stacked on a MLP and rolled out to the pad on a Saturn-era crawler-transporter. While Ares I-X was only held in place by the four hold-down posts on its aft skirt during rollout, a new vehicle stabilization system (VSS) attached to the vertical service structure kept the vehicle from undue swaying prior to launch at the pad, LC 39B. Following the launch, the flight test vehicle first stage was recovered with the aid of new parachutes resized to accommodate the five-segment-long first stage, which had a much greater length and mass than the Shuttle s reusable solid rocket boosters. After splashdown, recovery divers exercised extra care when handling the first stage to ensure that the flight data recorders in the fifth segment simulator were not damaged by exposure to sea water. The data recovered from the Ares I-X flight test will be very valuable in verifying the predicted environments and models used to design the vehicle. Lessons learned from Ares I-X will be shared with the Ares Projects through written and verbal reports and through integration of mission team members into the Project workforce.

Davis, Stephan R.↗
NASA NTRS2010

Integration Process for the Habitat Demonstration Unit

The Habitat Demonstration Unit (HDU) is an experimental exploration habitat technology and architecture test platform designed for analog demonstration activities The HDU project has required a team to integrate a variety of contributions from NASA centers and outside collaborators and poses a challenge in integrating these disparate efforts into a cohesive architecture To complete the development of the HDU from conception in June 2009 to rollout for operations in July 2010, a cohesive integration strategy has been developed to integrate the various systems of HDU and the payloads, such as the Geology Lab, that those systems will support The utilization of interface design standards and uniquely tailored reviews have allowed for an accelerated design process Scheduled activities include early fit-checks and the utilization of a Habitat avionics test bed prior to equipment installation into HDU A coordinated effort to utilize modeling and simulation systems has aided in design and integration concept development Modeling tools have been effective in hardware systems layout, cable routing and length estimation, and human factors analysis Decision processes on the shell development including the assembly sequence and the transportation have been fleshed out early on HDU to maximize the efficiency of both integration and field operations Incremental test operations leading up to an integrated systems test allows for an orderly systems test program The HDU will begin its journey as an emulation of a Pressurized Excursion Module (PEM) for 2010 field testing and then may evolve to a Pressurized Core Module (PCM) for 2011 and later field tests, depending on agency architecture decisions The HDU deployment will vary slightly from current lunar architecture plans to include developmental hardware and software items and additional systems called opportunities for technology demonstration One of the HDU challenges has been designing to be prepared for the integration of presently unanticipated systems Results of the HDU field tests will influence future designs of habitat systems.

Gill, Tracy↗
NASA NTRS2011

Integration Process for the Habitat Demonstration Unit

The Habitat Demonstration Unit (HDU) is an experimental exploration habitat technology and architecture test platform designed for analog demonstration activities. The HDU previously served as a test bed for testing technologies and sub-systems in a terrestrial surface environment. in 2010 in the Pressurized Excursion Module (PEM) configuration. Due to the amount of work involved to make the HDU project successful, the HDU project has required a team to integrate a variety of contributions from NASA centers and outside collaborators The size of the team and number of systems involved With the HDU makes Integration a complicated process. However, because the HDU shell manufacturing is complete, the team has a head start on FY--11 integration activities and can focus on integrating upgrades to existing systems as well as integrating new additions. To complete the development of the FY-11 HDU from conception to rollout for operations in July 2011, a cohesive integration strategy has been developed to integrate the various systems of HDU and the payloads. The highlighted HDU work for FY-11 will focus on performing upgrades to the PEM configuration, adding the X-Hab as a second level, adding a new porch providing the astronauts a larger work area outside the HDU for EVA preparations, and adding a Hygiene module. Together these upgrades result in a prototype configuration of the Deep Space Habitat (DSH), an element under evaluation by NASA's Human Exploration Framework Team (HEFT) Scheduled activates include early fit-checks and the utilization of a Habitat avionics test bed prior to installation into HDU. A coordinated effort to utilize modeling and simulation systems has aided in design and integration concept development. Modeling tools have been effective in hardware systems layout, cable routing, sub-system interface length estimation and human factors analysis. Decision processes on integration and use of all new subsystems will be defined early in the project to maximize the efficiency of both integration and field operations. In addition a series of tailored design reviews are utilized to quickly define the systems and their integration into the DSH configuration. These processes are necessary to ensure activities, such as partially reversing integration of the X-Hab second story of the HDU and deploying and stowing the new work porch for transportation to the JSC Rock Yard and to the Arizona Black Point Lava Flow Site are performed with minimal or no complications. In addition, incremental test operations leading up to an Integrated systems test allows for an orderly systems test program. For FY-11 activities, the HDU DSH will act as a laboratory utilizing a new X-Hab inflatable second floor with crew habitation features. In addition to the day to day operations involving maintenance of the HDU and exploring the surrounding terrain, testing and optimizing the use of the new X-Hab, work porch, Hygiene Module, and other sub-system enhancements will be the focus of the FY-11 test objectives. The HDU team requires a successful integration strategy using a variety of tools and approaches to prepare the DSH for these test objectives. In a challenging environment where the prototyping influences the system design, as well as Vice versa, results of the HDU DSH field tests will influence future designs of habitat systems.

Gill, Tracy↗
NASA NTRS2015

Armstrong Flight Research Center Flight Test Capabilities and Opportunities for the Applications of Wireless Data Acquisition Systems

The presentation will overview NASA Armstrong Flight Research Centers flight test capabilities, which can provide various means for flight testing of passive and active wireless sensor systems, also, it will address the needs of the wireless data acquisition solutions for the centers flight instrumentation issues such as additional weight caused by added instrumentation wire bundles, connectors, wire cables routing, moving components, etc., that the Passive Wireless Sensor Technology Workshop may help. The presentation shows the constraints and requirements that the wireless sensor systems will face in the flight test applications.

flight tests↗
NASA NTRSDate not supplied

A Preliminary Assessment of Physical Demand during Simulated Lunar Surface Extravehicular Activities

Returning to the moon requires many advances in current space technology. One major aspect of this development is a new exploration spacesuit (xEMU). Taking lessons learned from Apollo era suitsand the Extravehicular Mobility Unit (EMU) used on the International Space Station (ISS), xEMU will have increased mobility, dust mitigation, headspace, glove fit, and life support capabilities. Artemis astronauts in xEMU will complete a far more rigorous Extravehicular Activity (EVA) schedule than Apolloand ISS. Notably, metabolic rates during Apollo lunar EVA tasks were observed to be up to 50% lower than similar tasks performed in a ground analog environment under simulated partial gravity with newer suits. Therefore, understanding the physical demands of lunar surface exploration operations is criticalto ensuring best outcomes operating within the constraints of xEMU and planning for exploration EVA activities. This study utilized the Active Response Gravity Offload System (ARGOS) to simulate the lunar environment and continuously offload subjects to lunar gravity. Two male subjects completed two days of EVAs wearing the pressurized Mark III spacesuit, completing suit fit and mobility checks, as well as simulated lander operations, cable routing, crew rescue, geology, payload relocation, and traverse tasks in an end-to-end EVA (E2E) task block and standalone (SA) task blocks. We recorded continuous values of metabolic rate (MR) and heart rate (HR) to assess physical demand. During the E2E task block, subjects did not rest between tasks to simulate continuous effort from task to task, as in real EVAs. In comparison, subjects had a 5-minute break after each SA task block to allow for the metabolic rate and heart rate to return to baseline.MR values were categorized as low (≤ 700 BTU/hr), medium (700-1000 BTU/HR), and high (≥ 1000 BTU/hr), while HR values were categorized as low (≤150) and high (>150). During the 16 tasks in the E2E block, subjects averaged low MR in 6% of tasks, medium MR in 47% of tasks, and high MR in 47% of tasks. While MR was consistent between subjects, Subject 1 averaged low HR for 100% of these tasks, while Subject 2 averaged low HR in 44% of tasks. During the 23 tasks in the SA task blocks, subjects averaged low MR in 26% of tasks, medium MR in 52% of tasks, and high MR in 22% of tasks. Again, HR was different between subjects, with subject 1 averaging low HR in 100% of these tasks while subject 2 averaged low HR in 70%. Across all tasks in this study, subjects reached maximum MR and HR values during a 500m traverse at 30% grade in the E2E block (subject 1: 1747 BTU/hr, 150 BPM; subject 2: 1656 BTU/hr, 177 BPM).Understanding the physical demand to complete exploration EVA tasks will be instrumental to the future success of exploration spacesuit designs and missions. Further work in this study will be needed to characterize MR during exploration EVA tasks, including expanding the subject pool and testing new suit designs.

Taylor E Schlotman↗
NASA NTRSDate not supplied

A Preliminary Assessment of Cognition and Fatigue During Simulated Lunar Surface Extravehicular Activities

Introduction: Artemis astronauts will be required to complete more rigorous Extravehicular Activity (EVA) schedules than during ever before. While new spacesuits are designed to sustain high physical workloads during exploration EVAs (xEVA), crewmembers must also sustain cognitive performance throughout xEVA timelines. It is therefore necessary to characterize the effects of surface xEVA tasks and timelines on cognition and fatigue. Methods: This study utilized NASA Johnson Space Center’s Active Response Gravity Offload System (ARGOS) to simulate lunar gravity and assess xEVA tasks and cognitive performance. Two subjects completed two ~5-hour EVAs in a pressurized Mark III spacesuit, completing simulated lander operations, cable routing, crew rescue, geology, payload relocation, and traverses. Subjects completed two cognitive assessments (Digit-Symbol Substitution Task (DSST) and Psychomotor Vigilance Task (PVT)) before the first and after the second simulated EVA to assess effects of xEVA tasks on processing speed and vigilant attention. Additionally, sleep (e.g., quality, duration, and efficiency) was monitored (Oura Ring) for ≥7 days prior to the simulated EVAs, as well as between each EVA, to account for possible effects of sleep decrements on cognitive metrics. Results: Cognitive performance changed minimally from pre to post EVA for both DSST (response time (RT): S1 Δ129.1ms, S2 Δ40.7ms; Accuracy: S1 preEVA = 1.0, S1 postEVA = 0.98, S2 preEVA = 1.0, S2 postEVA = 1.0) and PVT (S1 PVT RT Δ17.7 ms, S2 PVT RT Δ-2.7 ms). Subjects’ sleep duration immediately prior to EVA showed minimal deviation from baseline (Δhrs; S1 preEVA1= + 0.67, S1 preEVA2 = -.03, S2 preEVA1 = - 1.1, S2 preEVA2 = -1.39) and efficiency (Δ%; S1 preEVA1 = 0.09, S1 preEVA2 = 9.54, S2 preEVA1 = 0, S2 preEVA2= 12). Notably, sleep waketime shifted earlier for one subject by ~1 hr which may have impacted performance. Conclusion: Understanding the impacts of xEVA workloads on cognitive performance will be instrumental to future exploration mission planning and success. Future work will expand the subject pool and test new spacesuit designs to better characterize cognitive performance and impacts of sleep during simulated xEVA and inform modeling and prediction capabilities for future Artemis xEVA planning.

Taylor E. Schlotman↗