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NASA NTRSDate not supplied

Supervised Autonomous Assembly to Create and Evolve Persistent Assets

Supervised autonomous assembly (SAA) will create a paradigm shift in the planning and design of future persistent assets (PAs), both in near zero-g environments and on planetary surfaces. SAA refers to an autonomy approach that has the benefits of autonomous assembly as well as the benefits provided by a supervisor (operator) who is available to resolve unexpected situations. SAA provides both increased design freedom as well as reduced programmatic risk. SAA enables evolution of future PAs over decades as in-space operations transition from single purpose missions to creation of PAs, such as laboratories and experimental stations which more closely resembling terrestrial laboratories that can easily adapt and evolve to new missions leveraging repeated visits to the PA. The ability to evolve enables PAs to rapidly respond to changing objectives resulting from new questions as our understanding improves. A recently initiated National Aeronautics and Space Administration (NASA) project in the Space Technology Mission Directorate (STMD) Game Changing Development (GCD) Program called the Precision Assembled Space Structure (PASS), leverages the advantages of SAA to develop technologies that enable efficient creation and evolution of hexagonal topologies; both planar (example: fuel depots) and curved (examples: telescopes and shelters). PASS will be used to provide context for the philosophy and concepts discussed as well as the decision and selections made. PASS objectives are: a) Develop confidence in SAA and on-orbit servicing, assembly and manufacturing (OSAM) technologies by executing a test campaign that uses a path-to-flight autonomous precision assembly process directly applicable to future space telescopes. b) Test autonomous technologies including automated path planning and error recovery, to emphasize a robust approach that relies on generic robots and special purpose tools. c) Validate critical component models using a digital twin that includes the assembled primary mirror support structure and assembly process. A digital twin is a high-fidelity simulation of the asset capable of predicting the on-orbit performance. The paper concludes after identifying the critical need for a modest assembly flight experiment to validate and develop confidence in the SAA paradigm, thus accelerating adoption of the benefits described. SAA is a game changing paradigm that enhances the ability of an organization to infuse new technology through rapid evolution of PAs while leveraging OSAM technologies.

Structural Modeling↗
NASA NTRSDate not supplied

Genesis Solar Wind – Capture, Return, Curate and Analyze: Looking Backward and Creating a Timeline

Introduction: In 1997 NASA’S Discovery Program selected the Genesis mission proposal to return solar wind samples to Earth for laboratory analyses. Principal Investigator Donald S. Burnett and the science team defined the purity of collector materials and ability to analyze solar wind composition to the precision required for planetary science. As a small mission, focused on a well-defined science goal, yet needing careful attention to engineering details, the communication among scientists and engineers, nurtured by Don Burnett, was exceptional. Genesis Mission and Curation Legacy: Genesis, as the first U. S. spacecraft to return astromaterial samples since Apollo, not only integrated the mission planning and flight teams, but also the science and sample curation teams during the mission development period. Since Genesis is a sample return mission, the Science Team was essential in certifying the collectors (sample containers for solar atoms). From inception, Genesis established mission funding for returned sample curation. JSC was lead in contamination control during mission preparation, including establishment of an ISO 4 cleanroom facility and use of ultrapure water (UPW) for cleaning flight hardware (and, as it turned out, for cleaning collectors after the mishap). Reliable, fast communication among scientists, engineers and curators at the hands-on level established deep respect among team members and efficient decision-making. JSC’s 50-years of astromaterial sample curation provided experienced sample processors onsite during recovery in Utah (a deep bench for emergency response). Post-recovery curation included iterative collaboration with science sample users to clean or verify cleanliness of samples. The science legacy from Genesis is addressed by Burnett and Jurewicz, this volume. In The Beginning: After Apollo sample return, Burnett and Marcia Neugebauer at JPL began discussing a solar wind sample return, with Neugebauer arguing that separate collection of solar wind regimes was essential science. By 1992 a solar wind sample return mission was presented at a workshop, and by 1994 a mission was proposed named Suess-Urey. The mission was re-proposed under a new name GENESIS and selected in 1997. Susan Niebur captured the Genesis mission history and stories, from high level management documents and from many interviews with participants [2]. Her account lets readers glimpse personality of participants in quotations from interviews. Need and Scope for Detailed Technical Timeline: A timeline constructed from lower level task documents has been initiated to document the resources and skills actually used, as well as task sequence or concurrency. Timelines for high level mission events are captured in two documents [1] [2] and for detailed re-entry events in [3]. A detailed technical timeline for Genesis mission and curation activities will provide data points for lower level tasks, such as ISO 4 curation facility construction time, preparation for nominal sample field recovery, mishap recovery, and UPW expansion. Changes in technology context 1990-2024: Semiconductor technologies were easily accessible in the U.S.A. (1990-1999), and the Genesis team used those resources for cleanroom design and UPW system expansion. Image documentation was changing from film to digital during cleanroom construction and payload cleaning (1997-2001). Engineering design was done using computer aided design proprietary software, making more difficult the archiving of payload configuration and materials. Email of documents, tracked delivery service and virtual meeting capability greatly improved communication efficiency. Information sources – Pre-launch mission preparation: Examples of mission science, engineering and contamination control are collector purity testing, payload design/fabrication and ISO 4 cleanroom construction. Information on timing of these activities comes from facility readiness reviews, management reviews, shipping documents, procurement documents, test reports, travel documents, laboratory logs, Quality Assurance documents, dates on images, participant notebooks and emails. Information sources – Sample return re-entry and field recovery activities: Information comes from event timelines produced by Mid-Air Recovery team, Lockheed team lead notes and from chase video, JPL Quality Assurance. Information also comes from images and logbooks from UTTR cleanroom operations and from curatorial documents. Information sources – Resulting science and sample cleaning processes: Agendas from the annual gatherings of the science team initially trace testing for collector purity/cleanliness, and after sample recovery, include collector cleaning and cleanliness assessment. Post-recovery documents include curatorial orders and procedures, sample allocation documents and LPSC abstracts. Timeline Objectives: A simple spreadsheet timeline with headers DATE, EVENT, PEOPLE, COMMENT, INFORMATION SOURCE has been initiated and currently has over 90 entries. While this is not definitive historical research, it is a quick look at the evolution of Genesis curation with pointers to documents or people with information. Engineers for future missions may find useful points of comparison for development of facilities. References:[1] Genesis Mission Reference Document, (2011) JPL D-62382.[2] Niebur S. M., edited by Brown D. W. (2023) NASA’s Discovery Program: The First 20 Years of Competitive Planetary Exploration, NASA-SP-2023-4238.[3] Genesis Mishap Investigation Board Report, Vol. 1 (July 2005).

solar wind↗
NASA NTRS2010

NASA Tech Briefs, September 2010

Topics covered include: Instrument for Measuring Thermal Conductivity of Materials at Low Temperatures; Multi-Axis Accelerometer Calibration System; Pupil Alignment Measuring Technique and Alignment Reference for Instruments or Optical Systems; Autonomous System for Monitoring the Integrity of Composite Fan Housings; A Safe, Self-Calibrating, Wireless System for Measuring Volume of Any Fuel at Non-Horizontal Orientation; Adaptation of the Camera Link Interface for Flight-Instrument Applications; High-Performance CCSDS Encapsulation Service Implementation in FPGA; High-Performance CCSDS AOS Protocol Implementation in FPGA; Advanced Flip Chips in Extreme Temperature Environments; Diffuse-Illumination Systems for Growing Plants; Microwave Plasma Hydrogen Recovery System; Producing Hydrogen by Plasma Pyrolysis of Methane; Self-Deployable Membrane Structures; Reactivation of a Tin-Oxide-Containing Catalys; Functionalization of Single-Wall Carbon Nanotubes by Photo-Oxidation; Miniature Piezoelectric Macro-Mass Balance; Acoustic Liner for Turbomachinery Applications; Metering Gas Strut for Separating Rocket Stages; Large-Flow-Area Flow-Selective Liquid/Gas Separator; Counterflowing Jet Subsystem Design; Water Tank with Capillary Air/Liquid Separation; True Shear Parallel Plate Viscometer; Focusing Diffraction Grating Element with Aberration Control; Universal Millimeter-Wave Radar Front End; Mode Selection for a Single-Frequency Fiber Laser; Qualification and Selection of Flight Diode Lasers for Space Applications; Plenoptic Imager for Automated Surface Navigation; Maglev Facility for Simulating Variable Gravity; Hybrid AlGaN-SiC Avalanche Photodiode for Deep-UV Photon Detection; High-Speed Operation of Interband Cascade Lasers; 3D GeoWall Analysis System for Shuttle External Tank Foreign Object Debris Events; Charge-Spot Model for Electrostatic Forces in Simulation of Fine Particulates; Hidden Statistics Approach to Quantum Simulations; Reconstituted Three-Dimensional Interactive Imaging; Determining Atmospheric-Density Profile of Titan; Digital Microfluidics Sample Analyzer; Radiation Protection Using Carbon Nanotube Derivatives; Process to Selectively Distinguish Viable from Non-Viable Bacterial Cells; and TEAMS Model Analyzer.

Source record↗
NASA NTRS2017

Structural Health Management of Damaged Aircraft Structures Using the Digital Twin Concept

The development of multidisciplinary integrated Structural Health Management (SHM) tools will enable accurate detection, and prognosis of damaged aircraft under normal and adverse conditions during flight. As part of the digital twin concept, methodologies are developed by using integrated multiphysics models, sensor information and input data from an in-service vehicle to mirror and predict the life of its corresponding physical twin. SHM tools are necessary for both damage diagnostics and prognostics for continued safe operation of damaged aircraft structures. The adverse conditions include loss of control caused by environmental factors, actuator and sensor faults or failures, and structural damage conditions. A major concern in these structures is the growth of undetected damage/cracks due to fatigue and low velocity foreign object impact that can reach a critical size during flight, resulting in loss of control of the aircraft. To avoid unstable, catastrophic propagation of damage during a flight, load levels must be maintained that are below a reduced load-carrying capacity for continued safe operation of an aircraft. Hence, a capability is needed for accurate real-time predictions of damage size and safe load carrying capacity for structures with complex damage configurations. In the present work, a procedure is developed that uses guided wave responses to interrogate damage. As the guided wave interacts with damage, the signal attenuates in some directions and reflects in others. This results in a difference in signal magnitude as well as phase shifts between signal responses for damaged and undamaged structures. Accurate estimation of damage size, location, and orientation is made by evaluating the cumulative signal responses at various pre-selected sensor locations using a genetic algorithm (GA) based optimization procedure. The damage size, location, and orientation is obtained by minimizing the difference between the reference responses and the responses obtained by wave propagation finite element analysis of different representative cracks, geometries, and sizes.

Seshadri, Banavara R.↗
NASA NTRSDate not supplied

Investigation of Hardware and Instrumentation to Measure Hand Grasp Activity with the Spacesuit Gloves

Introduction: During the 2022 suited injury summit, it was hypothesized that there will be concerns for hand and glove injuries for future exploration space missions, especially given the fact that the “total number of Extravehicular activity (EVA) hours and frequency” for lunar surface missions is expected to vastly increase [1]. It has been reported that the hands experienced the greatest “absolute numbers” of reported injuries and far exceeds other injuries during EVA [1, 2]. It was reported that the most fatiguing part of the surface EVA was the repetitive gripping tasks [3]. It was recommended that a “glove sub-team” be created to look at possible injury mechanism and mitigation strategies. Some of the recommendations that were suggested [1] are as follows: examine hand fatigue, utilize motion capture, examine the duration and frequency of hand movements, and identify frequent hand motions. We started assessing hardware and instrumentation to measure hand grasp activity in the pressurized glove environment. The purpose of this test was to perform a hardware evaluation for motion capture (MoCap) gloves obtained from StretchSense (Auckland, New Zealand). The specific gloves used were the Pro Fidelity and SuperSplay to determine the repeatability, reliability, feasibility, and useability inside of a pressurized gloved environment. Methods: The MoCap gloves were customized (e.g., battery/Bluetooth pack relocated to upper arm) to better suit the pressurized testing environment and protect the subject from unintentional injury (Fig. 1). Fourteen total subjects from different demographics (i.e., gender and pressurized glove experience level) participated in this test series. Testing included one session each of a baseline data collection (NASA Johnson Space Center (JSC) building 21) and a spacesuit glove box (Fig. 2 at JSC building 7 room 2027) data collection (under vacuum down to 4.3 psid), where each session lasted 3-5 hours. Controlled and reproducible tasks to systematically evaluate the repeatability and reliability of the hardware were performed during baseline data collection. Additionally, subjects performed simulated EVA-like tasks in a pressurized gloved environment. For all sessions, MoCap gloves were placed on each of the subjects’ hands and the signal from it, or the raw capacitance (Fig. 3), was analysed. The raw capacitance was used to estimate the open and closed hand states between the testing conditions and allow us to provide an offset caused by the pressurized environment. Results & Discussion: Initial observation with the bare hands (baseline) condition showed that the MoCap gloves appeared to track grasping and releasing of the fingers (opening and closing fist) with both high- and low-speed conditions, while adduction and abduction of the fingers were not relatively tracked. A hardware evaluation was done outside of the glove box to assess the reliability and repeatability of the MoCap glove. In one task, a point force was applied to various locations on the back of the hand. When the point force was applied to the space between the 1st digit and the pointer finger, there was a noticeable distortion to the MoCap data. Another task examining an increasing force from a 10 lb. sandbag applied to the back of the hand while lying flat on a table, showed a constant flat line with only a distortion when the weight was increased or added to the back of the hand. Fig. 3 shows an object relocation task where you can see when each individual finger “opened” and “closed” (changed position) when picking up and setting down the dumbbell. When the fingers were stationary, the signal remained relatively flat compared to the peaks and valleys that can be observed in Fig. 3. This study showed promising results and imperative input into an attempt to discriminate between hand states across various functional tasks and should be evaluated with context to the repeatability and reliability outcomes. Depending on the task done inside of the pressurized glove box environment and outside, the results appear to be affected by many different factors (i.e., drift, pressure, hand size, etc.). Significance: If this hardware proves to be reliable and repeatable in determining the open and closed hand states then this may provide critical insight into assisting in the characterization of the pressurized gloved environment and the effect on crew member exertion level. Ultimately, this tool will provide useful data for quantifying the repetitive nature of EVA training and tasks. Acknowledgments: The authors would like to acknowledge the NASA Mars Campaign Office for providing funding for this research. Lastly, thanks to all the engineers and technicians at NASA JSC who helped with this data collection. References: [1] Reiber, et al. (2022), NASA/TM-20220007605; [2] Scheuring, et al. (2009), Av., Sp., and Envir. Med. 80(2). [3] Scheuring, et al. (2007), NASA/TM–2007–214755.

Rachel L Thompson↗
NASA NTRS2016

Forward Skirt Structural Testing on the Space Launch System (SLS) Program

Structural testing was performed to evaluate heritage forward skirts from the Space Shuttle program for use on the Space Launch System (SLS) program. One forward skirt is located in each solid rocket booster. Heritage forward skirts are aluminum 2219 welded structures. Loads are applied at the forward skirt thrust post and ball assembly. Testing was needed because SLS ascent loads are roughly 40% higher than Space Shuttle loads. Testing objectives were to determine margins of safety, demonstrate reliability, and validate analytical models. Two forward skirts were structurally tested using the test configuration. The test stand applied loads to the thrust post. Four hydraulic actuators were used to apply axial load and two hydraulic actuators were used to apply radial and tangential loads. The first test was referred to as FSTA-1 (Forward Skirt Structural Test Article) and was performed in April/May 2014. The purpose of FSTA-1 was to verify the ultimate capability of the forward skirt subjected to ascent ultimate loads. Testing consisted of two liftoff load cases taken to 100% limit load followed by an ascent load case taken to 110% limit load. The forward skirt was unloaded to no load after each test case. Lastly, the forward skirt was tested to 140% limit and then to failure using the ascent loads. The second test was referred to as FSTA-2 and performed in July/August of 2014. The purpose of FSTA-2 was to verify the ultimate capability of the forward skirt subjected to liftoff ultimate loads. Testing consisted of six liftoff load cases taken to 100% limit load followed by the six liftoff cases taken to 140% limit load. Two ascent load cases were then tested to 100% limit load. The forward skirt was unloaded to no load after each test case. Lastly, the forward skirt was tested to 140% limit and then to failure using the ascent loads. The forward skirts on FSTA-1 and FSTA-2 successfully carried all applied liftoff and ascent load cases. Both FSTA-1 and FSTA-2 were tested to failure by increasing the ascent loads. Failure occurred in the forward skirt thrust post radius. The forward skirts on FSTA-1 and FSTA-2 had nearly identical failure modes. FSTA-1 failed at 1.72 times limit load and FSTA-2 failed at 1.62 times limit load. This difference is primarily attributed to variation in material properties in the thrust post region. Test data were obtained from strain gages, deflection gages, ARAMIS digital strain measurement, acoustic emissions, and high-speed video. Strain gage data and ARAMIS strain were compared to finite element (FE) analysis predictions. Both the forward skirt and tooling were modeled. This allows the analysis to simulate the loading as close as possible to actual test configuration. FSTA-1 and FSTA-2 were instrumented with over 200 strain gages to ensure all possible failure modes could be captured. However, it turned out that three gages provided critical strain data. One was located in the post bore and two on the post radius. More gages were not specified due to space limitations and the desire to not interfere with the use of the ARAMIS system on the post radius. Measured strains were compared to analysis results for the load cycle to failure. Note that FSTA-1 gages were lost before failure was reached. FSTA-2 gages made it to the failure load but one of the radius gages was lost before testing began. This gage was not replaced because of the time and cost associated with disassembly of the test structure. Correlation to analysis was excellent for FSTA-1. FSTA-2 was not quite as good because there was more residual strain from previous load cycles. FSTA-2 was loaded and unloaded with 12 liftoff cases and two ascent cases before taking the skirt to failure. FSTA-1 only had two liftoff cases and one ascent case before taking the skirt to failure. The ARAMIS system was used to determine strain at the post radius by processing digital images of a speckled paint pattern. Digital cameras recorded images of the speckled paint pattern. ARAMIS strain results for FSTA-2 just prior to failure. Note a high strain location develops near the left side. This high strain compares well to analysis prediction for both FSTA-1 and FSTA-2. The strain at this location was also plotted versus limit load. Both FSTA-1 and FSTA-2 had excellent correlation between ARAMIS and analysis strains. Acoustic emission (AE) sensors were used to monitor for damage formation that may occur during testing (e.g., crack formation and growth or propagation). AE was very important because after disassembly of FSTA-1, a crack was observed in the ball fitting radius. The ball fitting did not crack on FSTA-2. AE data was used to reconstruct when the crack occurred. The AE energy versus time plot for FSTA. The energy increased considerably at 850 seconds (152% limit load), indicating a crack could have formed at this point. The only visual evidence found that could have corresponded to this was the crack that initiated in the ball fitting. The cracks in the forward skirt aluminum structures would likely have been lower energy due to a lower modulus and all that were found after failure correlated to occurring after the initial crack in the post radius. This was verified by high-speed cameras used to record the failure.

Lohrer, J. D.↗
NASA NTRS2000

Color M-mode Doppler flow propagation velocity is a preload insensitive index of left ventricular relaxation: animal and human validation

OBJECTIVES: To determine the effect of preload in color M-mode Doppler flow propagation velocity (v(p)). BACKGROUND: The interpretation of Doppler filling patterns is limited by confounding effects of left ventricular (LV) relaxation and preload. Color M-mode v(p) has been proposed as a new index of LV relaxation. METHODS: We studied four dogs before and during inferior caval (IVC) occlusion at five different inotropic stages and 14 patients before and during partial cardiopulmonary bypass. Left ventricular (LV) end-diastolic volumes (LV-EDV), the time constant of isovolumic relaxation (tau), left atrial (LA) pre-A and LV end-diastolic pressures (LV-EDP) were measured. Peak velocity during early filling (E) and v(p) were extracted by digital analysis of color M-mode Doppler images. RESULTS: In both animals and humans, LV-EDV and LV-EDP decreased significantly from baseline to IVC occlusion (both p < 0.001). Peak early filling (E) velocity decreased in animals from 56 +/- 21 to 42 +/- 17 cm/s (p < 0.001) without change in v(p) (from 35 +/- 15 to 35 +/- 16, p = 0.99). Results were similar in humans (from 69 +/- 15 to 53 +/- 22 cm/s, p < 0.001, and 37 +/- 12 to 34 +/- 16, p = 0.30). In both species, there was a strong correlation between LV relaxation (tau) and v(p) (r = 0.78, p < 0.001, r = 0.86, p < 0.001). CONCLUSIONS: Our results indicate that color M-mode Doppler v(p) is not affected by preload alterations and confirms that LV relaxation is its main physiologic determinant in both animals during varying lusitropic conditions and in humans with heart disease.

Non-NASA Center↗
NASA NTRS2016

Image Correlation Pattern Optimization for Micro-Scale In-Situ Strain Measurements

The accuracy and precision of digital image correlation (DIC) is a function of three primary ingredients: image acquisition, image analysis, and the subject of the image. Development of the first two (i.e. image acquisition techniques and image correlation algorithms) has led to widespread use of DIC; however, fewer developments have been focused on the third ingredient. Typically, subjects of DIC images are mechanical specimens with either a natural surface pattern or a pattern applied to the surface. Research in the area of DIC patterns has primarily been aimed at identifying which surface patterns are best suited for DIC, by comparing patterns to each other. Because the easiest and most widespread methods of applying patterns have a high degree of randomness associated with them (e.g., airbrush, spray paint, particle decoration, etc.), less effort has been spent on exact construction of ideal patterns. With the development of patterning techniques such as microstamping and lithography, patterns can be applied to a specimen pixel by pixel from a patterned image. In these cases, especially because the patterns are reused many times, an optimal pattern is sought such that error introduced into DIC from the pattern is minimized. DIC consists of tracking the motion of an array of nodes from a reference image to a deformed image. Every pixel in the images has an associated intensity (grayscale) value, with discretization depending on the bit depth of the image. Because individual pixel matching by intensity value yields a non-unique scale-dependent problem, subsets around each node are used for identification. A correlation criteria is used to find the best match of a particular subset of a reference image within a deformed image. The reader is referred to references for enumerations of typical correlation criteria. As illustrated by Schreier and Sutton and Lu and Cary systematic errors can be introduced by representing the underlying deformation with under-matched shape functions. An important implication, as discussed by Sutton et al., is that in the presence of highly localized deformations (e.g., crack fronts), error can be reduced by minimizing the subset size. In other words, smaller subsets allow the more accurate resolution of localized deformations. Contrarily, the choice of optimal subset size has been widely studied and a general consensus is that larger subsets with more information content are less prone to random error. Thus, an optimal subset size balances the systematic error from under matched deformations with random error from measurement noise. The alternative approach pursued in the current work is to choose a small subset size and optimize the information content within (i.e., optimizing an applied DIC pattern), rather than finding an optimal subset size. In the literature, many pattern quality metrics have been proposed, e.g., sum of square intensity gradient (SSSIG), mean subset fluctuation, gray level co-occurrence, autocorrelation-based metrics, and speckle-based metrics. The majority of these metrics were developed to quantify the quality of common pseudo-random patterns after they have been applied, and were not created with the intent of pattern generation. As such, it is found that none of the metrics examined in this study are fit to be the objective function of a pattern generation optimization. In some cases, such as with speckle-based metrics, application to pixel by pixel patterns is ill-conditioned and requires somewhat arbitrary extensions. In other cases, such as with the SSSIG, it is shown that trivial solutions exist for the optimum of the metric which are ill-suited for DIC (such as a checkerboard pattern). In the current work, a multi-metric optimization method is proposed whereby quality is viewed as a combination of individual quality metrics. Specifically, SSSIG and two auto-correlation metrics are used which have generally competitive objectives. Thus, each metric could be viewed as a constraint imposed upon the others, thereby precluding the achievement of their trivial solutions. In this way, optimization produces a pattern which balances the benefits of multiple quality metrics. The resulting pattern, along with randomly generated patterns, is subjected to numerical deformations and analyzed with DIC software. The optimal pattern is shown to outperform randomly generated patterns.

Bomarito, G. F.↗