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NASA NTRS1998

On-board Science Understanding: NASA Ames' Efforts

In the near future NASA intends to explore various regions of our solar system using robotic devices such as rovers, spacecraft, airplanes, and/or balloons. Such platforms will likely carry imaging devices, and a variety of analytical instruments intended to evaluate the chemical and mineralogical nature of the environment(s) that they encounter. Historically, mission operations have involved: (1) return of scientific data from the craft; (2) evaluation of the data by space scientists; (3) recommendations of the scientists regarding future mission activity; (4) commands for achieving these activities being transmitted to the craft; and (5) the activity being undertaken. This cycle is then repeated for the duration of the mission with command opportunities once or perhaps twice per day. In a rapidly changing environment, such as might be encountered by a rover traversing hundreds of meters a day or a spacecraft encountering an asteroid, this historical cycle is not amenable to rapid long range traverses, discovery of novelty, or rapid response to any unexpected situations. In addition to real-time response issues, the nature of imaging and/or spectroscopic devices are such that tremendous data volumes can be acquired, for example during a traverse. However, such data volumes can rapidly exceed on-board memory capabilities prior to the ability to transmit it to Earth. Additionally, the necessary communication band-widths are restrictive enough so that only a small portion of these data can actually be returned to Earth. Such scenarios clearly require the enabling of some crucial decisions to be made on-board by these robotic explorers. These decisions transcend the electromechanical control, health, and navigation issues associated with robotic operations. Instead they focus upon a long term goal of automating scientific discovery based upon data returned by sensors of the robot craft. Such an approach would eventually enable it to understand what is interesting because the data deviates from expectations generated by current theories/models of planetary processes that could have resulted in the observed data. Such interesting data and/or conclusions can then be selectively transmitted to Earth thus reducing memory and communications demands.

Roush, Ted L.↗

NASA NTRS1993

Verification of a two-dimensional infiltration model for the resin transfer molding process

A two-dimensional finite element model for the infiltration of a dry textile preform by an injected resin was verified. The model, which is based on the finite element/control volume technique, determines the total infiltration time and the pressure increase at the mold inlet associated with the RTM process. Important input data for the model are the compaction and permeability behavior of the preform along with the kinetic and rheological behavior of the resin. The compaction behavior for several textile preforms was determined by experimental methods. A power law regression model was used to relate fiber volume fraction to the applied compaction pressure. Results showed a large increase in fiber volume fraction with the initial application of pressure. However, as the maximum fiber volume fraction was approached, the amount of compaction pressure required to decrease the porosity of the preform rapidly increased. Similarly, a power law regression model was used to relate permeability to the fiber volume fraction of the preform. Two methods were used to measure the permeability of the textile preform. The first, known as the steady state method, measures the permeability of a saturated preform under constant flow rate conditions. The second, denoted the advancing front method, determines the permeability of a dry preform to an infiltrating fluid. Water, corn oil, and an epoxy resin, Epon 815, were used to determine the effect of fluid type and viscosity on the steady state permeability behavior of the preform. Permeability values measured with the different fluids showed that fluid viscosity had no influence on the permeability behavior of 162 E-glass and TTI IM7/8HS preforms. Permeabilities measured from steady state and advancing front experiments for the warp direction of 162 E-glass fabric were similar. This behavior was noticed for tests conducted with corn oil and Epon 815. Comparable behavior was observed for the warp direction of the TTI IM7/8HS preform and corn oil. Mold filling and flow visualization experiments were performed to verify the analytical computer model. Frequency dependent electromagnetic sensors were used to monitor the resin flow front as a function of time. For the flow visualization tests, a video camera and high resolution tape recorder were used to record the experimental flow fronts. Comparisons between experimental and model predicted flow fronts agreed well for all tests. For the mold filling tests conducted at constant flow rate injection, the model was able to accurately predict the pressure increase at the mold inlet during the infiltration process. A kinetics model developed to predict the degree of cure as a function of time for the injected resin accurately calculated the increase in the degree of cure during the subsequent cure cycle.

Hammond, Vincent H.↗

NASA NTRS2024

EdgeCortix SAKURA-I Machine-Learning, PCIe Accelerator SEE Heavy Ion Test Report

To enable autonomy in space, machine-learning and computer vision applications become invaluable for sensor processing. However, these algorithms are computationally complex and unfeasible for many embedded central processing units (CPUs) and usually require external coprocessors, such as graphics processing units (GPUs) or accelerators specific to the application, including application specific integrated circuits (ASICs). In power-constrained systems, GPUs tend to consume more power than is acceptable (>40W), so lower-power accelerators have shown promise to provide the performance needed under spacecraft constraints. For radiation engineers, developing methodologies that can properly test CPUs, GPUs, and accelerators, and enable comparisons between them remains a necessary complication to solve as the devices become more complex. The methodology in this test aims to be a start in developing a baseline single-event effect (SEE) test for client-device machine learning accelerators. This category of devices do not host their own operating system. This testing campaign is a continuation of a previous 200 MeV proton test performed in January 2024. This report covers two heavy ion tests of the SAKURA-I card: one in April 2024, and one in June 2024. Additional data was needed after the April test due to ion-range issues experienced at higher linear-energy transfers (LETs). These range issues are described in more detail in Section 8. This experiment characterizes SEEs and data error susceptibility of the EdgeCortix SAKURA-I machine-learning accelerator under heavy ions. The device was monitored for single event upsets (SEUs) and single event functional interrupts (SEFIs) at the Lawrence Berkeley National Laboratory’s 88-inch cyclotron. The SAKURA-I board accelerates machine-learning inference applications on a host computer through a PCIex16 connection. For the purposes of devising an end to end automated analysis workflow for this experiment, the YOLO-V5 and SSD300 objection-detection models, and the ResNet-50, EfficientNet, and MobileNetV2 image classification models were used as a representative suite of analytical machine-learning models.

Seth S Roffe↗

NASA NTRS2017

NIAC Phase 1 Final Study Report on Titan Aerial Daughtercraft

Saturns giant moon Titan has become one of the most fascinating bodies in the Solar System. Even though it is a billion miles from Earth, data from the Cassini mission reveals that Titan has a very diverse, Earth-like surface, with mountains, fluvial channels, lakes, evaporite basins, plains, dunes, and seas [Lopes 2010] (Figure 1). But unlike Earth, Titans surface likely is composed of organic chemistry products derived from complex atmospheric photochemistry [Lorenz 2008]. In addition, Titan has an active meteorological system with observed storms and precipitation-induced surface darkening suggesting a hydrocarbon cycle analogous to Earths water cycle [Turtle 2011].Titan is the richest laboratory in the solar system for studying prebiotic chemistry, which makes studying its chemistry from the surface and in the atmosphere one of the most important objectives in planetary science [Decadal 2011]. The diversity of surface features on Titan related to organic solids and liquids makes long-range mobility with surface access important [Decadal 2011]. This has not been possible to date, because mission concepts have had either no mobility (landers), no surface access (balloons and airplanes), or low maturity, high risk, and/or high development costs for this environment (e,g. large, self-sufficient, long-duration helicopters). Enabling in situ mobility could revolutionize Titan exploration, similarly to the way rovers revolutionized Mars exploration. Recent progress on several fronts has suggested that small-scale rotorcraft deployed as daughtercraft from a lander or balloon mothercraft may be an effective, affordable approach to expanding Titan surface access. This includes rapid progress on autonomous navigation capabilities of such aircraft for terrestrial applications and on miniaturization, driven by the consumer mobile electronics market, of high performance of sensors, processors, and other avionics components needed for such aircraft. Chemical analysis, for example with a mass spectrometer, will be important to any Titan surface mission. Anticipating that it may be more practical to host chemical analysis instruments on a mothership than a daughtercraft, we defined system and mission concepts that deploy a small rotorcraft, termed a Titan Aerial Daughtercraft (TAD), from a lander or balloon to perform high-resolution imaging and mapping, potentially land to acquire microscopic images or other in situ measurements, and acquire samples to return to analytical instruments on the mothership. In principle, the ability to recharge batteries in TAD from a radioisotope or other long-lived power source on the mothership could enable multiple sorties. For a lander-based mission, a variety of landing sites is conceivable, including near lake margins, in dry lake beds, or in regions of plains, dunes, or putative cryovolanic or impact melt features. Such missions may require landing with greater precision than in previous missions (Huygens) and mission studies; this could also enhance the ability of TAD to reach interesting terrain from the landing site. Precision descent may also benefit balloon missions, with or without a daughtercraft, by increasing the probability that the balloon will drift over desired terrain early in its mission. Given these potential benefits, the overall concept studied here includes brief consideration of precision descent for landing or balloon deployment, followed by one or more sorties by a rotorcraft deployed from the mothership, with the ability to return to the mothership.

Saturn↗

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.↗