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Development of an Inertial Sensor-based Methodology for Spacesuited Geology Task Assessments during Simulated Lunar Extravehicular Activities

Lunar surface exploration during Artemis missions will require the specific skill set of geology sampling. Apollo astronauts had extensive training and used specialized tools to collect lunar rocks, core samples, pebbles, sand, and dust. The inflexibility of the pressurized Apollo spacesuits forced sampling to be taken at a standstill posture. However, new exploration spacesuits are expected to incorporate advanced materials and joint bearings, allowing for greater mobility and a wider range of functional postures. Thus, science and exploration during Artemis missions will likely involve a variety of standing, squatting, and kneeling postures. In preparation for future lunar exploration missions, NASA provides geologic training to astronauts and other mission personnel. This professional training with a spacesuit in simulated lunar environments will enhance performance and reduce risk of injury to astronauts on the lunar surface. However, anecdotally, untrained or newly trained people wearing prototype planetary spacesuits have been observed to performing motions differently than a trained geologist would when conducting the same geology sampling tasks. Therefore, a tool for evaluating geology postures at extravehicular activity (EVA) training facilities becomes required. In this paper, we introduce a novel inertial measurement unit (IMU)-based method of geology task assessments in spacesuited conditions during simulated lunar EVAs. As a case study, two subjects (one geologist and one non-geologist) participated and donned the Mark III prototype planetary spacesuit during offloading with the spreader bar gimbal in NASA’s Active Response Gravity Offload System (ARGOS). For automated geology task assessments, the spacesuit was instrumented with three wireless IMUs (APDM Opal, OR, USA): one on the chest and one each on the left and right ankle bearings. Then subjects performed geology tasks using various tools (rake, trench, hammer chisel, scoop, and drive tube) for 45 minutes each. The chest IMU measured the torso tilt angle in the sagittal plane. We used an ensemble learning method with the ankle IMUs to discriminate between standing and kneeling activities. IMU data were processed using custom MATLAB (Mathworks, MA, USA) software. In our case study, the developed method was able to discriminate differences in standing and kneeling activity levels between subjects who were all highly experienced with spacesuited testing. Our preliminary data showed one subject maintained the constant and lower range of the upper body tilt angle while both standing and kneeling, while the other subject showed more variation of the upper body tilt angle and preferred bending the upper body rather than changing from standing to kneeling posture and vice versa. While geology experience may be a factor, these results need further investigation as suit sizing and ARGOS offloading configurations have been proven to have a significant influence on suited ARGOS tasks. Also, more subjects will be needed to complete these tasks for validation. IMU-based geology task assessments can provide useful information for geology training programs. Additionally, our IMU-based posture analysis can provide new insights into how to evaluate spacesuited geology task characteristics of astronauts during simulated lunar EVAs.

Kyoung Jae Kim↗

NASA NTRS2010

Colorimetric Solid Phase Extraction (CSPE): Using Color to Monitor Spacecraft Water Quality

In August 2009, an experimental water quality monitoring kit based on Colorimetric Solid Phase Extraction (CSPE) technology was delivered to the International Space Station (ISS). The kit, called the Colorimetric Water Quality Monitoring Kit (CWQMK), was launched as a Station Development Test Objective (SDTO) experiment to evaluate the suitability of CSPE technology for routine use monitoring water quality on the ISS. CSPE is a sorption-spectrophotometric technique that combines colorimetric reagents, solid-phase extraction, and diffuse reflectance spectroscopy to quantify trace analytes in water samples. In CSPE, a known volume of sample is metered through a membrane disk that has been impregnated with an analyte-specific colorimetric reagent and any additives required to optimize the formation of the analyte-reagent complex. As the sample flows through the membrane disk, the target analyte is selectively extracted, concentrated, and complexed. Formation of the analyte-reagent complex causes a detectable change in the color of the membrane disk that is proportional to the amount of analyte present in the sample. The analyte is then quantified by measuring the color of the membrane disk surface using a hand-held diffuse reflectance spectrophotometer (DRS). The CWQMK provides the capability to measure the ionic silver (Ag +) and molecular iodine (I2) in water samples on-orbit. These analytes were selected for the evaluation of CSPE technology because they are the biocides used in the potable water storage and distribution systems on the ISS. Biocides are added to the potable water systems on spacecraft to inhibit microbial growth. On the United States (US) segment of the ISS molecular iodine serves as the biocide, while the Russian space agency utilizes silver as a biocide in their systems. In both cases, the biocides must be maintained at a level sufficient to control bacterial growth, but low enough to avoid any negative effects on crew health. For example, the presence of high levels of iodine in water can cause taste and odor issues that result in decreased water consumption by the crew. There are also concerns about potential impacts on thyroid function following exposure to high levels of iodine. With silver, there is a risk of developing argyria, an irreversible blue-gray discoloration of the skin, associated with long term consumption of water containing high concentrations of silver. The need to ensure that safe, effective levels of biocide are maintained in the potable water systems on the ISS provides a perfect platform for evaluating the suitability of CSPE technology for in-flight water quality monitoring. This paper provides an overview of CSPE technology and details on the silver and iodine methods used in the CWQMK. It also reports results obtained during in-flight analyses performed with the CWQMK and briefly discusses other potential applications for CSPE technology in both the spacecraft and terrestrial environments.

Gazda, Daniel B.↗

NASA NTRS2002

Overview of the High Performance Antiproton (HiPAT) Experiment

The annihilation of matter with antimatter represents the highest energy density of any known reaction, producing 10(exp 8) MJ/g, approximately 10 orders of magnitude more energy per unit mass than chemical based combustion. To take the first step towards using this energy for propulsion applications the NASA MSFC Propulsion Research Center (PRC) has initiated a research activity examining the storage of low energy antiprotons. Storage was identified as a key enabling technology since it builds the experience base necessary to understand the handling of antiprotons for virtually all utilization and high-density storage concepts. To address this need, a device referred to as the High Performance Antiproton Trap (HiPAT) is under development at the NASA MSFC PRC. The HiPAT is an electromagnetic system (Penning-Malmberg design) consisting of a 4 Tesla superconductor, a high voltage confinement electrode system (operation up to 20 KV), and an ultra high vacuum test section (operating in the 10(exp -12) torr range). The system was designed to be portable with an ultimate goal of maintaining 10(exp 12) charged particles with a half-life of 18 days. Currently, this system is being experimentally evaluated using normal matter ions which are cheap to produce and relatively easy to handle. These normal ions provide a good indication of overall trap behavior, with the exception of assessing annihilation losses. The ions are produced external to HiPAT using two hydrogen ion sources, with adjustable beam energy and current. Ion are transported in a beam line and controlled through the use of electrostatic optics. These optics serve to both focus and gate the incoming ions, providing microsecond-timed pulses that are dynamically captured by cycling the HiPAT electric containment field like a 'trap door'. The layout of this system more closely simulates the operations expected at an actual antiproton production facility where 'packets' of antiprotons with pulse widths measured in 100's of nanoseconds could be provided. Initial dynamic capture experiments have been performed with both trap and ton source system functioning at approximately 10% of maximum levels, minimizing the potential for extraneous effects. Dynamic trapping techniques demonstrated the successful capture of millions of hydrogen ions with good agreement with the predicted loading based on the timing sequence, trap electric field, and ion beam current. These techniques will be expanded to examine multiple shot capture or 'stacking' to increase the total number of ions stored within HiPAT.

Martin, James J.↗

NASA NTRS2004

Stacking Multiple Ion Captures in The High Performance Antiproton Trap (HiPAT)

The High performance Antiproton Trap (HiPAT) research project was initiated by the Marshall Space Flight Center's propulsion Research Center to examining the fundamental behavior of low energy antiprotons. Stored antiproton would ultimately be used for experimental demonstration of basic propulsive concepts. Matter-antimatter annihilation produces approximately 10(exp 8) MJ/g nearly 10 orders of magnitude more energy per unit mass than chemical based combustion, hence NASA's interest. To achieve containment, HiPAT utilizes a type of electromagnetic bottle know as a Penning trap positioned within an ultrahigh vacuum test section. Recently, the HiPAT hardware configuration has been enhanced to facilitate the capture of multiple normal matter ion burst. This endeavor is often referred to as "stacking" and used to increasing the number of captured particles. A prior normal matter experimental effort, successfully demonstrated the effectiveness of single burst capture. The stacking process is accomplished by manipulating the electric field generated by the confinement electrodes i.e. adjusting the well potential depth. These potential well values are initially configured to maximize the quantity of captured ions per burst; shallow wells with a depth of 100 volt or less (referenced to the incoming ion beam energy) are typically selected. Once captured, a cooling interval is required to reduce the energy of trapped particles below the lower extent of the "trap door" (or leading electrode) ion emitting potential. This is necessary such that a new burst of hot ions can be introduced while preventing those already inside from escaping. The cooling time is driven by a combination of mechanisms such as synchrotron radiation, background gas scattering, and resistive damping in a time scale on the order of minutes. A potential for reducing this hold period is to actively manipulate the electric field shape, using the power supply control system, to produce a deeper potential well. The trapped ions ride down the morphing well to a lower potential energy, leaving margin to once again cycle the "trap door" capturing a new burst while limiting the number of escaping ions. By adjusting the magnitude and timing of the potential well shaping, subsequent shots from the ion beam can be captured on a time scale shorter then that dictated by the standard inject, capture and cool technique. Currently, experimental tests are under way examining the functionally of this system for stacking multiple ions bursts within the HiPAT system.

Martin, James J.↗

NASA NTRS2014

Controllable Multi-Functional Heat Exchanger for Space Applications

Team Spacering will design SpaceRing, a cooling and waste heat recycling system that addresses NASA’s interest for a cooling and power-generating unit in its prototype deep space habitat[1]. The merits of this system are as follows: - Controllable cooling is critical in maintaining a habitable environment and in the functionality of life support systems, powering electronics and other devices in a spacecraft. - Power is expensive to produce in a space environment. Converting wasted thermal energy into electricity will save energy and money for the space station. Space habitation is a highly complex endeavor. Consequently, the SpaceRing must adhere to additional constraints, which include: - Lack of natural fluid or gas convection due to micro-gravity environment - Limited range for heat source and cold sink temperature - Subject to high fluctuations of incoming thermal energy - Minimal weight due to the high cost of transporting items into space After consulting with NASA and experts in thermal studies, several design objectives were identified and are listed below in order of importance: - High cooling capacity - Reliable safety control and alert system - Maximization of energy generation from wasted heat - Optimization of cooling capability and power generation - Long operational life and minimization of maintenance In space, conventional cooling systems utilize passive heat pipe systems for small-scale heat rejection and pumped pipes with heat exchangers for large-scale heat rejection. Thermal power generation in space is mainly achieved by using thermoelectric material that produces electric energy from temperature differentials. We propose a design that combines cooling and thermoelectric power generation. Using a hot pipe connected to a heat source, a cold pipe connected to a radiator, a heat exchanger in contact with both pipes, and a pump in each pipe to move the fluid, we make an active cooling system. The thermoelectric material is inserted in the heat exchanger between the hot and cold pipes to extract energy from the maximum temperature difference coming from the two pipes. It also provides controllable cooling capacity through the use of the thermoelectric material as cooling modules. We have tested our system under target heat source and sink conditions and measured the temperatures and flow rates. Our preliminary results are promising, demonstrating the output of 25 Watts of power on average. We are in the process of running control tests to compare the heat transfer performance without the thermoelectric generators, which is vital in determining whether or not the generators introduce an unacceptable amount of thermal resistance. While some control tests have been run already, the results have been noisy. We have modified our testing environment and data acquisition methods to allow for simple comparison between the control test results and thermoelectric performance results. Lastly, we have modified the heat exchanger design slightly to include acrylic baffles. This will allow the heat to flow through the heat exchanger more efficiently. We have presented our preliminary results to NASA and will deliver the final product by the end of May 2014.

Lee Xiong↗

NASA NTRS2019

Lightning Strike Distance Distribution Beyond a Preexisting Lightning Area

The 45th Weather Squadron (45 WS) asked the Applied Meteorology Unit (AMU) to review the 30-year-old, lightning stand-off distances of 5 nautical miles (nmi) for applicability to today's operations. This was based on the realization that previous lightning strike distance studies did not match how 45 WS issues lightning warnings (Roeder, 2008). The previous lightning distance studies were from the point of origin of the lightning or the average starting location that would tend to be in the core of the thunderstorm. However, the 45 WS issues lightning warnings based on the edge of a preexisting lightning area. Before beginning the AMU project, it took several years to develop a method to calculate a distance distribution beyond a preexisting area (Roeder, 2015). The AMU pulled Lightning Detection and Ranging (LDAR) sensor data from 1/1/2013 to 12/31/2013. This dataset consisted of 37 million individual source data points from the LDAR sensors. Only sources within 50 km north, south, east or west of the LDAR grid center were included in the dataset. This limited the use of LDAR data to that with the greatest accuracy of source detection and increased data processing. Points were grouped into flashes based on spatial and temporal criteria. Based on the sensitivity analysis the AMU performed on the flash clustering algorithm, a time value of 0.3 seconds was found to model flashes adequately. Distance parameters were tested from 1,500 to 7,500 meters (m) in 500 m increments. Distance parameters of both 3,000 m and 4,000 m produced results in the plotting tool that were most representative of the physical behavior of lightning. Thus statistics were gathered for the most representative of these spatial and temporal criteria on the flash size and the polygon expansion distance in order to find the correct data distributions. The best fit curves for the LDAR polygon expansion frequency vs. distances for both the 3 kilometer (km) and 4 km distance threshold values were exponential decay functions and had R2 values of > 0.998, indicating good model fits. The equations of the best fit curves were then used to calculate a desired safety radius of 4 nmi for either 3 km or 4 km distance threshold criteria. The AMU analysis concludes the safe reduction of the 5 nmi lightning warning circles to 4 nmi should improve the operational impact by 36% if based on distance from the center of the property area being protected. If based on the edge of the property being protected, then the reduction is 4.5 nmi to 4 nmi and the operational impact is decreased by 21%. For the 6 nmi lightning warning circles, the recommended 4 nmi stand-off distance will result in a safe reduction of operational impact of 31% if based on the center of the area being protected, or 16% if based on the edge of the property.

Flash clustering algorithm↗

NASA NTRS2011

From Paper to Production to Test: An Update on NASA's J-2X Engine for Exploration

The NASA/industry team responsible for developing the J-2X upper stage engine for the Space Launch System (SLS) Program has made significant progress toward moving beyond the design phase and into production, assembly, and test of development hardware. The J-2X engine exemplifies the SLS Program goal of using proven technology and experience from more than 50 years of United States spaceflight experience combined with modern manufacturing processes and approaches. It will power the second stage of the fully evolved SLS Program launch vehicle that will enable a return to human exploration of space beyond low earth orbit. Pratt & Whitney Rocketdyne (PWR) is under contract to develop and produce the engine, leveraging its flight-proven LH2/LOX, gas generator cycle J-2 and RS-68 engine capabilities, recent experience with the X-33 aerospike XRS-2200 engine, and development knowledge of the J-2S tap-off cycle engine. The J- 2X employs a gas generator operating cycle designed to produce 294,000 pounds of vacuum thrust in primary operating mode with its full nozzle extension. With a truncated nozzle extension suitable to support engine clustering on the stage, the nominal vacuum thrust level in primary mode is 285,000 pounds. It also has a secondary mode, during which it operates at 80 percent thrust by altering its mixture ratio. The J-2X development philosophy is based on proven hardware, an aggressive development schedule, and early risk reduction. NASA Marshall Space Flight Center (MSFC) and PWR began development of the J-2X in June 2006. The government/industry team of more than 600 people within NASA and PWR successfully completed the Critical Design Review (CDR) in November 2008, following extensive risk mitigation testing. Assembly of the first development engine was completed in May 2011 and the first engine test was conducted at the NASA Stennis Space Center (SSC), test stand A2, on 14 July 2011. Testing of the first development engine will continue through the autumn of 2011, be paused for test stand modifications to the passive diffuser, and then restart in the spring of 2012. This testing will be followed by specialized powerpack testing intended to examine the design and operating margins of the engine turbomachinery. The development plan beyond this point leads through more system-level, engine testing of several samples, analytical model validation activities, functional and performance verification, and then ultimate certification to support human spaceflight. This paper will discuss the J-2X development background, provide top-level information on design and development planning, and will explore some of the development challenges and mitigation activities pursued to date.

Kynard, Michael↗

NASA NTRS1997

New Anti-Corrosive Coatings with Resin-Bonded Polyaniline and Related Electroactive Groups

It is already known that polyaniline (an electroactive polymer) functions as a corrosion inhibitor for steel and in view of the fact that it is known to perform in the presence of hydrochloric acid, it has been considered likely that it may be useful to NASA for protecting launch structures at KSC which are exposed to not only continual ocean-side salt spray but also to hydrochloric acid at the times that solid-fuel boosters are fired. The currently used zinc-rich silicate-bonded coating is not wholly protective against the hydrochloric acid. Water pollution from zinc salts is another concern. Other earlier and concurrent NASA sponsored projects have been focussed on polyaniline specifically. Our project, administered for NASA by Dr. K. Thompson of KSC and these more-specifically polyaniline-related projects are included in a CRADA coordinated by Dr. F. Via of Akzo Nobel. A parallel project at Polytechnic under Prof K. Levon concentrated more specifically on polyaniline with various dopants. Our exploratory project reported herein was aimed at broadening the range of such corrosion inhibitors, to give protective paint compounders a wider latitude for adding corrosion inhibitors having polyaniline-like performance, and thus we diverged in several probing directions from polyaniline. Our working hypothesis was that physical variants of polyaniline, such as supported formulations on pigments or carriers, and chemical variants of polyaniline, including those having no electroconductive character, may have enhanced anticorrosion activity. We also hypothesized that small (non-polymeric) molecules having structures related to those occurring in polyaniline, may be active as corrosion inhibitors. We did preliminary testing, using an ASTM salt spray method at a nearby commercial paint testing laboratory. Our most interesting findings were that a non-electroconductive meta-isomer of polyaniline showed some corrosion activity, suggesting that the features of the polyaniline molecule associated with conductivity are not necessary for the anticorrosion action. Also, signtficantly, small molecular weight aromatic diamines and diimines resembling the reduced and the oxidized repeating unit in polyaniline showed an interesting degree of anticorrosive activity, suggesting that the polymeric feature of polyaniline is not necessary for anticorrosion action.

Weil, Edward D.↗

NASA NTRS1995

The JPL Field Emission Spectrometer

The Jet Propulsion Laboratory (JPL) Field Emission Spectrometer (FES) was built by Designs and Prototypes based on a set of functional requirements supplied by JPL. The instrument has a spectral resolution of 6 wavenumbers (wn) and can acquire spectra from either the Mid Infrared (3-5 mu m) or the Thermal Infrared (8-12 pm) depending on whether the InSb or HgCdTe detector is installed respectively. The instrument consists of an optical head system unit and battery. The optical head which is tripod mounted includes the interferometer and detector dewar assembly. Wavelength calibration of the interferometer is achieved using a Helium-Neon laser diode. The dewar needs replenishing with liquid Nitrogen approximately every four hours. The system unit includes the controls for operation and the computer used for acquiring viewing and processing spectra. Radiometric calibration is achieved with an external temperature-controlled blackbody that mounts on the fore-optics of the instrument. The blackbody can be set at 5 C increments between 10 and 55 C. The instrument is compact and weighs about 33 kg. Both the wavelength calibration and radiometric calibration of the instrument have been evaluated. The wavelength calibration was checked by comparison of the position of water features in a spectrum of the sky with their position in the output from a high resolution atmospheric model. The results indicatethat the features in the sky spectrum are within 6-8 wn of their position ill the model spectrum. The radiometric calibration was checked by first calibrating the instrument using the external blackbody supplied with the instrument and then measuring the radiance from another external blackbody at a series of temperatures. The temperatures of these radiance spectra were then recovered by inventing Planck's law and the recovered temperatures compared lo the measured blackbody temperature. These results indicate that radiometric calibration is good to 0.5 C over the range of temperatures 10 to 55 C. The results also indicate that the instrument drifts slowly over time and should be recalibrated every 20 to 30 minutes in the field to ensure good radiometric fidelity. The instrument has now been extensively tested in the field in the United States and Australia. These in situ field measurements are being used to validate emissivity spectra recovered from the Thermal Infrared Multispectral Scanner (TIMS) and also the Australian CO2 Laser. The availability of in situ measurements is proving crucial to validation of the spectra derived from the airborne instruments since many natural surfaces cannot be easily transported back to the laboratory.

Hook, Simon J.↗

NASA NTRS2018

NASA Kennedy Space Center: Contributions to Sea Turtle Science and Conservation

The National Aeronautics and Space Administration (NASA) is a United States (US) federal agency that oversees US space exploration and aeronautical research. NASA's primary launch site, Kennedy Space Center (KSC) is located along the east coast of Florida, on Cape Canaveral and the western Atlantic Ocean. The natural environment within KSC's large land boundaries, not only functions as an extensive safety buffer-area, it performs simultaneously as a wildlife refuge and a national seashore. In the early 1960s, NASA was developing KSC for rocket launches and the US was establishing an awareness of, and commitment to protecting the environment. The US began creating regulations that required the consideration of the environment when taking action on federal land or with federal funds. The timing of the US Endangered Species Act (1973), the US National Environmental Policy Act (1972), coincided with the planning and implementation of the US Space Shuttle Program. This resulted in the first efforts to evaluate the impacts of space launch operation operations on waterways, air quality, habitats, and wildlife. The first KSC fauna and flora baseline studies were predominantly performed by University of Central Florida (then Florida Technological University). Numerous species of relative importance were observed and sea turtles were receiving regulatory review and protection as surveys by Dr. L Ehrhart (UCF) from 1973-1978 described turtles nesting along the KSC beaches and foraging in the KSC lagoon systems. These data were used in the first NASA Environmental Impact Statement for the Space Transportation System (shuttle program) in 1980. In 1982, NASA began a long term ecological monitoring program with contracted scientists on site. This included efforts to track sea turtle status and trends at KSC and maintain protective measures for these species. Many studies and collaborations have occurred on KSC over these last 45 years with agencies (USFWS, NOAA, NAVY), students, and universities (UCF, University of Toronto, Texas A&M, UF). This presentation will review the various studies and collaborations on sea turtles at KSC that include: nest distributions and success, stranding network development, aerial survey testing for nest counts, predator control assessments, the earliest baseline blood chemistry health determinations on nesting females, stress hormones in nesting females, multi-year study of hatchling sex ratios, genetics, species composition, abundance and distribution of in-water juveniles, turtle cold stun response, exterior lighting impacts and control, and satellite tag tracking of post-nesting turtles in the vicinity of near shore shoals and sand mining sites. Through these studies, monitoring, and recommendations, KSC has provided excellent stewardship and protection of the local environment. While conducting its space program mission, KSC has also made significant contributions of information for agencies charged with the conservation and management of these species

Provancha, Jane A.↗

NASA NTRS2019

Safe2Ditch Steer-To-Clear Development and Flight Testing

This paper describes a series of small unmanned aerial system (sUAS) flights performed at NASA Langley Research Center in April and May of 2019 to test a newly added Steer-to-Clear feature for the Safe2Ditch (S2D) prototype system. S2D is an autonomous crash management system for sUAS. Its function is to detect the onset of an emergency for an autonomous vehicle, and to enable that vehicle in distress to execute safe landings to avoid injuring people on the ground or damaging property. Flight tests were conducted at the City Environment Range for Testing Autonomous Integrated Navigation (CERTAIN) range at NASA Langley. Prior testing of S2D focused on rerouting to an alternate ditch site when an occupant was detected in the primary ditch site. For Steer-to-Clear testing, S2D was limited to a single ditch site option to force engagement of the Steer-to-Clear mode. The implementation of Steer-to-Clear for the flight prototype used a simple method to divide the target ditch site into four quadrants. An RC car was driven in circles in one quadrant to simulate an occupant in that ditch site. A simple implementation of Steer-to- Clear was programmed to land in the opposite quadrant to maximize distance to the occupant’s quadrant. A successful mission was tallied when this occurred. Out of nineteen flights, thirteen resulted in successful missions. Data logs from the flight vehicle and the RC car indicated that unsuccessful missions were due to geolocation error between the actual location of the RC car and the derived location of it by the Vision Assisted Landing component of S2D on the flight vehicle. Video data indicated that while the Vision Assisted Landing component reliably identified the location of the ditch site occupant in the image frame, the conversion of the occupant’s location to earth coordinates was sometimes adversely impacted by errors in sensor data needed to perform the transformation. Logged sensor data was analyzed to attempt to identify the primary error sources and their impact on the geolocation accuracy. Three trends were observed in the data evaluation phase. In one trend, errors in geolocation were relatively large at the flight vehicle’s cruise altitude, but reduced as the vehicle descended. This was the expected behavior and was attributed to sensor errors of the inertial measurement unit (IMU). The second trend showed distinct sinusoidal error for the entire descent that did not always reduce with altitude. The third trend showed high scatter in the data, which did not correlate well with altitude. Possible sources of observed error and compensation techniques are discussed.

Petty, Bryan J.↗

NASA NTRS2020

Chrono-Validation of Near-Real-Time Landslide Susceptibility Models via Plugin Statistical Simulations

The idea behind any validation scheme in landslide susceptibility studies is to test whether a model calibrated on a certain data can predict an unknown dataset of the same nature (landslide presences/absences and covariates). Almost the entirety of landslide susceptibility studies are validated by subsetting a single dataset into a training and test sets. This dataset usually corresponds either to event-specific or to historical inventories. Very rarely, a multi-temporal inventory is available and, in the few cases where this condition is met, the validation practices involve training a model on a specific landslide inventory, deriving a single predictive equation and validating it on a subsequent landslide inventory. This commonly leads landslide predictive studies, even those with a strong statistical rigor, to neglect the uncertainty estimation in their modeling scheme. In statistics, validation can also be performed via statistical simulations. This means that after fitting a given model, one can generate any number of predictive functions and test their predictive skills on any type and number of unknown datasets. In this work, we take a similar direction and we apply it to model and validate three separate co-seismic inventories, including an uncertainty estimation phase. We mapped these inventories within the same area in Indonesia, for three earthquakes occurred in 2012, 2017 and 2018. Specifically, we build three event-specific Bayesian Generalize Additive Models of the binomial family. From each model we then simulate 1000 predictive realizations over the remaining two inventories, by using a plug-in scheme where all the morphometric covariates are kept fixed and only the ground motion is replaced according to the prediction target. By doing so, we introduce a new analytical tool for near-real-time landslide predictive purposes, which is able to produce a probabilistic model which stands in between the definitions of susceptibility and hazard. In fact, our model is able to accurately estimate “where” and “when” - although not “how frequently” - landslide have occurred by featuring the multitemporal information of the trigger. In our findings, the simulations are quite similar to the fitted models; and the nine combinations we analyse produce excellent performance. This result confirms the assumption that “the past is the key to the future”, as we show that the relative contribution of each variable and their interactions in each probabilistic model remains practically the same across temporal replicates. This information is not trivial because it supports the routines implemented in global near-real-time applications.

Temporal validation↗

NASA NTRS2023

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

As the space economy continues to expand through increasingly easy access to advanced and inexpensive technology, space missions themselves have become more ambitious with exploration targets growing ever distant while simultaneously requiring larger guidance and communication budgets. These conflicting desires of distance and control drive the need for advanced on-board intelligent decision making to reduce communication and control limitations by automating as many mission functions as possible in-situ. While the amount of research on such Artificial Intelligence and Machine Learning (AI/ML) software modules has grown exponentially, the capacity to experimentally validate such software modules in space in a rapid and inexpensive format has not. To this end, the Nano Orbital Workshop (NOW) group at NASA Ames Research Center has been at the forefront of performing initial flight evaluation tests of ‘commercially’ available bleeding-edge computational platforms via what is programmatically referred to as the BrainStack on the TechEdSat (TES-n) flight series. This on-orbit computational platform provides an evaluation laboratory where advanced software experiments are pre-loaded into memory prior to launch, then executed as payloads during mission operations with results reported back and program tweaks or new training sets uploaded as needed. Processors selected as part of the BrainStack are of ideal size, packaging, and power consumption for easy integration into a cube satellite structure. These experiments have included the evaluation of small, high-performance GPUs and, more recently, neuromorphic processors, in LEO operations. Neuromorphic processors are of particular interest due to their superior power efficiency over GPUs in intelligent automation applications. The first TES-n flight test of an Intel first-generation Loihi neuromorphic processor launched on TES-13, January 13, 2022, and continues to operate in orbit despite no significant modifications to harden the processor against the space environment. The Intel Loihi Gen-1 on TES-13 is characterized by a 14nm 128-core Spiking Neural Network (SNN) able to support on-chip training. The processor is packaged in the Kapoho Bay USB module, providing a relatively straight-forward interface to the bus avionics system. The Kapoho Bay was in turn managed by an Intel Pentium single-board computer to handle scheduling of the software application payloads and communications with the satellite’s primary computer. The recently released Intel Loihi Gen-2, able to support integer-valued spike payloads and produced using 7nm process, will form part of the continually evolving BrainStack in the upcoming three TES-n/NOW flights. The Kapoho Point unit will incorporate eight Loihi-2 processors, enabling neural networks of up to one million neurons and one billion synapsis. Additionally, it is planned to measure the radiation environment these processors experience to understand any degradation or computational artifacts caused by long term space radiation exposure on these novel architectures. This evolving flexible and collaborative environment involving various research teams across NASA and other organizations is intended to be a convenient orbital test platform from which many anticipated future space automation applications may be initially tested.

Artificial Intelligence↗

NASA NTRS2012

Examination of Surface Residuals Obtained During Re-Lubrication of the International Space Station (ISS) Solar Alpha Rotary Joint (SARJ)

The starboard SARJ mechanism on the ISS suffered a premature lubrication failure, resulting in widespread loss of the nitride case layer on its 10.3 meter circumference, 15-5PH steel race ring [1, 2]. To restore functionality, vacuum-stable grease was applied on-orbit, first to the port SARJ mechanism to save it from the damage suffered by the starboard mechanism. After 3 years of greased operation, telemetry indicated that the port mechanism required relubrication, so part of that process included sampling each of the three race ring surfaces to evaluate any wear debris recovered and the state of the originally applied grease. Extensive microscopic examination was conducted, which directed subsequent microanalysis of particulate. Since the SARJ mechanism operates in the vacuum of space, a sampling method and tool had to be developed for use by astronauts while working in the extravehicular mobility unit (EMU). The sampling tool developed was a cotton terry-cloth mitt for the EMU glove, with samples taken by swiping each of the three port SARJ race-ring surfaces. The sample mitts for each surface were folded inward after sampling to preserve sample integrity, for return and ground analysis. The sample mitt for what is termed the outer canted surface of the SARJ race-ring is shown in Figure 1. Figure 1 also demonstrates how increasing levels of magnification were used to survey the contamination removed in sampling, specifically looking for signs of wear debris or other features which could be further evaluated using Scanning Electron Microscopy (SEM) methods. The most surprising overall result at this point in the analysis was the relatively small amounts of grease recovered during sampling. It is clear that the mechanism was not operating with surplus lubricant. Obviously, evidence of molybdenum disulfide (MoS2), a major component in the grease applied, was prevalent in the analysis conducted. But a small amount of mechanism wear debris was observed. Figure 2 shows an example of a region of concentrated wear debris. Although some MoS2 is observed, most of the contaminant in this location is nitrided 15-5PH steel, as verified by the associated chemical analysis. High oxygen content was also observed which, when associated with the apparent friable nature of the steel material, suggests that this contaminant could be quite old, perhaps even associated with the mechanism s original manufacture and acceptance testing. Additional microscopic

Martinez, J. E.↗

NASA NTRS2004

Resolving the Issues with Flywheel Position Sensors

For the past few years, the Advanced Electrical Systems Branch here at NASA Glenn has been pursuing research in the area of flywheels. The purpose of these pursuits has been t o explore the potential for flywheels to replace current battery-powered systems in space. So far it has been learned that flywheels offer large momentum storage capacity, comparatively small volume, high durability, and near- complete discharge capabilities, all of which are advancements over the existing nickel hydrogen and nickel cadmium batteries. Another significant advantage of flywheels is the potential they offer for combining the function of attitude control with energy storage. During the summer of 2004, I worked with Dr. Barbara Kenny in the Advanced Electrical Systems Branch, supporting the work she is doing by analyzing and testing some new components for the new Generation-2 flywheel. To monitor the speed and angular position of the flywheel rotor, a once-around (OAR) signal along with a sensorless algorithm is used. The OAR signal is used for the magnetic bearings that keep the flywheel suspended for frictionless operation. The sensorless algorithm is used for the flywheel motor/generator control. The OAR is generated from position sensors that monitor a circular plate. The plate has a cut down the middle such that one half of the circle is on a slightly lower level than the other. Every half-turn, or 180, the sensors detect the "cut" on the plate, and trigger the OAR, telling the computer that the rotor has made half a revolution. This, however, doesn't provide needed detailed information about the angular position of the rotor, since it only provides a signal alert every half- revolution. This is enough information for the magnetic bearing control but is insufficient for the motor/generator control. A new resolver was designed such that it would give continuous angle information rather than the 180 degree information of the OAR. The new resolver has two separate observable pieces: a flat middle section to monitor vertical motion, and an angled section around the circumference, which, when observed from above, produces a sine-wave displacement through the entire 360" revolution. My first job when I arrived this summer was to calibrate the sensors that would be mounted on the inside of the flywheel casing to monitor the position (angular and vertical) of the shaft. After calibration, I used the sensors to evaluate voltage outputs created by position differences between two pairs of sensors on the angled portion of the resolver for eight different angular positions, moving the resolver vertically and laterally through its entire potential range of motion. The results of these tests will be used to determine the rotor angular (and axial) position from the sensor readings once the new flywheel unit is assembled. The sensorless algorighm mentioned above consists of two operations: the signal injection method and the back electro-motive force (EMF). The signal injection is meant to work at low speeds, while the back EMF algorithm is meant to work at higher speeds. Both work together to determine the correct estimate of rotor position and speed based on the measured motor/generator current. It was determined that we wanted to know exactly how accurate our estimation methods were, and so a resolver (a commercially available mechanical sensor mounted to the motor/generator shaft to measure rotor position and speed) and a "Resolver to Digital" (R2D) circuit board was purchased to make the comparison to the existing estimation. My work related to the R2D board has included the following: creating two connector cables (one to power the circuit and one to get readable output off the board), writing Simulink code to process the board's output, and building a dSpace panel to control and monitor the circuit. The next step in the process will be to perform tests to compare the estimated rotor position and speed from the sensorless algorithm to the actual rotor and speed from the resolver signal.

Fehrmann, Elizabeth A.↗

NASA NTRSDate not supplied

NASA Lunar Surface Innovation Initiative: Ensuring a Cohesive, Executable Strategy for Technology Development

Establishing a sustainable human presence on the Moon allows NASA to develop and test new approaches, technologies, and systems that will enable us to function in other, more challenging environments. The Lunar Surface Innovation Initiative (LSII) was established in 2019 and has evolved into a key agency asset to spur technology development and provide risk reduction for lunar surface system development and flight demonstrations. LSII coordinates activities implemented through a combination of in-house activities, competitive programs, and public-private partnerships to create transformative technologies needed for lunar surface exploration. This paper will outline the LSII model used to develop a technology pipeline that will retire the primary technology hurdles in six capability areas. In-situ resource utilization technologies for collecting, processing, storing, and using material found or manufactured on the Moon. Surface power technologies that provide the capability for sustainable, continuous power throughout the day and night for lunar missions. Dust mitigation strategies that diminish lunar dust hazards on lunar surface systems such as cameras, solar panels, space suits, habitats, and instrumentation. Extreme environments technologies that enable systems to operate throughout the full range of lunar surface conditions, including lunar noon (up to 150 at the equator), night (down to - 180 at the equator), multiple day/night cycles, and in permanently shadowed regions (down to -250). Extreme access technologies that enable humans or robotic systems to access, navigate, and explore previously inaccessible lunar surface or subsurface areas. Excavation and construction technologies that will allow affordable, autonomous manufacturing or construction. We outline key results, including milestones and achievements related to the capability areas and outcomes from partnerships with the commercial sector. A key tenet of the LSII is the Lunar Surface Innovation Consortium (LSIC), a collaboration across industry, academia, and government to successfully develop the transformative capabilities for lunar surface exploration. LSIC provides a forum for NASA to communicate technological requirements, needs, and opportunities and for the community to share existing capabilities and identify critical gaps with NASA. By working side by side with commercial enterprises and our international partners, NASA is able to combine the knowledge and expertise needed to explore the lunar surface and make technical advances that will feed technological and economic growth. Since its inception, LSII has engaged over 600 organizations across the United States and 46 countries to shape the technologies and systems needed to explore the lunar surface and stimulate a lunar surface economy.

lunar, lunar surface, technology development, ISRU↗

NASA NTRSDate not supplied

NASA Lunar Surface Innovation Initiative: Ensuring a Cohesive, Executable Strategy for Technology

Lunar↗

NASA NTRS2016

Piloted Well Clear Performance Evaluation of Detect and Avoid Systems with Suggestive Guidance

Regulations to establish operational and performance requirements for unmanned aircraft systems (UAS) are being developed by a consortium of government, industry and academic institutions (RTCA, 2013). Those requirements will apply to the new detect-and-avoid (DAA) systems and other equipment necessary to integrate UAS with the United States (U.S) National Airspace System (NAS) and will be determined according to their contribution to the overall safety case. That safety case requires demonstration that DAA-equipped UAS collectively operating in the NAS meet an airspace safety threshold (AST). Several key gaps must be closed in order to link equipment requirements to an airspace safety case. Foremost among these is calculation of the systems risk ratio, the degree to which a particular system mitigates violation of an aircraft separation standard (FAA, 2013). The risk ratio of a DAA system, in combination with risk ratios of other collision mitigation mechanisms, will determine the overall safety of the airspace measured in terms of the number of collisions per flight hour. It is not known what the effectiveness is of a pilot-in-the-loop DAA system or even what parameters of the DAA system most improve the pilots ability to maintain separation. The relationship between the DAA system design and the overall effectiveness of the DAA system that includes the pilot, expressed as a risk ratio, must be determined before DAA operational and performance requirements can be finalized. Much research has been devoted to integrating UAS into non-segregated airspace (Dalamagkidis, 2009, Ostwald, 2007, Gillian, 2012, Hesselink, 2011, Santiago, 2015, Rorie 2015 and 2016). Several traffic displays intended for use as part of a DAA system have gone through human-in-the-loop simulation and flight-testing. Most of these evaluations were part of development programs to produce a deployable system, so it is unclear how to generalize particular aspects of those designs to general requirements for future traffic displays (Calhoun, 2014). Other displays have undergone testing to collect data that may generalize to new displays, but have not been evaluated in the context of the development of an overall safety case for UAS equipped with DAA systems in the NAS (Bell, 2012). Other research efforts focus on DAA surveillance performance and separation standards. Together with this work, they are expected to facilitate validation of the airspace safety case (Park, 2014 and Johnson, 2015). The contribution of the present work is to quantify the effectiveness of the pilot-automation system to remain well clear as a function of display features and surveillance sensor error. This quantification will help enable selection of a minimum set of DAA design features that meets the AST, a set that may not be unique for all UAS platforms. A second objective is to collect and analyze pilot performance parameters that will improve the modeling of overall DAA system performance in non-human-in-the-loop simulations. Simulating the DAA-equipped UAS in such batch experiments will allow investigation of a much larger number of encounters than is possible in human simulations. This capability is necessary to demonstrate that a particular set of DAA requirements meets the AST under all foreseeable operational conditions.

detect and avoid↗