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NASA NTRS1993

Yana ring structure, North-Eastern Siberia: A possible counterpart of coronae on Venus

An arch of Verkhoyansky Range in NE Siberia, Russia is considered as W and S parts of the rim of the large ring structure, referred hereafter as Yana Ring Structure (YRS). It has general appearance similar to coronae on Venus and could be considered as the terrestrial counter part of coronae. The structure is located between 63 and 70 deg N, 125 and 140 deg E. The outer diameter of YRS (between the rim feet) is 680-700 km. The rim crest diameter is 500-520 km. The inner diameters (between the inner feet of the rim) is 320-350 km. The rim of YRS consist of the following topographic features: W segment is Orulgan Range (N part of Verkhoyansky Range), SW and S segments consist of S part of Verkhoyansky Range, SE segment is Elginskoye Ploskogorye (Tableland), E segment is Chersky Range (its part W of Indigirka River), NE segment is Selennyakhsky Range, and NW segment is Kular Range. Inside this ring of mountains Yanskoye Ploskogorye (Tableland) is located. The circular outlines of YRS are marked with the large river valleys located outside: Lena River (lower of Aldan River mouth) is located W from YRS, Aldan River (lower of Amga River mouth) is from S, Indigirka River (between 64 and 67 deg N lat) is from E, and Selennyakh River (the part running N to S) is from NE. The ring patterns inside the mountaineous rim of YRS are marked with the tributaries of Yana River. The largest ring here, 300 km in diameter, consists of Bytangay (with Bellyakh) River at W, Nelgese and Derbeke Rivers at S/SE, and Tuostakh River at E. The typical altitudes of YRS mountain rim are 1000-2000 m. The maximal ones are: 2400 m in W part of the rim, 2300 m in S, 1600 m in SE, 2200-2500 m in E, and 1300-1500 m in N. The central part of YRS have typical altitudes of 400-600 m. There are lowlands with altitudes 50-200 m to the S, W, N, and NW outside YRS Oymyakonskoye Nagorye (Highland) is located SE of YRS at 500-1500 m altitudes. It should be recognized from this description YRS have a general appearance of circular highland with its central plateau located 1000-2000 m lower than surrounding mountain rim, but 300-400 m higher than plains of lowlands located outside the rim. Such topographic patterns are typical for coronae on Venus. The diameter of YRS is equal to the largest coronae on Venus. There are only 3 or 4 structures of such or larger size on the whole Venus. This calls to compare morphology and geologic evolution of YRS with morphology and models of coronae evolutions especially the largest ones, to search the similarities and/or differences in geologic histories of the structures on the Earth and Venus.

Burba, G. A.↗
NASA NTRS1995

The magnetic evolution of AR 6555 which lead to two impulsive, readily compact, X-type flares

We study the evolution of the vector magnetic field and the sunspot motions observed in AR 6555 during 23-26 Mar. 1991. This region displays two locations of large magnetic shear that were also sites of flare activity. The first location produced two large (X-class) flares during the period covered by our observations. The second location had larger magnetic shear than the first, but produced only small (M- and C-class) flares during our observations. We study the evolution of the photospheric magnetic field in relation to the large flares in the first location. These flares occurred around the same included polarity, and have very similar characteristics (soft X-ray light curves, energies, etc.). However, the whole active region has changed substantially in the period between them. We found several characteristics of the region that appear related to the occurrence of these flares. (1) The flares occurred near regions of large magnetic 'shear,' but not at the locations of maximum shear or maximum field. (2) Potential field extrapolations of the observed field suggest that the topology changed, prior to the first of the two flares, in such a way that a null appeared in the coarse magnetic field. (3) This null was located close to both X-class flares, and remained in that location for a few days while the two flares were observed. (4) The flaring region has a pattern of vector field and sunspot motions in which material is 'squeezed' along the polarity inversion line. This pattern is very different from that usually associated with shearing arcades, but it is similar to that suggested previously by Fontenla and Davis. The vertical electric currents, inferred from the transverse field, are consistent with this pattern. (5) A major reconfiguration of the longitudinal field and the vertical electric currents occurred just prior to the first of the two flares. Both changes imply substantial variations of the magnetic structure of the region. On the basis of the available data we suggest that these changes made the flaring possible, and we develop a scenario that can explain the origin of the magnetic free energy that was released in these flares.

Ambastha, A.↗
NASA NTRS1995

Optical fiber sensors for damage analysis in aerospace materials

Under this grant, fiber optic sensors were investigated for use in the nondestructive evaluation of aging aircraft. Specifically, optical fiber sensors for detection and location of impacts on a surface, and for detection of corrosion in metals were developed. The use of neural networks was investigated for determining impact location by processing the output of a network of fiberoptic strain sensors distributed on a surface. This approach employs triangulation to determine location by comparing the arrival times at several sensors, of the acoustic signal generated by the impact. For this study, a neural network simulator running on a personal computer was used to train a network using a back-propagation algorithm. Fiber optic extrinsic Fabry-Perot interferometer (EFPI) strain sensors are attached to or embedded in the surface, so that stress waves emanating from an impact can be detected. The ability of the network to determine impact location by time-or-arrival of acoustic signals was assessed by comparing network outputs with actual experimental results using impacts on a panel instrumented with optical fiber sensors. Using the neural network to process the sensor outputs, the impact location can be inferred to centimeter range accuracy directly from the arrival time data. In addition, the network can be trained to determine impact location, regardless of material anisotropy. Results demonstrate that a back-propagation network identifies impact location for an anisotropic graphite/bismaleimide plate with the same accuracy as that for an isotropic aluminum plate. Two different approaches were investigated for the development of fiber optic sensors for corrosion detection in metals, both utilizing optical fiber sensors with metal coatings. In the first approach, an extrinsic Fabry-Perot interferometric fiber optic strain sensor was placed under tensile stress, and while in the resulting strained position, a thick coating of metal was applied. Due to an increase in the quantity of material, the sensor does not return to its original position upon removal of the applied stress, and some residual strain is maintained within the sensor element. As the metal thickness decreases due to corrosion, this strain is released, providing the sensing mechanism for corrosion detection. In the second approach, photosensitive optical fibers with long period Bragg gratings in the core were coated with metal. The Bragg gratings serve to couple core modes at discrete wavelengths to cladding modes. Since cladding modes interact with the metal coating surrounding the fiber cladding, the specific wavelengths coupled from core to cladding depend on the refractive index of the metal coating. Therefore, as the metal corrodes, the resulting change in index of the coating may be measured by measuring the change in wavelength of the coupled mode. Results demonstrate that both approaches can be successfully used to track the loss in metal coating on the optical fiber sensors due to corrosion.

Schindler, Paul↗
NASA NTRS1995

The Magnetic Evolution of AR 6555 which led to Two Impulsive, Relatively Compact, X-Type Flares

We study the evolution of the vector magnetic field and the sunspot motions observed in AR 6555 during 1991 March 23-26. This region displays two locations of large magnetic shear that were also sites of flare activity. The first location produced two large (X-class) flares during the period covered by our observations. The second location had larger magnetic shear than the first but produced only small (M- and C-class) flares during our observations. We study the evolution of the photospheric magnetic field in relation to the large flares in the first location. These flares occurred around the same included polarity and have very similar characteristics (soft X-ray light curves, energies, etc,). However, the whole active region has changed substantially in the period between them. We found several characteristics of the region that appear related to the occurrence of these flares: (1) The flares occurred near regions of large magnetic 'shear' but not at the locations of maximum shear or maximum field. (2) Potential field extrapolations of the observed field suggest that the topology changed, prior to the first of the two flares, in such a way that a null appeared in the coarse magnetic field. (3) This null was located close to both X-class flares and remained in that location for a few days while the two flares were observed. (4) The flaring region has a pattern of vector field and sunspot motions in which material is 'squeezed' along the polarity inversion line. This pattern is very different from that usually associated with shearing arcades, but it is similar to that suggested previously by Fontenia and Davis. The vertical electric currents, inferred from the transverse field, are consistent with this pattern. (5) A major reconfiguration of the longitudinal field and the vertical electric currents occurred just prior to the first of the two flares. Both changes imply substantial variations of the magnetic structure of the region. On the basis of the available data we suggest that these changes made the flaring possible, and we develop a scenario that can explain the origin of the magnetic free-energy that was released in these flares.

Fontenla, J. M.↗
NASA NTRS1999

Lunar Meteorites and Implications for Compositional Remote Sensing of the Lunar Surface

Lunar meteorites (LMs) are rocks found on Earth that were ejected from the Moon by impact of an asteroidal meteoroid. Three factors make the LMs important to remote-sensing studies: (1) Most are breccias composed of regolith or fragmental material; (2) all are rocks that resided (or breccias composed of material that resided) in the upper few meters of the Moon prior to launch and (3) most apparently come from areas distant from the Apollo sites. How Many Lunar Locations? At this writing (June 1999), there are 18 known lunar meteorite specimens. When unambiguous cases of terrestrial pairing are considered, the number of actual LMs reduces to 13. (Terrestrial pairing is when a single piece of lunar rock entered Earth's atmosphere, but multiple fragments were produced because the meteoroid broke apart on entry, upon hitting the ground or ice, or while being transported through the ice.) We have no reason to believe that LMs preferentially derive from any specific region(s) of the Moon; i.e., we believe that they are samples from random locations. However, we do not know how many different locations are represented by the LMs; mathematically, it could be as few as 1 or as many as 13. The actual maximum is < 13 because in some cases a single impact appears to have yielded more than one LM. Yamato 793169 and Asuka 881757 are considered "source-crater paired" or "launch paired" because they are compositionally and petrographically similar to each other and distinct from the others, and both have similar cosmic-ray exposure (CRE) histories. The same can be said of QUE 94281 and Y 793274. Thus the 13 meteorites probably represent a maximum of 11 locations on the Moon. The minimum number of likely source craters is debated and in flux as new data for different isotopic systems are obtained. Conservatively, considering CRE data only, a minimum of about 5 impacts is required. Compositional and petrographic data offer only probabilistic constraints. An extreme, but not unreasonable viewpoint, is that such data offer no constraint. For example, if one were to cut up the Apollo 17 landing site (which was selected for its diversity) into softball-sized pieces, some of those pieces (e.g., sample 70135) would be crystalline mare basalts like Y 793169 whereas others (e.g., sample 73131 would be feldspathic regolith breccias like MAC 88104/ 88105. However, nature is not so devious. Warren argues that LMs come from craters of only a few kilometers in diameter. If so, even though CRE data allow, for example, that ALHA 81005 and Y 791197) were launched simultaneously from the same crater, the probability is nevertheless low because the two meteorites are compositionally and mineralogically distinct. Thus, within the allowed range (5-11) for the number of locations represented by the LMs, values at the high end of the range are probably more likely. Mare Meteorites: Three LMs consist almost entirely of mare basalt. Two, Y 793169 and Asuka 881757, are unbrecciated, low-Ti, crystalline rocks that are compositionally and mineralogically similar (but not identical) to each other; they probably derive from a single lunar-mare location. The third, EET 87521/96008, is a fragmental breccia consisting predominantly of VLT mare basalt. Thus, these LMs probably represent only two lunar mare locations. The basaltic LMs have mineral and bulk compositions distinct from Apollo mare basalts. The petrography of Calcalong Creek has not been described in detail, but compositionally it is unique in that it corresponds to a mixture (breccia) of about one-half feldspathic material (i.e., the mean composition of the feldspathic lunar meteorites, below), one-fourth KREEP norite, one-fourth VLT mare basalt (like EET 87521), and 1% CI chondrite. With 4 micro g/g Th and correspondingly high concentrations of other incompatible elements, it is the only lunar meteorite that is likely to have come from within the Procellarum KREEP Terrane (PKT). Yamato 793274 and QUE 94281 are together distinct in being fragmental breccias containing subequal parts of feldspathic highland material and VLT mare basalt. Jolliff et al. estimate a mare to highland ratio of 54:46 for QUE 94281 and 62:38 for Y 793274; this difference is well within the range observed for soils collected only centimeters apart (in cores) at interface site like Apollo 15 and 17 [11]. Although the two meteorites were found on opposite sides of Antarctica, they are probably launch-paired. The strongest evidence is that the pyroclastic glass spherules that occur in both are of two compositional groups and the two groups are essentially the same in both meteorites. Yamato 791197 is nominally a feldspathic lunar meteorite (below), but among FLMs, it probably contains the highest abundance of clasts and glasses of mare derivation. As a consequence, its composition is at the high-Fe, low-Mg end of the range for FLMs and is not included in the FLM average of Table 1. Its composition is consistent with about 10% mare-derived material. Similarly, the two small (Y 82) pieces of Y 82192/82193186032 are more mafic than the large (Y 86) piece, probably as a result of about 7% mare-derived material. All Apollo missions went to areas in or near the PKT, and, consequently, all Apollo regolith samples are contaminated with Th-rich material from the PKT. At the nominally "typical" highland site, Apollo 16, about 30% of the regolith (<1-mm fines) is Th-rich ejecta from the Imbrium impact and about 6% is mare material probably derived from mare basins. Thus Apollo 16 regolith is not typical of the highlands. Among Apollo rocks, the compositions of the FLMs correspond most closely to the feldspathic granulitic breccias of Apollo 16 and 17. (Additional information is contained in original)

Korotev, R. L.↗
NASA NTRS2007

Advanced Systems for Monitoring Underwater Sounds

The term "Passive Acoustic Monitoring System" (PAMS) describes a developmental sensing-and-data-acquisition system for recording underwater sounds. The sounds (more precisely, digitized and preprocessed versions from acoustic transducers) are subsequently analyzed by a combination of data processing and interpretation to identify and/or, in some cases, to locate the sources of those sounds. PAMS was originally designed to locate the sources such as fish of species that one knows or seeks to identify. The PAMS unit could also be used to locate other sources, for example, marine life, human divers, and/or vessels. The underlying principles of passive acoustic sensing and analyzing acoustic-signal data in conjunction with temperature and salinity data are not new and not unique to PAMS. Part of the uniqueness of the PAMS design is that it is the first deep-sea instrumentation design to provide a capability for studying soniferous marine animals (especially fish) over the wide depth range described below. The uniqueness of PAMS also lies partly in a synergistic combination of advanced sensing, packaging, and data-processing design features with features adapted from proven marine instrumentation systems. This combination affords a versatility that enables adaptation to a variety of undersea missions using a variety of sensors. The interpretation of acoustic data can include visual inspection of power-spectrum plots for identification of spectral signatures of known biological species or artificial sources. Alternatively or in addition, data analysis could include determination of relative times of arrival of signals at different acoustic sensors arrayed at known locations. From these times of arrival, locations of acoustic sources (and errors in those locations) can be estimated. Estimates of relative locations of sources and sensors can be refined through analysis of the attenuation of sound in the intervening water in combination with water-temperature and salinity data acquired by instrumentation systems other than PAMS. A PAMS is packaged as a battery-powered unit, mated with external sensors, that can operate in the ocean at any depth from 2 m to 1 km. A PAMS includes a pressure housing, a deep-sea battery, a hydrophone (which is one of the mating external sensors), and an external monitor and keyboard box. In addition to acoustic transducers, external sensors can include temperature probes and, potentially, underwater cameras. The pressure housing contains a computer that includes a hard drive, DC-to- DC power converters, a post-amplifier board, a sound card, and a universal serial bus (USB) 4-port hub.

Lane, Michael↗
NASA NTRS2009

Using Decision Trees to Detect and Isolate Simulated Leaks in the J-2X Rocket Engine

The goal of this work was to use data-driven methods to automatically detect and isolate faults in the J-2X rocket engine. It was decided to use decision trees, since they tend to be easier to interpret than other data-driven methods. The decision tree algorithm automatically "learns" a decision tree by performing a search through the space of possible decision trees to find one that fits the training data. The particular decision tree algorithm used is known as C4.5. Simulated J-2X data from a high-fidelity simulator developed at Pratt & Whitney Rocketdyne and known as the Detailed Real-Time Model (DRTM) was used to "train" and test the decision tree. Fifty-six DRTM simulations were performed for this purpose, with different leak sizes, different leak locations, and different times of leak onset. To make the simulations as realistic as possible, they included simulated sensor noise, and included a gradual degradation in both fuel and oxidizer turbine efficiency. A decision tree was trained using 11 of these simulations, and tested using the remaining 45 simulations. In the training phase, the C4.5 algorithm was provided with labeled examples of data from nominal operation and data including leaks in each leak location. From the data, it "learned" a decision tree that can classify unseen data as having no leak or having a leak in one of the five leak locations. In the test phase, the decision tree produced very low false alarm rates and low missed detection rates on the unseen data. It had very good fault isolation rates for three of the five simulated leak locations, but it tended to confuse the remaining two locations, perhaps because a large leak at one of these two locations can look very similar to a small leak at the other location.

Schwabacher, Mark A.↗
NASA NTRS2013

An Update on Phased Array Results Obtained on the GE Counter-Rotating Open Rotor Model

Beamform maps have been generated from 1) simulated data generated by the LINPROP code and 2) actual experimental phased array data obtained on the GE Counter-rotating open rotor model. The beamform maps show that many of the tones in the experimental data come from their corresponding Mach radius. If the phased array points to the Mach radius associated with a tone then it is likely that the tone is a result of the loading and thickness noise on the blades. In this case, the phased array correctly points to where the noise is coming from and indicates the axial location of the loudest source in the image but not necessarily the correct vertical location. If the phased array does not point to the Mach radius associated with a tone then some mechanism other than loading and thickness noise may control the amplitude of the tone. In this case, the phased array may or may not point to the actual source. If the source is not rotating it is likely that the phased array points to the source. If the source is rotating it is likely that the phased array indicates the axial location of the loudest source but not necessarily the correct vertical location. These results indicate that you have to be careful in how you interpret phased array data obtained on an open rotor since they may show the tones coming from a location other than the source location. With a subsonic tip speed open rotor the tones can come form locations outboard of the blade tips. This has implications regarding noise shielding.

Podboy, Gary↗
NASA NTRS2015

Integrated Ultra-Wideband Tracking and Carbon Dioxide Sensing System Design for International Space Station Applications

A three-dimensional (3D) Ultra-Wideband (UWB) Time-of-Arrival (TOA) tracking system has been studied at NASA Johnson Space Center (JSC) to provide the tracking capability inside the International Space Station (ISS) modules for various applications. One of applications is to locate and report the location where crew experienced possible high level of carbon-dioxide (CO2) and felt upset. Recent findings indicate that frequent, short-term crew exposure to elevated CO2 levels combined with other physiological impacts of microgravity may lead to a number of detrimental effects, including loss of vision. To evaluate the risks associated with transient elevated CO2 levels and design effective countermeasures, doctors must have access to frequent CO2 measurements in the immediate vicinity of individual crew members along with simultaneous measurements of their location in the space environment. To achieve this goal, a small, low-power, wearable system that integrates an accurate CO2 sensor with an ultra-wideband (UWB) radio capable of real-time location estimation and data communication is proposed. This system would be worn by crew members or mounted on a free-flyer and would automatically gather and transmit sampled sensor data tagged with real-time, high-resolution location information. Under the current proposed effort, a breadboard prototype of such a system has been developed. Although the initial effort is targeted to CO2 monitoring, the concept is applicable to other types of sensors. For the initial effort, a micro-controller is leveraged to integrate a low-power CO2 sensor with a commercially available UWB radio system with ranging capability. In order to accurately locate those places in a multipath intensive environment like ISS modules, it requires a robust real-time location system (RTLS) which can provide the required accuracy and update rate. A 3D UWB TOA tracking system with two-way ranging has been proposed and studied. The designed system will be tested in the Wireless Habitat Testbed which simulates the ISS module environment. This report describes the research and development effort for this prototype integrated UWB tracking and CO2 sensing system. The remainder of the report is organized as follows. In Section II, the TOA tracking methodology is introduced and the 3D tracking algorithm is derived. The simulation results are discussed in Section III. In Section VI, prototype system design and field tests are discussed. Some concluding remarks and future works are presented in Section V.

Ni, Jianjun (David)↗
NASA NTRS2016

Mars Surface Systems Common Capabilities and Challenges for Human Missions

This paper describes the current status of common systems and operations as they are applied to actual locations on Mars that are representative of Exploration Zones (EZ) - NASA's term for candidate locations where humans could land, live and work on the Martian surface. Given NASA's current concepts for human missions to Mars, an EZ is a collection of Regions of Interest (ROIs) located within approximately 100 kilometers of a centralized landing site. ROIs are areas that are relevant for scientific investigation and/or development/maturation of capabilities and resources necessary for a sustainable human presence. An EZ also contains a habitation site that will be used by multiple human crews during missions to explore and utilize the ROIs within the EZ. The Evolvable Mars Campaign (EMC), a description of NASA's current approach to these human Mars missions, assumes that a single EZ will be identified within which NASA will establish a substantial and durable surface infrastructure that will be used by multiple human crews. The process of identifying and eventually selecting this single EZ will likely take many years to finalized. Because of this extended EZ selection process it becomes important to evaluate the current suite of surface systems and operations being evaluated for the EMC as they are likely to perform at a variety of proposed EZ locations and for the types of operations - both scientific and development - that are proposed for these candidate EZs. It is also important to evaluate proposed EZs for their suitability to be explored or developed given the range of capabilities and constraints for the types of surface systems and operations being considered within the EMC. Four locations identified in the Mars Exploration Program Analysis Group (MEPAG)'s Human Exploration of Mars Science Analysis Group (HEM-SAG) report are used in this paper as representative of candidate EZs that will emerge from the selection process that NASA has initiated. A field station site plan is developed for each of these four HEM-SAG sites. Because of the difficulty in getting equipment and supplies to the surface of Mars, specific assessments have been conducted to identify those systems and processes that can perform in multiple, sometimes completely unrelated, situations. Examples of common systems that are assessed at all of these sites include: (a) habitation and associated logistics storage systems, (b) a centralized power plant capable of supplying power to a geographically distributed (but within the central habitation zone) set of systems, (c) mobility systems that can be used to off-load and move payloads to specific locations at the central field station location that could also be used to traverse long distances to reach some of the more remote ROIs and (d) robotic systems that can support various activities (such as system set up and maintenance) at the field station that could also be used to explore scientific ROIs and used to support site-specific ISRU (In Situ Resource Utilization) production activities.

Toups, Larry↗
NASA NTRS2015

Area 3 Support Buildings (A3SB) H5-0992, H5-0996 PRL 218 Confirmatory Sampling Report

The Area 3 Support Buildings site (A3SB) consists of two separate areas located on the north side of Beach Road in the northern portion of Kennedy Space Center, Florida (KSC), outside the secured perimeter of KSC. The A3SB areas are approximately 0.6 miles apart, and were developed as Shiffler's Grocery Store and Service Station (west site) and as a residence (east site) prior to acquisition by the National Aeronautics and Space Administration (NASA) in 1963. Both areas were used by the Bendix Company in support of NASA as chemical laboratories from 1963 through 1969. Both of the buildings were demolished by 1987. The west portion of the site was used by the US Fish & Wildlife Service (F&W) in support of the Merritt Island National Wildlife Refuge (MINWR) for parking at the entrance to the Hammock Trails from 1969 to the present. The east portion of the site was used for intermittent suspect materials staging in the early 1990s and is still used as an apiary location, but is otherwise no longer active. In support of the NASA HSWA permit requirements, this site was identified as Potential Release Location (PRL) 218 and a Solid Waste Management Unit (SWMU) Assessment (SA) was conducted in 2013. Confirmatory Sampling (CS) was recommended and approved by the KSC Remediation Team (KSCRT). Three locations of concern (LOCs) were identified and sampled at the site. The LOCs include two former chemical labs and a former suspect staging area. The CS was conducted in March of 2015 at three locations by means of Direct Push Technology (DPT) groundwater sampling and at one location for soil sampling. The samples were collected and analyzed in accordance with the approved CS Work Plan. There were no exceedances of criteria detected in any of the samples from the three LOCs. The results of this investigation indicate that past and/or present operations have not negatively impacted environmental media at the A3SB. Based upon no confirmed groundwater detections above GCTLs and no soil impacts above applicable screening criteria no further investigation is warranted at the A3SB. A No Further Action (NFA) status for all locations was approved by the KSCRT at the June 2015 meeting.

Confirmatory sampling↗
NASA NTRS2017

Flight Deck Surface Trajectory-Based Operations (STBO): A Four-Dimensional Trajectory (4DT) Simulation

In four-dimensional trajectory (4DT) Surface Trajectory-Based Operations (STBO), aircraft are assigned a conflict-free 4DT which defines an expected location (x,y coordinates) at all times, t, along the taxi route (with altitude, being fixed). These 4DTs afford the highest temporal certainty at all points along the taxi route, and at the departure runway. In the present study, a 4DT flight deck display was presented on the Airport Moving Map (AMM) to support pilot conformance to a 4DT clearance while taxiing under manual control. This pilot-in-the-loop simulation compared the effect of 4DT flight deck display formats on distance from the expected 4DT location, conformance to the displayed tolerance band, eyes-out time, and pilot ratings of safety and workload. In the defined-tolerance display format, a graphical representation of the expected 4DT location, with a distance-based allowable-tolerance band, was depicted on the AMM. Two defined-tolerance band sizes were tested: plus or minus 164 feet and plus or minus 405 feet. In the undefined-tolerance display format, the expected 4DT location was displayed graphically on the AMM, with no indicated allowable-tolerance bounds. Each taxi trial included 4DT speed changes (two or five, per trial) and a range of 4DT taxi speeds. Results showed that the larger (plus or minus 405 feet) defined-tolerance band yielded higher conformance levels than the smaller (plus or minus 164 feet) band, with pilots staying within the specified and displayed conformance bounds more in the larger (99.71%) than the smaller defined-tolerance band (93.37 percent). However, in terms of being able to predict the location of the aircraft compared to the expected 4DT location, the smaller defined-tolerance band resulted in pilots keeping their aircraft closer to the 4DT location, for both average distance and for a given confidence interval (e.g., 95 percent), than either the larger defined-tolerance band or the undefined-tolerance display format. The larger tolerance band yielded more “eyes-out-the-window” time than the smaller tolerance band. Pilots also rated taxing with the larger tolerance band as safer than the smaller tolerance band.

STBO↗
NASA NTRS2019

Software Tool for Tracking & Mapping the NASA Orion AA-2 Test Flight Ejectable Data Recorders in Real Time

On 2 July 2019, the NASA Ascent Abort 2 flight took place off the Florida coast to test the emergency systems to separate the Orion Crew Module (CM) from the future Space Launch System rocket in the event of a malfunction. During this high-altitude test, instrumentation data was recorded on twelve customized buoyant Ejectable Data Recorders (EDRs) and subsequently jettisoned from the CM in mid-air. Upon release, the EDRs activated their GPS-Iridium beacon systems and began transmitting Short Burst Data (SBD) messages via the Iridium satellite network to relay their individual location and system health information. To locate, track and retrieve each EDR from the ocean surface in real-time, multiple open-source programming tools (Python and Linux shells) were developed for parsing the incoming Iridium binary SBD messages. For this, a Linux laptop was used to receive the Iridium-generated emails containing the SBD messages and autonomously execute the parsing tools. The received SBD data contained location, timestamp and health status information that was translated, saved, and subsequently used for simultaneously generating a continuously updated color-coded tabular display summary and unique KML files used with Google Earth to track their locations. Once their locations were known, dedicated recovery vessels retrieved all EDRs from the ocean. An additional tool was also developed in order to generate 5- and 10-minute geolocation predictions for each EDR by deriving the displacement distance, elapsed time, displacement heading and velocity based on the latest known information available. The recovery vessels were also tracked with the use of a separate commercial GPS beacon system. After jettison, 67% of the EDRs transmitted valid data by the time they were retrieved from the ocean. However, the real-time information presented by the plotting tool allowed for the ready depiction of EDR dispersal patterns and reference drift trajectories, which contributed to the recovery of all twelve EDRs and the AA-2 flight data. Lastly, the available data showed that the distance between the software’s reported drift/predicted locations and the recovery locations did not exceed 38 meters, therefore demonstrating the advantages of this software tool for supporting real-time tracking and recovery efforts of beacon devices.

Moxey, Lucas↗
NASA NTRSDate not supplied

An Updated Secondary Lunar Meteoroid Ejecta Model for Engineering Design

Introduction: The surface of the Moon is constantly being bombarded by a flux of meteoroids of various sizes. Impacts due to these meteoroids produce secondary ejecta material at much lower speeds but with a total mass larger than the original impactor. Details about the secondary ejecta are important for planning missions on the lunar surface. In this work, an updated ejecta model is presented called the Meteoroid Model of Secondary Ejecta (MeMoSeE), to re-place the Apollo-era ejecta model, NASA SP-8013 [1], in the SLS-SPEC 159 Design Specification for Natural Environments (DSNE) [2]. The model pro-duces secondary ejecta flux environments for a user-specified location on the lunar surface, and sorts the incoming secondary flux by angular direction and speed. Methods: MeMoSeE is separated into three parts: the inputs, the conversion step, and the integration of fluxes. Inputs to the model include the primary meteoroid fluxes and the primary near-Earth object (NEO) fluxes. Meteoroid fluxes, both asteroidal and cometary, are calculated using the Meteoroid Engineering Model (MEM3) [3] for different locations on the Moon. For each surface location, an ephemeris is generated using the JPL HORIZONS System [4] that feeds into MEM3. The NEO fluxes are approximated by the high-density population of MEM3 (i.e., only the directionality), where the speed distribution of the NEO fluxes is renormalized to match observations [5]. The regolith properties are used as defined in the DSNE [2]. The conversion step utilizes scaling laws given by Housen & Holsapple 2011 [6] to convert the primary impactor flux to the total mass of secondary ejecta. The ejecta distribution, at the point-of-impact (POI), is separated into a zenith angle and azimuthal angle distribution. The zenith angle distribution follows a beta distribution where the peak depends on the impact altitude angle and the impact azimuth [7]. We employ an ejecta azimuth distribution that is based on Rival & Mandeville 1999 [8] which focuses ejecta in the downstream direction for more oblique impacts. Finally, during the integration step, we sum secondary ejecta number fluxes at a particular region-of-interest (ROI) that originated from many POI locations over the entire surface of the Moon. We keep track of both altitude and azimuth angle bins as well as a range of speed bins, following the igloo gridding as done in MEM3 [9]. The ejecta particle size distribution and density is assumed to be the same as the lunar regolith [10, 2]. Results: The primary fluxes are computed for one Metonic cycle (19 years) for various locations over the lunar surface with a fixed orientation. Both the angular and speed distributions of the primary fluxes are dependent on the latitude and longitude. The over-all primary fluxes show a roughly 13% increase from the eastern limb to the western limb. In general, the speed distribution of the secondary fluxes span from a user-defined minimum speed to the escape speed of the Moon (2.38 km/s), roughly following a power-law relation [6]. Different parts of the speed distribution come from different primary impact locations on the Moon. The secondary ejecta is dominated by the slowest speeds, where these particles originate nearby the ROI. For speeds around 71% of the escape speed, the secondary ejecta originates from locations near the antipodal point. On the other hand, for secondary ejecta speeds that exceed roughly 90% the escape speed, the ejecta particles come from all over the lunar surface to the ROI. Comparing the secondary ejecta fluxes from MeMoSeE with NASA SP-8013 [1], there is a reduction by about 2-3 orders of magnitude for secondary ejecta particles greater than 1 µg. These estimates agree with recent findings from Bjorkman & Christiansen 2019 [11]. The secondary ejecta fluxes are also compared with the primary fluxes, where the ejecta fluxes are roughly an order of magnitude greater than the primary fluxes. References: [1] Cour-Palais, B. G., (1969) NASA SP-8013. [2] NASA SLS-SPEC-159 Rev. H (2020). [3] Moorhead, A. V., et al. (2019) JS&R, 1-17. [4] Giorgini, J. D., (2015) IAUGA, 29, 2256293. [5] Moorhead, A. V., (2020) Memo OSMA/MEO/Lunar-001. [6] Housen, K. R., and Holsapple, K. A., (2011) Icarus, 211(1), 856-875. [7] Gault, D. E., and Wedekind, J. A., (1978) L&PSCP, 9, 3843-3875. [8] Rival, M., and Mandeville, J., (1999) Space Debris, 1(1), 45-57. [9] Moorhead, A. V., (2019) MEM3 User Guide. [10] Carrier, W. D., (1973) The Moon, 6(3-4), 250-263. [11] Bjorkman, M. D. & Christiansen, E. L., (2019) ODC

impacts↗
NASA NTRSDate not supplied

Volume Raycasting of GNSS Signals through Ground Structure Lidar for UAV Navigational Guidance and Safety Estimation

Autonomous UAS navigation at low altitudes is often hindered by degradation of GNSS position estimates. The line of sight from the UAS to orbital satellites may be intersected by foliage (which attenuates the received signal) and by buildings (which block the signal). Since the geometric ray from the presumed UAS position to each GNSS satellite orbital location is predictable, if a 3D survey of ground structures is available, the degree of blockage of each GNSS signal can be estimated. In this study we show raycasting from a UAS location to GNSS satellites at two flight locations: one with overlying structures and bordered by tall trees, and another in an arboreal canyon bordered by tall trees. We confirm the intermittent blockage of satellites in the first location sufficient to lose GNSS position fix. We demonstrate low-altitude GNSS fidelity forecasting via the raycasting method at the second location that can be used to plan navigable flight locations and altitudes. Finally, we match the GNSS signal strength with raycast-derived foliage obstruction depth at hundreds of observation times from 55 recordings collected over 14 days from November 2018 to February 2021 at the second location. This matching confirms that signal attenuation varies with the depth of foliage blockage along a saturating exponential curve, as found in prior continuous-wave RF studies. The exponent and saturation value are species dependent and therefore vary from site to site; once determined empirically, they can be used to characterize foliage along a particular flight path, and refine GNSS fidelity forecasts of flights along that path. The techniques described in this study show the feasibility of a survey method to construct low-altitude navigation safety maps and forecasts.

Navigation↗
NASA NTRSDate not supplied

Sensitivity of Optimal Midcourse Correction Scheduling for Robust Cislunar Trajectory Design

A new approach to optimal trajectory design is the determination of optimal trajectories that are robust to initial trajectory dispersions, navigation errors, maneuver execution errors, and environment modeling errors. This paper investigates the sensitivity of cislunar robust optimal trajectory design to launch date, duration of navigation measurement passes, and navigation measurement frequency. For a given cislunar trajectory from translunar injection (TLI) to lunar orbit insertion (LOI), the optimal locations of midcourse corrections, also known as trajectory correction maneuvers (TCM) are determined by minimizing the final 3-σ ∆v subject to a final 3-σ position dispersion constraint for a given launch date, specified measurement pass duration prior to each maneuver, and measurement frequency. Optical navigation (OpNav) is assumed, and OpNav field-of-view (FOV) and lighting constraints are employed. These constraints turn out to be important elements of the problem. The sensitivity of the optimal TCM locations are then investigated by varying the launch date, duration of OpNav measurement passes, and the OpNav measurement frequency, and then re-optimizing the locations of the TCMs. Given the problem parameters provided herein, results show that while the optimal TCM locations with respect to TLI vary greatly from one launch date to another, their locations with respect to LOI are nearly invariant over a 2-month launch window. Results also show that in all cases the optimal location of the last TCM is found to be at the point where the OpNav lunar FOV constraint is first violated. For all other TCMs, OpNav measurement pass duration and measurement frequency can have a moderate to large affect on the optimal TCM locations.

Linear Covariance Analysis↗
NASA NTRS2023

Fire Station #2, Former Sewage Treatment Plant #17, and Towway Area-SWMU 114 PFAS Site Assessment Progress Report Kennedy Space Center, Florida

This PFAS Site Assessment Progress Report (SAPR) presents the findings of the 2022 PFAS investigation conducted from November 2021 through August 2022 at Solid Waste Management Unit (SWMU) 114 located within Kennedy Space Center (KSC), Florida. SWMU 114 includes area around Fire Station #2, Former Sewage Treatment Plant #17, the southern portion of the Shuttle Landing Facility Runway, Remote Launch Vehicle Hangar, and the Towway area. Fire Station #2 was constructed in 2008 and is currently active, housing fire station personnel and equipment, including aqueous film forming foam (AFFF). Releases of AFFF has occurred at SWMU 114. Previous environmental assessments have been performed at SWMU 114, including soil, groundwater, and surface water sampling for volatile organic compounds, polycyclic aromatic hydrocarbons, total petroleum hydrocarbons, and metals. No active remediation has been performed at the SWMU 114. PFAS site assessment field activities were conducted at SWMU 114 from November 2021 through August 2022. During the 2021-2022 Site Assessment, 124 direct-push samples were collected from 27 locations, 17 surface water samples were collected from 15 locations, 41 groundwater samples were collected from 37 newly installed monitoring wells, five concrete samples were collected from four locations, and one asphalt sample was collected. Additionally, two soil borings were advanced to 60 feet for lithologic descriptions, ten staff gauges were installed, and one round of water level measurements were collected from monitoring wells and staff gauges for groundwater flow determination. All groundwater and surface water samples were analyzed for 25 PFAS analytes by USEPA Method 537M. Concrete, and asphalt samples were analyzed by synthetic precipitation leaching procedure (SPLP) PFAS analysis by USEPA Modified Method 537M. Groundwater results were compared to the most recent Regional Screening Levels (RSLs) published by USEPA for residential tap water (USEPA, 2022a) to determine the extent of PFAS contamination at SWMU 114 for six PFAS analytes (PFOA, PFNA, PFBS, PFHxS, PFOS, and GenX). Surface water results were compared to the FDEP surface water screening levels (SW SLs) (FDEP, 2020) for PFOA and PFOS. The PFAS investigation concluded that groundwater exceeding RSLs extends east and south to Banana Creek and west to approximately the center of the SLF runway. The extent of PFAS is approximated to the north, to an area between Sharkey Road and Astronaut Road, where samples below the RSLs do not fully bound SWMU 114. At least two distinct PFAS source areas are located near Fire Station #2 and along Towway, at S114-MW0007S, within SWMU 114. Groundwater head measurements indicate that flow at SWMU 114 is generally similar across the shallow and intermediate water tables. A northeast to southwest trending groundwater divide is located near the middle of Towway where groundwater southeast of the divide flows to the south and groundwater northwest of the divide flows to the west. The groundwater divide generally separates the two areas of higher PFAS concentrations. Surface water samples indicated concentrations of PFOS above the SW SLs in surface water bodies across the site. Further assessment and sampling are required to better understand the interaction between groundwater and surface water at SWMU 114. Concrete and asphalt samples collected confirm that a significant release of AFFF occurred near the stormwater pond northwest of Fire Station #2. Additional concrete samples surrounding Fire Station #2 and at the northwest and southeast edges of the SLF tarmac indicate elevated PFOS concentrations. These results indicate that discharges of AFFF in these locations have infiltrated into asphalt and concrete and may act as a continuing source of PFAS to groundwater and surface water after rain events. Additional direct-push samples are required to delineate PFAS at SWMU 114. Samples may need to extend beyond the Former SLF Rescue Building and Morpheous Test Site to delineate PFAS in groundwater. Monitoring wells should be sampled and gauged quarterly to determine if seasonal impacts are observable, especially in shallow wells near surface water features. Furthermore, surface water samples should be collected from additional ditches to further define the extent of surface water impacts at SWMU 114 and extending along the SLF runway. Staff gauges should be gauged quarterly with groundwater gauging to determine surface water flow and interaction with groundwater. The PFAS sampling results and path forward for SWMU 114 were presented to the KSC Remediation Team in October 2022. Once the PFAS SAPR is approved, it will be submitted to the Florida Department of Environmental Protection.

Howard Franklin Fowler↗
DOE OSTI2022

System, method, and computer program product for transporting an unmanned vehicle

A method, system, and computer program product is provided for transporting an unmanned vehicle to a destination location. The method includes determining a ground vehicle from a plurality of ground vehicles based on a location of the ground vehicle, the destination location, and a location of the unmanned vehicle, controlling the unmanned vehicle to the location of the ground vehicle, controlling at least one attachment mechanism to attach the unmanned vehicle to the ground vehicle, in response to the ground vehicle traveling to a second location, controlling the at least one attachment mechanism to detach the unmanned vehicle from the ground vehicle, and controlling the unmanned vehicle to the destination location.

Samaras, Constantinos↗