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NASA NTRS2018

Antarctic Martian Meteorites at Johnson Space Center

This past year marked the 40th anniversary of the first Martian meteorite found in Antarctica by the ANSMET Antarctic Search for Meteorites) program, ALH 77005. Since then, an additional 14 Martian meteorites have been found by the ANSMET program making for a total of 15 Martian meteorites in the U. S. Antarctic meteorite collection at Johnson Space Center (JSC). Of the 15 meteorites, some have been paired so the 15 meteorites actually represent a total of approximately 9 separate samples. The first Martian meteorite found by ANSMET was ALH 77005 (482.500 g), a lherzolitic shergottite. When collected, this meteorite was split as a part of the joint expedition with the National Institute of Polar Research (NIPR) Japan. Originally classified as an "achondrite-unique", it was re-classified as a Martian lherzolitic shergottite in 1982. This meteorite has been allocated to 137 scientists for research and there are 180.934 g remaining at JSC. Two years later, one of the most significant Martian meteorites of the collection at JSC was found at Elephant Moraine, EET 79001 (7942.000 g), a shergottite. This meteorite is the largest in the Martian collection at JSC and was the largest stony meteorite sample collected during the 1979 season. In addition to its size, this meteorite is of particular interest because it contains a linear contact separating two different igneous lithologies, basaltic and olivine-phyric. EET 79001 has glass inclusions that contain noble gas and nitrogen compositions that are proportionally identical to the Martian atmosphere, as measured by the Viking spacecraft. This discovery helped scientists to identify where the "SNC" meteorite suite had originated, and that we actually possessed Martian samples. This meteorite has been allocated to 205 scientists for research and 5,298.435 g of sample is available.

Funk, R. C.↗
NASA NTRS2018

Science Service Status 2019 World Radiocommunication Conference

Science missions such as Earth-exploration and remote sensing thatuse frequencies allocated for Earth Exploration-Satellite Service(EESS) provide valuable information about, for example: (1) Air quality monitoring (2) Soil moisture mapping (3) Sensing sea salinity (4) Weather forecasting and climate models (winds, storms, clouds).Another set of science missions use Space Research Service (SRS)allocations. These space research missions can support: (1) On orbit research that for example can help in the creation of new drugsor the impact of the space environment on satellites (2) Scientific information about the universe – stars, planetary science, solarsystem, and the future evolution of the universe.

Roura, Corali↗
NASA NTRS2018

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.

NextGen↗
NASA NTRS2018

Evaluation of Multiple Flow Constrained Area Capacity Setting Methods for Collaborative Trajectory Options Program

The purpose of this study was to compare flow constrained area (FCA) capacity setting methods for Collaborative Trajectory Options Program (CTOP) as they pertain to the Integrated Demand Management (IDM) concept. IDM uses flow balancing to manage air traffic across multiple FCAs with a common downstream constraint, as well as constraints at the respective FCA locations. FCA capacity rates can be set manually, but generating capacities for multiple, interdependent FCAs could potentially over-burden a user. A new enhancement to CTOP called the FCA Balance Algorithm (FBA) was developed at NASA Ames Research Center to improve the process of allocating capacity across multiple flow constrained segments in the airspace. The FBA evaluates the predicted demand and capacity across multiple FCAs and dynamically generates capacity settings for the FCAs that best meet capacity limits for all identified constraints. In a human-in-the-loop simulation study, both manual and automated capacity setting methods were evaluated in terms of their overall feasibility using measures of system performance, human performance, and qualitative feedback. Subject matter experts were asked to use three different methods to allocate capacity to three FCAs, either (1) by manually setting capacity for every 60-minute time window, (2) by manually setting capacity for every 15-minute time window, or (3) by using the FBA capability to automatically generate capacity settings. Results showed no significant differences in terms of overall system performance, indicated by similar ground delay and airport throughput numbers between methods. However, differences in individual strategies afforded by the manual methods allowed some participants to achieve system-wide delay that was much lower than the average. The FBA was the fastest method of capacity setting, and it received the lowest subjective rating scores on physical task load, mental task load, task difficulty and task complexity out of the three methods. Finally, participants explained through qualitative feedback that there were many benefits to using the FBA, such as ease of use, accuracy, and low risk of human input error. Participants did not experience the same limitations with the FBA that they did with the manual methods, such as reduced accuracy in the 60-minute manual condition, or high complexity in the 15-minute/manual condition. These results suggest that the FBA automation enhancement to CTOP maintains system performance while improving human performance. Therefore, the FBA could be introduced as a way to mitigate operator workload while planning a CTOP.

NextGen↗
NASA NTRS2015

A Stochastic Scheduler for Integrated Arrival, Departure and Surface Operations in Los Angeles

In terminal airspace, integrating arrivals, departures, and surface operations with competing resources provides the potential of improving operational efficiency by removing barriers between different operations. This work develops a centralized stochastic scheduler for operations in a terminal area including airborne and surface operations using Non-dominated sorting genetic algorithm and Monte Carlo simulations. The scheduler handles completing resources between different flows, such as runway allocations, runway crossing, departure fixes, and other interaction way points between arrivals and departures. Meanwhile, the scheduler also takes time-varied uncertainties into account when optimizing schedules. The scheduler is run sequentially to identify the best and robust schedule for the next planning window. Resulting schedules decide the routes, speed or delays, and runway assignments with separation constraints at mergingdiverging waypoints in the air and crossing and separations on runways. The Los Angels terminal area was used as an example. The implementation of this stochastic scheduler for integrated arrival, departure and surface operations is completed. And several preliminary runs are finished for over 1,200 flights in LAX in a typical day. Sensitivity studies on various planning window sizes are presented, which shows that trade-off exits between planning window size and achievable minimum delay. Preliminary results on runway usage are also presented in this abstract. Because arrivals on the outer runways have to be followed by crossings on the inner runways, algorithmic runway allocation prefers inner runways for arrivals and outer runways for departures. More results will be presented in the final paper. And current terminal arrival and departure procedures based on first-come-first-serve procedure will also be set up and used as a baseline for comparison.

integrated scheduler↗
NASA NTRS2014

Controller Inhibition of Automated Conflict Resolutions in a Maximum NextGen Condition

With the continued projection of increases in air traffic density, operations in the National Airspace System are expected to exceed human capabilities in the near future. In order to address the bottleneck of human workload capacity, highly automated safety-critical systems are under development to support air traffic controllers. A human-in-the-loop experiment examined controllers transition through four NextGen automation stages: Current-Day, Minimum, Moderate, and Maximum. Maximum NextGen simulated a fully automated environment where the automation was responsible for detecting and resolving conflicts within simulation parameters in high-density airspace. By allocating these tasks to the automation, the controllers task changed. The human moved to primarily a supervisory position- typically only regaining control over separation assurance tasks during conflict situations deferred by the automation. While tasks were allocated a-priori between the controller and automated agent, controllers maintained authority to inhibit the automation from interacting with particular aircraft. Preliminary work is complete, where significant differences were found in inhibition frequency between simulation participants. However, the contexts in which the controllers inhibited the automation, and their reasons for doing so, remain unclear. This analysis attempts to identity factors contributing to human controllers inhibition of the automation in the Maximum NextGen condition.

adaptable automation↗
NASA NTRS2019

A Permanent Human Lunar Surface Presence Enabled by a CLV Class JUMP Lander

There are compelling advantages of a human presence on the surface of the Moon, as evidenced partly by the preponderance of lunar surface architectures that have existed throughout NASA, industry, and academia since the Apollo program. This paper specifically advocates and illustrates an example of a permanent human lunar surface presence enabled by a commercial launch vehicle (CLV) class Joinable Undercarriage to Maximize Payload (JUMP) lunar lander. The paper will discuss purposes for such a surface presence, including SPD-1 fulfillment, global collaboration, US industry advancement, US government leadership in spaceflight, a Mars dress rehearsal, Mars collaborative exploration, and lunar village development. An architectural description will be presented, including site selection, primary elements, and surface configuration. Element and lander allocation to CLV and Space Launch System (SLS) rockets will be discussed in terms of launch vehicle selection philosophy and allocation to specific launch manifests. This will enable a presentation of a lunar campaign spanning the period from 2026 to 2056. In conclusion, various aspects of the architecture will be suggested for further study.

Howard, Robert L., Jr.↗
NASA NTRS2020

On-Orbit Validation of a Framework for Spacecraft-Initiated Communication Service Requests with NASA's SCaN Testbed

We design, analyze, and experimentally validate a framework for demand-based allocation of high-performance space communication service in which the user spacecraft itself initiates a request for service. Leveraging machine-to-machine communications, the automated process has potential to improve the responsiveness and efficiency of space network operations. We propose an augmented ground station architecture in which a hemispherical-pattern antenna allows for reception of service requests sent from any user spacecraft within view. A suite of ground-based automation software acts upon these direct-to-Earth requests and allocates access to high-performance service through a ground station or relay satellite in response to immediate user demand. A software-defined radio transceiver, optimized for reception of weak signals from the helical antenna, is presented. Design and testing of signal processing equipment and a software framework to handle service requests is discussed. Preliminary results from on-orbit demonstrations with a testbed onboard the International Space Station are presented to verify feasibility of the concept.

Adam M Gannon↗
NASA NTRSDate not supplied

Impacts of Hybrid Parallelism and Vectorization on the Performance of Newton-Krylov Methods in Computational Aerodynamics

Finding the numerical solution of moderate and high-fidelity aerodynamics problems on modern computer architectures involves, 1) decomposing the domain into smaller regions of nearly equal size, and 2) allocating computational resources for calculations on each domain and communication between domains. Modern computer clusters are composed from hierarchies of processing, memory, and communication resources with varying capabilities and latencies.This paper focuses on the combination of domain decomposition provided by ParMETIS [1]and Newton-Krylov Methods [2–5] for the solution of Computational Aerodynamics problems of interest to NASA. Herein, trade-offs encountered when mapping aerodynamics problems to modern computer architectures are explored through examples and discussions of trade-offs in parallelism from MPI [6], Open MP [7], and vectorization as partition sizes and computational resources are varied. An example of the impact that domain decomposition and MPI+OpenMPresource allocation can have on an adjoint calculation is presented in this abstract. The full paper will include more detailed examples, discussions of difficulties and potential methods to overcome them, and topics identified for future study.

Computational Aerodynamics, Hybrid Parallelism, Ve↗
NASA NTRSDate not supplied

M:N Operations NASA/Uber Collaboration

In this presentation, current approaches to enable multiple-operator, multiple vehicle (M:N) operations are reviewed together with recent collaborative efforts between NASA and Uber. Topics include a review of human-automation teaming (HAT) concepts, including plays and working agreements, and a particular task-allocation method called Automation Level-based Task Allocation (ALTA). Following introductory material on HAT, an overview of a recent (July 2020) cognitive walkthrough study of M:N operations in the context of a food delivery via small-Unmanned Aircraft Systems application is provided. Initial results from this cognitive walkthrough detailing operator feedback on displays, operator and supervisor roles and responsibilities, and the overall concept of operation are reviewed. The presentation concludes with a description of a future, human-in-the-loop simulation experiment of M:N operations in a high-fidelity environment, which will examine the effects of high workload and assistive automation/tools on operator performance.

human-automation teaming↗
NASA NTRS1993

(abstract) FASTER -- A Tool for DSN Forecasting and Scheduling

FASTER, the Forecasting And Scheduling Tool for Earth-based Resources is a suite of software tools developed at JPL to aid in the process of allocating DSN 70 and 34 meter antennas and equipment to support deep space satellites and ground based astronomy. FASTER has been designed for use by a diverse user community, including mid-level managers, data entry and analysis teams, and project scheduling personnel. The system helps to automate many of the previously labor intensive tasks and ensure proper analysis and consistency throughout all phases of the allocation process. FASTER implements an interactive environment for both forecasting and scheduling. This paper will discuss technical aspects of the FASTER system, including forecasting and scheduling algorithms, issues related to large scale use of a scheduling and forecasting system, implications to the process in which a forecasting and scheduling system is embedded, and lessons learned and implications to similar systems.

forecasting↗
NASA NTRSDate not supplied

Flight Trajectory Prediction Based on Hybrid-Recurrent Networks

The development of future technologies for the National Airspace System (NAS) will be reliant on a new communications infrastructure capable of managing the limited available spectrum for communications among aircraft and ground systems. Emerging approaches to autonomous allocation of aviation spectrum mostlyrely on machine learning techniques, where 4D (longitude, latitude, altitude, time) trajectory prediction is an important data input to enable real-time resource allocation. This study explores and evaluates effective data sources and deep recurrent neural network techniques when determining flight trajectories. Specifically, data are collected and evaluated in a 100-day and 14-day period. Sources of data include NASA Sherlock Data Warehouse, MIT Lincoln Labs Corridor Integrated Weather Service (CIWS), and assorted NOAA weather datasets. Deep learning models for 4D predictions all utilize a hybrid-recurrent technique. A baseline model is considered via the convolutional-LSTM design from the existing literature. The modified design considers Gated Recurrent Units (GRU), Independently Recurrent Neural Networks (IndRNN), and stand-alone self-attention layers. Results indicatethe effectiveness of LSTM and GRUcells for state-of-the-art data processing (interpolation). Additionally, GRUs may be quickly trained with limited data, allowing for exacting improvements with optimizer selection. Attention mechanisms provide notable performance improvements to convolutional layers and may extend dimensional capabilities of a learning model. Finally, NOAA measurements provide only a supplemental value, requiring support from tailored measurements for Air Traffic Management.

Nathan Schimpf↗
NASA NTRSDate not supplied

Internal Architecture of the Common Habitat

The core stage liquid oxygen tank of the Space Launch System can be manufactured as a habitat instead of as a propellant tank, with a common design such that it is equally suitable for use in 0g, 1/6g, 3/8g, 1g, or variable artificial gravity. This Common Habitat can be the central element of a human spaceflight architecture that encompasses the Moon, Mars, and other destinations within the inner solar system. The Common Habitat is specifically used within an alternative architecture study (that is not part of the current NASA baseline) as the core habitation element within a Lunar Basecamp, Mars Basecamp, and the Deep Space Exploration Vehicle. The Common Habitat internal architecture applies a design philosophy to separate crew functions according to deck. The lower deck is reserved for private functions. It includes eight private crew quarters and four waste and hygiene clusters – each with a private waste management compartment, private full body hygiene compartment, and foyer/clothes changing area. The mid deck is primarily allocated to mission-related working functions. It includes an exercise facility, fabrication / maintenance / repair facility, physical science laboratory (physics, geology, and astronomy), and life science laboratory (biology and human research). The mid deck also has four external hatches, clocked one every 90 degrees, centered on the vehicle vertical centerline. Each hatch has a 60-inch tall by 40-inch wide opening with the mid deck floor 16 inches below the bottom lip of the hatch opening. The upper deck is primarily allocated to group or social functions. It includes a large galley, wardroom with projector and display screen, plant growth chambers, bulk stowage, command and control station, medical facility, hygiene compartment, and vehicle subsystems. A Vertical Translation System, based in part on results from a GrabCAD public challenge, enables crew and equipment traverse between habitat decks in 0g, 1/6g, 3/8g, and 1g. A 40-inch by 60-inch vertical translation corridor ensures that anything that can fit through the external hatches can also be moved from deck to deck. The system includes three component systems: a deploying floor to safety barrier system that folds down to become a traversable floor when vertical translation is not in use and deploys to become a safety barrier during vertical translations; a folding ladder that stows in the ceiling when not in use; and an elevator platform that can attach to the ladder for cargo or incapacitated crew member transport. This system is complemented by a Horizontal Translation System, also based in part on the same GrabCAD challenge, provides for horizontal crew translation in microgravity but requires no vehicle reconfiguration for fractional or whole gravity operation. It relies primarily on gecko-inspired grippers, originally developed at Stanford and NASA JPL, attached to footwear to enable crew to emulate walking. Some handrails are also strategically placed throughout the Common Habitat to aid translation in both gravity and microgravity environments.

Common Habitat↗
NASA NTRSDate not supplied

Challenges, Considerations, and Opportunities for Exercise and Medical Accommodation Inside a Small Pressurized Rover

Pressurized Rovers (PR) can enable crew to explore away from a lander or surface habitat at distances not possible on foot or even in unpressurized rovers. Sustaining crew for multiple days, they can rove for weeks, independent of other surface elements. Because these are essentially mobile habitats, it is critical that they provide sufficient volume to accommodate the exercise and medical systems to maintain human health in remote, low gravity environments such as the Moon and Mars. This is an area of extensive unknowns as requirements have not yet been developed for exercise or medical systems in pressurized rovers. Yet they must be considered in vehicle sizing studies as they are significant volume drivers, requiring allocation for stowed and deployed hardware inside the rover cabin. Previously flown spacecraft have allocated varying amounts of volume based on the expected crew mission and the state of the art in these systems. NASA-STD-3001 provides high-level requirements for standards of medical care and exercise capabilities. Crew injuries are possible both inside the cabin and on extravehicular activities (EVA), therefore requiring medical capability. Exercise countermeasures are needed to counteract the debilitating effects of lowered gravity. This may include both reconditioning following a lengthy microgravity transit as well as ongoing countermeasures against the effect of low surface gravity. The NASA reference concept for the PR dates back to the Constellation Program and prototypes have been extensively tested in NASA’s Desert Research and Technology Studies (DRATS) program as well as at the NASA Johnson Space Center. The PR cabin is designed to accommodate two crewmembers and is subdivided into a forward cockpit area and a main body for crew habitation. EVAs are accomplished by transitioning through suit ports in the aft bulkhead into spacesuits. While no exercise devices have been developed for the PR, some have been prototyped and demonstrated in DRATS analog missions. A cycle ergometer performed reasonably well in DRATS testing as an aerobic exercise device and recent analysis work has theorized that a combination aerobic and resistive device could be packaged into a form factor similar to the DRATS ergometer. It is therefore suitable for use as an initial volumetric placeholder. No sensorimotor devices have been considered for the PR to aid in adaptation to surface gravity. However, there are commercially available treadmills that at minimum represent examples of the type of exercise system that could potentially be used for such a purpose. A combination of field test data, analysis, and CAD modeling will be used to perform a first pass assessment of whether these exercise devices can be stowed and deployed within the PR. Medical inventories from the International Space Station will be used as a volume placeholder for the PR medical system. A configuration will be discussed for medical deployment, including positioning of caregiver, patient, and medical equipment / supplies.

Pressurized Rover↗
NASA NTRSDate not supplied

Internal Architecture of the Common Habitat

The core stage liquid oxygen tank of the Space Launch System can be manufactured as a habitat instead of as a propellant tank, with a common design such that it is equally suitable for use in 0g, 1/6g, 3/8g, 1g, or variable artificial gravity. It is capable of sustaining a crew size of eight for missions up to 1200 days in duration. This Common Habitat can be the central element of a human spaceflight architecture that encompasses the Moon, Mars, and other destinations within the inner solar system. Within this archtiecture, the Common Habitat is specifically used as the core habitation element within a Lunar Base Camp, Mars Base Camp, and the Deep Space Exploration Vehicle. The Common Habitat internal architecture applies a design philosophy to separate crew functions according to deck. The lower deck is reserved for private functions. It includes eight private crew quarters and four waste and hygiene clusters – each with a private waste management compartment, private full body hygiene compartment, and private foyer/clothes changing area. The mid deck is primarily allocated to mission-related functions. It includes an exercise facility, fabrication / maintenance / repair facility, physical science laboratory (physics, geology, and remote sensing: astronomy, heliophysics, planetary science, and Earth science), and life science laboratory (biology and human research). The mid deck also has four external hatches, clocked one every 90 degrees, centered on the vehicle vertical centerline. Each hatch has a 60-inch tall by 40-inch wide opening with the mid deck floor 16 inches below the bottom lip of the hatch opening. The upper deck also includes some mission functions, but is primarily allocated to social functions. It includes a large galley, wardroom with projector and display screen, plant growth chambers, bulk stowage, command and control station, medical facility, hygiene compartment, and vehicle subsystems.

Habitability↗
NASA NTRSDate not supplied

Soluble Organic Matter (SOM) analysis of the Hayabusa2 samples: The first results

The Hayabusa2 spacecraft successfully collected the surface and possible sub-surface materials of the asteroid 162173 Ryugu. Ryugu is a C-type asteroid characterized by a low-albedo surface probably consisting of hydrous minerals and carbonaceous materials. [1] The direct optical and spectral analysis of the returned samples indicates that Ryugu material is dominated by hydrous carbonaceous chondrite-like matter (similar to CI chondrites) [2]. Since carbonaceous chondrites have generally yielded various types of organic matter, the collected Ryugu grains are expected to contain diverse types of organic compounds including bio-related molecules. The occurrence of organic compounds in the Ryugu surface will provide clues to the evolution of prebiotic molecules and their preservations associated with aqueous alteration of the primitive asteroid. The initial analysis of soluble organic matter (SOM) of the Hayabusa2-returned samples has been performed by an international team consisting of 32 members. Because the sample amount available for comprehensive SOM analyses is limited, and because the SOM is expected to be present as a complex mixture of various types of organic compounds with very small concentrations of each compound, high-sensitivity and high-resolution analytical techniques have been developed using carbonaceous meteorites [e.g. 3]. Two aggregate samples of the Ryugu grains (A106 and C107) were allocated for the solvent extractions and bulk carbon (C), hydrogen (H), nitrogen (N), sulfur (S) and oxygen (O) measurements. The A106 sample was collected during the 1st sampling in February 2019 and the C107 sample was collected during the 2nd sampling in July 2019 after the Small Carry Impactor (SCI) operation. They consist mainly of particles smaller than 1 mm in diameter, and each sample mass was 38-39 mg. They were firstly investigated spectroscopically in the near infrared wavelength range by the Stone Team prior to the solvent extractions. Other small grains (A0080 and C0057) were also allocated for this study to investigate the spatial distribution of organic compounds on the sample surface. The extraction and analytical measurements implemented by the SOM Team are summarized in Figure 1. Each powder sample was extracted sequentially with non-polar to polar solvents, i.e., hexane, dichloromethane (DCM), methanol (MeOH) and H2O, for non-targeted analysis to reveal the compound composition. Each solvent extract was analyzed by solution state nuclear magnetic resonance (NMR) spectroscopy [4], Fourier transform- ion cyclotron resonance/mass spectrometry (FT-ICR/MS) with ESI and APPI ionization [5] and by high-resolution mass spectroscopy using Orbitrap MS coupled with nano-liquid chromatography (nanoLC/Orbitrap MS) [6], and using two dimensional gas chromatography/mass spectrometry (GC×GC/MS). The extracted residues were passed to the Chemistry Team for further inorganic element analysis. The other powder sample was subjected to the hot water extraction for amino acid analyses including chiral isomer separation, which was performed by three-dimensional (3D) high-performance liquid chromatography (HPLC) with high-sensitivity fluorescence detection (FD) [7] and by HPLC/FD coupled with quadrupole-time of flight/mass spectrometry (QToF/MS) [8]. After the hot water extraction, the residue was split into two halves. One half was further extracted with hydrochloric acid (HCl) to analyze for amino acids in bound-form. The other half was sequentially extracted with DCM/MeOH (1/1) to analyze semi-polar compounds such as polycyclic aromatic hydrocarbons (PAHs) by GC/MS, followed by further extraction with formic acid to analyze polar heterocyclic compounds, and subsequent extraction with HCl to detect bound-form polar compounds. The extracted residues were passed to the IOM Team for the analysis of insoluble organic matter (IOM). Compound-specific stable isotope analyses will be performed using GC/combustion/isotope ratio mass spectrometry (GC/C/IRMS) if the compound concentration is high enough to enable such an isotopic measurement. All extraction procedures were performed on an ISO 6 (Class 100) clean bench inside an ISO 5 (Class 1000) clean room. Baked serpentine powder was also analyzed as a procedural blank. In situ organic compound analysis with the molecular imaging was performed using desorption electrospray ionization (DESI) equipped with Orbitrap MS [9, 10], followed by spatial imaging of organic compounds using ToF/secondary ion mass spectrometry (ToF/SIMS) [11]. The bulk chemical and isotopic compositions of CNS and HO were determined using nano-elemental analysis/isotope ratio mass spectrometry (nanoEA/IRMS) [12] and EA/pyrolysis/IRMS, respectively. We have identified a variety of indigenous organic compounds in the extracts of both A106 and C107 samples. The Ryugu grains host organic molecules under the high-vacuum and cosmic-ray irradiation environment of the asteroid surface. The analysis of extracted molecules is in progress, and the first results will be presented at the symposium.

Hiroshi Naraoka↗
NASA NTRSDate not supplied

Characterizing Detailed Grain Shape and Size Distribution Properties of Lunar Regolith

Introduction: As the nation prepares to return to the Moon, there is an increasing need for testing tools, instruments, and equipment in simulated environments on Earth to ensure successful operations during lunar missions. Regolith will affect all aspects of future lunar missions, from plume interactions during landing to space suit and tool design [1]. Because of this, it is important to understand the grain shape and size properties of lunar regolith and how those influence regolith behavior in order to prepare for these missions. This knowledge is also vital to create more accurate lunar regolith simulants for testing equipment in a lunar environment. While particle size analyses have been performed on most Apollo soils using simple sieving, shape has only been crudely addressed [2]. This work analyzes 4 lunar regolith samples to provide a better understanding of these size and shape parameters and will provide a more accurate baseline of data to create high-fidelity lunar regolith simulants. Methods: New technologies exist today that are capable of measuring size and shape simultaneously for hundreds of thousands of particles in a single measurement. We conducted a rigorous analysis of the particle size distribution (PSD) as well as the size-dependent 2D and 3D shape parameters of lunar regolith samples of different compositions and maturity levels. This analysis was done using a Microtrac SYNC which provides a unique combination of tri-laser diffraction and Dynamic Image Analysis (DIA). Sample Selection. Four regolith samples were selected for analysis based on maturity level and lunar terrain type: • 10084 – Mature high-Ti mare regolith • 15601 – Immature low-Ti mare regolith • 64501 – Mature highland regolith • 67461 – Immature highland regolith Sample Analysis. After receiving the samples, each sample was imaged with an optical microscope (Figure 1). To obtain 2D and 3D particle size and shape, 0.1 g of each sample was then added to the SYNC for analysis, which outputs more than 30 size and shape parameters for each individual grain as well as the complete size distribution from 0.01-2000 μm by blending laser diffraction and DIA together. For the 0.1 g sample masses requested, ~100,000 grains per sample were captured by DIA. Results: From the PSD analysis, it can be seen that the average particle size of 10084 is ~24.5 µm which is much smaller than the average particle size of the Apollo sample collection (~72 µm) [3], while the average particle size of samples 15601, 64501, and 67461 are larger than the Apollo sample average at ~106 µm, ~103 µm, and ~118.5 µm respectively. The size and shape measurements for the samples output ~30 parameters, four of which were focused on for this study: sphericity, aspect ratio, roundness, and concavity (Figure 3). However, after analyzing the plots it was found that only sphericity and aspect ratio showed differences between the samples. These two parameters are measured on a scale from 0 to 1, with 1 being a perfect sphere with equal dimensions. The results show that the sphericity values are slightly high-er for the mature samples 10084 and 64501 (~0.96) than they are for samples 15601 and 67461 (~0.95) (Figure 4). The aspect ratio values are slightly lower for samples 64501 (~0.7) and 67461 (~0.74) than they are for samples 10084 (~0.76) and 15601 (~0.8) (Figure 5). Discussion: Mature regoliths are those that have been exposed to micrometeorite and solar wind bombardment for long periods of time, breaking up particles and causing them to become more rounded [4]. Therefore, the smaller particle sizes and higher sphericity values for samples 10084 and 64501 are expected due to their higher maturity level compared to 15601 and 67461. However, the aspect ratio values are not dependent on maturity and are instead dependent on terrain type. The lower aspect ratio values for the high-land samples is potentially due to the higher plagioclase content, which occurs in elongated particles and does not break down as easily as the pyroxenes or olivines that are present in the mare. Conclusion and Future Work: The results of this work provide a baseline of high-quality data that will contribute to the creation of high-fidelity lunar simulants and will greatly benefit NASA’s efforts of establishing a human presence on the Moon. Future work includes performing unsupervised image classification on the ~105 particle images per sample in order to identify different classes of grains. These grain classes can then be linked to detailed shape properties, and the relative abundance of each class in the samples can be compared. Acknowledgments: We would like to thank the Extraterrestrial Materials Analysis Group (ExMAG) and the Astromaterials Allocation Review Board (AARB) for allocating lunar regolith samples 10084,9010, 15601,365, 64501,249, and 67461,171 for this work. References: [1] Taylor, L. A. et al. (2005) AIAA #2510. [2] Katagiri et al. (2015) ASCE. [3] Carrier III, W. D. (2005) Lunar Geotech Institute Tech Report. [4] McKay, D. S. et al. (1991) The Lunar Sourcebook, Chapter 7.

S R Deitrick↗
NASA NTRS2020

Space Ground Sensorwebs for Volcano Monitoring

Increased space and ground sensing is enabling dramatic new measurements of a wide range of Earth Science and Applied Earth Science phenomena, including: volcanism, flooding, wildfires, weather, and many other phenomena. New Space ventures have produced significantly greater access to data and miniaturization of sensing has enabled cubesats and smallsats to deliver data of outstanding resolution. The advent of the internet of things has produced incredible amounts of relevant terrestrial data as well. Artificial Intelligence offers the potential to automate both data interpretation and resource allocation to best allocate sensing assets. We describe efforts to build and experiment with such “sensorweb” systems and offer some direction for the future sensorweb observation systems.

Zuleta, Ignacio↗