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NASA NTRSDate not supplied

JETT3: A Holistic, Integrated Analog for Artemis Lunar Surface Exploration

Since 1972, NASA astronauts have performed hundreds of Extravehicular Activities (EVAs) in support of Skylab, Space Shuttle and International Space Station missions. Not since Apollo, however, have EVAs been driven by discovery-based principles of scientific exploration. Upcoming Artemis missions are challenged to build on lessons learned from Apollo, merging 50 years of EVA experience with the planetary science community’s expertise in the remote surface exploration of Mars. The highest-fidelity preparation for Artemis includes both operational and scientific underpinning to represent the complete, complex picture of lunar surface operations. The Joint EVA & Human Surface Mobility Test Team (JETT) is an interdisciplinary team providing such an environment for collaborative analog testing. JETT builds upon prior analog campaigns (e.g., [1, 2]) to provide high-fidelity environments for hardware and concept of operations development. Sponsored by the NASA EVA & Human Surface Mobility Program (EHP), JETT includes representatives from EHP, NASA Engineering, the Science Mission Directorate (SMD), Human Health & Performance, and the Flight Operations Directorate (FOD). JETT tests evaluate NASA reference designs for EVA (e.g., suits and tools), address gaps and risks for Artemis lunar surface operations, develop capabilities for EVA and science tasks, enable technology maturation, and provide training for Artemis EVA operations. JETT3, the final JETT field test of FY22, occurred Oct 3-11, 2022 in the San Francisco Volcanic Field north of Flagstaff, AZ. The test focused on developing the Artemis concept of operations and systems, including integrating an Artemis-like Science Team into a NASA Flight Control Team (FCT) to plan and execute a series of simulated lunar EVAs in an environment analogous to Artemis 3.

T. E. Caswell↗
NASA NTRSDate not supplied

JETT3: A Holistic, Integrated Analog for Artemis Lunar Surface Exploration

Since 1972, NASA astronauts have performed hundreds of Extravehicular Activities (EVAs) in support of Skylab, Space Shuttle and International Space Station missions. Not since Apollo, however, have EVAs been driven by discovery-based principles of scientific exploration. Upcoming Artemis missions are challenged to build on lessons learned from Apollo, merging 50 years of EVA experience with the planetary science community’s expertise in the remote surface exploration of Mars. The highest-fidelity preparation for Artemis includes both operational and scientific underpinning to represent the complete, complex picture of lunar surface operations. The Joint EVA & Human Surface Mobility Test Team (JETT) is an interdisciplinary team providing such an environment for collaborative analog testing. JETT builds upon prior analog campaigns (e.g., [1, 2]) to provide high-fidelity environments for hardware and concept of operations development. Sponsored by the NASA EVA & Human Surface Mobility Program (EHP), JETT includes representatives from EHP, NASA Engineering, the Science Mission Directorate (SMD), Human Health & Performance, and the Flight Operations Directorate (FOD). JETT tests evaluate NASA reference designs for EVA (e.g., suits and tools), address gaps and risks for Artemis lunar surface operations, develop capabilities for EVA and science tasks, enable technology maturation, and provide training for Artemis EVA operations. JETT3, the final JETT field test of FY22, occurred Oct 3-11, 2022 in the San Francisco Volcanic Field north of Flagstaff, AZ. The test focused on developing the Artemis concept of operations and systems, including integrating an Artemis-like Science Team into a NASA Flight Control Team (FCT) to plan and execute a series of simulated lunar EVAs in an environment analogous to Artemis 3.

T. E. Caswell↗
NASA NTRS1994

Shared Problem Models and Crew Decision Making

The importance of crew decision making to aviation safety has been well established through NTSB accident analyses: Crew judgment and decision making have been cited as causes or contributing factors in over half of all accidents in commercial air transport, general aviation, and military aviation. Yet the bulk of research on decision making has not proven helpful in improving the quality of decisions in the cockpit. One reason is that traditional analytic decision models are inappropriate to the dynamic complex nature of cockpit decision making and do not accurately describe what expert human decision makers do when they make decisions. A new model of dynamic naturalistic decision making is offered that may prove more useful for training or aiding cockpit decision making. Based on analyses of crew performance in full-mission simulation and National Transportation Safety Board accident reports, features that define effective decision strategies in abnormal or emergency situations have been identified. These include accurate situation assessment (including time and risk assessment), appreciation of the complexity of the problem, sensitivity to constraints on the decision, timeliness of the response, and use of adequate information. More effective crews also manage their workload to provide themselves with time and resources to make good decisions. In brief, good decisions are appropriate to the demands of the situation and reflect the crew's metacognitive skill. Effective crew decision making and overall performance are mediated by crew communication. Communication contributes to performance because it assures that all crew members have essential information, but it also regulates and coordinates crew actions and is the medium of collective thinking in response to a problem. This presentation will examine the relation between communication that serves to build performance. Implications of these findings for crew training will be discussed.

Orasanu, Judith↗
NASA NTRS2002

Evaluation of the Effect of Water Vapor On the Performance of NASA's NMRO Catalysts for Carbon Monoxide Oxidation

The Noble Metal Reducible Oxide (NMRO) catalysts for the low temperature oxidation of carbon monoxide were developed by NASA for the reoxidation of carbon monoxide which forms by the dissociation of carbon dioxide during the operation of sealed carbon dioxide lasers. The NMRO catalyst, which consists of a noble metal in conjunction with a reducible metal oxide, was evaluated under conditions that will be encountered in a CO2 laser operation, namely temperatures in the range 298 to 373 K and no significant reaction gas components other than CO, CO2 and O2. The NMRO catalysts may have significant potential for spin-off applications such as the prevention of carbon monoxide build-up in closed spaces as in space vehicle cabins or submarines, and the elimination of the cold start-up problem of automobile exhaust catalysts. The most significant difference in the conditions of these possible future applications is the high moisture content of the gases to be processed. Lack of understanding of the effects of water vapor and high temperature on catalyst activity and operation for extended periods are currently the main stumbling blocks for the transfer of this NASA technology to be used for commercial purposes. In the original proposal the following objectives were stated: To obtain experimental data on the adsorption, desorption and reaction characteristics of CO and CO2 the catalysts under high moisture conditions; to collect evidence on the presence of carbonate and hydroxyl surface species and their involvement in the CO oxidation mechanism; and to model the reaction system using a Monte-Carlo simulation to gain insight on the various steps involved. After the work has commenced the NASA technical monitor Mr. David Scheyer informed us that there was increased interest in the possible use of the NMRO catalysts as automobile exhaust catalysts and therefore NASA wanted to know whether the catalysts can operate at high temperatures as well as with high moisture gases. At that meeting it was decided that investigation of the high temperature performance of the NMRO catalysts should be given priority and replace the Monte-Carlo simulation objective. As a result, the modified objectives of the investigation were taken as the investigation of the high-temperature activity of the NMRO catalysts, and the effect of water vapor on the performance of these catalysts.

Akyurtlu, Ates↗
NASA NTRS2005

Robotic and Human-Tended Collaborative Drilling Automation for Subsurface Exploration

Future in-situ lunar/martian resource utilization and characterization, as well as the scientific search for life on Mars, will require access to the subsurface and hence drilling. Drilling on Earth is hard - an art form more than an engineering discipline. Human operators listen and feel drill string vibrations coming from kilometers underground. Abundant mass and energy make it possible for terrestrial drilling to employ brute-force approaches to failure recovery and system performance issues. Space drilling will require intelligent and autonomous systems for robotic exploration and to support human exploration. Eventual in-situ resource utilization will require deep drilling with probable human-tended operation of large-bore drills, but initial lunar subsurface exploration and near-term ISRU will be accomplished with lightweight, rover-deployable or standalone drills capable of penetrating a few tens of meters in depth. These lightweight exploration drills have a direct counterpart in terrestrial prospecting and ore-body location, and will be designed to operate either human-tended or automated. NASA and industry now are acquiring experience in developing and building low-mass automated planetary prototype drills to design and build a pre-flight lunar prototype targeted for 2011-12 flight opportunities. A successful system will include development of drilling hardware, and automated control software to operate it safely and effectively. This includes control of the drilling hardware, state estimation of both the hardware and the lithography being drilled and state of the hole, and potentially planning and scheduling software suitable for uncertain situations such as drilling. Given that Humans on the Moon or Mars are unlikely to be able to spend protracted EVA periods at a drill site, both human-tended and robotic access to planetary subsurfaces will require some degree of standalone, autonomous drilling capability. Human-robotic coordination will be important, either between a robotic drill and humans on Earth, or a human-tended drill and its visiting crew. The Mars Analog Rio Tinto Experiment (MARTE) is a current project that studies and simulates the remote science operations between an automated drill in Spain and a distant, distributed human science team. The Drilling Automation for Mars Exploration (DAME) project, by contrast: is developing and testing standalone automation at a lunar/martian impact crater analog site in Arctic Canada. The drill hardware in both projects is a hardened, evolved version of the Advanced Deep Drill (ADD) developed by Honeybee Robotics for the Mars Subsurface Program. The current ADD is capable of 20m, and the DAME project is developing diagnostic and executive software for hands-off surface operations of the evolved version of this drill. The current drill automation architecture being developed by NASA and tested in 2004-06 at analog sites in the Arctic and Spain will add downhole diagnosis of different strata, bit wear detection, and dynamic replanning capabilities when unexpected failures or drilling conditions are discovered in conjunction with simulated mission operations and remote science planning. The most important determinant of future 1unar and martian drilling automation and staffing requirements will be the actual performance of automated prototype drilling hardware systems in field trials in simulated mission operations. It is difficult to accurately predict the level of automation and human interaction that will be needed for a lunar-deployed drill without first having extensive experience with the robotic control of prototype drill systems under realistic analog field conditions. Drill-specific failure modes and software design flaws will become most apparent at this stage. DAME will develop and test drill automation software and hardware under stressful operating conditions during several planned field campaigns. Initial results from summer 2004 tests show seven identifi distinct failure modes of the drill: cuttings-removal issues with low-power drilling into permafrost, and successful steps at executive control and initial automation.

Glass, Brian↗
NASA NTRSDate not supplied

Analysis and Application of Novel and Heritage Acceleration Limiting Algorithms for SLS on Ascent

National Aeronautics and Space Administration (NASA) is currently building the Space Launch System (SLS) Block-1 launch vehicle, to be used as the crewed heavy-lift vehicle for the Artemis series of missions. The SLS Block-1 guidance subsystem utilizes a nonlinear algorithm derived from Shuttle heritage for limiting the vehicle’s induced maximum axial acceleration during ascent flight, known as g-limiting. Even though g-limiting has demonstrated stability and robustness through several design analysis cycles and the extensive Shuttle flight history, there are no available documents that demonstrate that this algorithm has been proven stable through conventional controls stability analysis. This paper highlights the non-linear nature of g-limit, presents an alternative methodology to employ a linear version of this algorithm, performs assessment of selected linear gains using classical stability analysis and, conducts a comparison of both approaches through Six Degrees-of-Freedom (6-DOF) Monte Carlo (MC) simulations.

Jason Everett↗
NASA NTRS2024

Experimental Studies on the Effect of Impact Processes on the Formation and Evolution of Amino Acids

Introduction: A critical step in the emergence of life on Earth was the synthesis of larger organic molecules from simple building blocks such as NH3, CO2, H2O, and CH3OH. The presence of amino acids and other complex organics in comets and meteorites demonstrates that widespread organic synthesis likely occurred across the early solar system. Building on previous work [e.g., 1-3], we systematically explore impact-driven chemical evolution of exogenous organics and their precursors. Collisional processes may also have provided a source of energy for the formation of more complex organics from endogenous building blocks. The high flux of impactors to Earth immediately prior to and during the origins of life suggests that impacts could have played a critical role. Key Questions: 1. How are the formation and evolution of amino acids affected by the presence of a mineral matrix during cometary and asteroidal impacts onto the early Earth? 2. Do some minerals (e.g., phyllosilicates) provide a more robust protective framework or reactive surface site for amino-acid formation and/or polymerization? 3. Does the abundance of ices and/or amino acids relative to that of the mineral matrix affect the formation and evolution of amino acids? 4. Are there impact velocities/shock pressures at which formation or polymerization of amino acids is favored or precluded? Experimental Approach: This study systematically examines the conditions under which amino acids and other organic molecules can form, be polymerized, and/or be destroyed during impact events into particulate regolith simulants. Variable parameters include the modal composition of this regolith (silicate matrices, ratios of ices, silicates, and amino acids) and impact velocities/shock pressures. Impacts experiments were performed using the two-stage light-gas gun (LGG), vertical gun (VG), and flat-plate accelerator (FPA) in the Experimental Impact Lab at JSC. FPA experiments were performed over a range of shock pressures (11.3-31.5 GPa) using CM chondrite simulant mixed with amino acids at ratios of 0:10, 1:10, 1:103, and 1:106 (amino acid:host). Techniques for mixing cometary ices have been optimized and test runs have been performed using the LGG (see figure below). Analysis: Post-impact, samples are heated in water to extract amino acids and peptides. Extracts are characterized via liquid chromatography-mass spectrometry (LC-MS) and the mineralogies of solid residues are characterized using X-ray diffraction, scanning electron microscopy and transmission electron microscopy. Additional LC-MS and mineralogical analyses are underway.

Eve L Berger↗
NASA NTRS2008

Solar Concentrator Demonstrator for Lunar Regolith Processing

NASA at the Marshall Space Flight Center (MSFC) is building a portable inflatable solar concentrator ground demonstrator for use in testing in-situ resource utilization (ISRU) lunar regolith processing methods. Of primary interest is the production of oxygen as a propellant oxidizer and for life support. There are various processes being proposed for the in-situ reduction of the lunar regolith, the leading processes are hydrogen reduction, carbothermal reduction and vapor phase pyrolysis. The concentrator system being built at MSFC could support demonstrations of all of these processes. The system consists of a light inflatable concentrator that will capture sunlight and focus it onto a receiver inside a vacuum chamber. Inflatable concentrators are good for space based applications due to their low weight and dense packaging at launch. The hexapod design allows the spot size to be increased to reduce the power density if needed for the process being demonstrated. In addition to the hardware development, a comprehensive simulation model is being developed and will be verified and validated using the system hardware. The model will allow for the evaluation of different lunar locations and operational scenarios for the lunar regolith processing with a high confidence in the predicted results.

Fikes, John C.↗
NASA NTRS2019

The Non-Destructive Separation of Diverse Astrobiologically Relevant Organic Molecules By Customizable Capillary Zone Electrophoresis and Monolithic Capillary Electrochromatography

The in situ detection of organic molecules in space is key to understanding the variety and the distribution of the building blocks of life, and possibly the detection of extraterrestrial life itself. Gas chromatography mass spectrometry (GC-MS) has been the most sensitive analytical instrument for organic analyses in flight, and was used on missions from NASA’s Viking, Phoenix, Curiosity missions to ESA’s Rosetta space probe. While pyrolysis GC-MS revealed the first organics on Mars, this step alters or degrades certain fragile molecules that are excellent biosignatures including polypeptides, oligonucleotides and polysaccharides, rendering the intact precursors undetectable. We have identified a solution tailored to the detection of biopolymers and other biomarkers by the use of liquid-based capillary electrophoresis and electrochromatography. In this study, we show that a capillary electrochromatography (CEC) approach using monolithic stationary phases with tailor-made surface chemistry can separate and identify various polycyclic aromatic hydrocarbons (PAHs), nucleobases and aromatic acids that could be formed under astrophysically relevant conditions. In order to simulate flyby organic sample capture, we conducted hypervelocity impact experiments which consisted of accelerating peptide-soaked montmorillonite particles to a speed of 5.6 km/sec, and capturing them in an amorphous silica aerogel of 10 and 30 mg/cc bulk density. Bulk peptide extraction from aerogel followed by capillary zone electrophoresis led to the detection of only two stereoisomeric peptide peaks. The recovery rates of each step of the extraction procedure after the hypervelocity impact suggest that major peptide loss occurred during the impact. Our study provides initial exploration of feasibility of this approach for capturing intact peptides, and subsequently detecting candidate biomolecules during flight missions that would be missed by GC-MS alone. As the monolith-based electrochromatography technology could be customized to detect specific classes of compounds as well as miniaturized, these results demonstrate the potential of the instrumentation for future astrobiology-related spaceflight missions.

Flyby sample return↗
NASA NTRS2017

Flight Tests of a Remaining Flying Time Prediction System for Small Electric Aircraft in the Presence of Faults

This paper addresses the problem of building trust in the online prediction of a battery powered aircraft's remaining flying time. A series of flight tests is described that make use of a small electric powered unmanned aerial vehicle (eUAV) to verify the performance of the remaining flying time prediction algorithm. The estimate of remaining flying time is used to activate an alarm when the predicted remaining time is two minutes. This notifies the pilot to transition to the landing phase of the flight. A second alarm is activated when the battery charge falls below a specified limit threshold. This threshold is the point at which the battery energy reserve would no longer safely support two repeated aborted landing attempts. During the test series, the motor system is operated with the same predefined timed airspeed profile for each test. To test the robustness of the prediction, half of the tests were performed with, and half were performed without, a simulated powertrain fault. The pilot remotely engages a resistor bank at a specified time during the test flight to simulate a partial powertrain fault. The flying time prediction system is agnostic of the pilot's activation of the fault and must adapt to the vehicle's state. The time at which the limit threshold on battery charge is reached is then used to measure the accuracy of the remaining flying time predictions. Accuracy requirements for the alarms are considered and the results discussed.

Hogge, Edward F.↗
NASA NTRS1994

A model predicting the evolution of ice particle size spectra and radiative properties of cirrus clouds. Part 2: Dependence of absorption and extinction on ice crystal morphology

This study builds upon the microphysical modeling described in Part 1 by deriving formulations for the extinction and absorption coefficients in terms of the size distribution parameters predicted from the micro-physical model. The optical depth and single scatter albedo of a cirrus cloud can then be determined, which, along with the asymmetry parameter, are the input parameters needed by cloud radiation models. Through the use of anomalous diffraction theory, analytical expressions were developed describing the absorption and extinction coefficients and the single scatter albedo as functions of size distribution parameters, ice crystal shapes (or habits), wavelength, and refractive index. The extinction coefficient was formulated in terms of the projected area of the size distribution, while the absorption coefficient was formulated in terms of both the projected area and mass of the size distribution. These properties were formulated as explicit functions of ice crystal geometry and were not based on an 'effective radius.' Based on simulations of the second cirrus case study described in Part 1, absorption coefficients predicted in the near infrared for hexagonal columns and rosettes were up to 47% and 71% lower, respectively, than absorption coefficients predicted by using equivalent area spheres. This resulted in single scatter albedos in the near-infrared that were considerably greater than those predicted by the equivalent area sphere method. Reflectances in this region should therefore be underestimated using the equivalent area sphere approach. Cloud optical depth was found to depend on ice crystal habit. When the simulated cirrus cloud contained only bullet rosettes, the optical depth was 142% greater than when the cloud contained only hexagonal columns. This increase produced a doubling in cloud albedo. In the near-infrared (IR), the single scatter albedo also exhibited a significant dependence on ice crystal habit. More research is needed on the geometrical properties of ice crystals before the influence of ice crystal shape on cirrus radiative properties can be adequately understood. This study provides a way of coupling the radiative properties of absorption, extinction, and single scatter albedo to the microphysical properties of cirrus clouds. The dependence of extinction and absorption on ice crystal shape was not just due to geometrical differences between crystal types, but was also due to the effect these differences had on the evolution of ice particle size spectra. The ice particle growth model in Part 1 and the radiative properties treated here are based on analytical formulations, and thus represent a computationally efficient means of modeling the microphysical and radiative properties of cirrus clouds.

Mitchell, David L.↗
NASA NTRSDate not supplied

Uncertainty Quantification using Deep Ensembles for Decision Making in Cyber-Physical-Human Systems

In this paper and its companion, Differential Equation Approximation Using Gradient-Boosted Quantile Regression, Robison et al., we examine an approach to quantifying model uncertainty with the aim of increasing the trustworthiness of computational models in human-machine interactions. In Differential Equation Approximation Using Gradient-Boosted Quantile Regression, we focus on gradient-boosted decision trees, while in this one, we give more details about deep ensembles. Uncertainty quantification is crucial for building trustworthy autonomous decision-making agents in human-machine teams. There are two types of uncertainties: aleatoric and epistemic. The former is related to the inherent stochasticity (noise) of the process, whereas the latter is associated with the lack of knowledge or representation capability of models, such as neural networks. By lack of knowledge, we mean the model’s inability to accurately predict outputs for all possible inputs. The aleatory uncertainty can be estimated fairly easily with, for example, filters, whereas epistemic uncertainty is challenging to compute. This paper uses deep ensembles to quantify both aleatory and epistemic uncertainty. It can act as an uncertainty-aware surrogate transition model for decision-making frameworks. "Uncertainty-aware" means that the surrogate transition model should make predictions along with confidence in those predictions. In the context of decision-making, the transition models are ordinary differential equations (ODEs). Since ODEs can be simulated to make one-step or multi-step predictions, a good surrogate model for them should perform reasonably well in both modes. In a multi-step approach, the trajectory sampling method TS∞ was used to propagate uncertainty over multiple steps. The cartpole dynamical system was selected to demonstrate the ability of deep ensembles as good surrogate transition models for decision-making frameworks. The deep ensembles modeled the dynamics of cartpole ODEs and made uncertainty-aware predictions in single-step and multi-step transition modes.

CPH systems↗
NASA NTRS2008

The Integrated Medical Model: Statistical Forecasting of Risks to Crew Health and Mission Success

The Integrated Medical Model (IMM) helps capture and use organizational knowledge across the space medicine, training, operations, engineering, and research domains. The IMM uses this domain knowledge in the context of a mission and crew profile to forecast crew health and mission success risks. The IMM is most helpful in comparing the risk of two or more mission profiles, not as a tool for predicting absolute risk. The process of building the IMM adheres to Probability Risk Assessment (PRA) techniques described in NASA Procedural Requirement (NPR) 8705.5, and uses current evidence-based information to establish a defensible position for making decisions that help ensure crew health and mission success. The IMM quantitatively describes the following input parameters: 1) medical conditions and likelihood, 2) mission duration, 3) vehicle environment, 4) crew attributes (e.g. age, sex), 5) crew activities (e.g. EVA's, Lunar excursions), 6) diagnosis and treatment protocols (e.g. medical equipment, consumables pharmaceuticals), and 7) Crew Medical Officer (CMO) training effectiveness. It is worth reiterating that the IMM uses the data sets above as inputs. Many other risk management efforts stop at determining only likelihood. The IMM is unique in that it models not only likelihood, but risk mitigations, as well as subsequent clinical outcomes based on those mitigations. Once the mathematical relationships among the above parameters are established, the IMM uses a Monte Carlo simulation technique (a random sampling of the inputs as described by their statistical distribution) to determine the probable outcomes. Because the IMM is a stochastic model (i.e. the input parameters are represented by various statistical distributions depending on the data type), when the mission is simulated 10-50,000 times with a given set of medical capabilities (risk mitigations), a prediction of the most probable outcomes can be generated. For each mission, the IMM tracks which conditions occurred and decrements the pharmaceuticals and supplies required to diagnose and treat these medical conditions. If supplies are depleted, then the medical condition goes untreated, and crew and mission risk increase. The IMM currently models approximately 30 medical conditions. By the end of FY2008, the IMM will be modeling over 100 medical conditions, approximately 60 of which have been recorded to have occurred during short and long space missions.

Fitts, M. A.↗
NASA NTRSDate not supplied

The Lunar GNSS Receiver Experiment (LuGRE)

The Lunar GNSS Receiver Experiment (LuGRE) is a joint NASA-Italian Space Agency (ASI) payload on the Firefly Blue Ghost Mission 1 (BGM1) with the goal to demonstrate GNSS-based positioning, navigation, and timing at the Moon. LuGRE was chosen by the NASA Commercial Lunar Payload Services (CLPS) program as one of ten payloads on its “19D” task order for delivery to the lunar surface in 2023. The LuGRE payload consists of a weak-signal GNSS receiver, a high-gain L-band patch antenna, a low-noise amplifier, and an RF filter. The receiver will track GPS L1 C/A and L5, and Galileo E1 and E5a signals and will return pseudorange, carrier phase, and Doppler measurements to the ground. It will also calculate least-squares point solutions and Kalman-filter based navigation solutions onboard. In addition, the receiver features the capability to record raw I/Q baseband samples for downlink and ground processing. LuGRE will build on the legacy of prior missions in the Space Service Volume (SSV) including the initial experiments by AMSAT-OSCAR 40 and others, the GOES-R series of geostationary weather satellites, and the NASA Magnetospheric Multiscale (MMS) mission currently operating on GPS-based navigation at nearly 50% of lunar distance. Further, LuGRE will be one of the very first demonstrations of GNSS signal reception and navigation in the lunar environment and on the lunar surface, paving the way for operational use by future lunar missions such as Orion, Gateway, robotic and human landers, and surface rovers. Ultimately, all LuGRE science data will be released to a public data archive for the benefit of the GNSS and space communities. This paper provides a detailed overview of the LuGRE payload, including its design, concept of operations, and its predicted ability to meet its core science objectives. The baseline science investigations and priorities are outlined. Simulated performance results are shown based on the latest calibrated models including signal strength, signal availability, onboard navigation performance and convergence properties, and ground-based post-processed navigation performance.

LuGRE↗
NASA NTRSDate not supplied

Selection, Production, and Properties of Regolith Polymer Composites for Lunar Construction

NASA’s Artemis Program seeks to establish a long-term presence on the Moon to enable scientific exploration and expand the cis-lunar economy by utilizing lunar resources through public-private and international partnerships. Over the next decades, a lunar spaceport will need to be established to provide the services and facilities that are necessary to achieve this goal. Robotic construction technologies using in-situ materials must be developed to build up enabling infrastructure such as launch/landing pads, blast protection, power/communications infrastructure, improved roads, improved operational surfaces, and radiation protection shelters. Kennedy Space Center’s Granular Mechanics and Regolith Operations laboratory at Swamp Works has partnered with SpaceFactory and LERA Consulting Structural Engineers to develop the architectural and structural design of an unpressurized lunar shelter. The shelter, called Lunar Infrastructure Asset (LINA), is designed to support 2.3 m of regolith overburden to protect astronauts and surface assets from radiation, meteoroid impact, thermal gradients/cycling, and to withstand moonquakes. LINA’s structural design criteria and the resulting structure design are detailed in separate papers. A Fused Filament Fabrication (FFF) construction process using regolith polymer composites has been developed and is detailed in a separate publication. This paper presents material formulations and selection rationale for each of the composite components that were examined. Formulations include 70:30, 80:20, and 85:15 wt.% mixture ratios of lunar mare simulant Black Point-1 (BP-1): Polylactic Acid (PLA), 80:20 Lunar Highlands Simulant-1 (LHS-1): PLA and an 80:20 BP-1: PLA formulation with a flow enhancer additive. Test samples were printed in simulated lunar dirty thermal vacuum conditions (-190 °C, 10-3 torr). A series of tests were performed on each formulation to characterize the achieved mixture ratio, mechanical strength properties, off-gassing products during vacuum printing, and porosity and density of printed products. The LHS-1: PLA formulation yielded an advantageous combination of properties and was used in a final test that additively constructed a sub-scaled LINA on regolith simulant in dirty vacuum conditions. The materials and construction process presented in this paper are considered to be at Technology Readiness Level (TRL) 5 with additional testing necessary to characterize long term lunar environmental exposure effects.

lunar infrastructure↗
NASA NTRS1994

Infinite possibilities: Computational structures technology

Computational Fluid Dynamics (or CFD) methods are very familiar to the research community. Even the general public has had some exposure to CFD images, primarily through the news media. However, very little attention has been paid to CST--Computational Structures Technology. Yet, no important design can be completed without it. During the first half of this century, researchers only dreamed of designing and building structures on a computer. Today their dreams have become practical realities as computational methods are used in all phases of design, fabrication and testing of engineering systems. Increasingly complex structures can now be built in even shorter periods of time. Over the past four decades, computer technology has been developing, and early finite element methods have grown from small in-house programs to numerous commercial software programs. When coupled with advanced computing systems, they help engineers make dramatic leaps in designing and testing concepts. The goals of CST include: predicting how a structure will behave under actual operating conditions; designing and complementing other experiments conducted on a structure; investigating microstructural damage or chaotic, unpredictable behavior; helping material developers in improving material systems; and being a useful tool in design systems optimization and sensitivity techniques. Applying CST to a structure problem requires five steps: (1) observe the specific problem; (2) develop a computational model for numerical simulation; (3) develop and assemble software and hardware for running the codes; (4) post-process and interpret the results; and (5) use the model to analyze and design the actual structure. Researchers in both industry and academia continue to make significant contributions to advance this technology with improvements in software, collaborative computing environments and supercomputing systems. As these environments and systems evolve, computational structures technology will evolve. By using CST in the design and operation of future structures systems, engineers will have a better understanding of how a system responds and lasts, more cost-effective methods of designing and testing models, and improved productivity. For informational and educational purposes, a videotape is being produced using both static and dynamic images from research institutions, software and hardware companies, private individuals, and historical photographs and drawings. The extensive number of CST resources indicates its widespread use. Applications run the gamut from simpler university-simulated problems to those requiring solutions on supercomputers. In some cases, an image or an animation will be mapped onto the actual structure to show the relevance of the computer model to the structure. Transferring the digital files to videotape presents a number of problems related to maintaining the quality of the original image, while still producing a broadcast quality videotape. Since researchers normally do not create a computer image using traditional composition theories or video production requirements, often the image loses some of its original digital quality and impact when transferred to videotape. Although many CST images are currently available, those that are edited into the final project must meet two important criteria: they must complement the narration, and they must be broadcast quality when recorded on videotape.

Beam, Sherilee F.↗
NASA NTRS2000

Information Power Grid: Distributed High-Performance Computing and Large-Scale Data Management for Science and Engineering

We use the term "Grid" to refer to distributed, high performance computing and data handling infrastructure that incorporates geographically and organizationally dispersed, heterogeneous resources that are persistent and supported. This infrastructure includes: (1) Tools for constructing collaborative, application oriented Problem Solving Environments / Frameworks (the primary user interfaces for Grids); (2) Programming environments, tools, and services providing various approaches for building applications that use aggregated computing and storage resources, and federated data sources; (3) Comprehensive and consistent set of location independent tools and services for accessing and managing dynamic collections of widely distributed resources: heterogeneous computing systems, storage systems, real-time data sources and instruments, human collaborators, and communications systems; (4) Operational infrastructure including management tools for distributed systems and distributed resources, user services, accounting and auditing, strong and location independent user authentication and authorization, and overall system security services The vision for NASA's Information Power Grid - a computing and data Grid - is that it will provide significant new capabilities to scientists and engineers by facilitating routine construction of information based problem solving environments / frameworks. Such Grids will knit together widely distributed computing, data, instrument, and human resources into just-in-time systems that can address complex and large-scale computing and data analysis problems. Examples of these problems include: (1) Coupled, multidisciplinary simulations too large for single systems (e.g., multi-component NPSS turbomachine simulation); (2) Use of widely distributed, federated data archives (e.g., simultaneous access to metrological, topological, aircraft performance, and flight path scheduling databases supporting a National Air Space Simulation systems}; (3) Coupling large-scale computing and data systems to scientific and engineering instruments (e.g., realtime interaction with experiments through real-time data analysis and interpretation presented to the experimentalist in ways that allow direct interaction with the experiment (instead of just with instrument control); (5) Highly interactive, augmented reality and virtual reality remote collaborations (e.g., Ames / Boeing Remote Help Desk providing field maintenance use of coupled video and NDI to a remote, on-line airframe structures expert who uses this data to index into detailed design databases, and returns 3D internal aircraft geometry to the field); (5) Single computational problems too large for any single system (e.g. the rotocraft reference calculation). Grids also have the potential to provide pools of resources that could be called on in extraordinary / rapid response situations (such as disaster response) because they can provide common interfaces and access mechanisms, standardized management, and uniform user authentication and authorization, for large collections of distributed resources (whether or not they normally function in concert). IPG development and deployment is addressing requirements obtained by analyzing a number of different application areas, in particular from the NASA Aero-Space Technology Enterprise. This analysis has focussed primarily on two types of users: the scientist / design engineer whose primary interest is problem solving (e.g. determining wing aerodynamic characteristics in many different operating environments), and whose primary interface to IPG will be through various sorts of problem solving frameworks. The second type of user is the tool designer: the computational scientists who convert physics and mathematics into code that can simulate the physical world. These are the two primary users of IPG, and they have rather different requirements. The results of the analysis of the needs of these two types of users provides a broad set of requirements that gives rise to a general set of required capabilities. The IPG project is intended to address all of these requirements. In some cases the required computing technology exists, and in some cases it must be researched and developed. The project is using available technology to provide a prototype set of capabilities in a persistent distributed computing testbed. Beyond this, there are required capabilities that are not immediately available, and whose development spans the range from near-term engineering development (one to two years) to much longer term R&D (three to six years). Additional information is contained in the original.

Johnston, William E.↗
NASA NTRS1989

Building an environment model using depth information

Modeling the environment is one of the most crucial issues for the development and research of autonomous robot and tele-perception. Though the physical robot operates (navigates and performs various tasks) in the real world, any type of reasoning, such as situation assessment, planning or reasoning about action, is performed based on information in its internal world. Hence, the robot's intentional actions are inherently constrained by the models it has. These models may serve as interfaces between sensing modules and reasoning modules, or in the case of telerobots serve as interface between the human operator and the distant robot. A robot operating in a known restricted environment may have a priori knowledge of its whole possible work domain, which will be assimilated in its World Model. As the information in the World Model is relatively fixed, an Environment Model must be introduced to cope with the changes in the environment and to allow exploring entirely new domains. Introduced here is an algorithm that uses dense range data collected at various positions in the environment to refine and update or generate a 3-D volumetric model of an environment. The model, which is intended for autonomous robot navigation and tele-perception, consists of cubic voxels with the possible attributes: Void, Full, and Unknown. Experimental results from simulations of range data in synthetic environments are given. The quality of the results show great promise for dealing with noisy input data. The performance measures for the algorithm are defined, and quantitative results for noisy data and positional uncertainty are presented.

Roth-Tabak, Y.↗