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At least 163 records · Page 9
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NASA NTRS2026

Simulating the Lunar Thermal Environment for the Surface-Deployed LEMS Artemis III TVAC Test

The Lunar Environment Monitoring Station (LEMS) is an autonomous, survive-the lunar-night seismic suite to be deployed on the Lunar surface by the Artemis III crew and designed to operate continuously for two years. It will see the extremes of the Lunar south pole thermal environment where surface temperatures range from -200°C to +20°C and where nighttime duration is at least 354 hours. Given power and mass constraints, the thermal system is limited to 2.5 Watts of heat during the lunar night. Presented is the system thermal vacuum test plan and configuration to validate the thermal control system performance in a flight-like environment. The test will measure the nighttime heat leaks for the bus and 18 seismometers to ensure lunar night survival and operability.

TVAC↗
NASA NTRS2023

Using Virtual Reality to Envision Deployment of Spacesuit-Compatible Augmented Reality Displays for Lunar Surface Operations

The National Aeronautics and Space Administration (NASA) aims to land crew on the lunar surface to establish a sustainable presence and develop operational concepts for future long-duration missions. New technologies will be necessary to extend planning and execution capabilities for lunar surface activities. NASA’s Joint Augmented Reality Visual Informatics System (Joint AR) is one such technology. Joint AR is a suit-mounted augmented reality (AR) display and computes system which facilitates unprecedented information exchange and data visualization capabilities between mission support operators and suited crew. This paper describes challenges associated with developing AR technology for an envisioned work domain by applying a sociotechnical lens to the iterative testing and development of novel AR technology through virtual reality (VR). A VR testbed was established to simulate a representative lunar surface environment, enabling a series of three human-in-the-loop (HITL) tests evaluating AR navigation interfaces for exploration extravehicular activity (xEVA). Our findings identify several considerations for future Joint AR design and testing efforts, including challenges with data overload, attentional demands, and environment-related perceptual challenges. Trade-offs and potential approaches are discussed to mitigate these challenges and improve future Joint AR testing fidelity.

Jacob Keller↗
NASA NTRSDate not supplied

Using Virtual Reality to Envision Deployment of Spacesuit-Compatible Augmented Reality Displays for Lunar Surface Operations

The National Aeronautics and Space Administration (NASA) aims to land crew on the lunar surface to establish a sustainable presence and develop operational concepts for future long-duration missions. New technologies will be necessary to extend planning and execution capabilities for lunar surface activities. NASA’s Joint Augmented Reality Visual Informatics System (Joint AR) is one such technology. Joint AR is a suit-mounted augmented reality (AR) display and computes system which facilitates unprecedented information exchange and data visualization capabilities between mission support operators and suited crew. This paper describes challenges associated with developing AR technology for an envisioned work domain by applying a sociotechnical lens to the iterative testing and development of novel AR technology through virtual reality (VR). A VR testbed was established to simulate a representative lunar surface environment, enabling a series of three human-in-the-loop (HITL) tests evaluating AR navigation interfaces for exploration extravehicular activity (xEVA). Our findings identify several considerations for future Joint AR design and testing efforts, including challenges with data overload, attentional demands, and environment-related perceptual challenges. Trade-offs and potential approaches are discussed to mitigate these challenges and improve future Joint AR testing fidelity.

Matthew Miller↗
NASA NTRS1973

Extravehicular mobility unit thermal simulator

The analytical methods, thermal model, and user's instructions for the SIM bay extravehicular mobility unit (EMU) routine are presented. This digital computer program was developed for detailed thermal performance predictions of the crewman performing a command module extravehicular activity during transearth coast. It accounts for conductive, convective, and radiative heat transfer as well as fluid flow and associated flow control components. The program is a derivative of the Apollo lunar surface EMU digital simulator. It has the operational flexibility to accept card or magnetic tape for both the input data and program logic. Output can be tabular and/or plotted and the mission simulation can be stopped and restarted at the discretion of the user. The program was developed for the NASA-JSC Univac 1108 computer system and several of the capabilities represent utilization of unique features of that system. Analytical methods used in the computer routine are based on finite difference approximations to differential heat and mass balance equations which account for temperature or time dependent thermo-physical properties.

Hixon, C. W.↗
NASA NTRS2025

Lunar Terrain Vehicle (LTV) Remote Teleoperation Studies Under Four Lunar Communication Latencies

Remotely operating a lunar rover from Earth while subject to an Earth-Moon time delay of multiple seconds could result in a dangerous state where the roving vehicle is either damaged or lost, thereby potentially compromising an entire mission or series of missions. Providing the right capabilities to the remote operator to manage inherent communication latencies will be important for remote driving to be successful. The National Aeronautics and Space Administration (NASA) conducted two studies to investigate the average speed and number of kilometers per day that an operator on Earth could teleoperate a notional Artemis unpressurized rover with minimal remote operator capabilities under 0- and 4-second communication delays (April 2023 study) and 6- and 8-second delays (August 2023 study). A primary goal of these studies was to understand if an Artemis Lunar Terrain Vehicle (LTV) could cover 6 kilometers (km) in 24 hours when operated remotely. During the April 2023 evaluation, eight test operators used an in-house simulation of the lunar surface South Pole to teleoperate a NASA government reference LTV. Each operator received approximately 30 minutes of remote driving familiarization/training prior to their test run. Operators viewed the surrounding terrain via a single, rover mast-mounted, high-resolution camera with pan/tilt/zoom capabilities; continuous communication was provided throughout all testing. In the August 2023 evaluation, remote operators received approximately 3 hours of familiarization training in each latency, and the simulation environment provided remote operators with an operator-selected rate limiter to enable finer sensitivity in the hand controller and a predictive circle function to better assist operators with predicting the path the vehicle could take. All test operators were able to successfully navigate and drive through six different types of terrain and five planned traverse scenarios using natural lighting under all communication delays. Results for average speeds for each communication delay, computed by averaging the data from all test conditions for that latency and all operators, are shown in the table below. The average speed data was then used to derive the total time needed to cover 6 km, 8 km, and 20 km. Remote operators drove slower and used the brake more frequently when subject to a communication latency as opposed to no communication latency. Subjective workload assessments revealed that while operating in a latency the overall workload significantly increased when compared to a 0-s delay with mental demand, frustration, and performance being the primary contributing factors. Driving strategies in the 0-s delay did not vary significantly among subjects; however, in the 4-s delay condition, three different driving strategies were identified. In the 6-s and 8-s latency conditions the operator’s use of the cruise control to maintain speed was more apparent. Additionally, over the course of the August study, the operator took advantage of the predictive circle indicator on the navigation display and over 95% of the operator’s navigation used the mast camera 180-degree panning function for ground truthing in terms of boulders and craters. Operators started to define more specific parameters in driving strategies for general operations. This consisted of setting the vehicle into a low-speed cruise mode of approximately 1–1.5 kph and noticing driving performance of the vehicle seemed to be much harder at slower speeds 0.4–0.8 kph; however, the vehicle was more responsive at speeds of 2.9–3.6 kph. Regardless of communication delay, operators used both the horizontal translation rails and the vehicle fenders as guides to predict a path for the vehicle through heavily concentrated terrain features. Test operators acknowledged that the teleoperations training for this study was substantially less than what an actual LTV remote operator will ultimately receive. They estimated a minimum of 20 to 100 hours spread across multiple days and weeks (e.g., strategies included immersion training over a 3-day period, to a short 8-week starter program) would be needed to get an operator ~ 60% proficient (i.e., able to complete a subset of remote driving tasks), to a yearlong program for full proficiency in remote driving tasks under all terrain types and natural lighting conditions. Remotely operating a vehicle on another planetary body while subject to communication latency is a complex task. Speed, distance covered, time spent driving, time spent navigating, brake usage and rock contacts are all affected by operator workload, driving strategies, workstation ergonomics and training. These studies provided a “firstlook” answer to a potential system requirement (namely if a remote operator could cover a given distance in a given amount of time); however, considerable general knowledge was gained to begin to understand what it will take to make a successful lunar rover teleoperator.

LTV↗
NASA NTRS2024

Lunar Terrain Vehicle (LTV) Remote Teleoperation Studies Under Four Lunar Communication Latencies

Remotely operating a lunar rover from Earth while subject to an Earth-Moon time delay of multiple seconds could result in a dangerous state where the roving vehicle is either damaged or lost, thereby potentially compromising an entire mission or series of missions. Providing the right capabilities to the remote operator to manage inherent communication latencies will be important for remote driving to be successful. NASA conducted two studies to investigate the average speed and number of kilometers per day that an operator on Earth could teleoperate a notional Artemis unpressurized rover with minimal remote operator capabilities under 0- and 4-second communication delays (April 2023 study) and 6- and 8-second delays (August 2023 study). A primary goal of these studies was to understand if an Artemis Lunar Terrain Vehicle (LTV) could cover 6 kilometers (km) in 24 hours when operated remotely. During the April 2023 evaluation, eight test operators used an in-house simulation of the lunar surface South Pole to teleoperate a NASA government reference LTV. Each operator received approximately 30 minutes of remote driving familiarization/training prior to their test run. Operators viewed the surrounding terrain via a single, rover mast-mounted, high-resolution camera with pan/tilt/zoom capabilities; continuous communication was provided throughout all testing. In the August 2023 evaluation, remote operators received approximately 3 hours of familiarization training in each latency, and the simulation environment provided remote operators with an operator-selected rate limiter to enable finer sensitivity in the hand controller and a predictive circle function to better assist operators with predicting the path the vehicle could take. All test operators were able to successfully navigate and drive through six different types of terrain and five planned traverse scenarios using natural lighting under all communication delays. Results for average speeds for each communication delay, computed by averaging the data from all test conditions for that latency and all operators, are shown in the table below. The average speed data was then used to derive the total time needed to cover 6 km, 8 km, and 20 km (distances relevant to LTV-SYS071 and -029 requirements). Remote operators drove slower and used the brake more frequently when subject to a communication latency as opposed to no communication latency. Subjective workload assessments revealed that while operating in a latency the overall workload significantly increased when compared to a 0-s delay with mental demand, frustration, and performance being the primary contributing factors. Driving strategies in the 0-s delay did not vary significantly among subjects; however, in the 4-s delay condition, three different driving strategies were identified. In the 6-s and 8-s latency conditions the operator’s use of the cruise control to maintain speed was more apparent. Additionally, over the course of the August study, the operator took advantage of the predictive circle indicator on the navigation display and over 95% of the operator’s navigation used the mast camera 180-degree panning function for ground truthing in terms of boulders and craters. Operators started to define more specific parameters in driving strategies for general operations. This consisted of setting the vehicle into a low-speed cruise mode of approximately 11.5 kph and noticing driving performance of the vehicle seemed to be much harder at slower speeds 0.4–0.8 kph; however, the vehicle was more responsive at speeds of 2.9–3.6 kph. Regardless of communication delay, operators used both the horizontal translation rails and the vehicle fenders as guides to predict a path for the vehicle through heavily concentrated terrain features. Test operators acknowledged that the teleoperations training for this study was substantially less than what an actual LTV remote operator will ultimately receive. They estimated a minimum of 20 to 100 hours spread across multiple days and weeks (e.g., strategies included immersion training over a 3-day period, to a short 8-week starter program) would be needed to get an operator ~ 60% proficient (i.e., able to complete a subset of remote driving tasks), to a yearlong program for full proficiency in remote driving tasks under all terrain types and natural lighting conditions. Remotely operating a vehicle on another planetary body while subject to communication latency is a complex task. Speed, distance covered, time spent driving, time spent navigating, brake usage and rock contacts are all affected by operator workload, driving strategies, workstation ergonomics and training. These studies provided a “first-look” answer to a potential system requirement (namely if a remote operator could cover a given distance in a given amount of time); however, considerable general knowledge was gained to begin to understand what it will take to make a successful lunar rover teleoperator.

LTV↗
NASA NTRS2018

Solar Wind Implantation into Lunar Regolith II: Monte Carlo Simulations of Hydrogen Retention in a Surface with Defects and the Hydrogen (H, H2) Exosphere

Recently, the near-infrared observations of the OH veneer on the lunar surface by the Moon Mineralogy Mapper (M3) have been refined to constrain the OH content to 500-750 parts per million (ppm). The observations indicate diurnal variations in OH up to 200 ppm possibly linked to warmer surface temperatures at low latitude. We examine the M3 observations using a statistical mechanics approach to model the diffusion of implanted H in the lunar regolith. We present results from Monte Carlo simulations of the diffusion of implanted solar wind H atoms and the subsequently derived H and H2 exospheres.

Exosphere↗
NASA NTRS2024

Digital Lunar Exploration Sites (DLES) Terrain Crafting

Humans will soon be returning to the surface of the Moon with NASA’s Artemis program. The Artemis program is an international collaboration that will consist of a complex series of space systems and missions to explore the lunar surface and pave the way for the future exploration of Mars. NASA and its partners rely heavily on simulation for lighting and navigation studies as well as training astronauts, flight controllers, and mission support staff. The NASA Exploration Systems Simulations (NExSyS) team in the Simulation and Graphics Branch (ER7) in the Engineering Directorate at NASA’s Johnson Space Center has built up many simulation products to support this effort, one of which is the Digital Lunar Exploration Sites (DLES). DLES is a collection of products used to simulate and render the lunar surface in a digital environment. We discussed and presented an overview of the DLES products at the 2022 IEEE Aerospace Conference in Big Sky, MT with a paper titled "Digital Lunar Exploration Sites". This “DLES Terrain Crafting” paper will expand on the information previously provided in “DLES” paper and dive deeper into the details of the terrain crafting process and the toolsets used to support this task. The best digital data currently available of the lunar surface is provided by the Lunar Reconnaissance Orbiter (LRO). Its Lunar Orbiter Laser Altimeter (LOLA) achieves an impressive resolution of 5m per pixel at the Lunar South Pole (LSP) and can generate datasets covering a large continuous region near the LSP. There are a few additional methods, such as Shape from Shading which can infer higher resolution data (up to 1m per pixel) from the LRO Narrow Angle Camera (NAC) images. However, surface-based simulations require higher-resolution data, and this paper will discuss the process of enhancing the terrain to meet that need. The process begins with capturing statistical data of craters in the regions of interest using images provided by the LRO NAC. This data is then used to scatter artificial features which are not captured in the truth data, resulting in an enhanced DEM with a much higher resolution of 20cm per pixel. Many tools were built up to assist in the creation of these artificial Digital Elevation Models (DEM), which this paper will discuss in detail. DEMs themselves are a very powerful representation of a planetary surface, and many operations and tools can utilize the data they contain. This paper includes a description of the rendering of the lunar surface in a graphics engine, generation of contact patches to simulate tire to ground interaction, and ray tracing utilities to model Line of Sight (LOS) interactions with the terrain. This paper will also explore some new tool sets currently under development which aim to utilize Machine Learning (ML) to assist in the identification of craters from LRO NAC imagery. While this is not a novel idea, the NExSyS team is developing a unique approach which may result in more robust identification of crater characteristics.

Artemis↗
NASA NTRSDate not supplied

Using Virtual Reality for Science Missions At The Lunar South Pole

The Lunar VR toolkit, built on Mixed Reality Exploration Toolkit (MRET), combines LOLA 5m topographic data, CAD models (e.g., lander, rover), procedural textures, and geologic features (e.g., rocks, craters) for sub-5m simulation of the lunar surface. Future capabilities include the incorporation of real-time mission telemetry to provide a full mission lifecycle tool, test instrument design and operation concepts, pre-operations planning and walk-throughs of traverses, and situational awareness support during actual mission operations. We will discuss the critical features we think are needed for lunar south pole mission planning and the development of our Lunar VR toolkit.

Thomas G Grubb↗
NASA NTRSDate not supplied

Development of the Advanced Regolith Ground Operations (ARGO) Test Bed– A Robotic Construction Test Facility with Simulated Lunar Environments

NASA’s Artemis Program is working towards developing a sustained presence on the Moon and eventually Mars. To achieve this goal, robotic excavation, site preparation and construction technologies are under development to establish the capability to construct infrastructure such as launch/landing pads and radiation protection shelters. Technologies must be proven in simulated Lunar conditions prior surface demonstration missions. To that end, the Relevant Additive Construction Technology (REACT) Announcement of Collaboration Opportunities (ACO) project with AI Space Factory and the NASA Kennedy Space Center’s (KSC) Granular Mechanics and Regolith Operations Laboratory (a.k.a. Swamp Works) has developed the Advanced Regolith Ground Operations (ARGO) Test Bed. ARGO includes a ~1.5m x 1.5m x 1.2m (~5x5x4ft) vacuum chamber, cryogenically cooled thermal shroud, a 3-axis robotic positioning system, and a regolith bin. For the REACT project, a pellet extruder and feed hopper have been installed on ARGO to advance the Technology Readiness Level (TRL) of regolith-polymer composite Fused Deposition Modeling (FDM) additive construction systems, processes, and materials. This paper will focus on the design and operational characteristics of the ARGO Test Bed with pellet extruder.

Moon↗
NASA NTRS1974

Lunar soil properties and soil mechanics

The long-range objectives were to develop methods of experimentation and analysis for the determination of the physical properties and engineering behavior of lunar surface materials under in situ environmental conditions. Data for this purpose were obtained from on-site manned investigations, orbiting and softlanded spacecraft, and terrestrial simulation studies. Knowledge of lunar surface material properties are reported for the development of models for several types of lunar studies and for the investigation of lunar processes. The results have direct engineering application for manned missions to the moon.

Mitchell, J. K.↗
NASA NTRSDate not supplied

Generating Cryogenic Lunar Simulants Within the Planetary Exploration & Astromaterials Research Laboratory

The Planetary Exploration & Astromaterials Research Laboratory (PEARL) aims to provides capabilities for the creation of—and research on—cryogenic lunar regolith simulants (CRS) containing surface volatile analytes. CRS represent regolith samples that might be collected from lunar Permanently Shadowed Regions (PSRs) during future missions. Handling CRS requires procedural and engineering development due to extremely cold (i.e. ≤ - 196°C) working temperatures. However, there is an imperative to understand the physical and chemical alteration of samples during collection, transport, and curation processes throughout the Artemis missions. The chemistries that will be encountered within the PSRs need to be understood based upon prior mission data analysis. The ability to utilize these techniques provides future tests that could be relevant to planetary protection applications regarding future robotic sample return.

Lunar↗
NASA NTRSDate not supplied

Grain Shape Characterization as an Enabling Capability for Lunar Surface Technologies

Lunar regolith has unique physical and geotechnical properties compared with familiar granular materials on Earth, and most lunar simulants as well. Specifically, the cohesion, angle of repose, and compressibility are much higher, and flowability is much lower for lunar regolith than otherwise similar terrestrial-derived materials[1,2]. There is confusion in the literature about the relative importance of vacuum, gravity, and inherent grain characteristics in driving these differences. Here we emphasize the importance of characterizing grain types and shapes for designing and test-ing lunar surface technologies, including for rover mobility, material handling, soil sampling, and heat transfer analyses. We demonstrate laboratory capabilities and preliminary studies, and outline further work to better characterize and simulate lunar grains to reduce risks for surface activities

K. M. Cannon↗
NASA NTRSDate not supplied

Demonstration of Capability to Simulate Particle Irregular Shape and Poly-Disperse Mixtures Within Lunar Lander Plume-Surface Interaction

Plume-Surface Interaction (PSI) between lander engine plumes and regolith soil creates hazards in obscuration and contamination by particle clouds, high-energy ejecta streams, and landing area cratering damage. The MSFC Fluid Dynamics Branch is developing simulation tools to offer a predictive PSI capability to NASA customers such as the Human Lander System (HLS) and Commercial Lunar Payload Services (CLPS). The Gas-Granular Flow Solver (GGFS) is the main application tool for coupled gas-particle two-phase flow simulations to predict the range of PSI effects from onset of surface erosion to deep crater formation. GGFS features an Eulerian-Eulerian modeling approach, treating both gas and granular material as interacting continuum phases. Modeling the lunar regolith granular material fluidic characteristics poses special challenges due to complex particle shapes and mixture composition. The lunar regolith is poorly sorted with broad particle size distributions and large fines content. It has significant cohesion, due to interlocking jagged particle shapes. Eulerian granular material flow modeling requires closure formulations for the granular material constitutive models (stress, friction, collisional and kinetic energy dissipation, drag, etc.). While closure models for spherical particles are available from particle kinetic theory, closure models for realistic non-spherical particles must be extracted from unit physics Discrete Element Model (DEM) particle interaction simulations and provided in the form of tabular datasets. The effects of particle irregular shape (non-spherical shape factors, angular particle surface roughness, and interlocking features) are simulated by approximating the particle features in the form of grouped elemental spheres to form composite particles in the DEM simulations. The effects of the wide range of regolith mixture particle sizes and the strong effects of the presence of the small particle sizes results in high cohesion and low porosity of the regolith mixture. The range of particle sizes is simulated by binning the particle sizes into an appropriate finite number of particle-size species and solving the problem as a species mixture. Combining these two modeling approaches enables simulations to capture both, the contributions of the irregular particle shape and the particle size distribution. The integration and maturation of the DEM-based constitutive model database generation process and poly-disperse mixture binning approach into the GGFS simulation framework are proceeding under funding by the NASA Game Changing Development program. The status of current capabilities will be presented in comparisons of crater characteristics resulting for spherical and irregular shape particles, and for mono-, bi-, and tri-disperse mixture simulations of Apollo LM plume-surface interaction. The computational results confirm the significance of including the particle shape and mixture effects. Going forward plans for the full implementation of the general poly-disperse regolith modeling capability and maturation towards NASA project application readiness under the GCD program will be presented.

Peter A Liever↗