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At least 919 records · Page 51

Designing the Design Process for Early Problem Discovery for a Complex Aeronautics Systems Challenge

The earliest stage in the innovation lifecycle, problem formulation, is crucial for setting direction in an innovation effort. When faced with an interesting problem, engineers commonly assume the approximate solution area and focus on ideating innovative solutions. However, in this project, NASA and their contracted partner, Accenture, collaboratively conducted problem discovery to ensure that solutioning efforts were focused on the right problems, for the right users, and addressing the most critical needs—in this case, exploring weather tolerant operations (WTO) to further urban air mobility (UAM) – known as UAM WTO. The project team leveraged generative, qualitative methods to understand the ecosystem, players, and where challenges in the industry are inhibiting development. The complexity of the problem area required that the team constantly observe and iterate on problem discovery, effectively “designing the design process.” This report discusses the approach, methodologies, and selected results, including insights on the application of early-stage design methodologies to a complex, system-level problem.

Problem formulation↗

Maintenance-optimized Modular Robotic Concepts for Planetary Surface ISRU Excavators

Modular robotic concepts are identified and evaluatedover the design and operations/maintenance lifecycle forautonomous Lunar, Mars, and partial gravity planetary surfaceexcavation and in-situ earthworks equipment. In-Situ ResourceUtilization (ISRU) is the exploitation of available resources at thesite of a landed spacecraft on the surface of another planetary body.It is intended that this ISRU excavator concept be capable ofmaterial extraction from native regolith, and will be able to operatein a variety of planetary surface environments after initial shakedownon the moon. Using heritage from highly multi-functional,reconfigurable robotic systems like the All-Terrain Hex-LimbedExtra-Terrestrial Explorer (ATHLETE), Regolith AdvancedSurface Systems Operations Robot (RASSOR), and Marsexploration rovers, we propose a flexible maintenance-optimizedmobility platform concept with quick-connect/disconnect featuresfor robotically swappable excavation implements. Dust toleranttorque transmission, power & data docking, thermal fluidconnectors, and modular avionics and instrumentation will allow forautonomous swapping of tools, replacement of spares, and longtermmaintenance of robotic excavators. The architecture includesmodular tools for conventional excavate / scoop / haul / dump /process functions of a terrestrial mining operation on Earth, but alsowill have the capability to operate and robotically maintain itselfwithout human intervention. The concepts described in this studywill provide a suite of technologies, configurations, and operationsready for inclusion into a final flight-ready excavator system.

Schuler, Jason↗

Run Time Improvement Efforts for the Roman Space Telescope Thermal Analysis

"Observatory thermal models for large, complex missions, such as the Wide Field InfraRed Survey Telescope (WFIRST) mission, produce an immense amount of data to be processed. Configuration management of the model throughout the project life cycle has mainly focused on which versions of the subsystem models form the current observatory level configuration. However, the results produced by the model are not nearly as well The Roman Space Telescope (RST), formerly known as the Wide Field InfraRed Survey Telescope, is the next great astrophysics observatory mission to follow the James Webb Space Telescope with a planned launch in 2026. As a large scale, flagship mission for NASA with challenging wave front error stability requirements, a single model approach for both thermal discipline analysis and thermo-optical distortion analysis has been used since the early days of the project. In alleviating the need to maintain two separate models for different analysis types, it imposes run time penalties on the thermal analysis with a large model with significant radiation heat exchange. Throughout the lifecycle of the project, the component models have steadily grown in size, resulting in a continuous growth of the overall observatory model with each update and consequently a considerable increase in the model run time. While ongoing efforts to reduce run time are continuously investigated, previous efforts had primarily focused on timestep size and total simulation time to reach quasi-equilibrium. More recently, studies were performed on the total number of radiation couplings (radks) included in the model, which has a nearly linear impact on run time, but increases exponentially with node count. As standard practice for spacecraft analysis, small radks were excluded from the temperature solution based on the assumption that their interchange/view factors have a negligible impact on heat flow. Four approaches were investigated to reduce the model run time while minimizing the impact on accuracy: (1) the Equivalent Radiation Network node, (2) Progressive Radk Inclusion as solution proceeds, (3) Targeted Radk Filtering for critical/non critical areas, and lastly (4) Representation of culled radks with Backloads. Furthermore, the investigation of model run time also revealed that cold cases took noticeably longer to run than hot cases; the root computational inefficiencies were explored along with the computation penalty of linearization of the external radks and recalculation of temperature dependent linear couplings at each timestep. This paper outlines the details of each of the above approaches and their impact on run time and model accuracy.

Thermal Analysis↗

Astromaterial Curation and Research at NASA

Astromaterial sample return missions from other planetary bodies (e.g., the Moon, asteroids, the Sun) and astromaterial sample collection missions here on Earth (e.g., Antarctic Meteorites, Cosmic Dust) have been a vital part of NASA’s science vision since nearly its inception. Beginning with the Apollo missions to the Moon and extending to the recent successful sample collection by the OSIRIS-REx asteroid sample return mission, these astromaterials collections have been an invaluable resource to scientists and educators around the world. Sample studies continue to provide fundamental insight into how our solar system and its constituent bodies formed and evolved over the past 4.5 billion years. As evidence of their broad impact, there are over 19,141 samples on loan to 433 Principal Investigators in 24 countries [1]. As we plan for exploration missions through 2050, sample return missions will continue to play a vital role in NASA’s science vision. Returned samples truly are the gift that keeps on giving. Having the samples accessible on Earth allows new generations of scientists and new generations of instrumentation to pursue ever evolving scientific questions. For example, the Apollo samples were collected ~50 years ago, yet our views of how the Earth-Moon system formed, the role of volatiles in the early inner solar system, and even the positions of the gas giants in the outer solar system have changed dramatically as a result of Apollo sample analyses conducted very recently. Vital to the long-term viability of any sample return mission is the careful curation of the samples. Curatorial efforts need to begin early in the project lifecycle, not with the return of the samples, but at mission conception. The Astromaterials Acquisition and Curation Office at NASA Johnson Space Center is responsible for curating all of NASA’s current and future extraterrestrial samples. Looking at possible sample return missions over the next 35+ years [2], many samples would require curation efforts a step beyond current capabilities, e.g., cold or cryogenic curation, organically and biologically clean curation, curation of gases and ices, and curation of samples with extreme pressure, temperature, or redox requirements. During the lecture, we discuss the current curatorial efforts in JSC curation, as well as discoveries from the astromaterial research. [1] Zeigler, R. A. et al. (2017) Planetary Science Vision 2050 Workshop. [2] McCubbin F. M. et al. (2017) Planetary Science Vision 2050 Workshop.

astromaterial↗

Run Time Improvement Efforts for the Roman Space Telescope Thermal Analysis

Observatory thermal models for large, complex missions, such as the Wide Field InfraRed Survey Telescope (WFIRST) mission, produce an immense amount of data to be processed. Configuration management of the model throughout the project life cycle has mainly focused on which versions of the subsystem models form the current observatory level configuration. However, the results produced by the model are not nearly as well The Roman Space Telescope (RST), formerly known as the Wide Field InfraRed Survey Telescope, is the next great astrophysics observatory mission to follow the James Webb Space Telescope with a planned launch in 2026. As a large scale, flagship mission for NASA with challenging wave front error stability requirements, a single model approach for both thermal discipline analysis and thermo-optical distortion analysis has been used since the early days of the project. In alleviating the need to maintain two separate models for different analysis types, it imposes run time penalties on the thermal analysis with a large model with significant radiation heat exchange. Throughout the lifecycle of the project, the component models have steadily grown in size, resulting in a continuous growth of the overall observatory model with each update and consequently a considerable increase in the model run time. While ongoing efforts to reduce run time are continuously investigated, previous efforts had primarily focused on timestep size and total simulation time to reach quasi-equilibrium. More recently, studies were performed on the total number of radiation couplings (radks) included in the model, which has a nearly linear impact on run time, but increases exponentially with node count. As standard practice for spacecraft analysis, small radks were excluded from the temperature solution based on the assumption that their interchange/view factors have a negligible impact on heat flow. Four approaches were investigated to reduce the model run time while minimizing the impact on accuracy: (1) the Equivalent Radiation Network node, (2) Progressive Radk Inclusion as solution proceeds, (3) Targeted Radk Filtering for critical/non critical areas, and lastly (4) Representation of culled radks with Backloads. Furthermore, the investigation of model run time also revealed that cold cases took noticeably longer to run than hot cases; the root computational inefficiencies were explored along with the computation penalty of linearization of the external radks and recalculation of temperature dependent linear couplings at each timestep. This paper outlines the details of each of the above approaches and their impact on run time and model accuracy.

Thermal Analysis↗

A Model-Based Systems Engineering Journey to Developing a Concept of Operations

Starting in 2017, NASA’s Human Research Program (HRP) Exploration Medical Capability (ExMC) element began a systems engineering transition from traditional, document-centric development to model-centric development when defining its foundation medical systems. These foundation medical systems define a Concept of Operations (ConOps) and identify the generic requirements for a medical system based on assumptions about a generic crew and mission environments and guidance from NASA standards (e.g., Medical “Levels of Care”). By making the transition, ExMC intends to improve communication among stakeholders about foundation medical system requirements and content. In addition, this transition will enable ExMC to lower both development and crew treatment risks for future, mission-specific medical systems. ExMC followed a Model Based Systems Engineering (MBSE) paradigm when developing the foundation medical systems. A model-based approach provides several advantages over a traditional, document-centric approach. First, when Systems Engineers (SE) develop diagrams in a model using a standard modeling language, they produce information dense pictures that facilitate understanding much more efficiently with less room for misinterpretation than text. Second, due to the evolving nature of projects, documentation becomes out of date the minute it is published. This can result in people making decisions based on information that is no longer current, especially if they are referencing a locally-stored copy of a document. A model, on the other hand, is always up to date with the latest approved changes and information. It serves as a single point of truth. Third, a model-centric approach centralizes all important information in one place. Rather than having to flip through separate ConOps documents, design specifications, requirements specifications, and the like to coordinate information, a model captures the content in one, integrated spot. This integration makes tracing information from end-to-end easier with greater reliability. The ExMC Systems Engineering Lifecycle follows a well-defined process. ExMC Systems Engineers perform all major steps of the process, regardless of the development methodology. One of the first steps in the process is developing the ConOps that describes the operation of the system from the point of view of the users. It includes a list of the users and their needs, the goals of the medical system, key assumptions about the system, and definitions of the medical system’s operational environments. For this development effort, ExMC chose to replace the traditional text-based ConOps document with a model. While the decision to change the development workflow was not difficult, implementing the structural and organizational workflows were. It required showing ExMC’s users, most of whom are not Systems Engineers, how the information they require would be presented in the model and to gain their acceptance of this approach. This paper documents key lessons learned during the ConOps transformation by focusing on how the model represents information, the agile workflow used by SEs when developing the model and how it integrates into a project plan, how leadership influenced key users to accept the transformation, and how the users interact with the model information.

Jeffrey Robert Cohen↗

Bion-M2

Bion-M2, scheduled to launch in April 2023, continues the 30+ year collaboration between the Institute of Biomedical Problems of the Russian Academy of Sciences (IBMP RAS) and the National Aeronautics and Space Administration (NASA). Bion-M2 is the second biosatellite in the Bion-M series and its goal is to investigate how the space environment affects living organisms, with emphasis on physiological changes in rodents, gravitational biology using a wide variety of specimens, and radiation biology. The Bion-M2 biosatellite will complete a 30-day low earth orbit (LEO) flight to study the combined effects of microgravity and ionizing radiation (IR) on multiple organisms, where the payload may be exposed to IR at 20-30 times thedose rate seen on the International Space Station. Following return, nine U.S. collaborators selected through the NASA Space Biology Research Announcement will conduct post-flight rodent experiments using male C57BL/6 mice. The post-flight experiments will investigate the effects of the space environment on bone and skeletal muscle health, cardiac function, reproductive system function, neurovascular systems, protein composition in plasma, and thermoregulation in the mice. Currently, the Bion-M2 mission is in the development phase of theproject lifecycle. The mission objectives, constraints, requirements, and timeline have been defined in the project plan and contracts. Technology for the mission is under development and science procedures will be finalized by FY22. The aim of this presentation is to highlight the importance of the Bion-M2 mission and provide insight into the mission development process, including an overview of the project plan and the tissue sharing plan that will be utilized during the post-flight dissection procedures.

Bion-M2↗

Surface Systems Capability Gaps for Enabling NASA’s Sustainable Lunar Operations

This paper discusses the NASA Ground, Test, and Surface Systems Taxonomy (TX-13) related capability gaps, including details of architecture, technology, engineering, and policy gaps for enabling sustainable lunar surface operations and subsequent Mars missions. Architecture gaps include standardized architectures and interfaces, multi-element systems engineering and integration, design for supportability, and nuclear payload processing and launch approach. Technology gaps, primarily focused on uncrewed surface operations, include automated/autonomous cryogenic loading, transfer, servicing, and storage of commodities; health determination and fault management; automated/autonomous planning and scheduling; automated/autonomous inspection, maintenance and repair; logistics management and reliability; launch and landing site preparation; commodity management; and advanced umbilicals and dust tolerant interfaces. Engineering gaps include high-purity propellant production for ground and surface applications and large-scale xenon servicing capabilities. The policy gap includes nuclear propulsion acceptance testing and qualification approach. Strategically identifying human/automation roles and tasks and infusing automation and autonomy practices early in a system’s lifecycle is essential for achieving the mission objectives for a sustainable human lunar presence, improving performance and mission effectiveness, reducing operations costs and reliance on humans to perform tasks, and accommodating ground communication delays.

Surface Systems↗

How Environment and Operational Considerations Guide Requirements Development for Clinical Decision Support Beyond Low Earth Orbit

The Aerospace Medical community is acutely aware of the need for automated cognitive systems to support astronauts in responding to and making critical decisions about assessing – and treating - medical conditions and assuring wellness during exploration spaceflight missions. Such systems will be critically important to mission success as we venture farther from terrestrial settings (particularly low-earth orbit platforms) and encounter increasingly Earth-independent medical decision-making scenarios and requirements. This need would likely be met through the development of a Clinical Decision Support System (CDSS) that assimilates information from various sources (e.g., vehicle environmental control system, blood pressure cuff, and heart rate monitor) integrated with medical and wellness data to provide detailed guidance tailored to individual crew member needs. This presentation will address some of the fundamental considerations and their implications that must be fully understood by CDSS requirement developers early in the system lifecycle.

B Burian↗

Updraft Dynamics and Microphysics: On the Added Value of The Cumulus Thermal Reference Frame in Simulations of Aerosol–Deep Convection Interactions

One fundamental question about atmospheric moist convection processes that remains debated is whether, or under which conditions, a relevant variability in background aerosol concentrations may have a significant dynamical impact on convective clouds and their associated precipitation. Furthermore, current climate models must parameterize both the microphysical and the cumulus convection processes, but this is usually implemented separately, whereas in nature there is a strong coupling between them. As a first step to improve our understanding of these two problems, we investigate how aerosol concentrations modify key properties of updrafts in eight large-eddy-permitting regional simulations of a case study of scattered convection over Houston, Texas, in which convection is explicitly simulated and microphysical processes are parameterized. Dynamical and liquid-phase microphysical responses are investigated using the following two different reference frames: static cloudy updraft grid cells versus tracked cumulus thermals. In both frameworks, we observe the expected microphysical responses to higher aerosol concentrations, such as higher cloud number concentrations and lower rain number concentrations. In terms of the dynamical responses, both frameworks indicate weak impacts of varying aerosol concentrations relative to the noise between simulations over the observationally derived range of aerosol variability for this case study. On the other hand, results suggest that thermals are more selective than cloudy updraft grid cells in terms of sampling the most active convective air masses. For instance, vertical velocity from thermals is significantly higher at upper levels than when sampled from cloudy updraft grid points, and several microphysical variables have higher average values in the cumulus thermal framework than in the cloudy updraft framework. In addition, the thermal analysis is seen to add rich quantitative information about the rates and covariability of microphysical processes spatially and throughout tracked thermal lifecycles, which can serve as a stronger foundation for improving subgrid-scale parameterizations.

aerosols↗

TAMU: a new space mission operations paradigm

The Transferable, Adaptable, Modular and Upgradeable (TAMU) Flight Production Process (FPP) is a model-centric System of System (SoS) framework which cuts across multiple organizations and their associated facilities, that are, in the most general case, in geographically diverse locations, to develop the architecture and associated workflow processes for a broad range of mission operations. Further, TAMU FPP envisions the simulation, automatic execution and re-planning of orchestrated workflow processes as they become operational. This paper provides the vision for the TAMU FPP paradigm. This includes a complete, coherent technique, process and tool set that result in an infrastructure that can be used for full lifecycle design and decision making during any flight production process. A flight production process is the process of developing all products that are necessary for flight.

Meshkat, Leila↗

Validation on the Europa Clipper Mission in the Formulation Phase

The Europa Clipper mission will perform a detailed investigation of Europa’s environment and habitability by placing a spacecraft into a looping orbit around Jupiter and performing repeated close Europa flybys. The Europa Clipper Project Verification and Validation (V&V) team is responsible for verifying that the Project System is compliant with the science and engineering requirements levied on it and validating that it is capable of meeting the mission objectives. Europa Clipper has developed a V&V framework to ensure that mission capabilities are realized at a reasonable confidence level prior to launch. The V&V team will coordinate the validation activities defined by this framework throughout the project lifecycle as the spacecraft evolves from design to implementation and operations. Validation of space missions is typically grouped into three categories: 1) requirements validation, 2) model validation, and 3) system validation. System validation, along with verification activities, are often the primary focus of V&V programs and these efforts peak in the implementation phase. However, the increasing reliance of exploration missions on models and simulations, and the complexity of the Europa Clipper mission, have dictated attention to requirements and model validation in the formulation phase. This paper discusses the development of the Europa Clipper V&V framework with emphasis on the validation of models and simulations, and of requirements. Approaches include the adaptation of institutional guidelines, such as those in the NASA-STD-7009 document, to create a Project Model V&V Plan and the use of tools such as DOORS NG to plan model validation and derive requirement quality metrics.

Srivastava, Priyanka↗

Psyche Early Project Verification & Validation Planning Development

The Psyche mission to the asteroid (16) Psyche was selected as the fourteenth mission in the Discovery program in January 2017. The Psyche mission will determine if (16) Psyche is the core of a larger differentiated body. As part of the development of this mission a Verification and Validation (V&V) engineer was assigned early in the project’s design Phase B. This paper will discuss some of the strategies that the Psyche team is using to take full advantage of the early planning for V&V on flight projects and specifically how the Psyche mission is approaching these tasks. This paper will discuss the effects of having a V&V mindset on: 1) The Psyche requirements development process, and how focusing not only on how the team will verify these requirements but also on developing the tools necessary to track and monitor that verification feeds back into the requirement development process. 2) The Psyche testbed development, and how using a verification mindset is useful for identifying holes in the testbed development process, including the required testbed speed and how to think about testbed certification early in the process while encouraging trades and developing relationships with the testbed team. 3) Developing new V&V Tools for Psyche, and how developing tools early in the project development process means that they can influence the development of other requirement and scheduling tools. 4) Verification Activity Planning, which is typically done to a preliminary level during Phase B of the project, and is important for understanding the major testing that is needed to ensure that the system as built represents the design. On Psyche we are not only focused on bringing this planning to a preliminary level, we are also developing a V&V focused schedule to help us de-conflict V&V activities that may require similar resources early on in the program’s development. 5) Validation Planning, for which we are working with the testbed and model development teams to ensure that their models can be effectively validated and that the plans to do so are in place. In this paper we will describe how the Psyche mission is approaching each of these V&V areas and identify lessons that can be taken by other space missions trying to decide how much effort should be put into V&V early in the project lifecycle.

Solish, Benjamin↗

On-demand Command and Control of ASTERIA with Cloud-based Ground Station Services

ASTERIA (Arcsecond Space Telescope Enabling Research in Astrophysics) was a 6-unit CubeSat technology demonstration mission that deployed from the International Space Station on November 20th, 2017. After successfully completing its 90-day primary mission that demonstrated arcsecond-level line-of-sight pointing and focal plane thermal stability for exoplanet detection, it entered an extended mission performing onboard software demonstrations to mature technology both in space and on the ground. One of the technologies was a completely cloud-based ground system leveraging Amazon Web Services (AWS) Ground Station service.Announced in December 2018 and launched in May 2019, AWS Ground Station is a fully managed ground station service that aims to reduce the overhead associated with developing and maintaining ground system infrastructure throughout the mission lifecycle. AWS Ground Station makes available the suite of features required for any ground system in support of low-Earth orbit (LEO) and medium-Earth Orbit (MEO) satellite operations on-demand and without setting up or maintaining long-term contracts. Charges are incurred on a per-minute basis for antenna usage during scheduled tracks. Support is available for S-band uplink and downlink, along with X-band narrowband and wideband downlink. Missions that use the service may reserve tracks with any licensed AWS Ground Station antennas located across each service region and have direct access to any AWS services in support of mission operations.The cloud-based architecture built around the AWS Ground Station service greatly enhanced ASTERIA mission operations by enabling end-to-end pass automation, on-demand contact scheduling and contingency planning, along with more efficient data downlink through station availability and station-to-station handovers. It incorporated open-source software, particularly NASA's AMMOS Instrument Toolkit (AIT) and Open Mission Control Technologies (OpenMCT), along with the AWS application programming interfaces (API) to the Ground Station, Elastic Compute Cloud (EC2) and Simple Storage Service (S3) services. After showcasing operability in August 2019, the team continued using and improving this novel ground system architecture until the end of mission in December 2019. This paper describes the cloud-based ground system, how it was designed, tested, and evaluated with an in-orbit spacecraft, the operational capabilities that it enabled, along with lessons learned and recommendations for future missions.

Fesq, Lorraine↗

Developing and Validating Measurement Scales During Pandemic Conditions: A Case Study with the Scale for Habitat Usability

At NASA, habitat evaluations often employ subjective measures. Some measures are frequently used, well established tools, whereas others are homegrown measures tailored to specific projects. The variety of measures used makes evaluation comparisons across projects difficult. Additionally, some of these measures are burdensome, may be too specialized, or may require an expert to use and interpret, limiting their utility. Taken together, these drawbacks suggest the need for a new measurement tool. To that purpose, a team at NASA worked on developing a new scale for measuring habitat usability, the Scale for Habitat Usability (SHU). The SHU is intended to be a quick, multi-faceted measure for evaluating habitat usability across the development lifecycle. However, like many research projects, the development of the SHU faced setbacks due to the COVID-19 pandemic. Pandemic prevention protocols precluded in-person data collection, forcing the team to take some non-traditional approaches to scale development. This paper reports the steps the team took to complete the project.

Ian Robertson↗

On-demand Command and Control of ASTERIA with Cloud-based Ground Station Services

ASTERIA (Arcsecond Space Telescope Enabling Research in Astrophysics) was a 6-unit CubeSat technology demonstration mission that deployed from the International Space Station on November 20th, 2017. After successfully completing its 90-day primary mission that demonstrated arcsecond-level line-of-sight pointing and focal plane thermal stability for exoplanet detection, it entered an extended mission performing onboard software demonstrations to mature technology both in space and on the ground. One of the technologies was a completely cloud-based ground system leveraging Amazon Web Services (AWS) Ground Station service. Announced in December 2018 and launched in May 2019, AWS Ground Station is a fully managed ground station service that aims to reduce the overhead associated with developing and maintaining ground system infrastructure throughout the mission lifecycle. AWS Ground Station makes available the suite of features required for any ground system in support of low-Earth orbit (LEO) and medium-Earth Orbit (MEO) satellite operations on-demand and without setting up or maintaining long-term contracts. Charges are incurred on a per-minute basis for antenna usage during scheduled tracks. Support is available for S-band uplink and downlink, along with X-band narrowband and wideband downlink. Missions that use the service may reserve tracks with any licensed AWS Ground Station antennas located across each service region and have direct access to any AWS services in support of mission operations. The cloud-based architecture built around the AWS Ground Station service greatly enhanced ASTERIA mission operations by enabling end-to-end pass automation, on-demand contact scheduling and contingency planning, along with more efficient data downlink through station availability and station-tostation handovers. It incorporated open-source software, particularly NASA's AMMOS Instrument Toolkit (AIT) and Open Mission Control Technologies (OpenMCT), along with the AWS application programming interfaces (API) to the Ground Station, Elastic Compute Cloud (EC2) and Simple Storage Service (S3) services. After showcasing operability in August 2019, the team continued using and improving this novel ground system architecture until the end of mission in December 2019. This paper describes the cloud-based ground system, how it was designed, tested, and evaluated with an inorbit spacecraft, the operational capabilities that it enabled, along with lessons learned and recommendations for future missions.

Fesq, Lorraine↗

Uncrewed Lunar Surface Operations and Support Activities

Sustained human presence on the surface of the Moon and future missions to Mars require increased independence from surface crews and Earth-based mission control to operate efficiently, safely, and reliably. The time for surface crews to perform tasks will be limited. Extravehicular activities by surface personnel are burdensome and time-consuming, even when a continuous human presence on the surface occurs. Identifying and balancing human/automation roles and tasks and infusing automation and autonomy practices early in a system’s lifecycle will be essential to achieve mission objectives. Among these objectives are attaining a sustained human presence, improving performance and mission effectiveness, reducing operations and maintenance (O&M) costs, and ensuring operations that are robust to communication delays. To achieve these objectives, an operational shift toward increased automation and autonomy with less reliance on humans is needed. Uncrewed lunar surface operations and support activities occur when surface crews are not present or are independent of surface crew timeline activities requiring no surface crew oversight or intervention. These uncrewed surface opportunities can also be planned to minimize crew workload that avoids routine maintenance and support tasks, thus maximizing crew exploration time. Uncrewed preparations such as staging and prepositioning equipment and materials before the crew arrives could improve crew task efficiency. Additional opportunities exist to conduct uncrewed science, exploration, and utilization. Uncrewed surface architecture functions can include science and exploration; habitation; launch and landing support; surface communication and navigation; surface power generation and distribution; human surface mobility; lifting, handling, manipulating; excavation, construction, and site preparation; logistics management; maintenance and repair; surface resource utilization; integrated site operations and shared support services (e.g., site scheduling/prioritization, dust mitigation/contamination control, and surface safety). Early robotic lunar surface campaigns will provide information on the availability of resources, such as oxygen and water, and demonstrate surface-based technologies. After the Artemis III human lunar return mission, a series of landers will deliver surface systems, cargo, supplies, science packages, spare parts, and commodities. A balance of crewed and uncrewed surface operations will enable a sustained lunar surface presence at the South Pole of the Moon at a site that will be known as the Artemis Base Camp (ABC). It is envisioned that base camp operations on and around the Moon will then help prepare for the mission durations and activities needed to support the first human mission to Mars. Before long-duration crew missions to the base camp can occur, the necessary surface infrastructure will be pre-deployed and verified operational. Surface assets will be teleoperated and remotely managed from Earth. Additionally, robotic and short-duration crewed missions to the ABC will ensure the site’s merit to achieve long-term science objectives, availability of usable resources, and that terrain, seasonal variations, and illumination conditions are acceptable. ABC will consist of different areas where specific functions and services are rendered, including: • Launch and Landing Area • Habitation Area • Power Production Area • Resource Areas Launch and Landing Area—The launch and landing area will support associated functions for the arrival and departure of vehicles, such as crewed landing and ascent and uncrewed cargo deliveries and offloading. It will evolve from an unimproved site at the beginning of the exploration campaign to a more sustainable landing and launch area that can support repeated arrivals and departures. Initial uncrewed Lunar Terrain Vehicle (LTV) surface operations may include emplacement of navigation beacons and communication equipment, real-time video and photography of landing/liftoff events, and element repositioning, such as portable utility power (PUP) (applicable for other landed assets at other areas). Site preparations, such as surface leveling, soil compaction, and berm/path construction, may be needed for a more sustainable launch and landing area capable of accommodating vehicles that are increasingly more reusable and reduce the effects of plume surface interactions and ejecta impacts on nearby surface assets. During the ABC missions, cargo and logistics will be delivered to the lunar surface via robotic cargo landers before the crew arrives. These shipments, which can arrive in pressurized logistics carriers, will deliver the logistics necessary to support a crewed mission and include items such as food, water, equipment spares, etc. Providing the capability to retrieve, offload, and transport the logistics closer to the ABC site before the arrival of the crew will increase the overall efficiency of crew operations once they arrive. In the sustained phase of exploration, other supporting services may be needed, such as lander propellant servicing, surface power services, commodity refreshes, and additional inspection, maintenance, and repair capabilities, to sustain a cadence of extended personnel stays and cargo arrivals and departures. Habitation Area—Uncrewed support to surface habitation could involve supporting activation and pre-entry operations of the habitat while the crew is in orbit at the Gateway outpost preparing for a surface landing. Surface Habitat (SH) uncrewed operations may include bringing the cabin environment to a habitable temperature and air mix and activating other critical crew support systems. Potential crop production uncrewed tasks in the SH could also include autonomous watering and tending. Additionally, when the crew departs, the SH enters dormancy for the long period of uncrewed operation. A logistical staging area could also be collocated near the SH. If so, staging operations for crew supplies, waste re-location, and recycling operations may be opportunities for uncrewed operations. Power Production Area—The Fission Surface Power (FSP) element and its supporting distribution equipment provide power to surface elements as needed across the ABC to supplement day-to-day operations and survive lunar nights. Uncrewed support of this power system includes any initial LTV-assisted deployments of cables and other distributed equipment, associated electrical connections, and system testing and activation operations. Robotically performing some inspections, maintenance, or repair tasks on the power distribution equipment could reduce the surface crew workload. Resource Area— Uncrewed resource prospecting, mapping, and characterizing possible resource sites is likely to be time-consuming and represents an opportunity for uncrewed operations between crewed missions. Uncrewed mobile equipment operations will be needed in the extreme environments of permanently shadowed locations where resource extractions occur. As In-Situ Resource Utilization (ISRU) pilot plant operations begin, uncrewed surface support activities with available mobile and portable assets (LTV, PUP, etc.) will better support these operations. Any produced commodities can be stored at a centralized storage location for future use. Also associated with these operations is the use of mobile robotic excavators for resource acquisition and robotic/autonomous regolith processing. The waste tailings generated during excavation and regolith processing would also need to be transported and deposited at a dedicated location. Surface assets will continue operating between crew visits to maintain surface capabilities, conduct lunar surface science, technology demonstrations, and public outreach opportunities. Additionally, certain sustaining tasks that would consume valuable crew time could be performed before crew arrival, or after their departure. This capability may offer more affordable options to construct, activate, test, and maintain a broad set of surface assets. Telerobotically operated human surface mobility systems, such as the LTV and Pressurized Rover (PR), can be utilized for various tasks. Surface environmental conditions pose a distinct challenge for all these activities. Surface illumination and localized shadows are one such factor. Night-survival operations could consist of thermal management, battery pre-charging, and load shedding. Some surface systems may hibernate through the night and then awake and continue nominal operations. Uncrewed mobile assets may use a more adaptive approach to optimize their power and operations; one method is to follow the sunlight. Night-survival operations may be initiated remotely by teleoperation, automated, or accomplished by supervised autonomous operation. The ability to pre-deploy and control remote assets in orbit or on Mars before the arrival of the mission crew is a key capability that can be simulated on the moon. The base camp provides a venue where these advanced operational concepts, technologies, and autonomous methods and techniques, including the incorporation of time delays to simulate Earth-Mars latency can be replicated to help buy down future Mars mission risks. This paper will examine the evolution of uncrewed lunar surface operations and support activities. It will also discuss the lunar surface environmental conditions (thermal, lighting, terrain, topography, communications) along with the challenges they pose on uncrewed surface operations, and the performance of these activities with limited to minimal human interaction and/or teleoperation. Since lunar missions include Mars mission analogs, such investigation provides the framework for future uncrewed Mars mission support.

Mark E Lewis↗

Updraft Dynamics and Microphysics: On the Added Value of the Cumulus Thermal Reference Frame in Simulations of Aerosol–Deep Convection Interactions

One fundamental question about atmospheric moist convection processes that remains debated is whether or under what conditions a relevant variability in background aerosol concentrations may have a significant dynamical impact on convective clouds and their associated precipitation. Furthermore, current climate models must parameterize both the microphysical and the cumulus convection processes, but this is usually implemented separately, whereas in nature there is a strong coupling between them. As a first step to improve our understanding of these two problems, we investigate how aerosol concentrations modify key properties of updrafts in eight large-eddy permitting regional simulations of a case study of scattered convection over Houston, Texas, in which convection is explicitly simulated and microphysical processes are parameterized. Dynamical and liquid-phase microphysical responses are investigated using two different reference frames: static cloudy-updraft grid cells versus tracked cumulus thermals. In both frameworks we observe the expected microphysical responses to higher aerosol concentrations, such as higher cloud number concentrations and lower rain number concentrations. In terms of the dynamical responses, both frameworks indicate weak impacts of varying aerosol concentrations relative to the noise between simulations over the observationally derived range of aerosol variability for this case study. On the other hand, results suggest that thermals are more selective than cloudy-updraft grid cells in terms of sampling the most active convective air masses. For instance, vertical velocity from thermals is significantly higher at upper levels than when sampled from cloudy-updraft grid points, and several microphysical variables have higher average values in the cumulus thermal framework than in the cloudy-updraft framework. In addition, the thermal analysis is seen to add rich quantitative information about the rates and covariability of microphysical processes spatially and throughout tracked thermal lifecycles, which can serve as a stronger foundation for improving subgrid-scale parameterizations.

Daniel Hernandez-Deckers↗