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NASA NTRS2018

Ground Software Technologies – Embracing Change: Mission Drivers and Technology Opportunities to Enable Long Lived Missions

Mission lifecycles have proven to extend well beyond their original design. The benefits to this are countless but introduce challenges in today’s rapidly changing ground infrastructure and software technologies used to enable mission success. What remains constant is the risk posture missions maintain when accepting change and the use of new technologies. Larger missions are ready for change in early lifecycle development but near launch and especially in operations, few continue to evolve beyond what is set in place in phase C. This paper will discuss how the Advance Multi-Mission Operations System (AMMOS) intends to address, three driving missions concerns: Maintaining functionality (hardware/software) for decades, rapidly responding to security vulnerabilities in software, and finally the ability to quickly evolve infrastructure and software changes. These driving concerns are briefly described below: 1. Maintaining functionality (hardware/software) for decades. Hardware updates considerably faster than 10 years ago. Expectations that a system can remain in place for more than 10 years is no longer valid. Expecting to find hardware replacements for a system older than 5 years will increasingly become more and more challenging. How than do missions plan for hardware changes for long lived missions? Principle Objective: Provide abstraction by virtualizing and containerizing software abstract away any hardware dependencies and package up the application lightweight units. 2. Rapidly responding to security vulnerabilities in software. Cost is often the main impediment and largely driven by the revalidation and testing of system that undergo change. In todays, environment security updates are a major diver demanding systems remain up to date. How then do missions accept these changes and avoid large testing efforts? Principle Objective: Help reduce the cost of re-testing by automation of testing, deployment, and compartmentalizing change. 3. Ability to quickly evolve infrastructure and software changes. Responding quickly to change is similar to the second concern in this paper regarding security vulnerabilities. In this case, it address broader concerns of updating software and infrastructure on a more realistic timeline. How do missions stay up to date with the most recent versions of software and allowing for improved functionality? Principle Objective: Use continuous integration techniques at the system level to ensure rapid turnaround. This paper explores each of these concerns in more detail. It focuses the AMMOS’s current plans, challenges and current roadmap.

Giovannoni, Brian J.↗

NASA NTRSDate not supplied

Assessment of Crew Time for Maintenance and Repair Activities for Lunar Surface Missions

NASA is currently evaluating different methods to predict how much time crewmembers will spend conducting repair and maintenance activities on future space missions. As mission scope and spacecraft architectures change, understanding how crew repair and maintenance timelines are impacted by mission operations and technology changes is vital for future mission planning. Past work has been done using historical International Space Station (ISS) data to accurately predict crew habitation and operation timelines, resulting in the development of NASA’s Exploration Crew Time Model (ECTM). However, understanding crew maintenance and repair requirements has posed a unique challenge due to the complexity of available datasets, the probabilistic nature of sub-system failures, and the impacts of reliability growth on failure rates. This paper presents a methodology to collect and condition empirical repair and maintenance time data from available datasets, to extrapolate from that data to estimate projected maintenance and repair times for a lunar Surface Habitat (SH), and to assess how uncertainty in repair time could impact utilization time on the lunar surface. NASA ISS maintenance and crew time data are logged into two central databases: the Maintenance Data Collection (MDC) and the Operations Planning Timeline Integration System (OPTimIS). Separately, each of these two datasets capture only portions of the complete set of data required to generate an accurate assessment of crew time spent on maintenance activities at a sub-system level. To create a more useful crew time estimate for maintenance timelines, the authors developed a methodology to capture relevant data from each set and combine and utilize that data by linking crew time requirements to specific components. The authors compare the failure logs in the MDC to crew activity logs pulled from OPTimIS and then process the data to estimate required repair time for each failure and repair event. The entire maintenance activity dataset is then categorized based on the class of failed component to ensure a significant sample size for each class and accurate crew time estimates for any components lacking relevant data. This resultant component repair time data can be used in the future to generate Mean Time to Repair (MTTR) estimates and confidence intervals for each class of component based on a probabilistic distribution of documented maintenance events. These improved MTTR values can then be applied to candidate element sub-system architectures, along with component Mean Time Between Failure (MTBF) data to generate distributions for potential required system crew repair time estimates for a given mission. The authors applied these modeling methods to a case study of a crewed mission to the planned SH and produced expected corrective maintenance crew time distributions. The results produced an expected corrective maintenance crew time at over 24 hours per mission, and a maintenance crew time distribution that reflects the importance of planning for sufficient maintenance requirements each mission. Repair time distributions can then be used to develop more accurate crew schedules and to assess potential available utilization time.

Crew Time↗

NASA NTRS2019

Hybrid chemical-electric trajectories for a Mars Sample Return orbiter

The Earth return orbiter component of a Mars sample return campaign is a high total impulse mission with challenging timeline constraints. These competing demands mean a hybrid chemical-electric propulsion architecture may be needed for a feasible design, with chemical propulsion providing timely impulse and electric propulsion providing high volume impulse. We describe an approach to map out the hybrid trajectory design space and create a database to use in conjunction with a spacecraft design tool, enabling co-optimization of trajectory and spacecraft. This method is applied to both the outbound and inbound legs of a Mars sample return mission concept.

Lock, Rob↗

NASA NTRS2024

An Integrated Architecture Study for Autonomous Lunar Construction

Lunar construction is an expanding field within NASA’s Moon to Mars objectives that presents many challenges and requires innovative and reliable forms of autonomous operations on the surface of the Moon to further the technologies needed for human space exploration. Marshal Space Flight Center’s (MSFC) Advanced Concepts Office (ACO) addressed Lunar Infrastructure Objective LI-4 l by developing a Pre-Phase A, integrated architecture to inform a demonstration for lunar construction operations. The ACO study traded three architectures that would survey and prepare a construction area to build a landing pad out of lunar regolith using MMPACT (Moon-to-Mars Planetary Autonomous Construction Technology) platforms, rovers, and navigation outposts. The main trades examined navigation for the system/architecture, options for rover navigation, battery vs continuous tether power for the MMPACT robotic arm, and assigning site prep functionality to the rovers vs the platforms. Results of the study determined that the best options for the scenario provided would be local navigation (more accurate and continuous), a combination of Light Detection and Ranging (LiDAR) for initial site mapping with subsequent Smart Video Guidance Sensors (SVGS) to save power for construction, and using tethered power to decrease mission duration. The team also concluded that assigning site prep functionality to either the rovers or the platforms has benefits and challenges; future studies could explore having that functionality on both the rovers and platforms. Lastly, the team provided a Concept of Operations (ConOps) timeline that can be used in real-time ground demonstrations to explore the mission timeline, construction processes, autonomous operations, and communication systems that can be tested using MSFC’s lunar regolith field and Lunar Utilization Control Area (LUCA).

Sarah Triana↗

NASA NTRS1998

NASA/Mir Phase 1: A Lesson Learned in Long Duration Mission Planning and Operations

The NASA/Mir Phase I Program is a precursor to the assembly and operations of the International Space Station (ISS). The Phase I Program covers a four-year period and encompasses over ten shuttle flights to the Mir, culminating with the flight of STS-91 in June 1998. The Mir-Orbiting Station (Mir-OS) provides an excellent environment, both onboard and on the ground, for learning and studying the characteristics associated with crew-tended operations on long duration missions. By the end of the Phase I program, NASA astronauts will have accumulated over two years of continuous operations experience working and living onboard the Mir-OS. Ground controllers, working in Russia and at remote sites in the United States, will have gained valuable experience in the generation, maintenance, and coordination of the information and products required to support the long duration crew members onboard the Mir-OS. The experience gained by the crew and ground support personnel in the area of long duration mission operations has resulted in a number of factors that need to be considered in the definition and implementation of the processes and products for the ISS. While there are many areas in which experience has been gained, this paper focuses on the lessons learned regarding the level of detail and flexibility of crew timelines. Provided in this paper is an overview of the characteristics associated with long duration mission timeline development and execution, a summary of applicable lessons learned identified and documented through participation in the NASA/Mir Phase I Program, a detailed discussion of "Gross Timelines" as implementation which addresses the lessons learned. Also discussed are the challenges that must be overcome in getting the ISS program to recognize, evaluate, and learn from the crew and ground controller experience gained through participation in the NASA/Mir Phase I Program.

Hagopian, Jeff↗

NASA NTRS1993

Mars Observer Lecture: Mars Orbit Insertion

The Mars Observer mission spacecraft was primarily designed for exploring Mars and the Martian environment. The Mars Observer was launched on September 25, 1992. The spacecraft was lost in the vicinity of Mars on August 21, 1993 when the spacecraft began its maneuvering sequence for Martian orbital insertion. This videotape shows a lecture by Suzanne R. Dodd, the Mission Planning Team Chief for the Mars Observer Project. Ms Dodd begins with a brief overview of the mission and the timeline from the launch to orbital insertion. Ms Dodd then reviews slides showing the trajectory of the spacecraft on its trip to Mars. Slides of the spacecraft being constructed are also shown. She then discusses the Mars orbit insertion and the events that will occur to move the spacecraft from the capture orbit into a mapping orbit. During the trip to Mars, scientists at JPL had devised a new strategy, called Power In that would allow for an earlier insertion into the mapping orbit. The talk summarizes this strategy, showing on a slide the planned transition orbits. There are shots of the Martian moon, Phobos, taken from the Viking spacecraft, as Ms Dodd explains that the trajectory will allow the orbiter to make new observations of that moon. She also explains the required steps to prepare for mapping after the spacecraft has achieved the mapping orbit around Mars. The lecture ends with a picture of Mars from the Observer on its approach to the planet.

Dodd, Suzanne R.↗

NASA NTRSDate not supplied

Innovative IO Psychology Research for Future Space Exploration

Crewed space exploration is evolving. The commercialization of space includes Private Astronauts who interact with NASA astronauts on the International Space Station. Astronauts are scheduled to complete a variety of tasks within a fast paced timeline. Future exploration missions to Mars will include challenges such as a small crew living and working in an isolated and confined environment for up to 2 ½ years, with significant communication delays from Earth. This symposium brings together four innovative studies designed to mitigate the risks associated with space flight.

Suzanne Tamara Bell↗

NASA NTRSDate not supplied

Trustworthy Autonomy for Gateway Vehicle System Manager

The Vehicle System Manager (VSM) is the highest-level software control system in the Gateway hierarchical Autonomous System Management Architecture. The VSM provides four function categories: Mission Management and Timeline Execution, Resource Management, Fault Management, Vehicle Control and Operation. VSM provides various levels of automation ranging from fully autonomous operations with no flight crew and minimal ground monitoring to advisory automation when Gateway is crewed and has full ground monitoring. Trustworthiness is achieved via verified specification, comprehensive development verification, and real-time verification using assume-guarantee contracts. Development verification includes semantic verification of the data model via peer review and testing and assume-guarantee contracts implemented using the PlusCal/TLA+ environment. VSM also uses runtime assume-guarantee contracts, implemented in R2U2 via a runtime monitor that feeds the necessary telemetry data to R2U2 and which receives and responds to the R2U2 verdict stream. The full lifecycle verification approach and use of assume-guarantee contracts provides increased trustworthiness to VSM. Preliminary results provide encouragement that VSM can be both autonomous and trustworthy.

Assume-guarantee contracts↗

NASA NTRSDate not supplied

Gateway Autonomy for Enabling Deep Space Exploration

The Gateway spacecraft is an important stepping-stone to exploration of the solar system, integrating commercial and international partners into a tightly coupled system, enabling cislunar activities, and implementing key technologies for missions to Mars. Autonomy is a capability area necessary to handle long communication outages where intervention from Earth is impossible, to prepare to operate with long communication delays that will be common in interplanetary travel, and to make spaceflight more affordable and accessible by reducing sustaining operations costs. The Gateway Concept of Operations states that one of Gateway’s goals is to “focus on infrastructure and systems that will allow autonomous operations aboard the Gateway with robotics, automated systems, advanced communications, and distributed computing.” Gateway’s Vehicle Systems Manager (VSM) and associated Autonomous Spacecraft Management Architecture (ASMA) are key products towards delivering autonomous capability. The primary functions of the control architecture are Mission Management and Timeline Execution, Resource Management, Fault Management, and Vehicle Control and Operation (VCO). In each of these areas, there is an initial level of capability to be delivered at launch, with plans to continue development and grow to greater capability. The initial deployment of VSM will focus on maintaining vehicle safety by focusing on full fault management capabilities and deploying only enough resource and timeline planning functionality to support that. The final deployment of VSM will add significant planning and control optimization functionality to support nominal operations for up to 21 days without ground support, even accommodating fault and failure conditions. While the VSM is the vehicle-level representation of autonomous reasoning, distributed automation is essential to provide the right scope and abstraction of information to process. Module and system support of automation and simplicity of interfaces are two important design paradigms that Gateway is focusing on to garner a systems approach to autonomy. Distribution of reasoning can increase complexity, so Gateway is also taking a strict hierarchical approach to information flow and decision making. VSM is not the only capability necessary to achieve an autonomous spacecraft. Robotics support for maintenance of the spacecraft will be essential to provide continued vehicle functionality even when crew is not present. Technical and programmatic challenges exist when implementing autonomous robotics operations. These challenges include sufficient network flexibility to support data transfer to the rest of the vehicle to coordinate module-to-module robotic walk-offs and finding the proper interfaces to allow sufficient dexterity. Communication system upgrades planned for Gateway include Delay Tolerant Networking to best utilize the complex network of relays that will be part of mature cislunar operations. Distributed computing and management will provide failure tolerance, robustness, and growth of capabilities while still allowing significant reuse of heritage software on heritage systems as well as reuse of common applications across a spacecraft to minimize new development, but this requires adherence to key standards and interfaces. The Gateway program has demonstrated significant progress towards these capabilities and has identified challenges other spacecraft developers should be aware of from the start.

Molly Anderson↗

NASA NTRSDate not supplied

Gateway Autonomy for Enabling Deep Space Exploration

Molly Anderson↗

NASA NTRSDate not supplied

Assessment of Crew Time for Maintenance and Repairs Activities for Lunar Surface Missions

NASA is currently evaluating different methods to predict how much time crewmembers will spend conducting repair and maintenance activities on future space missions. As mission scope and spacecraft architectures change, it will be necessary to understand how crew repair and maintenance timelines are impacted by mission operations and technology changes. Past work has been done using historical ISS data to accurately predict crew habitation and operation timelines, resulting in the development of NASA’s Exploration Crew Time Model (ECTM). However, understanding crew maintenance and repair requirements has posed a unique challenge due to the complexity of available datasets, the probabilistic nature of sub-system failures, and the impacts of reliability growth on failure rates. This paper presents a methodology to collect and condition empirical repair and maintenance time data from available data sets, to extrapolate from that data to estimate projected maintenance and repair times for a lunar Surface Habitat, and to assess how uncertainty in repair time could impact utilization time on the lunar surface. NASA International Space Station (ISS) maintenance and crew time data are logged into two central databases, the Maintenance Data Collection (MDC) and the Operations Planning Timeline Integration System (OPTimIS) respectively. Separately, each of these two datasets capture only portions of the complete set of data required to generate an accurate assessment of crew time spent on maintenance activities at a sub-system level. MDC provides a detailed catalog of failure events and an overview of the failure’s required maintenance and OPTimIS provides a description of crew activities and crew time durations dedicated to maintenance. To create a more useful crew time estimate for maintenance timelines, the authors developed a methodology to capture relevant data from each set and combine and utilize that data by linking crew time requirements to specific components. The authors compare the failure logs in the MDC to crew activity logs pulled from OPTimIS and then process the data to estimate required repair times for each failure event. Data is also classified by the outcome of each repair event, whether the failed component was replaced or whether it was repaired in place. The entire maintenance activity dataset is then categorized based on the class of failed component to allow for a statistically significant sample size for each class and to provide accurate crew time estimates for any components lacking relevant data. This resultant component repair time data can be used in the future to generate Mean Time To Repair (MTTR) estimates and confidence intervals for each class of component based on a probabilistic distribution of documented maintenance events. These improved MTTR values can then be applied to candidate element sub-system architectures, along with component Mean Time Between Failure (MTBF) data to generate distributions for potential required system crew repair time estimates for a given mission. Repair time distributions can then be used to develop more accurate crew schedules and to assess potential available utilization time.

Crew Time↗

NASA NTRS2003

Reduce costs with multimission sequencing and a multimission operations system

The paper will then propose extending this multi-mission philosophy to skeleton timeline development, science sequencing, and spacecraft sequencing. Finally, the paper will investigate a multi-mission approach to MOS development.

sequencing mission operations system↗

NASA NTRS1987

PLAN-IT - Knowledge-based mission sequencing

PLAN-IT (Plan-Integrated Timelines), a knowledge-based approach to assist in mission sequencing, is discussed. PLAN-IT uses a large set of scheduling techniques known as strategies to develop and maintain a mission sequence. The approach implemented by PLAN-IT and the current applications of PLAN-IT for sequencing at NASA are reported.

Biefeld, Eric W.↗

NASA NTRS2018

Evaluation of Crew-Centric Onboard Mission Operations Planning and Execution Tool: Year 2

Currently, mission planning for the International Space Station (ISS) is largely affected by ground operators in mission control. The task of creating a week-long mission plan for ISS crew takes dozens of people multiple days to complete, and is often created far in advance of its execution. As such, re-planning or adapting to changing real-time constraints or emergent issues is similarly taxing. As we design for future mission operations concepts to other planets or areas with limited connectivity to Earth, more of these ground-based tasks will need to be handled autonomously by the crew onboard.There is a need for a highly usable (including low training time) tool that enables efficient self-scheduling and execution within a single package. The ISS Program has identified Playbook as a potential option. It already has high crew acceptance as a plan viewer from previous analogs and can now support a crew self-scheduling assessment on ISS or on another mission. The goals of this work, a collaboration between the Human Research Program and the ISS Program, are to inform the design of systems for more autonomous crew operations and provide a platform for research on crew autonomy for future deep space missions. Our second year of the research effort have included new insights on the crew self-scheduling sessions performed by the crew through use on the HERA (Human Exploration Research Analog) and NEEMO (NASA Extreme Environment Mission Operations) analogs. Use on the NEEMO analog involved two self-scheduling strategies where the crew planned and executed two days of EVAs (Extra-Vehicular Activities). On HERA year two represented the first HERA campaign where we were able to perform research tasks. This involved selected flexible activities that the crew could schedule, mock timelines where the crew completed more complex planning exercises, usability evaluation of the crew self-scheduling features, and more insights into the limit of plan complexity that the crew could effectively self-schedule. In parallel we have added in new features and functionality in the Playbook tool based off of our insights from crew self-scheduling in the NASA analogs. In particular this year we have added in the ability for the crew to add, edit, and remove their own activities in the Playbook tool, expanding the type of planning and re-planning possible in the tool and opening up the ability for more free form plan creation. The ability to group and manipulate groups of activities from the plan task list was also added, allowing crew members to add predefined sets of activities onto their mission timeline. In addition we also added a way for crew members to roll back changes in their plan, in order to allow an undo like capability. These features expand and complement the initial self-scheduling features added in year one with the goal of making crew autonomous planning more efficient. As part of this work we have also finished developing the first version of our Playbook Data Analysis Tool, a research tool built to interpret and analyze the unobtrusively collected data obtained during the NASA analog missions through Playbook. This data which includes user click interaction as well as plan change information, through the Playbook Data Analysis Tool, allows us to playback this information as if a video camera was mounted over the crewmember's tablet. While the primary purpose of this tool is to allow usability analysis of crew self-scheduling sessions used on the NASA analog, since the data collected is structured, the tool can automatically derive metrics that would be traditionally tedious to achieve without manual analysis of video playback. We will demonstrate and discuss the ability for future derived metrics to be added to the tool. In addition to the current data and results gathered in year two we will also discuss the preparation and goals of our International Space Station (ISS) onboard technology demonstration with Playbook. This technology demonstration will be preformed as part of the CAST payload starting in late 2016.

onboard planning↗

NASA NTRSDate not supplied

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↗

NASA NTRS2021

Assessing Relay Communications for Mars Sample Return Surface Mission Concepts

The Mars Sample Return (MSR) Campaign would be a 3-mission campaign concept supported by NASA and ESA to return samples from the Mars surface. MSR would, for the first time ever, present a need to communicate with multiple surface assets that are co-located on Mars in a coordinated effort to accomplish the unified objective of fetching, transporting, and returning samples from Mars. Currently, Mars surface assets relay data to and from Earth using a number of orbiters in what’s known as the Mars Relay Network (MRN). This network is characterized by a small number of surface assets distributed across the Martian globe and a larger number of orbiters to provide relay services. As of June 2020, there are two surface assets for which five orbiters are providing relay. During the MSR Campaign, there would be two rovers and a lander that all would require relay communication from a small number of Mars orbiters to meet the aggressive MSR timeline. The inversion of the current MRN paradigm, a system of many surface assets requiring relay and few orbiters to provide relay, necessitates the unique challenge of optimally allocating relay passes to maximize the operational capability of all assets. The allocation must consider a large number of trade variables including Mars asset operational requirements and Earth ground system constraints, including staffing schedules, operations planning across time zones, and more. To address these telecommunication challenges, the Mars Asset Relay Mission Link Allocation Design Environment (MARMLADE) tool was developed. It is a MATLAB-based tool to assign orbiter passes or Direct-From-Earth (DFE) links to each of the three surface assets and quantify the operational efficiency of each surface asset.MARMLADE uses a data set of simulated Mars relay orbiter geometry and telecommunication capabilities provided by JPL’s Telecom Orbit Analysis and Simulation Tool (TOAST) software to compute which asset should get each pass based on a series of heuristics and predictions of all assets’ states. Within MARMLADE, the user can provide inputs including the option for time-based pass splitting, fixed FWD data rate capabilities, DFE communication capabilities, and link parameters allowing for the assessment of complex operations and hardware trades using surface mission operational efficiency as a primary figure of merit. As the MSR mission concepts continue to mature, MARMLADE is being used to assess ability of all MSR elements to meet the surface mission timeline requirements and to provide relay link allocations to each of the MSR surface assets.This paper will describe the motivation and design of the MARMLADE tool and how it is being used to perform campaign and mission level trades, generate requirements, and support development of the MSR surface mission scenarios.

Lee, Charles↗

NASA NTRSDate not supplied

Genesis Solar Wind – Capture, Return, Curate and Analyze: Looking Backward and Creating a Timeline

Introduction: In 1997 NASA’S Discovery Program selected the Genesis mission proposal to return solar wind samples to Earth for laboratory analyses. Principal Investigator Donald S. Burnett and the science team defined the purity of collector materials and ability to analyze solar wind composition to the precision required for planetary science. As a small mission, focused on a well-defined science goal, yet needing careful attention to engineering details, the communication among scientists and engineers, nurtured by Don Burnett, was exceptional. Genesis Mission and Curation Legacy: Genesis, as the first U. S. spacecraft to return astromaterial samples since Apollo, not only integrated the mission planning and flight teams, but also the science and sample curation teams during the mission development period. Since Genesis is a sample return mission, the Science Team was essential in certifying the collectors (sample containers for solar atoms). From inception, Genesis established mission funding for returned sample curation. JSC was lead in contamination control during mission preparation, including establishment of an ISO 4 cleanroom facility and use of ultrapure water (UPW) for cleaning flight hardware (and, as it turned out, for cleaning collectors after the mishap). Reliable, fast communication among scientists, engineers and curators at the hands-on level established deep respect among team members and efficient decision-making. JSC’s 50-years of astromaterial sample curation provided experienced sample processors onsite during recovery in Utah (a deep bench for emergency response). Post-recovery curation included iterative collaboration with science sample users to clean or verify cleanliness of samples. The science legacy from Genesis is addressed by Burnett and Jurewicz, this volume. In The Beginning: After Apollo sample return, Burnett and Marcia Neugebauer at JPL began discussing a solar wind sample return, with Neugebauer arguing that separate collection of solar wind regimes was essential science. By 1992 a solar wind sample return mission was presented at a workshop, and by 1994 a mission was proposed named Suess-Urey. The mission was re-proposed under a new name GENESIS and selected in 1997. Susan Niebur captured the Genesis mission history and stories, from high level management documents and from many interviews with participants [2]. Her account lets readers glimpse personality of participants in quotations from interviews. Need and Scope for Detailed Technical Timeline: A timeline constructed from lower level task documents has been initiated to document the resources and skills actually used, as well as task sequence or concurrency. Timelines for high level mission events are captured in two documents [1] [2] and for detailed re-entry events in [3]. A detailed technical timeline for Genesis mission and curation activities will provide data points for lower level tasks, such as ISO 4 curation facility construction time, preparation for nominal sample field recovery, mishap recovery, and UPW expansion. Changes in technology context 1990-2024: Semiconductor technologies were easily accessible in the U.S.A. (1990-1999), and the Genesis team used those resources for cleanroom design and UPW system expansion. Image documentation was changing from film to digital during cleanroom construction and payload cleaning (1997-2001). Engineering design was done using computer aided design proprietary software, making more difficult the archiving of payload configuration and materials. Email of documents, tracked delivery service and virtual meeting capability greatly improved communication efficiency. Information sources – Pre-launch mission preparation: Examples of mission science, engineering and contamination control are collector purity testing, payload design/fabrication and ISO 4 cleanroom construction. Information on timing of these activities comes from facility readiness reviews, management reviews, shipping documents, procurement documents, test reports, travel documents, laboratory logs, Quality Assurance documents, dates on images, participant notebooks and emails. Information sources – Sample return re-entry and field recovery activities: Information comes from event timelines produced by Mid-Air Recovery team, Lockheed team lead notes and from chase video, JPL Quality Assurance. Information also comes from images and logbooks from UTTR cleanroom operations and from curatorial documents. Information sources – Resulting science and sample cleaning processes: Agendas from the annual gatherings of the science team initially trace testing for collector purity/cleanliness, and after sample recovery, include collector cleaning and cleanliness assessment. Post-recovery documents include curatorial orders and procedures, sample allocation documents and LPSC abstracts. Timeline Objectives: A simple spreadsheet timeline with headers DATE, EVENT, PEOPLE, COMMENT, INFORMATION SOURCE has been initiated and currently has over 90 entries. While this is not definitive historical research, it is a quick look at the evolution of Genesis curation with pointers to documents or people with information. Engineers for future missions may find useful points of comparison for development of facilities. References:[1] Genesis Mission Reference Document, (2011) JPL D-62382.[2] Niebur S. M., edited by Brown D. W. (2023) NASA’s Discovery Program: The First 20 Years of Competitive Planetary Exploration, NASA-SP-2023-4238.[3] Genesis Mishap Investigation Board Report, Vol. 1 (July 2005).

solar wind↗

NASA NTRS2003

Low/Medium Density Biomass, Coastal and Ocean Carbon: A Carbon Cycle Mission

As part of the Global Carbon Cycle research effort, an agency-wide planning initiative was organized between October 2000 and June 2001 by the NASA Goddard Space Flight Center (GSFC) at the behest of the Associate Administrator for Earth Science. The goal was to define future research and technology development activities needed for implementing a cohesive scientific observation plan. A timeline for development of missions necessary to acquire the selected new measurements was laid out, and included missions for low - medium density terrestrial biomass / coastal ocean / and ocean carbon. This paper will begin with the scientific justification and measurement requirements for these specific activities, explore the options for having separate or combined missions, and follow-up with an implementation study centered on a hyperspectral imager at geosynchronous altitudes.

Esper, Jaime↗