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NASA NTRS2018

Overview of Primitive Volatile Explorer (PrOVE) Cubesat or Smallsat Concept

Here we describe the Primitive Object Volatile Explorer (PrOVE), a smallsat mission concept to study the surface structure and volatile inventory of comets in their perihelion passage phase when volatile activity is near peak. CubeSat infrastructure imposes limits on propulsion systems, which are compounded by sensitivity to the spacecraft disposal state from the launch platform and potential launch delays. We propose circumventing launch platform complications by using waypoints in space to park a deep space SmallSat or CubeSat while awaiting the opportunity to enter a trajectory to flyby a suitable target. In our Planetary Science Deep Space SmallSat Studies (PSDS3) project, we investigated scientific goals, waypoint options, potential concept of operations (ConOps) for periodic and new comets, spacecraft bus infrastructure requirements, launch platforms, and mission operations and phases. Our payload would include two low-risk instruments: a visible image (VisCAM) for 5-10 m resolution surface maps; and a highly versatile multispectral Comet CAMera (ComCAM) will measure 1) H2O, CO2, CO, and organics non-thermal fluorescence signatures in the 2-5 µm MWIR, and 2) 7-10 and 8-14 µm thermal (LWIR) emission. This payload would return unique data not obtainable from ground-based telescopes and complement data from Earth-orbiting observatories. Thus, the PrOVE mission would (1) acquire visible surface maps, (2) investigate chemical heterogeneity of a comet nucleus by quantifying volatile species abundance and changes with solar insolation, (3) map the spatial distribution of volatiles and determine any variations, and (4) determine the frequency and distribution of outbursts.

Zucherman, Aaron↗
NASA NTRS2021

High-Density Automated Vertiport Concept of Operations

The National Aeronautics and Space Administration (NASA) vision for Advanced Air Mobility (AAM) includes Urban Air Mobility (UAM) – a concept involving vertical takeoff and landing (VTOL) aircraft, decentralized (or federated) traffic management, and new infrastructure to support urban, suburban, and rural flight operations. High-density performance-based routes or corridors enable prompt transportation of people and goods from node to node, where each node represents a vertiport, defined as an identifiable ground or elevated area used for the takeoff and landing of VTOL aircraft. In the presence of uncertainty surrounding aircraft turnaround time on the ground, vertiports are the critical end points in scheduling, sequencing, and spacing (SSS) of aircraft in dense metropolitan environments. This Concept of Operations (ConOps) includes vertiports of varying sizes, configurations, service offerings, and locations. UAM air vehicles include conventional rotorcraft, unmanned VTOL aircraft, and novel piloted VTOL aircraft. This ConOps focuses on operations at a high-density vertiport, supported by a Vertiport Automation System (VAS) with high-throughput operation capabilities under conditions defined as NASA’s Urban Air Mobility Maturity Level Four (UML-4).

UAM↗
NASA NTRSDate not supplied

An Approach for Defining IASMS Services, Functions, and Capabilities

Assuring safety in the NAS with the inclusion of new entrants, such as Advanced Air Mobility (AAM), will require overcoming unique safety challenges that result from combining innovative technologies with novel airspace concepts for moving people and cargo using autonomous vehicles. The focus of the In-time Aviation Safety Management System (IASMS) is to overcome AAM’s safety assurance challenges. The IASMS Concept of Operations (ConOps) describes an interconnected set of services, functions, and capabilities (SFCs) designed to manage operational risks, identify unknown risks, and inform system designs. This paper describes an approach for defining SFCs based on technology trends in research, assessment of known and unknown risks in voluntary safety reports, and causal and contributing factors in aviation accidents and incidents. This approach would identify potential SFCs that further expand the Monitor, Assess, and Mitigate (M-A-M) functionality that represents the enabling framework of the IASMS. Safety implications that will result from integration of AAM in the transformation of the National Airspace System (NAS) were addressed in National Academies committees reports on AAM and IASMS. Development of a ConOps for IASMS was a top recommendation and can be represented as a reframing of safety assurance that builds on real-time alerting such as the Traffic Alert and Collision Avoidance System, and adds the more encompassing in-time temporal parameter in recognition of the different timelines for collecting and assessing safety data for risk mitigations. For example, mining for safety trends from data sources such as the Aviation Safety Information Analysis and Sharing system occurs over a longer time period. Research on AAM operations poses that SFCs can be designed to monitor the safety margin appropriate for AAM including with regards to the distance between current flight parameters and nominal ideal conditions. These in-time comparisons will become more complex as the density of operations increases at least in certain areas and can include planned and actual 4D trajectory, and in-time comparisons having implications on conflict modeling and prediction including expected and actual departure time, fix/waypoint crossing times, and arrival time. These comparisons would be integrated as part of SFCs that redefine and inform new safety margin. An increased safety margin improves management of operational risks while reducing the potential for anomalies. An increased safety margin also has implications for operator confidence in the certainty of its operations and trust in automation. Technology trends in research could be used to refine existing SFCs and define needs for additional SFCs that provide safety improvements to the design and operation of vehicles, airspace design, and operator performance requirements. NASA is developing innovative approaches to safeguard against major accidents and incidents that have occurred in the NAS and those anticipated with the inclusion of envisioned AAM operations. The innovations use operational performance data to monitor, detect, and predict flight variations exceeding safe nominal patterns, such as would be caused by navigational error, severe weather complications, or hijacking of UAS controls. These innovative approaches have high potential to prevent accidents and incidents in the new AAM era. It is anticipated that elements of the innovations will evolve into SFCs for the IASMS. Voluntary safety reports can be monitored to identify anomalies related to design or operational performance risks. Reports could be periodically monitored and assessed for specific topics. Reports might serve as weak signals or precursors indicative of emergent risk such as when combined with other safety information. The architecture could include SFCs that are based on voluntary safety reports recognizing the periodic temporal nature of data analysis. As previously mentioned, aviation accidents with their causal and contributing precursors can inform the need for SFCs in the IASMS. Accidents and incidents at San Francisco International Airport such as Asiana 214 and Air Canada 759 illustrate how combinations of different factors lead to increased risk. These types of precursors and different factors have implications on the types of SFCs that could be needed to monitor and manage different sources and types of design and operational risk. Continuing to assure the safety of AAM as designs and operations gain in complexity can be accompanied by defining SFCs that also increase in complexity. These SFCs can leverage information from findings and recommendations synthesized across on-going research, voluntary safety reports, and accident and incident reports. These SFCs can serve to refine accuracy of algorithms and resolve limitations with current practices. The IASMS architecture represents the framework for the SFCs and their critical role in safety assurance.

In-Time Aviation Safety Management System↗
NASA NTRSDate not supplied

Using Earth-based Operational Field Tests as High-Fidelity Analogs for Planetary Surface Exploration

NASA is preparing to land the first woman and first person of color on the Moon within the next decade and establish a permanent sustainable human presence before sending humans onto Mars. To ensure the success of these missions, NASA has performed operational testing in terrestrial, aquatic, and laboratory analog environments that simulate Lunar and Martian environmental characteristics to evaluate exploration concepts of operations (ConOps), engineering design requirements, science support needs, mission operations techniques, and crew training. Terrestrial analogs include Desert Research and Technology Studies (D-RATS), Biologic Analog Science Associated with Lava Terrains (BASALT), and Next Space Technologies for Exploration Partnerships (NextSTEP)Habitat Ground Testing. Aquatic analogs include NASA Extreme Environment Mission Operations (NEEMO) and Pavilion Lake Research Project (PLRP).Laboratory analogs include the Neutral Buoyancy Laboratory (NBL), Active Response Gravity Offload System(ARGOS), rock yards, and virtual and hybrid reality simulation environments. While no single Earth-based analog environment is perfect for simulating all characteristics of other planetary surfaces, testing across multiple locations leverages the strengths of each to provide an integrated understanding of how to best conduct real spaceflight surface exploration missions.

B A Janoiko↗
NASA NTRSDate not supplied

Using Earth-based Operational Field Tests as High-Fidelity Analogs for Planetary Surface Exploration

NASA is preparing to land the first woman and first person of color on the Moon within the next decade and establishing a permanent sustainable human presence before sending humans onto Mars. To ensure the success of these missions, NASA has performed operational testing in terrestrial, aquatic, and laboratory analog environments that simulate Lunar and Martian environmental characteristics to evaluate exploration concepts of operations (ConOps), engineering design requirements, science support needs, mission operations techniques, and crew training.

B. A. Janoiko↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

Defining Services, Functions, and Capabilities for an Advanced Air Mobility (AAM) In-time Aviation Safety Management System (IASMS)

NASA’s vision for Advanced Air Mobility (AAM) Mission is to help emerging aviation markets to safely develop an air transportation system that moves people and cargo between places previously not served or underserved by aviation. The integration of new operational paradigms and vehicle classes in this system requires a transformation of the National Airspace System (NAS) that includes substantive changes critical for assuring safety. These changes are compelled by unique challenges posed by AAM to the safety management system (SMS). These challenges were assessed by committees of the National Academies in their reports on a vision for an In-time Aviation Safety Management System (IASMS) and a blueprint for AAM [1,2]. In their description of an IASMS, the top recommendation was development of a concept of operations (ConOps) for IASMS. This paper describes the high-priority recommendations from the National Academies for its IASMS vision and how they are addressed through a distributed system-of-systems architecture. The IASMS architecture is structured on the services, functions, and capabilities (SFCs) necessary for In-time System-wide Safety Assurance (ISSA)initially developed for urban air mobility (UAM). The paper then posits where these SFCs would reside across vehicles, airspace, or service suppliers such as Supplemental Data Service Providers (SDSPs), and how SFCs scale with increasing complexity in design and operations of AAM. SFCs are foundational building blocks for a system that targets an individual or family of risks using a Monitor-Assess-Mitigate risk paradigm for anomalies, precursors and trends. An IASMS could be conceived that uses a portfolio of SFCs for AAM in general or prioritizes SFCs for a specific domain or operation.

K Ellis↗
NASA NTRSDate not supplied

An Approach for Identifying IASMS Services, Functions, and Capabilities From Data Sources

Assuring safety in the NAS with the inclusion of new entrants that are part of Advanced Air Mobility (AAM) will require overcoming unique safety challenges that result from combining innovative technologies with novel airspace concepts for moving people and cargo using semi-autonomous/autonomous vehicles. Overcoming these AAM safety assurance challenges is the focus of the In-time Aviation Safety Management System (IASMS). The IASMS Concept of Operations (ConOps) describes an interconnected set of services, functions, and capabilities (SFCs)designed to manage operational risks, identify unknown risks, and inform system design to mitigate risk. This paper describes a broad approach for identifying SFCs involving technology trends in research, assessment of known and unknown risks in safety reports, and causal and contributing factors in aviation accidents and incidents. This approach leverages these sources to identify potential SFCs that enable the Monitor, Assess, and Mitigate (M-A-M)functionality that represents the enabling framework of the IASMS.

Kyle Ellis↗
NASA NTRSDate not supplied

Evolving the Design of a Volcanic Monitoring UAS over Several Flight Campaigns

A multi-organization effort has been underway for several years to develop and validate the use of small unmanned aircraft systems (UAS) for volcanic monitoring. The overall goal is to develop the aircraft, supporting systems, concept of operations, scientific payloads and regulatory framework to allow regular and reliable sampling in challenging and dynamic atmospheric conditions around volcanic summits. Central to this effort has been the development and refinement of the “S2” aircraft, which contains a tightly integrated system consisting of the airframe, avionics, and payload sensors specifically designed to measure atmospheric properties around volcanic plumes. The aircraft has a 3-meter wingspan and can carry a 2.3 kg payload for up to 100 km while operating at altitudes up to 6,000 m. To date, the system has been flown in Costa Rica to sample CO2 gases around Turrialba Volcano (Costa Rica), in Hawaii to assess the 2018 eruption of Kīlauea with several different sensors, and is currently planned for deployment in Alaska for gas sampling and photogrammetry at Makushin Volcano. Before and after each deployment, all aspects of the system and concept of operations (CONOPS) were extensively examined and modified to improve the safety and performance. This has culminated in the upcoming deployment which will fly up to 30 km - beyond visual line of sight for the first time. This expansion of the operational range through additional safety features and redundancy will pave the way for monitoring and accessing areas that were previously very difficult to reach from both a technical and regulatory perspective. These developments can be extended to a variety of missions requiring UAS for atmospheric sampling, specifically ones that would benefit from beyond visual line of sight operations or flights into harsh or difficult atmospheric environments.

UAS↗
NASA NTRSDate not supplied

CLINICAL DECISION SUPPORT: PATH TO FUNCTIONAL REQUIREMENTS

Long-duration, deep-space exploration missions present significant challenges to crew health and performance. These challenges include the individual and combined effects of microgravity, radiation exposure, isolation, limited resources (mass, volume, power, data and crew time), limited options for evacuation and those associated with delayed or constrained communications, all of which demand greater crew autonomy. Specifically, as the communication delays intensify the further we explore space, the unqualified need for Earth-independent medical operations focused on autonomous diagnosis, treatment and prevention will be key to mission continuation and success. To augment the requisite knowledge, skills and abilities (KSAs) of a time-constrained crew operating under stressful conditions, combatting fatigue, and facing a potential medical crisis, a robust clinical decision support system (CDSS) is a probable solution that would facilitate, guide and inform Earth-independent medical operations, while assisting crewmembers through various clinical presentations. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) is expanding the boundaries of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit. ExMC is actively identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses gap Medical-701 within the Inflight Medical Conditions risk: “Enhance medical capabilities within an exploration medical system.” Though mass, volume, and power will face increasing constraints, the projected computational capabilities of spacecraft systems will increase exponentially as information technology continues to advance this decade and beyond. Hence, data, software and computational resources will play an essential and synergistic role in maintaining crew health, wellness and performance in deep space missions. The focus of the CDS project is to develop recommended requirements for an in-vehicle CDSS that acts as a ‘virtual assistant’ for delivering optimal health, performance and medical care during exploration missions. The CDSS is envisioned as an integrated, software-based tool deployed on a laptop computer or handheld device. The CDSS will assist the crew and ground support when interacting with knowledge/databases (e.g. records, pharmacy, schedule), instrumentation (e.g. imaging, physiological monitoring devices), and habitat (e.g. wellness system, task performance system) and vehicle systems (e.g. environmental system, communication system). In addition, the human interface will employ a context-based approach that accounts for the crew’s situation. Thus, extraneous and clinically/operationally non-relevant information are reduced to avoid an increase in cognitive load. The framework of an ideal spaceflight CDSS is to include core and advanced analytical features that incorporate work from collaborators yet maintain a flexible platform for integrating new technology in the future. In fiscal year 2021 (FY21), the CDS project identified requirements through two primary mechanisms: (i) the development of software implementation prototypes and (ii) the application of systems engineering processes. The CDS project developed and tested a series of increasingly complex system prototypes that were based on use cases derived from the CDSS concept of operations (ConOps). These software implementations yielded insights on CDSS functionality as well as lessons learned that provided the initial requirements for CDSS capability. By applying a systems engineering (SE) approach, medical scenarios provided in the ConOps and the use cases for software implementation underwent functional decomposition to identify CDSS functionality. Also, systems-based modeling language (SysML) tools such as activity diagrams were developed from the same ConOps and use cases to identify CDSS functionality. The lessons learned from software implementation defined both specific requirements and broad areas of requirements. Within these defined broad requirement areas, further analysis of the SE products identified specific capability that resulted in the final functional requirements. In summary, the software prototypes, functional decomposition of the ConOps and use cases, and SysML diagrams provided the basis for the CDSS requirements developed in FY21. In the upcoming year, these requirements will be refined for their final ExMC baseline review in latter FY22.

clinical decision support↗
NASA NTRSDate not supplied

Implementation of a SysML Model-Based Concept of Operations for Level of Care IV: Long-Duration Lunar Orbital and Surface Operations

One goal of the Human Research Program (HRP) Exploration Medical Capability (ExMC) Element Systems Engineering (SE) team is to define the technical system needed to support crew medical system capabilities for future exploration missions, including orbital and surface operations for long duration lunar missions. This is accomplished through the development of a Medical System Foundation, which communicates medical system requirements, capabilities, conditions, and resources that define a starting point for a medical system that meets the specification for design reference missions and associated Levels of Care (as defined by NASA-STD-3001). The starting point for creating this Medical System Foundation Model is the development of a Concept of Operations (ConOps) that describes the operation of the system from the point of view of the users. It includes a comprehensive and thoroughly vetted list of the users, their specific needs, the goals of the system, key assumptions about the system, and definitions of the system’s operational environments. The use case scenarios included in the ConOps illustrate required medical system capabilities for Level of Care IV and enable the ExMC SE team to develop integrated medical system requirements and identify capabilities required to meet those requirements. For this “Long Duration” Medical System Foundation development effort, ExMC replaced the traditional document-based ConOps with a model-based ConOps using model-based systems engineering. This approach has several advantages, including the facilitation of more efficient understanding of the material through information-dense images with less opportunity for misinterpretation than text alone, the roll-out of changes to the ConOps to stakeholders in real-time as they are approved, and the consolidation of all salient information into one centralized location. This discussion will focus on both how the model represents the ConOps content and how the SE team utilized lessons learned in an agile environment to improve the way this information was created and presented to stakeholders.

M Kaetzer↗
NASA NTRSDate not supplied

A Model-Based Systems Engineering Evaluation of the Evolution to an In-Time Aviation Safety Management System

In 2018, as result of a recommendation from the National Academies, NASA began to prototype an In-Time Aviation Safety Management System (IASMS). The purpose of the IASMS is to enable innovative aviation operations and greater heterogeneity of the overall National Airspace (NAS) by automating much of the safety monitoring, assessment, and risk and hazard mitigation function present in today’s Safety Management Systems (SMS). NASA has worked together with early industry collaborators to understand how such a system might work and has published several early Concepts of Operation (ConOps) and other technical memoranda that illustrate the primary considerations for selected aviation domains. The shift from an SMS to an IASMS is predicated on several assumptions, including: 1.) automating safety functions will decrease the amount of time necessary for risk and hazard identification and analysis, making it more likely that safety concerns are understood ‘in-time’ to mitigate them, and 2.) an IASMS will allow easier tailoring of safety management processes to the particular risks and hazards inherent to that aviation operation. In this paper, we begin to validate these assumptions through the use of Model-Based Systems Engineering (MBSE).

IASMS↗
NASA NTRSDate not supplied

Validation of Fitness for Duty Standards Using Pre- and Post-Flight Capsule Egress and Suited Functional Performance Tasks in Simulated Reduced Gravity (Pilot Egress Fitness)

As NASA prepares for exploration missions, it will be critical to understand and build upon known crew capabilities. Specifically, we need to know the functional capacities of crew at different stages of a mission and characterize these profiles so that the appropriate vehicle requirements and mission concepts of operations (ConOps) can be developed. One of the most complex phases of any missions is when there is a transition between gravity environments. For instance, both physiological adaptation to microgravity and subsequent re-entry into a gravity environment result in reduced functional capacity, even with rigorous adherence to inflight countermeasures. Quantification of the astronauts’ post-landing functional performance is necessary to design ConOps for exploration missions. Specifically, these two high-risk tasks may have to be performed soon after gravity transitions: •Unassisted capsule egress task after return to Earth •Planetary extravehicular activity (EVA) soon after landing on Mars or the Moon This study has been broken down into two phases. A pilot phase to assess the overall feasibility and demonstrate the capability to do these tasks shortly after landing and the full Egress Fitness study, which will be part of the CIPHER complement. This study uses a functional task approach to characterize performance of these high-risk tasks in long-duration ISS crewmembers before flight and shortly after return to Earth. Prior to any testing, each astronaut subject completes a suit fit check to ensure adequate sizing and mobility to be able to complete the EVA tasks. Pilot Egress Fitness pre-flight and post-flight testing includes an Earth based emergency egress out of a functional capsule mockup, and a short Mars gravity EVA simulation including suit donning, hatch egress, ladder descent, task board cable operations, baggage transfer over sand/rocky regolith, alignment with a rear entry port, and suit egress. Pre-flight testing can occur almost anytime pre-flight, but post-flight scheduling is much more critical with the capsule egress test occurring 1-4 hours after landing and the planetary EVA approximately 18-36 hours after landing. Data collected for both tasks includes task completion time, photo, and video. The EVA portion also includes collection of metabolic and heart rate. Pilot Egress Fitness study has completed baseline pre-flight testing on 3 astronaut subjects. Post-flight testing of the first two subjects will be completed in November 2021 and the final subject around March 2022. Results and lessons learned from this pilot study will inform the full Egress Fitness study, which will incorporate additional pre-flight sessions, longer EVA tasks, and post-flight testing on R+1, 4, and 7 to characterize the timeframe of recovery

J R Norcross↗
NASA NTRS2021

Concept of Operations for OSIRIS-REx Optical Navigation Image Planning

Optical navigation (OpNav) is a critical subsystem of the OSIRIS-REx asteroid sample return mission, which operated in the vicinity of near-Earth asteroid (101955) Bennu from August 2018 through April 2021. A substantial amount of mission resources across multiple subsystems and institutions is required to ensure that the OpNav data are successfully acquired. The KinetX OpNav team, part of the Flight Dynamics System (FDS), is responsible for performing required analysis to develop the OpNav operations plans; requesting, reviewing and verifying the plans; and ultimately using the image data for critical navigation operations. The FDS team, responsible for the mission navigation, is operated by KinetX Aerospace with management and operations support from NASA’s Goddard Space Flight Center. The Science Processing and Operations Center (SPOC), located at the University of Arizona’s Lunar and Planetary Laboratory, is responsible for generating the planning products for all science and most OpNav data. These plans are integrated into the spacecraft sequences, tested, and commanded by the Mission Support Area (MSA) at Lockheed Martin Space. To ensure mission-critical navigation image data are successfully acquired, the plan is developed through a waterfall of planning cycles over the course of 3 months prior to onboard plan execution. During the initial strategic planning for a mission phase, detailed analysis is performed by the OpNav team to conceptualize the concept of operations (ConOps) for image data collection. This phase OpNav Narrative is included along with other strategic planning documents for the key ground segment stakeholders to review and provide feedback. The detailed OpNav plans get defined in the tactical planning cycle, which spans 8 to 3 weeks before the week-long integrated sequence is executed on-board the spacecraft. During the tactical cycle, the initial OpNav Request is submitted along with the science requests, kicking off development of the science and OpNav plans. Once the initial plan is drafted, interfaces are exercised so that the plan can be reviewed and iterated, if necessary. A rigorous schedule is followed by the planning teams during the implementation cycle, spanning the last 18 days before uplink, to ensure all the necessary integration, testing, and reviewing can occur on time. The development of the OpNav planning ConOps, including responsibilities, interfaces, timelines, and procedures, took extensive collaboration across mission elements and institutions. The process was robust throughout the 137 weeks of continuous Optical Navigation Operations at Bennu, which concluded on April 9th, 2021.

Coralie D. Adam↗
NASA NTRSDate not supplied

Clinical Decision Support: Path to Functional Requirements

Long-duration, deep-space exploration missions present significant challenges to crew health and performance. These challenges include the individual and combined effects of microgravity, radiation exposure, isolation, limited resources (mass, volume, power, data and crew time), limited options for evacuation and those associated with delayed or constrained communications, all of which demand greater crew autonomy. Specifically, as the communication delays intensify the further we explore space, the unqualified need for Earth-independent medical operations focused on autonomous diagnosis, treatment and prevention will be key to mission continuation and success. To augment the requisite knowledge, skills and abilities (KSAs) of a time-constrained crew operating under stressful conditions, combatting fatigue, and facing a potential medical crisis, a robust clinical decision support system (CDSS) is a probable solution that would facilitate, guide and inform Earth-independent medical operations, while assisting crewmembers through various clinical presentations. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) is expanding the boundaries of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit. ExMC is actively identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses gap Medical-701 within the Inflight Medical Conditions risk: “Enhance medical capabilities within an exploration medical system.” Though mass, volume, and power will face increasing constraints, the projected computational capabilities of spacecraft systems will increase exponentially as information technology continues to advance this decade and beyond. Hence, data, software and computational resources will play an essential and synergistic role in maintaining crew health, wellness and performance in deep space missions. The focus of the CDS project is to develop recommended requirements for an in-vehicle CDSS that acts as a ‘virtual assistant’ for delivering optimal health, performance and medical care during exploration missions. The CDSS is envisioned as an integrated, software-based tool deployed on a laptop computer or handheld device. The CDSS will assist the crew and ground support when interacting with knowledge/databases (e.g. records, pharmacy, schedule), instrumentation (e.g. imaging, physiological monitoring devices), and habitat (e.g. wellness system, task performance system) and vehicle systems (e.g. environmental system, communication system). In addition, the human interface will employ a context-based approach that accounts for the crew’s situation. Thus, extraneous and clinically/operationally non-relevant information are reduced to avoid an increase in cognitive load. The framework of an ideal spaceflight CDSS is to include core and advanced analytical features that incorporate work from collaborators yet maintain a flexible platform for integrating new technology in the future. In fiscal year 2021 (FY21), the CDS project identified requirements through two primary mechanisms: (i) the development of software implementation prototypes and (ii) the application of systems engineering processes. The CDS project developed and tested a series of increasingly complex system prototypes that were based on use cases derived from the CDSS concept of operations (ConOps). These software implementations yielded insights on CDSS functionality as well as lessons learned that provided the initial requirements for CDSS capability. By applying a systems engineering (SE) approach, medical scenarios provided in the ConOps and the use cases for software implementation underwent functional decomposition to identify CDSS functionality. Also, systems-based modeling language (SysML) tools such as activity diagrams were developed from the same ConOps and use cases to identify CDSS functionality. The lessons learned from software implementation defined both specific requirements and broad areas of requirements. Within these defined broad requirement areas, further analysis of the SE products identified specific capability that resulted in the final functional requirements. In summary, the software prototypes, functional decomposition of the ConOps and use cases, and SysML diagrams provided the basis for the CDSS requirements developed in FY21. In the upcoming year, these requirements will be refined for their final ExMC baseline review in latter FY22.

Clinical decision support↗
NASA NTRSDate not supplied

Implementation of a SysML Model-Based Concept of Operations for Level of Care IV: Long-Duration Lunar Orbital and Surface Operations

One goal of the Human Research Program (HRP) Exploration Medical Capability (ExMC) Element Systems Engineering (SE) team is to define the technical system needed to support crew medical system capabilities for future exploration missions, including orbital and surface operations for long duration lunar missions. This is accomplished through the development of a Medical System Foundation, which communicates medical system requirements, capabilities, conditions, and resources that define a starting point for a medical system that meets the specification for design reference missions and associated Levels of Care (as defined by NASA-STD-3001). The starting point for creating this Medical System Foundation Model is the development of a Concept of Operations (ConOps) that describes the operation of the system from the point of view of the users. It includes a comprehensive and thoroughly vetted list of the users, their specific needs, the goals of the system, key assumptions about the system, and definitions of the system’s operational environments. The use case scenarios included in the ConOps illustrate required medical system capabilities for Level of Care IV and enable the ExMC SE team to develop integrated medical system requirements and identify capabilities required to meet those requirements. For this “Long Duration” Medical System Foundation development effort, ExMC replaced the traditional document-based ConOps with a model-based ConOps using model-based systems engineering. This approach has several advantages, including the facilitation of more efficient understanding of the material through information-dense images with less opportunity for misinterpretation than text alone, the roll-out of changes to the ConOps to stakeholders in real-time as they are approved, and the consolidation of all salient information into one centralized location. This discussion will focus on both how the model represents the ConOps content and how the SE team utilized lessons learned in an agile environment to improve the way this information was created and presented to stakeholders.

Mary Susan Kaetzer↗
NASA NTRSDate not supplied

A Notional Artemis Lunar Surface Exploration Package (ArLSEP) based on the Gandalf Staff Platform

Introduction: The Artemis program is planning to deliver crew and cargo to the lunar surface, but there is no current package for supporting lunar in-struments and experiments similar to the Apollo Lunar Surface Exploration Package (ALSEP). This abstract provides a possible concept for such a package using the Gandalf Staff Platform as a common core. Gandalf Staff: The Gandalf Staff is an early prototype system developed over FY’21/FY’22 using NASA Science Technology Mission Directorate (STMD) Center Information Fund (CIF) grants to de-sign, build and test “proof-of-concept” components. These components include a 24v battery powered monopole that powers a suite of subsystems, including a Graphical User Interface (GUI) for crew, surface voice and data communications, Lunar Search and Rescue (LunaSAR) navigation and communications, LiDAR, field site external lighting, 360-degree camera, and a geothermal instrument for measuring sub-surface temperature gradient. The staff can be carried independently by an Extra-Vehicular Activity (EVA) astronaut, or can be mounted into a tripod for “hands free” support at a surface site being investigated. The staff can be attached to an external solar array and power storage system for long-duration operations. [1,2] ALSEP: An ASLEP flew on each mission Apollo 12 to Apollo 17. For Apollo 11, a simplified packaged called the Early Apollo Scientific Experiments Pack-age (EASEP) was flown. Each package included a “Central Station” that provided the power and communications connected to a variety of instruments and sensors. The power was provided by a Radioisotope Thermoelectric Generator (RTG) fueled by Plutoni-um-238 generating 70 watts of power (initially, decayed over time) [3]. The communications system provide for direct to Earth data transfer from the lunar surface. Each pack-age was stowed externally in the Lunar Module (LM) Scientific Equipment (SEQ) bay with a mass up to 163 kg (Apollo 17). The crew unloaded the ALSEP from the LM and deployed the instruments on the lunar surface. Although designed to operate for only 1 year, many sites operated for up to 8 years successfully [4]. The Active Seismic Experiment (ASE) included 3 geophones for detecting seismic waves created by mortars and thumpers deployed by the crew. Other active experiments measured the lunar atmosphere, the heat flow in the subsurface, the lunar gravity and potential gravity waves, the lunar magnetic field, the solar wind and plasma interactions in cislunar space. Passive experiments included collectors for dust and cosmic rays, and retroreflectors for precise measurements of distance using a laser from Earth. The ALSEP program continues to generate insights into lunar formation and evolution. ArLSEP Concepts: The lunar surface science package for the Artemis program will hopefully exceed the capability of the ALSEP. There are multiple issues for discussion leading to the design of a new ArLSEP, needing requirements definition from the science community, NASA mission architecture, and NASA budget planners. 1. Delivery Mechanism Two possible projects currently provide capability to deliver scientific cargo to the lunar surface: 1) the Commercial Lunar Payload Services (CLPS) [5] and the Human Landing System (HLS) [6, 7]. Each project is controlled by a different organization within NASA and budgeted with different criteria although both support lunar exploration. The HLS system delivers crew (and potentially cargo) to human landing sites. If an ArLSEP is “predeployed” to such a site, the design must include power (either from the vehicle or independently) to keep the electronics functioning until deployed by the crew. If an ArLSEP is delivered on a vehicle after the crew is present on the lunar surface, safety protocols require adequate distance from the humans for impact from descent propelled sur-face regolith ejecta. This distance can not exceed the capability of the crew to walk (if no rover) to the vehicle for ArLSEP deployment. 2. Overall Guidelines The general design of ArLSEP will likely follow the ALSEP with a common system for communications and power; however, significant architecture differences between Apollo and Artemis exist. Power: The RTG will not be available for early Artemis missions nor likely follow-on Lunar Exploration Transportation Services (LETS) missions [8]. Thus, ArLSEP power must be supplied by solar arrays with sufficient battery capability to “keep alive” necessary electronics during any lunar surface eclipse period. Communication: The Artemis program is developing a series of communications satellites for lunar orbit to provide surface transmission of data and voice to Earth. Called “LunaNET”, this network is component useful for ArLSEP since south polar locations may not always have direct “line-of-sight” to Earth [9]. 3. Concept of Operations (ConOps) The general ConOps for ArLSEP is to deliver the package to lunar surface before the crew arrives, and then have the crew deploy the package after some period of time. This requires coordinated design (for power systems) and launch window (for schedule) on both the cargo and crew missions. Once the ArLSEP is deployed, it will operate autonomously for a number of years. It should be designed to be EVA compatible for crew maintenance and upgrade. 4. Notional Design (for discussion purpose only) The landing site near the South Pole is expected to have no eclipse cycle exceeding 5 days, so the “keep alive” power is 144 hours (6 days to include margin). A 12v ArLSEP will use rechargeable LiFePO4 cells, which are common in the Electric Vehicle (EV) industry. With a current of 5 amps and a 125 watt system, the mass is about 90kg. The comm. system and structure adds another 10kg, thus the “Central Station” is approximately 100kg. The solar power is collected on four arrays (each 2m above the surface), and the entire ArLSEP is designed to stow in a 2m x 1m x 1m volume. The experiment and instrument design will vary for each installation and add mass to the total (although they are expected to fit within the 2m3 volume). Seismic wave generation will likely not be provided with mortars, thus an electric “thumper” will be required. Active instruments such as imaging systems and sensing instruments will benefit from the additional power and communication capability provided by ArLSEP. Passive systems such as retroreflectors, witness plates, and cosmic dust collectors can be added to either the landing vehicle and/or the ArLSEP. With repeated HLS missions to the same human site, the ArLSEP can be expanded and easily maintained for long duration science collection on the lunar surface.

ALSEP↗
NASA NTRSDate not supplied

Crew Performance Support System to Aid in Anomaly Resolution: Concept of Operations

As missions progress into deep space, communication delays and disruptions will disenable the crew’s reliance on Earth experts. There are also limitations in the amount of data that can be downlinked to the ground. It is prudent to assume that critical, complex vehicle or habitat sub-systems will malfunction at a time when a lunar or Mars’ crew cannot rely on the Earth-Support team to detect, diagnose and resolve the problem and it is impractical to expect a small crew to step-in with the same level of expertise as 50+ authorities. The crew will need novel processes and advanced technological support to independently identify and resolve safety- and time-critical anomalies. That a self-reliant crew is unable to respond appropriately to time-critical anomalies is a significant risk to crew safety and mission success. This risk is driven by several factors; novel and unanticipated anomalies would not have been trained pre-flight, the crew could forget their pre-flight training or spaceflight stressors could impair the crew’s problem-solving ability. At last year’s IWS, Beard reported that a single spaceflight stressor (elevated CO2) could undermine the crew’s ability to independently respond to emergencies. Concept of Operations (ConOps) provide a common view of future system functions to all stakeholders. For the current project, a ConOps was developed that describes the operational processes, practices and capabilities needed by a crew of astronauts on deep space missions to autonomously respond to anticipated and unanticipated anomalies. It is crucial to recognize that, as of August 2018 existing technologies are unable to effectively support crew anomaly response to unanticipated events. “Intelligent technology” has not reached a maturity level that permits generalizing a solution to novel situations. For example, to train intelligent technology requires volumes of data that do not exist. The complexities involved in a manned mission to Mars cannot be compared to sending rovers to Mars using scripted software. This ConOps proposes a Crew Performance Support System (CPSS) that will push NASA and its industry partners toward what will be required for a safe and successful manned mission to Mars. Anomaly resolution during a deep space mission will take place within a dynamic, or changing, context. The figure to the left shows five broad contextual variables: the organizational culture, mission context, system characteristics, team characteristics and individual characteristics. The yellow arrow indicates that spaceflight and task-related stressors can affect system, team and individual crewmember characteristics and therefore anomaly response potential. The figure depicts a protective umbrella of Human-System Integration (HSI) principles that should be instituted during CPSS development including a balanced workload, shared situation awareness and building an appropriate level of trust in the automation. The figure also depicts two interrelated and cooperative components, an HSI Data System and other Enabling Capabilities will be required to support crew anomaly response and Earth-Support situation awareness. As we journey from ISS to Gateway to Mars, multiple, simultaneous and integrated research and development efforts (i.e., support systems co-evolution) must be implemented to meet the problem-solving challenges a self-reliant crew will face on a Mars’ mission. The crossovers between the capabilities are just as important as the discrete capabilities themselves. As the capabilities mature, the lines between the support subdomains will blur and an integrated system will emerge. The ConOps summarizes current knowledge about how highly trained people solve anomalies in safety- and time-critical situations, describes a group of capabilities that could help to reduce the extant risk and documents requirements levied on additional systems that provides critical inputs to the CPSS. Scenarios are used to promote a shared understanding of processes, practices and technological goals needed for safe and productive manned missions beyond LEO.

HSIA risk↗