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The NASA Earth Science Applied Sciences Disasters Program: Making EO Data and Expertise Available through the Disasters Mapping Portal to Inform Decision-Makers throughout the Disaster Cycle

The NASA Earth Science Applied Sciences Disasters Program promotes the use of Earth Observations (EO) to inform disaster risk reduction and resilience throughout the disaster cycle, from local to global scales, by harnessing NASA science and technology capabilities, through engagement with end users to demonstrate the value and impact of EO to support decision-making, and by supporting end users in their use of EO in decision-making while developing relationships to grow as a trusted source of relevant science and useful results. Through the NASA Earth Science Applied Sciences Disasters Program Mapping Portal, an Esri-backed hub of geospatially enabled disaster products, event-based and near-real-time products are hosted to provide end users with analysis-ready data and data services, keeping in mind their expressed EO needs. In this presentation, case studies of past events will be highlighted, showcasing how EO data and services were provided by the Program and utilized by end users during the disaster cycle. Additionally, this presentation will highlight some of the Program’s ongoing collaboration activities to assist end users in understanding and preparing for utilization of EO data from the Mapping Portal to inform their decision-making throughout the disaster cycle. Ongoing efforts to advance the science provided by the Program on the Mapping Portal through new developments and capabilities will be highlighted, and common challenges and data needs end users often encounter when using EO data and our Program’s innovative solutions to these challenges will be addressed. Furthermore, this presentation will touch on the challenges faced and the solutions created by the Mapping Portal team in managing and hosting a plethora of EO data for end users across various disciplines.

Ronan Lucey↗

Increasing the Uptake of Ecological Model Results in Policy Decisions to Improve Biodiversity Outcomes

Models help decision-makers anticipate the consequences of policies for ecosystems and people; for instance, improving our ability to represent interactions between human activities and ecological systems is essential to identify pathways to meet the 2030 Sustainable Development Goals. However, use of modeling outputs in decision-making remains uncommon. We share insights from a multidisciplinary National Socio-Environmental Synthesis Center working group on technical, communication, and process-related factors that facilitate or hamper uptake of model results. We emphasize that it is not simply technical model improvements, but active and iterative stakeholder involvement that can lead to more impactful outcomes. In particular, trust- and relationship-building with decision-makers are key for knowledge-based decision making. In this respect, nurturing knowledge exchange on the interpersonal (e.g., through participatory processes), and institutional level (e.g., through science-policy interfaces across scales), represent promising approaches. To this end, we offer a generalized approach for linking modeling and decision-making.

Biodiversity-ecosystem function relationships↗

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↗

Ground-Based Automated Scheduling for the Mars 2020 Rover

The Mars 2020 Rover Mission will be using an automated ground-based scheduling system called Copilot to schedule the rover’s activities at landing. Using automated scheduling technology will allow for plans to be generated more quickly. Because automated scheduling tools have not been widely used for prior rover missions, developing users’ trust in the system is crucial. An explainable scheduling tool called Crosscheck has been developed to visualize the creation of a schedule, and to explain why activities failed to schedule given their constraints. This will allow science planners to change activity constraints to allow failed activities to successfully schedule, achieving their science goals.

Towey, S.↗

Using Explainable Scheduling for the Mars 2020 Rover Mission

Understanding the reasoning behind the behavior of an auto- mated scheduling system is essential to ensure that it will be trusted and consequently used to its full capabilities in critical applications. In cases where a scheduler schedules activities in an invalid location, it is usually easy for the user to infer the missing constraint by inspecting the schedule with the in- valid activity to determine the missing constraint. If a sched- uler fails to schedule activities because constraints could not be satisfied, determining the cause can be more challenging. In such cases it is important to understand which constraints caused the activities to fail to be scheduled and how to al- ter constraints to achieve the desired schedule. In this pa- per, we describe such a scheduling system for NASA’s Mars 2020 Perseverance Rover, as well as Crosscheck, an explain- able scheduling tool that explains the scheduler behavior. The scheduling system and Crosscheck are the baseline for oper- ational use to schedule activities for the Mars 2020 rover. As we describe, the scheduler generates a schedule given a set of activities and their constraints and Crosscheck: (1) provides a visual representation of the generated schedule; (2) analyzes and explains why activities failed to schedule given the con- straints provided; and (3) provides guidance on potential con- straint relaxations to enable the activities to schedule in future scheduler runs.

Chien, Steve↗

NASA’s Strategic Analysis Cycle 2021 (SAC21) Human Mars Architecture

[Note: this is the presentation for a companion paper with the following abstract] The National Aeronautics and Space Administration’s (NASA) Mars Architecture Team (MAT) was challenged to develop a mission architecture capable of transporting humans to the surface of Mars and back as fast—and as soon—as practical. This challenge represented a significant departure from previous approaches that minimized Earth-launched mass and maximized in-space transportation efficiency, often resulting in roundtrip missions of three years or more in duration. In the interest of crew health, MAT’s cross-Agency team of subject matter experts was challenged to develop an architecture capable of shortening crew time away from Earth to about two years. MAT was given specific mission constraints, such as number of crew, as well as mandates to minimize surface infrastructure as much as possible and to incorporate nuclear transportation options. The resulting MAT-developed concept, referred to here as the Strategic Analysis Cycle 2021 (SAC21) architecture, leverages Artemis elements and emerging commercial capabilities for cargo and logistics launches, and features a hybrid Nuclear Electric Propulsion (NEP)/Chemical transportation system able to complete the 1.8 billion kilometer round-trip journey to Mars and back in 760 to 850 days transit time for the 2039 Earth departure opportunity. Three Mars Descent Systems (MDS), each capable of landing about 25 metric tons of useful cargo on the surface of Mars, would be pre-deployed in advance of crew departure from Earth; two of these MDS’s would deliver a partially fueled Mars Ascent Vehicle (MAV), a fission power system, surface mobility, and additional MAV propellant. To minimize surface infrastructure, only two of the four Mars crew would descend and live in an MDS-landed pressurized rover, exploring the martian surface for 30 martian days, or sols, before returning to Mars orbit aboard their MAV and rejoining the other two crew on the Deep Space Transport for the Earth return voyage. Specifics of many of these architecture elements are detailed in separate technical publications; this paper outlines the end-to-end integrated architecture performance and concept of operations, including synergies with Artemis lunar architecture elements. It is important to note that NASA does not have a formal human Mars program and no decisions have been made; the architecture described here is intended to fill in an often-overlooked corner of the trade space, helping to complete the menu of options available to decision-makers as they chart the course for humans to Mars. Note: Slide 9 contains a ~2 min video, best viewed when downloaded. Once downloaded to begin video you may be requested to hit options and Trust this document.

Long-duration spaceflight↗

AAM NC ATI TechTalk - Aerograph Architecture v1

Aerograph is NASA’s data management system for Advanced Air Mobility. Its mission is to support AAM research by providing a reliable and secure system that collects, stores, protects, and shares AAM data. Its vision is to provide a system that AAM research scientists, aerospace engineers, data scientists, and analysts trust for obtaining NC data and performing key analyses. The types of data Aerograph manages involves data related to flight test events, including: Aircraft Performance and Characterization (e.g., position reports) Airspace (e.g., operation intent, waypoints, and constraints) Environment (e.g., surface and wind weather) Infrastructure (e.g., surveillance coverage) Derivative Analytical Artifacts (e.g., glide path performance chart, 3D position chart, Integrated Data Product)

Aerograph↗

Risk of Performance and Behavioral Health Decrements Due to Inadequate Cooperation, Coordination, and Psychosocial Adaptions within a Team

The Risk of Performance and Behavioral Health Decrements Due to Inadequate Cooperation, Coordination, Communication, and Psychosocial Adaptation within a Team (the Team Risk) is primarily performance-focused, with a secondary emphasis on behavioral health outcomes resulting from team performance and interpersonal interactions. Monitoring tools, measures, and countermeasures are aimed at enhancing team processes and team composition configurations to optimize team performance and functioning. Long-duration exploration missions (LDEMs) will include major challenges that could affect team performance, including social isolation, physical confinement, a small and diverse crew, communication delays between crew and ground, limited or no crew rotation or evacuation options, limited or no resupply, and a high-consequence environment. Each of these conditions will affect the crew’s coordination, cooperation, psychological well-being, and performance. Although the International Space Station (ISS) remains important for studies that require spaceflight testing and validation, the current conditions on the ISS do not adequately mimic the exploration environment that is required for National Aeronautics and Space Administration (NASA) teams research, and thus access to terrestrial or ground-based analogs of LDEM conditions is paramount. The emphasis on analogs for research is reflected in this updated evidence review of the Team Risk, and includes data from studies conducted at isolated, confined, extreme (ICE) environments (e.g., Antarctic stations), and from several mission simulation analogs such as the Human Exploration Research Analog (HERA) (HERA Experiment Information Package, 2014), also known as isolated, confined, controlled (ICC) environments. These studies have characterized many team factors regarding LDEMs, and the Team Risk has now matured from risk characterization to focusing more on countermeasure development. Because spaceflight evidence for team-level research is lacking, no reliable data is available to quantify the impact of team-level variables on individual and team-level outcomes during spaceflight missions. Until recently, no systematic attempt had been undertaken to measure the performance effects of team cohesion, team composition, team training, or team-related psychosocial adaptation during spaceflight. The Team Risk is a relatively young research area for NASA, with substantial growth only since the 2000s, and with limited access to spaceflight performance data. As a result, spaceflight evidence is lacking to identify specifically what team composition, level of training, amount of cohesion, or quality of psychosocial adaptation is necessary to reduce the risk of performance errors in space. However, astronaut journals and interviews and reports from spaceflight subject matter experts (SMEs) provide testimonies that team performance during spaceflight is important for mission success and to maintain crew health. Team spaceflight data is now being collected as part of the Spaceflight Standard Measures task (Clement, 2021)—a set of core measurements related to many human spaceflight risks that are collected from astronauts before, during, and after long-duration missions. The team-related standard measures focus on team cohesion, team performance, group living, team climate, and team processes. Collection of standard measures data is ongoing and published data is not yet available. Finally, although spaceflight evidence is lacking, evidence gleaned from ground studies and spaceflight analog studies will help close the gaps outlined in the Team Risk. Ground-based studies provide quantitative evidence for team functioning in ICE environments. Academic research on teams has produced dozens of meta-analyses that can be used to understand the general relationships among team inputs (e.g., team member characteristics and skills, job context), team processes, and emergent states (e.g., coordination, communication, cooperation, cohesion, trust, shared cognition), and team outcomes (e.g., effectiveness, errors, adaptation). Teams are complex, incorporating individual characteristics of team members, but also existing at a level that is greater than the sum of its parts. Therefore, the Team Risk must be integrated with other individual-focused NASA Human Research Program (HRP) risks, including Behavioral Medicine (BMed), Sleep, and Human-Systems Integration Architecture (HSIA), and emerging research indicates more integration may needed between the Team Risk and the physiologically oriented risks. Much of this integration occurs through the Human Systems Risk Board (HSRB). A lack of team functioning may be a stressor in some circumstances, but the team often acts as a countermeasure. For example, support for team leaders and teammates can facilitate individual functioning and encourage psychological and physically healthy behaviors and attitudes. However, more research is needed regarding teams during LDEMs and the remaining gaps in the research are described in the current report.

Lauren Blackwell Landon↗

Lower Illinois River Valley Ecological Forecasting: Inundation Mapping of the Lower Illinois River Valley Using Synthetic Aperture Radar and Optical Satellite Imagery for Wetland Conservation and Restoration Prioritization Efforts

The Lower Illinois River Valley (LIRV) is home to some of the richest agricultural lands in the United States and its wetlands provide key ecosystem services like clean water and flood reduction. It has also experienced extensive degradation due to development and urban pollution. The Great Rivers Land Trust (GRLT), the National Great Rivers Research & Education Center, Principia College, and the American Geophysical Union’s (AGU) Thriving Earth Exchange sought to incorporate inundation and surface water extent layers into their geodatabases to more accurately identify priority areas for wetland restoration. This project aimed to determine the feasibility of detecting inundation extent and duration along the valley using remotely sensed data. The team used Sentinel-1 C-band Synthetic Aperture Radar (SAR) data to classify open water and inundated vegetation within the study site. The open water classification was compared to Dynamic Surface Water Extent (DSWE) derived from Landsat 8 Operational Land Imager. The team successfully created layers of inundation minimum and maximum extent, as well as inundation duration across the study area for 2019 and 2020. The open water classification resulted in an overall accuracy of 86% when validated against DSWE classifications. These analyses will help end users to identify high priority areas along the LIRV best suited for land conversion projects in the future.

Vanessa Machuca↗

Forward for the new edition of: “What Every Engineer Should Know About Risk Engineering and Management"

In aerospace and engineering in general, the major metrics are capability, cost, and safety/risk. With the increasingly rapid emergence and utilization of new technologies and systems of increasing complexity, ensuring safety becomes more difficult. The technology and practice/applications of safety/risk technologies require updating in concert with capability and systems technology changes. Hence the new, updated edition of this risk engineering book. Major changes in technology and applications, now and going forward, increasingly involve artificial intelligence (AI)/autonomy and complex systems, which are rapidly developing and moving targets when it comes to risk/safety analysis. These introduce both new risks and safety issues, and they alter more usual ones. The current reality is that often the best AI is when it is “Black Boxed”, developed “independently”, without detailed human understanding of how and by what processes decisions and results are produced. There are ongoing efforts to make the AI processes more understandable by humans, with results to be determined. Also, trusted and true autonomy is free of human intervention, which would require machines to ideate to solve in real time issues that arise due to unknown unknowns and even known unknowns. Machines using generative adversarial network (GANs) and other approaches are beginning to ideate. Overall, the capabilities and practice of AI/autonomy utilization is a work in progress with the rate of progress substantial and the impacts upon system risk/safety major.

Dennis M. Bushnell↗

Decision Support Tool for Risk Assessment & Maneuver Planning in Collision Avoidance

As the quantity of orbital debris continues to grow, so too does the rate of conjunction messages that suggest possible collisions between high value payloads and debris. The abundance of these conjunction messages, and eventual misses, has led to a culture of ignored alerts, and an increase in satellite operation costs as a result of the frequent need to plan resources for maneuver planning and execution. The loss of “trust” in conjunction alerts is due to the poorly characterized evolution in probability of collision (Pc) as time approaches the time of closest approach (TCA) between two objects, as well as the interpretation of Pc in the context of maneuver planning. To address these problems, and in collaboration with the NASA Conjunction Assessment Risk Analysis (CARA) program, the Industrial Sciences Group has developed a novel Maneuver Decision Support System (MDSS) to assist satellite operations in conjunction assessment and Maneuver planning. It provides a meaningful and intuitive Urgency metric for actionable maneuver decisions, based on the physical dynamics of conjunctions. It is based on a forecast of the evolution of Pc over time and represents an advance over current methods that are in use for satellite conjunction monitoring and planning. The result is to give satellite operators a validated decision support systems to plan for maneuver execution or mitigation or monitoring up to 3 days before TCA.

Decision Support Tool↗

A Flight Replanning Tool for Terminal Area Urban Air Mobility Operations

In this presentation we describe and evaluate a flight replanning tool, called the trial planner, for terminal area air transport applications. The trial planner employs predefined airspace structures to generate rerouting options between vertiports. In a simplified definition, vertiports are facilities that provide services for managing the take-off and landing of autonomous or manned electric vertical take-off or landing (eVTOL) aircraft. The airspace structures involved in our test cases are arrival routes that consist of predefined entry points to which a transitional path is computed dynamically from the current position of the aircraft. Rerouting options include the transitional path and approach segment along the arrival route; these rerouting options are not vetted for potential conflicts with other operations until a human operator commits to a choice and forwards the flight plan modification for approval from an automated airspace management service. A selected rerouting option is executed by loading a flight plan file to the aircraft ground control station. We conducted a qualitative evaluation of the trial planner using ratings provided by flight crews and air transportation human factors experts with relevant experience from air traffic control. Evaluation criteria included trust in the route recommendations and adequate explanation for the route options. We detail the logic and implementation of the trial planner, as well as report the results of the evaluation of the implementation herein.

Trial planning↗

Lower Illinois River Valley Ecological Forecasting: Inundation Mapping of the Lower Illinois River Valley Using Synthetic Aperture Radar and Optical Satellite Imagery for Wetland Conservation and Restoration Prioritization Efforts

The Lower Illinois River Valley (LIRV) is home to some of the richest agricultural lands in the United States and its wetlands provide key ecosystem services like clean water and flood reduction. It has also experienced extensive degradation due to development and urban pollution. The Great Rivers Land Trust (GRLT), the National Great Rivers Research & Education Center, Principia College, and the American Geophysical Union’s (AGU) Thriving Earth Exchange sought to incorporate inundation and surface water extent layers into their geodatabases to more accurately identify priority areas for wetland restoration. This project aimed to determine the feasibility of detecting inundation extent and duration along the valley using remotely sensed data. We used Sentinel-1 C-band Synthetic Aperture Radar (SAR) data to classify open water and inundated vegetation within the study site. The open water classification was compared to Dynamic Surface Water Extent(DSWE) derived from Landsat 8 Operational Land Imager. We successfully created layers of inundation minimum and maximum extent, as well as inundation duration across the study area for 2019 and 2020. The open water classification resulted in an overall accuracy of 86% when validated against DSWE classifications. These analyses will help end users to identify high priority areas along the LIRV best suited for land conversion projects in the future.

Vanessa Machuca↗

Safety Culture at the World’s Premier Multi-User Spaceport

NASA’s Agency-wide Safety Culture is implemented at the Kennedy Space Center (KSC) using a unique strategy due an unparalleled approach in making human spaceflight history. Kennedy Space Center, the world’s premier multi-user spaceport, enables U.S. government and commercial space access, while providing the world a resource to allow the exploration of and the ability to work in space. A consistently healthy safety culture at KSC is imperative for mission success: desired achievements, protection of space flight hardware, and ultimately, the preservation of human life requires the support of a healthy safety culture. Emphasis on the NASA Agency-wide development of Safety Culture began with the conception of the NASA Agency Safety Culture Working Group. After the devastating loss of life and mission of the Space Shuttle Colombia, a broken safety culture was identified as an organizational cause by the Columbia Accident Investigation Board Report. Thus, the Agency Safety Culture Working Group was developed in 2009 to assess the status of the Agency’s Safety Culture, while addressing safety culture concerns at the NASA Center-level. A Five-factor model was developed to serve as the guiding principles for Safety Culture: 1) Reporting Culture, 2) Just Culture, 3) Flexible Culture, 4) Learning Culture, and 5) Engaged Culture. These five factors are included in the NASA Safety Culture logo, which was intentionally designed as a DNA double helix to prompt the permeation of safety into day-to-day work. KSC specifically implements the NASA Agency-wide Safety Culture principles in a tailored approach that is relevant to the diversity of work being performed. An emphasis is placed on the implementation to include safety at home, not exclusively at work. This emphasis is a KSC-specific element that has been intentionally added to promote a closed loop Safety Culture. To advertise the safety culture, various safety and health events are held throughout the calendar year, providing innovative speakers and engaging activities, while also promoting a wide range of curated safety initiatives. Development and continuous improvement of the KSC safety tracking database, allows for advanced tracking-to-closure, along with providing data sets used to identify areas of emphasis. Other safety initiatives rely solely on employee participation, such as the photo challenges; participants are encouraged to identify and capture themselves, coworkers, or family members participating in safe or healthy activities to share with others within the Center and at Agency levels. Fabrication of exclusive videos and graphics are utilized to advertise and inform employee of safety initiatives, upcoming safety events, and general dispersion of safety information. In addition, an anonymous Agency-wide Safety Culture Survey is advertised, administered, and analyzed at Kennedy Space Center, with the purpose of receiving basic feedback on Safety Culture perceptions to help prevent future incidents from occurring. Through these briefly identified means, and many other forms of employee engagement, Kennedy Space Center aims to maintain safety in the forefront, while creating an environment where everyone trusts that safety is a priority.

Larrin E. Moody↗

Kamodo’s Model-Agnostic Satellite Flythrough: Lowering the Utilization Barrier for Heliophysics Model Outputs

Heliophysics model outputs are increasingly accessible, but typically are not usable by the majority of the community unless directly collaborating with the relevant model developers. Prohibitive factors include complex file output formats, cryptic metadata, unspecified and often customized coordinate systems, and non-linear coordinate grids. Some pockets of progress exist, giving interfaces to various simulation outputs, but only for a small set of outputs and typically not with open-source, freely available packages. Additionally, the increasing array of tools built upon these sporadic interfaces are typically model-specific. We present Kamodo’s model-agnostic satellite flythrough capabilities as the solution to the utilization barrier for heliophysics model outputs. Developed at the Community Coordinated Modeling Center, these flythrough capabilities are built in Python upon a network of model-agnostic interfaces developed in collaboration with model developers, providing interpolation results the community can trust. Kamodo’s flythrough capabilities present the user with a growing variety of flythrough tools based upon a rapidly expanding library of heliophysics model outputs in several domains, currently including a variety of Ionosphere-Thermosphere-Mesosphere and global magnetosphere model outputs. Each capability is designed to be easily accessible via simplistic model-agnostic syntax, with the entire package freely available in the cloud on Github. Here, we describe the tools developed, include several sample applications for common science questions, demonstrate interoperability with selected packages, and summarize ongoing developments.

Software↗

NASA Earth Observations and the NASA Earth Science Disasters Program: Providing Data, Services and Science Expertise to Inform End User Decision-Making Throughout the Disaster Management Cycle

Program Goals: - Harness NASA Capabilities for Disaster Risk Reduction (DRR) and resilience - Engage stakeholders in the use of Earth Observations (EO) throughout the disaster lifecycle - Demonstrate the value and impact of EO to support decision making and actions - Grow as a trusted source for delivering useful results

Ronan Lucey↗

NASA’s Safety, Reliability, and Mission Assurance Digital Future

The evolution from “document-centric” to “data-centric” and “model-centric” information leveraging structured data and model-based approaches is at the heart of digital engineering transformational efforts underway across industry and government. It is these approaches that pave the way for data lakes, Authoritative Sources of Truth (ASOTs), and systems- of-systems interoperability and the corresponding transformational benefits thereof. Such benefits include increased data availability, data access equity, data traceability, real-time analytics, batch analytics, and (most importantly) acceleration of the time-to-value and time-to-insights associated with engineering products and analyses. The longer-term benefits of reusability, customization and traceability are even more promising. For Safety and Mission Assurance (SMA), and Mission Success (SMS) activities; realization of such benefits is essential to provide engineers and analysts alike vital information when needed to support critical decision making throughout the entire life cycle. The SMA community often operate in parallel with engineering activities, for which information exchange with relevant context is paramount. Far too often, such information lags key decision points and/or is absent of the robust, integrated, knowledge needed, given inherent barriers associated with traditional document-centric means to data sharing, analysis, and reporting. This paper provides an overview of how NASA’s Office of Safety and Mission Assurance (OSMA) is evolving its policies, standards, guidance, and training to transform to eliminate such barriers, thus realizing the benefits emerging in this new digital era. A roadmap for achieving this digital future is presented along with key building blocks involving use and implementation of concepts such as: Objectives-Hierarchies, Objective-Driven Requirements, Accepted Standards, Safety and Assurance Cases, data digitization (i.e., ontologies, structured data, and model-centric data), FAIR (Findable, Accessible, Interoperable, & Reusable) and/or FAIRUST (Findable, Accessible, Interoperable, Reusable, Understandable, Secure, and Trusted) principles [1]. This paper also describes how OSMA, leveraging the Agency’s overall commitment to Digital Transformation (DT), is using the power of Policy, “Digital” Domain representation, Product Evolution, and Community Outreach and Engagement as part of a strategic vision and roadmap to evolve and transform its SMA organizations to become better able to serve its stakeholders and customers. Future publications will elaborate on these building blocks and deeper concepts.

Authoritative Source of Truth (ASOT),↗

Dynamic Assurance of Autonomous Systems through Ground Control Software

Assurance cases are being increasingly acknowledged as a way to build trust in complex systems with autonomous capabilities [1]. An assurance case is a comprehensive, defensible, and valid justification that a system will function as intended for the specific mission and operating environment. Such justifications for systems with autonomous capabilities are often based on various probabilistic quantifications [2]. Due to the dynamic nature of the environmental conditions in which these systems operate, as well as the changing nature of the autonomous systems themselves, these probabilistic quantifications cannot be simply estimated once during design time. Rather, they need to be continually evaluated during systems operations to ensure that the assurance case justifications are valid. We refer to the assurance case that combines both the static and dynamic elements as a Dynamic Assurance Case (DAC). Such complex systems with autonomous capabilities are often deployed with a Ground Control Software (GCS) component to enable remote operation. Whether the system is composed of a single unit or a fleet of units, deployed distributed or in remote environments, GCS acts as a window into the behavior of the deployed system. It receives telemetry from the system, issues commands to the system and provides various functionalities to visualize the system performance. We propose a dynamic assurance framework where the GCS acts as a relay between the autonomous system and its DAC. GCS can be used to measure both unit-specific as well as system-wide probabilistic quantifications using the incoming telemetry. We embed these quantifications throughout the DAC as variables that can be updated by external sources. We use the GCS to periodically update these variables, which allows us to continually evaluate the formally defined assurance case justifications. We demonstrate our dynamic assurance framework in the NASA Ames project Troupe1 that aims at developing a fleet of rovers capable of au- tonomously mapping their environment. The rovers work cooperatively, each collecting data for different parts of the environment. Each rover runs an identical core Flight System (cFS) [4] application. Troupe1 uses OpenC3 Cosmos [5] as the ground system, and AdvoCATE [3] to capture the system DAC. We show how we can measure both rover-specific and system-wide quantifications in Cosmos using its Ruby scripting editor and pass them into the DAC modelled in AdvoCATE. Then, we show how these incoming variables can be embedded in different parts of the DAC and how effects of their updates can be observed

Irfan Sljivo↗