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NASA NTRS2024

Ensuring Safety of Government Personnel During Suborbital Spaceflight

The NASA Suborbital Crew (SubC) project is focused on enabling flights by NASA civil servants, such as scientists and engineers conducting research, on suborbital vehicles. A broader goal is ensuring that commercial human spaceflight is both viable and safe. Within the Commercial Crew Program (CCP), the SubC project is exploring game-changing methods to perform safety assessments to enable NASA personnel to fly on suborbital missions. Commercial suborbital space flight capabilities are anticipated to be more accessible, affordable, and available than missions to the International Space Station and could provide additional opportunities for testing and qualification of space flight hardware, human-tended microgravity research, and further cutting-edge research enabled by the space environment. Although NASA currently permits human tended suborbital payloads for non-civil servants under auspices of NASA’s Flight Opportunities Program, the SubC effort will enable civil servant scientists, researchers, and even engineers to accompany their experiments and tests into the space microgravity environment. Figure 1 illustrates how the SubC program complements other microgravity experimental platforms. The targeted scope for SubC includes end-to-end suborbital capabilities reaching ~80km with several minutes of sustained microgravity (Table 1). The NASA SubC project office is working with the Federal Aviation Administration’s Office of Commercial Space Transportation (FAA-AST) and the commercial suborbital space transportation industry to develop an efficient and holistic approach to a safety review and eventual government participation in suborbital flight. The current FAA certification process for suborbital launches is congressionally mandated to only consider public safety. NASA is responsible for understanding the risks to its employees should they fly on a commercially available suborbital flight. The SubC project is employing a Safety Case approach, applied to commercial suborbital providers, which is not a traditional certification process as was used for the SpaceX Dragon and Boeing Starliner vehicles. Rather, it is an assessment using elements of NASA’s Risk-Informed Safety Case and the Armstrong Flight Research Center’s Airworthiness Assessment process.

Elizabeth C Blome↗

NASA NTRS2022

NASA Crew Transportation System Certification Plan

NASA Crew Transportation System (CTS) Certification is the authorization granted by the Agency that allows the use of a Commercial Provider’s CTS to transport NASA Crew to and from the ISS. The CTS Certification decision is made by the NASA Associate Administrator based on the comprehensive assessment of the Certification Review Board and recommendations from the CCP and ISS Program Managers and the NASA Associate Administrator of Space Operations Mission Directorate. The Commercial Provider is responsible for developing and executing its plan for certifying the CTS. The Commercial Crew Program (CCP) with the International Space Station (ISS) Program must substantiate the Commercial Provider’s certification assertion of compliance with NASA requirements and NASA Crew safety.

CCP↗

NASA NTRS2016

Safety Characteristics in System Application of Software for Human Rated Exploration Missions for the 8th IAASS Conference

NASA and its industry and international partners are embarking on a bold and inspiring development effort to design and build an exploration class space system. The space system is made up of the Orion system, the Space Launch System (SLS) and the Ground Systems Development and Operations (GSDO) system. All are highly coupled together and dependent on each other for the combined safety of the space system. A key area of system safety focus needs to be in the ground and flight application software system (GFAS). In the development, certification and operations of GFAS, there are a series of safety characteristics that define the approach to ensure mission success. This paper will explore and examine the safety characteristics of the GFAS development. The GFAS system integrates the flight software packages of the Orion and SLS with the ground systems and launch countdown sequencers through the 'agile' software development process. A unique approach is needed to develop the GFAS project capabilities within this agile process. NASA has defined the software development process through a set of standards. The standards were written during the infancy of the so-called industry 'agile development' movement and must be tailored to adapt to the highly integrated environment of human exploration systems. Safety of the space systems and the eventual crew on board is paramount during the preparation of the exploration flight systems. A series of software safety characteristics have been incorporated into the development and certification efforts to ensure readiness for use and compatibility with the space systems. Three underlining factors in the exploration architecture require the GFAS system to be unique in its approach to ensure safety for the space systems, both the flight as well as the ground systems. The first are the missions themselves, which are exploration in nature, and go far beyond the comfort of low Earth orbit operations. The second is the current exploration system will launch only one mission per year even less during its developmental phases. Finally, the third is the partnered approach through the use of many different prime contractors, including commercial and international partners, to design and build the exploration systems. These three factors make the challenges to meet the mission preparations and the safety expectations extremely difficult to implement. As NASA leads a team of partners in the exploration beyond earth's influence, it is a safety imperative that the application software used to test, checkout, prepare and launch the exploration systems put safety of the hardware and mission first. Software safety characteristics are built into the design and development process to enable the human rated systems to begin their missions safely and successfully. Exploration missions beyond Earth are inherently risky, however, with solid safety approaches in both hardware and software, the boldness of these missions can be realized for all on the home planet.

capability↗

NASA NTRS2007

Sample Return Primer and Handbook

This three-part Sample Return Primer and Handbook provides a road map for conducting the terminal phase of a sample return mission. The main chapters describe element-by-element analyses and trade studies, as well as required operations plans, procedures, contingencies, interfaces, and corresponding documentation. Based on the experiences of the lead Stardust engineers, the topics include systems engineering (in particular range safety compliance), mission design and navigation, spacecraft hardware and entry, descent, and landing certification, flight and recovery operations, mission assurance and system safety, test and training, and the very important interactions with external support organizations (non-NASA tracking assets, landing site support, and science curation).

Stardust↗

NASA NTRSDate not supplied

Adaptive Stress Testing: Using Reinforcement Learning to Find Failures in Safety-Critical Systems

Emerging applications in artificial intelligence, such as driverless cars and autonomous aircraft promise to be more efficient, cheaper to operate, and always available. However, ensuring the safety of these systems remains a major challenge to their certification and adoption. These autonomous systems are expected to routinely make safety-critical decisions where failures can have serious consequences including loss of life and property. Testing and validation techniques aim to identify and diagnose potential failures before the system is deployed. However, finding failure scenarios in autonomous systems can be very challenging due to high-dimensional and continuous state spaces, interaction with large environments over many time steps, and the rarity of failures. This talk presents Adaptive Stress Testing (AST), a simulation-based testing framework for finding the most likely path to a failure event of a safety-critical system. The key idea of AST is that stress testing can be formulated as a Partially Observable Markov Decision Process (POMDP), which enables reinforcement learning techniques to be used for finding failure events. Reinforcement learning algorithms can efficiently explore the search space and have been shown to scale to very large systems. We present applications of AST to find failures in various safety-critical systems including the aircraft collision avoidance systems, autonomous cars, and small unmanned aerial vehicles.

autonomous vehicles↗

NASA NTRS2010

Climbing the Extravehicular Activity (EVA) Wall - Safely

The success of the EVA team, that includes the EVA project office, Crew Office, Mission Operations, Engineering and Safety, is assured by the full integration of all necessary disciplines. Safety participation in all activities from hardware development concepts, certification and crew training, provides for a strong partnership within the team. Early involvement of Safety on the EVA team has mitigated risk and produced a high degree of mission success.

Fuentes, Jose↗

NASA NTRS2002

Human Factors Process Task Analysis Liquid Oxygen Pump Acceptance Test Procedure for the Advanced Technology Development Center

A process task analysis effort was undertaken by Dynacs Inc. commencing in June 2002 under contract from NASA YA-D6. Funding was provided through NASA's Ames Research Center (ARC), Code M/HQ, and Industrial Engineering and Safety (IES). The John F. Kennedy Space Center (KSC) Engineering Development Contract (EDC) Task Order was 5SMA768. The scope of the effort was to conduct a Human Factors Process Failure Modes and Effects Analysis (HF PFMEA) of a hazardous activity and provide recommendations to eliminate or reduce the effects of errors caused by human factors. The Liquid Oxygen (LOX) Pump Acceptance Test Procedure (ATP) was selected for this analysis. The HF PFMEA table (see appendix A) provides an analysis of six major categories evaluated for this study. These categories include Personnel Certification, Test Procedure Format, Test Procedure Safety Controls, Test Article Data, Instrumentation, and Voice Communication. For each specific requirement listed in appendix A, the following topics were addressed: Requirement, Potential Human Error, Performance-Shaping Factors, Potential Effects of the Error, Barriers and Controls, Risk Priority Numbers, and Recommended Actions. This report summarizes findings and gives recommendations as determined by the data contained in appendix A. It also includes a discussion of technology barriers and challenges to performing task analyses, as well as lessons learned. The HF PFMEA table in appendix A recommends the use of accepted and required safety criteria in order to reduce the risk of human error. The items with the highest risk priority numbers should receive the greatest amount of consideration. Implementation of the recommendations will result in a safer operation for all personnel.

Diorio, Kimberly A.↗

NASA NTRS1988

Zero/zero rotorcraft certification issues. Volume 1: Executive summary

This report analyzes the Zero/Zero Rotorcraft Certification Issues from the perspectives of manufacturers, operators, researchers and the FAA. The basic premise behind this analysis is the zero/zero, or at least extremely low visibility, rotorcraft operations are feasible today from both a technological and an operational standpoint. The questions and issues that need to be resolved are: What certification requirements do we need to ensure safety. Can we develop procedures which capitalize on the performance and maneuvering capabilities unique to rotorcraft. Will exptremely low visibility operations be economically feasible. This is Volume 1 of three. It provides an overview of the Certification Issues Forum held in Phoenix, Arizona in August of 1987. It presents a consensus of 48 experts from government, manufacturer, and research communities on 50 specific Certification Issues. The topics of Operational Requirements, Procedures, Airworthiness, and Engineering Capabilities are discussed.

Adams, Richard J.↗

NASA NTRS1983

A preliminary damage tolerance methodology for composite structures

The certification experience for the primary, safety-of-flight composite structure applications on the F-16 is discussed. The rationale for the selection of delamination as the major issue for damage tolerance is discussed, as well as the modeling approach selected. The development of the necessary coupon-level data base is briefly summarized. The major emphasis is on the description of a full-scale fatigue test where delamination growth was obtained to demonstrate the validity of the selected approach. A summary is used to review the generic features of the methodology.

Wilkins, D. J.↗

NASA NTRS1982

Experience with specifications applicable to certification

The Jet Propulsion Laboratory has developed a number of photovoltaic test and measurement specifications to guide the development of modules toward the requirements of future large-scale applications. Experience with these specifications and the extensive module measurement and testing that has accompanied their use is examined. Conclusions are drawn relative to three aspects of product certification: performance measurement, endurance testing and safety evaluation.

Ross, R. G., Jr.↗

NASA NTRS2021

ATTRACTOR: Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability

Autonomous systems (AS) are crucial to realizing the vision of new, complex transportation modes, such as advanced air mobility (AAM) and urban air mobility (UAM). A chief barrier to induction of AS into aviation is insufficient understanding of AS reliability in time-critical and safety-critical environments—an obstacle to certification. ATTRACTOR is aimed at building a basis for certification of classes of autonomous cyber-physical-human systems (CPHS) via establishing metrics and models of trustworthiness and trust in multi-agent team interactions, analyzable trajectories, explainability of computational algorithms (explainable artificial intelligence, or XAI), and persistent modeling and simulation, in the context of missions planning and operation. By “building a basis for certification,” we mean acquiring an understanding of when a system is trustworthy and developing computable means to estimate trustworthiness and trust in order to eventually inform functional requirements that contribute to certification. The outcomes are applicable not just to aviation but to all domains that rely on autonomous systems.

Autonomy↗

NASA NTRSDate not supplied

Safety Assessment of a Machine Learning-Based Aircraft Emergency Braking System: A Case Study

Machine Learning (ML) is revolutionizing many technological fields, but its use in aviation remains restricted due to stringent certification requirements. Efforts by the aviation community to establish standards for certifying ML-based systems are progressing, yet challenges persist, particularly with safety assessment methods for ML-based systems. This research addresses these challenges through a case study of an autonomous emergency braking system utilizing a computer vision deep neural network (DNN). We demonstrate a safety assessment process tailored to ML-specific concerns, such as low integrity and performance variability in quantitative safety analysis. This study can serve as an illustrative example to facilitate the discussion and convergence on certification aspects for ML-based systems within the aviation community.

Safety certification↗

NASA NTRS2016

Safety Characteristics in System Application Software for Human Rated Exploration

exploration↗

NASA NTRS2022

Functional Hazard Assessment for the eVTOL Aircraft Supporting Urban Air Mobility (UAM) Applications: Exploratory Demonstrations

The active development community surrounding electric vertical takeoff and landing (eVTOL) aircraft has demonstrated potential to bring new technological capabilities to market, encouraging visions of widespread and diverse Urban Air Mobility (UAM) applications. New capabilities always come with safety considerations, some familiar and others less so. OEMs who intend to obtain FAA type certification for their eVTOL designs must plan for and execute sufficient safety engineering processes to demonstrate that credible hazards associated with these eVTOL designs are adequately mitigated. This work provides an orientation for eVTOL stakeholders, especially new entrants and those in hybrid roles, to the safety and regulatory context for assuring eVTOL aircraft for UAM applications. We further present selections of functional hazard assessment (FHA) performed on a reference eVTOL concept, with process and decision narration. The exercise allows exploration of several safety considerations specific to eVTOL systems and demonstrates the FHA process together with negotiation of some of its options and variations.

Hazard Analysis↗

NASA NTRSDate not supplied

Verification and Validation of Safety-Critical Aircraft Systems Operating under Off-Nominal, Contingency, and Emergency Conditions

Verification and validation (V&V) of safety-critical technologies developed for loss of control (LOC) prevention and recovery and other aviation safety concerns pose significant challenges. Aircraft LOC can result from a wide spectrum of hazards, often occurring in combination, which cannot be fully replicated during evaluation. Technologies developed for LOC prevention and recovery must therefore be effective under a wide variety of hazardous and uncertain conditions, and the verification and validation of these technologies must provide some measure of assurance that the new vehicle safety technologies do no harm (i.e., that they themselves do not introduce new safety risks). V&V technologies must also enable the identification of system limitations and constraints, as well as enable the identification of safe and unsafe operating conditions (and their boundaries). Additionally, the V&V of complex, increasingly autonomous systems is a fundamental concern. Scalable, reproducible and cost-effective techniques for the assurance of safety critical systems during their design and operation is a key barrier to fielding new systems or updating current systems. Moreover, these techniques need to provide artifacts that enable a comprehensive evidence-based approach to certification. This briefing summarizes research performed under NASA’s Aviation Safety Program and follow-on research for the V&V of safety-critical aircraft system technologies developed for LOC prevention and recovery and increasingly autonomous systems, and for a broad assurance capability in both current and emerging aviation applications. Note that, in this briefing, the term “validation” refers to a confirmation that the system implementation (e.g., algorithms etc.) is performing the intended function(s), as well as an affirmation of effectiveness in these functions. “Verification” refers to a confirmation that the system implementation in the software and hardware meets its (hopefully validated) specifications (e.g., correctly executes algorithms as designed).

Validation↗

NASA NTRS2018

Serious Gaming for Building a Basis of Certification via Trust and Trustworthiness of Autonomous Systems

Autonomous systems governed by a variety of adaptive and nondeterministic algorithms are being planned for inclusion into safety-critical environments, such as unmanned aircraft and space systems in both civilian and military applications. However, until autonomous systems are proven and perceived to be capable and resilient in the face of unanticipated conditions, humans will be reluctant or unable to delegate authority, remaining in control aided by machine-based information and decision support. Proving capability, or trustworthiness, is a necessary component of certification. Perceived capability is a component of trust. Trustworthiness is an attribute of a cyber-physical system that requires context-driven metrics to prove and certify. Trust is an attribute of the agents participating in the system and is gained over time and multiple interactions through trustworthy behavior and transparency. Historically, artificial intelligence and machine learning systems provide answers without explanation - without a rationale or insight into the machine “thinking”. In order to function as trusted teammates, machines must be able to explain their decisions and actions. This transparency is a product of both content and communication. NASA’s Autonomy Teaming & TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) project seeks to build a basis for certification of autonomous systems via establishing metrics for trustworthiness and trust in multi-agent team interactions, using AI (Artificial Intelligence) explainability and persistent modeling and simulation, in the context of mission planning and execution, with analyzable trajectories. Inspired by Massively Multiplayer Online Role Playing Games (MMORPG) and Serious Gaming, the proposed ATTRACTOR modeling and simulation environment is similar to online gaming environments in which player (aka agent) participants interact with each other, affect their environment, and expect the simulation to persist and change regardless of any individual agent’s active participation. This persistent simulation environment will accommodate individual agents, groups of self-organizing agents, and large-scale infrastructure behavior. The effects of the emerging adaptation and coevolution can be observed and measured to building a basis of measurable trustworthiness and trust, toward certification of safety-critical autonomous systems.

Allen, B. Danette↗

NASA NTRS2008

Certifying Auto-Generated Flight Code

Model-based design and automated code generation are being used increasingly at NASA. Many NASA projects now use MathWorks Simulink and Real-Time Workshop for at least some of their modeling and code development. However, there are substantial obstacles to more widespread adoption of code generators in safety-critical domains. Since code generators are typically not qualified, there is no guarantee that their output is correct, and consequently the generated code still needs to be fully tested and certified. Moreover, the regeneration of code can require complete recertification, which offsets many of the advantages of using a generator. Indeed, manual review of autocode can be more challenging than for hand-written code. Since the direct V&V of code generators is too laborious and complicated due to their complex (and often proprietary) nature, we have developed a generator plug-in to support the certification of the auto-generated code. Specifically, the AutoCert tool supports certification by formally verifying that the generated code is free of different safety violations, by constructing an independently verifiable certificate, and by explaining its analysis in a textual form suitable for code reviews. The generated documentation also contains substantial tracing information, allowing users to trace between model, code, documentation, and V&V artifacts. This enables missions to obtain assurance about the safety and reliability of the code without excessive manual V&V effort and, as a consequence, eases the acceptance of code generators in safety-critical contexts. The generation of explicit certificates and textual reports is particularly well-suited to supporting independent V&V. The primary contribution of this approach is the combination of human-friendly documentation with formal analysis. The key technical idea is to exploit the idiomatic nature of auto-generated code in order to automatically infer logical annotations. The annotation inference algorithm itself is generic, and parametrized with respect to a library of coding patterns that depend on the safety policies and the code generator. The patterns characterize the notions of definitions and uses that are specific to the given safety property. For example, for initialization safety, definitions correspond to variable initializations while uses are statements which read a variable, whereas for array bounds safety, definitions are the array declarations, while uses are statements which access an array variable. The inferred annotations are thus highly dependent on the actual program and the properties being proven. The annotations, themselves, need not be trusted, but are crucial to obtain the automatic formal verification of the safety properties without requiring access to the internals of the code generator. The approach has been applied to both in-house and commercial code generators, but is independent of the particular generator used. It is currently being adapted to flight code generated using MathWorks Real-Time Workshop, an automatic code generator that translates from Simulink/Stateflow models into embedded C code.

Denney, Ewen↗

NASA NTRS1999

Streamlining Software Aspects of Certification: Report on the SSAC Survey

The aviation system now depends on information technology more than ever before to ensure safety and efficiency. To address concerns about the efficacy of software aspects of the certification process, the Federal Aviation Administration (FAA) began the Streamlining Software Aspects of Certification (SSAC) program. The SSAC technical team was commissioned to gather data, analyze results, and propose recommendations to maximize efficiency and minimize cost and delay, without compromising safety. The technical team conducted two public workshops to identify and prioritize software approval issues, and conducted a survey to validate the most urgent of those issues. The SSAC survey, containing over two hundred questions about the FAA's software approval process, reached over four hundred industry software developers, aircraft manufacturers, and FAA designated engineering representatives. Three hundred people responded. This report presents the SSAC program rationale, survey process, preliminary findings, and recommendations.

Hayhurst, Kelly J.↗