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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Viewgraphs on technology drivers for flight telerobotic system software are included. Topics covered include: flight software lines of code; flight computer architecture; system safety; safety critical parameters; system safety - software functions.
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.
We report here on our on-going work that addresses the automated analysis and test case generation for software systems modeled using multiple Statechart formalisms. The work is motivated by large programs such as NASA Exploration, that involve multiple systems that interact via safety-critical protocols and are designed with different Statechart variants. To verify these safety-critical systems, we have developed Polyglot, a framework for modeling and analysis of model-based software written using different Statechart formalisms. Polyglot uses a common intermediate representation with customizable Statechart semantics and leverages the analysis and test generation capabilities of the Symbolic PathFinder tool. Polyglot is used as follows: First, the structure of the Statechart model (expressed in Matlab Stateflow or Rational Rhapsody) is translated into a common intermediate representation (IR). The IR is then translated into Java code that represents the structure of the model. The semantics are provided as "pluggable" modules.
The use of overhead traveling bridge cranes in many varied applications is common practice. In particular, the use of cranes in the nuclear, military, commercial, aerospace, and other industries can involve safety critical situations. Considerations for Human Injury or Casualty, Loss of Assets, Endangering the Environment, or Economic Reduction must be addressed. Traditionally, in order to achieve additional safety in these applications, mechanical systems have been augmented with a variety of devices. These devices assure that a mechanical component failure shall reduce the risk of a catastrophic loss of the correct and/or safe load carrying capability. ASME NOG-1-1998, (Rules for Construction of Overhead and Gantry Cranes, Top Running Bridge, and Multiple Girder), provides design standards for cranes in safety critical areas. Over and above the minimum safety requirements of todays design standards, users struggle with obtaining a higher degree of reliability through more precise functional specifications while attempting to provide "smart" safety systems. Electrical control systems also may be equipped with protective devices similar to the mechanical design features. Demands for improvement of the cranes "control system" is often recognized, but difficult to quantify for this traditionally "mechanically" oriented market. Finite details for each operation must be examined and understood. As an example, load drift (or small motions) at close tolerances can be unacceptable (and considered critical). To meet these high functional demands encoders and other devices are independently added to control systems to provide motion and velocity feedback to the control drive. This paper will examine the implementation of Programmable Electronic Systems (PES). PES is a term this paper will use to describe any control system utilizing any programmable electronic device such as Programmable Logic Controllers (PLC), or an Adjustable Frequency Drive (AID) 'smart' programmable motion controller. Therefore the use of the term Programmable Electronic Systems (PES) is an encompassing description for a large spectrum of programmable electronic control devices.
Space applications need to overcome a very critical challenge of predicting remaining useful life of its critical systems/subsystems, with batteries being one of them. Batteries, power electronics conditioning system and motors and one of the most critical systems. Similarly in case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. Two approaches are presented with battery prognostics application. The first approach presentation covers a physics based-modeling approach implemented for battery prognostics. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making. A second hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems i.e. batteries is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.
Space applications need to overcome a very critical challenge of predicting remaining useful life of its critical systems/subsystems, with batteries being one of them. Batteries, power electronics conditioning system and motors and one of the most critical systems. Similarly in case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. Two approaches are presented with battery prognostics application. The first approach presentation covers a physics based-modeling approach implemented for battery prognostics. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making. A second hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems i.e. batteries is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.
This paper is a work of fiction, but it is fiction with a very real purpose: to stimulate careful thought and friendly discussion about some questions for which thought is often careless and discussion is often unfriendly. To accomplish this purpose, the paper creates a fictional legal case. The most important issue in this fictional case is whether certain proffered expert testimony about software engineering for safety critical systems should be admitted. Resolving this issue requires deciding the extent to which current practices and research in software engineering, especially for safety-critical systems, can rightly be considered based on knowledge, rather than opinion.
In Linear Temporal Logic (LTL) model checking, we check LTL formulas representing desired behaviors against a formal model of the system designed to exhibit these behaviors. To accomplish this task, the LTL formulas must be translated into automata [21]. We focus on LTL compilation by investigating LTL satisfiability checking via a reduction to model checking. Having shown that symbolic LTL compilation algorithms are superior to explicit automata construction algorithms for this task [16], we concentrate here on seeking a better symbolic algorithm.We present experimental data comparing algorithmic variations such as normal forms, encoding methods, and variable ordering and examine their effects on performance metrics including processing time and scalability. Safety critical systems, such as air traffic control, life support systems, hazardous environment controls, and automotive control systems, pervade our daily lives, yet testing and simulation alone cannot adequately verify their reliability [3]. Model checking is a promising approach to formal verification for safety critical systems which involves creating a formal mathematical model of the system and translating desired safety properties into a formal specification for this model. The complement of the specification is then checked against the system model. When the model does not satisfy the specification, model-checking tools accompany this negative answer with a counterexample, which points to an inconsistency between the system and the desired behaviors and aids debugging efforts.
The inability to establish appropriate assurance methods for AI/ML components in safety critical systems leaves us unable to effectively manage the risks and benefits of such systems. It drives cost of development for systems with AI/ML components uneconomically high, it delays the adoption of systems with AI/ML components at scale, and it can result in catastrophic consequences in terms of the safety of systems with AI/ML components. In this presentation we will explore what constitutes sufficient scientific-based evidence to substantiate a safety claim related to an AI/ML component performing a safety-critical function.
NASA and the Aviation Industry is looking into reduced crew operations (RCO) that would cut today's required two-person flight crews down to a single pilot with support from ground-based crews. Shared responsibility across air and ground personnel will require highly reliable and secure data communication and supporting automation, which will be safety-critical for passenger and cargo aircraft. This paper looks at the different types and degrees of authority delegation given from the air to the ground and the ramifications of each, including the safety and security hazards introduced, the mitigation mechanisms for these hazards, and other demands on an RCO system architecture which would be highly invasive into (almost) all safety-critical avionics. The adjacent fields of unmanned aerial systems and autonomous ground vehicles are viewed to find problems that RCO may face and related aviation accident scenarios are described. The paper explores possible data communication architectures to meet stringent performance and information security (INFOSEC) requirements of RCO. Subsequently, potential challenges for RCO data communication authentication, encryption and non-repudiation are identified. The approach includes a comprehensive safety-hazard analysis of the RCO system to determine top level INFOSEC requirements for RCO and proposes an option for effective RCO implementation. This paper concludes with questioning the economic viability of RCO in light of the expense of overcoming the operational safety and security hazards it would introduce.
System safety, an integral component in software development, often poses a challenge to engineers designing computer-based systems. While the relaxed constraints on software design allow for increased power and flexibility, this flexibility introduces more possibilities for error. As a result, system engineers must identify the design constraints necessary to maintain safety and ensure that the system and software design enforces them. Safeware Engineering Corporation, of Seattle, Washington, provides the information, tools, and techniques to accomplish this task with its Specification Tools and Requirements Methodology (SpecTRM). NASA assisted in developing this engineering toolset by awarding the company several Small Business Innovation Research (SBIR) contracts with Ames Research Center and Langley Research Center. The technology benefits NASA through its applications for Space Station rendezvous and docking. SpecTRM aids system and software engineers in developing specifications for large, complex safety critical systems. The product enables engineers to find errors early in development so that they can be fixed with the lowest cost and impact on the system design. SpecTRM traces both the requirements and design rationale (including safety constraints) throughout the system design and documentation, allowing engineers to build required system properties into the design from the beginning, rather than emphasizing assessment at the end of the development process when changes are limited and costly.System safety, an integral component in software development, often poses a challenge to engineers designing computer-based systems. While the relaxed constraints on software design allow for increased power and flexibility, this flexibility introduces more possibilities for error. As a result, system engineers must identify the design constraints necessary to maintain safety and ensure that the system and software design enforces them. Safeware Engineering Corporation, of Seattle, Washington, provides the information, tools, and techniques to accomplish this task with its Specification Tools and Requirements Methodology (SpecTRM). NASA assisted in developing this engineering toolset by awarding the company several Small Business Innovation Research (SBIR) contracts with Ames Research Center and Langley Research Center. The technology benefits NASA through its applications for Space Station rendezvous and docking. SpecTRM aids system and software engineers in developing specifications for large, complex safety critical systems. The product enables engineers to find errors early in development so that they can be fixed with the lowest cost and impact on the system design. SpecTRM traces both the requirements and design rationale (including safety constraints) throughout the system design and documentation, allowing engineers to build required system properties into the design from the beginning, rather than emphasizing assessment at the end of the development process when changes are limited and costly.
NASA and the Aviation Industry is looking into reduced crew operations (RCO) that would cut today's required two-person flight crews down to a single pilot with support from ground-based crews. Shared responsibility across air and ground personnel will require highly reliable and secure data communication and supporting automation, which will be safety-critical for passenger and cargo aircraft. This paper looks at the different types and degrees of authority delegation given from the air to the ground and the ramifications of each, including the safety and security hazards introduced, the mitigation mechanisms for these hazards, and other demands on an RCO system architecture which would be highly invasive into (almost) all safety-critical avionics. The adjacent fields of unmanned aerial systems and autonomous ground vehicles are viewed to find problems that RCO may face and related aviation accident scenarios are described. The paper explores possible data communication architectures to meet stringent performance and information security (INFOSEC) requirements of RCO. Subsequently, potential challenges for RCO data communication authentication, encryption and non-repudiation are identified.
The addition of automation has greatly extended humans' capability to accomplish tasks, including those that are difficult, complex and safety critical. The majority of Human - Automation Interact~on (HAl) results in more efficient and safe operations, ho,,:,ever ~ertain un~~pected a~tomatlon behaviors or "automation surprises" can be frustrating and, In certain safety critical operations (e.g. transport~tion, manufacturing control, medicine), may result in injuries or. the loss of life.. (Mellor, 1994; Leveson, 1995; FAA, 1995; BASI, 1998; Sheridan, 2002). This pap~r describes ~he development of a design tool that enables on the rapid development and evaluation. of automat~on prototypes. The ultimate goal of the work is to provide a design platform upon which automation surprise vulnerability analyses can be integrated.
Software plays an increasingly larger role in all aspects of NASA's science missions. This has been extended to the identification, management and control of faults which affect safety-critical functions and by default, the overall success of the mission. Traditionally, the analysis of fault identification, management and control are hardware based. Due to the increasing complexity of system, there has been a corresponding increase in the complexity in fault management software. The NASA Independent Validation & Verification (IV&V) program is creating processes and procedures to identify, and incorporate safety-critical software requirements along with corresponding software faults so that potential hazards may be mitigated. This Specific to Generic ... A Case for Reuse paper describes the phases of a dependability and safety study which identifies a new, process to create a foundation for reusable assets. These assets support the identification and management of specific software faults and, their transformation from specific to generic software faults. This approach also has applications to other systems outside of the NASA environment. This paper addresses how a mission specific dependability and safety case is being transformed to a generic dependability and safety case which can be reused for any type of space mission with an emphasis on software fault conditions.
Application agreement and integration services are required by distributed, fault-tolerant, safety critical systems to assure required performance. An analysis of distributed and hierarchical agreement strategies are developed against the backdrop of observed agreement failures in fielded systems. The documented work was performed under NASA Task Order NNL10AB32T, Validation And Verification of Safety-Critical Integrated Distributed Systems Area 2. This document is intended to satisfy the requirements for deliverable 5.2.11 under Task 4.2.2.3. This report discusses the challenges of maintaining application agreement and integration services. A literature search is presented that documents previous work in the area of replica determinism. Sources of non-deterministic behavior are identified and examples are presented where system level agreement failed to be achieved. We then explore how TTEthernet services can be extended to supply some interesting application agreement frameworks. This document assumes that the reader is familiar with the TTEthernet protocol. The reader is advised to read the TTEthernet protocol standard [1] before reading this document. This document does not re-iterate the content of the standard.
Runtime Assurance (RTA) is a design-time architecture for safety-critical systems where an internal monitor acts upon detecting a violation of a property. The simplex architecture is an instance of RTA, where the action taken is to hand control of the overall system to a trusted controller when an untrusted one violates a safety property. Simplex RTA is emerging as a method for allowing AI/ML and other unverified software to be integrated into safety-critical applications like aircraft. To this end, the American Society for Testing and Materials (ASTM) and NASA have each published guidelines on the use of RTA in such systems. In the simplex RTA framework, a system has an advanced controller (AC) and a reversionary controller (RC). The system is allowed to operate with the AC until a runtime monitor detects that some property has been violated and then the RC takes over. Assuming that the sample rate of the monitor will detect improper functioning with enough time for the RC to correct the impending problem, and that the RC is trusted, the system will operate as intended. This use of the simplex RTA framework can allow for the integration of untrusted, but possibly more performant, controllers in a safe way. This paper presents a formalization of a simplex RTA framework in the Prototype Verification System (PVS) theorem prover using an embedding of differential dynamic logic (DDL) called Plaidypvs. A novel feature of this framework is that it can be instantiated at different levels of abstraction. This feature allows for the formal verification of a system with an untrusted black box component, such as an AI/ML controller. This paper does not address the many difficulties in deploying RTA in an industrial-level system. Instead, the focus is on the formal verification of the simplex RTA framework in the language of hybrid programs. Hybrid programs are programs that include both discrete and continuous dynamics and can be used to model complex cyber-physical systems. Plaidypvs is a tool that enables formalization of hybrid programs in the PVS theorem prover. Plaidypvs enables the verification of the general simplex RTA framework and then, by specializing some components of the hybrid program, verifying instances of the framework while treating the untrusted component as a black box. A selection of Unmanned Aircraft Systems (UAS) operations are shown as instances of the general RTA framework in PVS. This offers the benefit of design time verification of relevant safety properties to the system, and it also gives requirements on the sample rate of sensors that determine the time interval in which the ‘switch’ property of the RTA framework is checked.
High reliability of mission- and safety-critical software systems has been identified by NASA as a high-priority technology challenge. We present an approach for the performance analysis of a neural network (NN) in an advanced adaptive control system. This problem is important in the context of safety-critical applications that require certification, such as flight software in aircraft. We have developed a tool to measure the performance of the NN during operation by calculating a confidence interval (error bar) around the NN's output. Our tool can be used during pre-deployment verification as well as monitoring the network performance during operation. The tool has been implemented in Simulink and simulation results on a F-15 aircraft are presented.
This talk will provide a brief introduction to the formal methods developed at NASA Langley and the National Institute for Aerospace (NIA) for air traffic management applications. NASA Langley's formal methods research supports the Interagency Joint Planning and Development Office (JPDO) effort to define and develop the 2025 Next Generation Air Transportation System (NGATS). The JPDO was created by the passage of the Vision 100 Century of Aviation Reauthorization Act in Dec 2003. The NGATS vision calls for a major transformation of the nation s air transportation system that will enable growth to 3 times the traffic of the current system. The transformation will require an unprecedented level of safety-critical automation used in complex procedural operations based on 4-dimensional (4D) trajectories that enable dynamic reconfiguration of airspace scalable to geographic and temporal demand. The goal of our formal methods research is to provide verification methods that can be used to insure the safety of the NGATS system. Our work has focused on the safety assessment of concepts of operation and fundamental algorithms for conflict detection and resolution (CD&R) and self- spacing in the terminal area. Formal analysis of a concept of operations is a novel area of application of formal methods. Here one must establish that a system concept involving aircraft, pilots, and ground resources is safe. The formal analysis of algorithms is a more traditional endeavor. However, the formal analysis of ATM algorithms involves reasoning about the interaction of algorithmic logic and aircraft trajectories defined over an airspace. These trajectories are described using 2D and 3D vectors and are often constrained by trigonometric relations. Thus, in many cases it has been necessary to unload the full power of an advanced theorem prover. The verification challenge is to establish that the safety-critical algorithms produce valid solutions that are guaranteed to maintain separation under all possible scenarios. Current research has assumed perfect knowledge of the location of other aircraft in the vicinity so absolute guarantees are possible, but increasingly we are relaxing the assumptions to allow incomplete, inaccurate, and/or faulty information from communication sources.