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In FY03 QS10 began building an S&MA web based data management tool,"Safety & Mission Assurance Requirements Tool" (SMART) that identifies S&MA requirements, tailors requirements to IAW project/program categories, tracks implementation, and provides a template for developing requirements and tracking waivers. This report provides a SMART process flow, typical application, typical data requirement deliverables, progress in 03, and FY04 activities.
Fundamental to vehicle health management is the deployment of systems incorporating advanced technologies for predicting and detecting anomalous conditions in highly complex and integrated environments. Integrated structural integrity health monitoring, statistical algorithms for detection, estimation, prediction, and fusion, and diagnosis supporting adaptive control are examples of advanced technologies that present considerable verification and validation challenges. These systems necessitate interactions between physical and software-based systems that are highly networked with sensing and actuation subsystems, and incorporate technologies that are, in many respects, different from those employed in civil aviation today. A formidable barrier to deploying these advanced technologies in civil aviation is the lack of enabling verification and validation tools, methods, and technologies. The development of new verification and validation capabilities will not only enable the fielding of advanced vehicle health management systems, but will also provide new assurance capabilities for verification and validation of current generation aviation software which has been implicated in anomalous in-flight behavior. This paper describes the research focused on enabling capabilities for verification and validation underway within NASA s Integrated Vehicle Health Management project, discusses the state of the art of these capabilities, and includes a framework for prioritizing activities.
There is a trend in the aviation industry to go from federated to integrated computing systems. Combining a number of traditional stand-alone federated systems into an integrated common platform (called Integrated Modular Avionics, IMA) has the benefit of increased power efficiency, reduced support hardware, and reduced cabling. However, changing from federated to integrated has a significant impact on the system architecture and hence the process of how avionic systems are to be analyzed. Traditional approaches to safety analysis become inefficient when functional boundaries can no longer be assumed for failure independence and fault isolation. In this report, we describe a tool that we developed to accelerate the safety engineer's ability to perform safety analysis of IMA systems through modeling, as well as optimize the system engineer's ability to develop a system through architecture synthesis. This work was the result of a three-year research effort called SOTERIA (Safe and Optimal Techniques Enabling Recovery, Integrity, and Assurance). We developed a compositional modeling language that supports rapid development, modification, and evaluation of architectures. The modeling language is structured such that the end-user defines a library of components with information on component reliability, connectivity, and fault propagation logic. The system model is built by instantiating the components from the library, connecting the components, and identifying the top-level faults of interest. Our tool is compositional in that the end-user only needs to define safety aspects at the component level. The tool takes the model and automatically synthesizes both the qualitative and quantitative safety analyses. We go further by allowing users to describe system information such as components to use in an architecture and their connection compatibility and automatically synthesize an architecture that meets the top-level probability target adhering to end-user specified constraints. This capability allows users to rapidly explore a design space..
As spaceflight systems increase in complexity, Fault Management (FM) systems are ranked high in risk-based assessment of software criticality, emphasizing the importance of establishing highly competent domain expertise to provide assurance. Adverse conditions (ACs) and specific vulnerabilities encountered by safety- and mission-critical software systems have been identified through efforts to reduce the risk posture of software-intensive NASA missions. Acknowledgement of potential off-nominal conditions and analysis to determine software system resiliency are important aspects of hazard analysis and FM. A key component of assuring FM is an assessment of how well software addresses susceptibility to failure through consideration of ACs. Focus on significant risk predicted through experienced analysis conducted at the NASA Independent Verification Validation (IVV) Program enables the scoping of effective assurance strategies with regard to overall asset protection of complex spaceflight as well as ground systems. Research efforts sponsored by NASA's Office of Safety and Mission Assurance defined terminology, categorized data fields, and designed a baseline repository that centralizes and compiles a comprehensive listing of ACs and correlated data relevant across many NASA missions. This prototype tool helps projects improve analysis by tracking ACs and allowing queries based on project, mission type, domaincomponent, causal fault, and other key characteristics. Vulnerability in off-nominal situations, architectural design weaknesses, and unexpected or undesirable system behaviors in reaction to faults are curtailed with the awareness of ACs and risk-significant scenarios modeled for analysts through this database. Integration within the Enterprise Architecture at NASA IVV enables interfacing with other tools and datasets, technical support, and accessibility across the Agency. This paper discusses the development of an improved workflow process utilizing this database for adaptive, risk-informed FM assurance that critical software systems will safely and securely protect against faults and respond to ACs in order to achieve successful missions.
As spaceflight systems increase in complexity, Fault Management (FM) systems are ranked high in risk-based assessment of software criticality, emphasizing the importance of establishing highly competent domain expertise to provide assurance. Adverse conditions (ACs) and specific vulnerabilities encountered by safety- and mission-critical software systems have been identified through efforts to reduce the risk posture of software-intensive NASA missions. Acknowledgement of potential off-nominal conditions and analysis to determine software system resiliency are important aspects of hazard analysis and FM. A key component of assuring FM is an assessment of how well software addresses susceptibility to failure through consideration of ACs. Focus on significant risk predicted through experienced analysis conducted at the NASA Independent Verification & Validation (IV&V) Program enables the scoping of effective assurance strategies with regard to overall asset protection of complex spaceflight as well as ground systems. Research efforts sponsored by NASAs Office of Safety and Mission Assurance (OSMA) defined terminology, categorized data fields, and designed a baseline repository that centralizes and compiles a comprehensive listing of ACs and correlated data relevant across many NASA missions. This prototype tool helps projects improve analysis by tracking ACs and allowing queries based on project, mission type, domain/component, causal fault, and other key characteristics. Vulnerability in off-nominal situations, architectural design weaknesses, and unexpected or undesirable system behaviors in reaction to faults are curtailed with the awareness of ACs and risk-significant scenarios modeled for analysts through this database. Integration within the Enterprise Architecture at NASA IV&V enables interfacing with other tools and datasets, technical support, and accessibility across the Agency. This paper discusses the development of an improved workflow process utilizing this database for adaptive, risk-informed FM assurance that critical software systems will safely and securely protect against faults and respond to ACs in order to achieve successful missions.
A capability for rapidly performing quantitative risk assessments has been developed by JSC Safety and Mission Assurance for use on project design trade studies early in the project life cycle, i.e., concept development through preliminary design phases. A risk assessment tool set has been developed consisting of interactive and integrated software modules that allow a user/project designer to assess the impact of alternative design or programmatic options on the probability of mission success or other risk metrics. The risk and design trade space includes interactive options for selecting parameters and/or metrics for numerous design characteristics including component reliability characteristics, functional redundancy levels, item or system technology readiness levels, and mission event characteristics. This capability is intended for use on any project or system development with a defined mission, and an example project will used for demonstration and descriptive purposes, e.g., landing a robot on the moon. The effects of various alternative design considerations and their impact of these decisions on mission success (or failure) can be measured in real time on a personal computer. This capability provides a high degree of efficiency for quickly providing information in NASA s evolving risk-based decision environment
Marketed as the "Software of the Future," Optimal Engineering Systems P.I. EXPERT(TM) technology offers statistical process control and optimization techniques that are critical to businesses looking to restructure or accelerate operations in order to gain a competitive edge. Kennedy Space Center granted Optimal Engineering Systems the funding and aid necessary to develop a prototype of the process monitoring and improvement software. Completion of this prototype demonstrated that it was possible to integrate traditional statistical quality assurance tools with robust optimization techniques in a user- friendly format that is visually compelling. Using an expert system knowledge base, the software allows the user to determine objectives, capture constraints and out-of-control processes, predict results, and compute optimal process settings.
NASA is using Probabilistic Risk Assessment (PRA) as one of the tools in its Safety & Mission Assurance (S&MA) tool belt to identify and quantify risks associated with human spaceflight. This paper discusses some of the challenges and benefits associated with developing and using PRA for NASA human space programs. Some programs have entered operation prior to developing a PRA, while some have implemented PRA from the start of the program. It has been observed that the earlier a design change is made in the concept or design phase, the less impact it has on cost and schedule. Not finding risks until the operation phase yields much costlier design changes and major delays, which can result in discussions of just accepting the risk. Risk contributors identified by PRA are not just associated with hardware failures. They include but are not limited to crew fatality due to medical causes, the environment the vehicle and crew are exposed to, the software being used, and the reliability of the crew performing required actions. Some programs have entered operation prior to developing a PRA, and while PRA can still provide a benefit for operations and future design trades, the benefit of implementing PRA from the start of the program provides the added benefit of informing design and reducing risk early in program development. Currently, NASA’s International Space Station (ISS) program is in its 20th year of on-orbit operations around the Earth and has several new programs in the design phase preparing to enter the operation phase all of which have active (or living) PRAs. These programs incorporate PRA as part of their Risk-Informed, Decision-Making (RIDM) process. For new NASA human spaceflight programs discussion begins with mission concept, establishing requirements, forming the PRA team, and continues through the design cycles into the operational phase. Several examples of PRA related applications and observed lessons are included.
Validation of technologies developed for loss of control (LOC) prevention and recovery poses 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 validation framework 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). This paper summarizes a proposed validation framework for safety-critical systems, provides an overview of validation methods and tools developed by NASA to date within the Vehicle Systems Safety Project, and develops a preliminary set of test scenarios for the validation of technologies for LOC prevention and recovery
The investigation of the possible development of two optical devices, one to take two images as inputs and to present their arithmetic sum as a single output, the other to take one image as input and present two identical images as outputs is described. Significant engineering time was invested in establishing precision fiber optics drawing capabilities, real time monitoring of the fiber size and exact measuring of fiber optics ribbons. Various assembly procedures and tooling designs were investigated and prototype models were built and evaluated that established technical assurance that the device was feasible and could be fabricated. Although the interleaver specification in its entirety was not achieved, the techniques developed in the course of the program improved the quality of images transmitted by fiber optic arrays by at least an order of magnitude. These techniques are already being applied to the manufacture of precise fiber optic components.
The research is directed towards the design and implementation of a comprehensive deductive environment for the development of high-assurance systems, especially reactive (concurrent, real-time, and hybrid) systems. Reactive systems maintain an ongoing interaction with their environment, and are among the most difficult to design and verify. The project aims to provide engineers with a wide variety of tools within a single, general, formal framework in which the tools will be most effective. The entire development process is considered, including the construction, transformation, validation, verification, debugging, and maintenance of computer systems. The goal is to automate the process as much as possible and reduce the errors that pervade hardware and software development.
Ceramic matrix composites are being evaluated as candidate materials for many high temperature applications such as engine combustor liners for the High-Speed Civil Transport (HSCT). They are required to have an assured life of several thousand hours. Estimating the reliability of these components is quite a complex process and requires knowledge of the uncertainties that occur at various scales. The properties of ceramic matrix composites (CMC) are known to display a considerable amount of scatter due to variations in fiber/matrix properties, interphase/coating properties, bonding, amount of matrix voids, and many geometry- and fabrication-related parameters such as ply thickness and ply orientations. The objective of this research effort is to account for these uncertainties in a formal way by probabilistically analyzing both the stiffness- and strength related properties of CMC's. In current deterministic approaches, uncertainties are usually accounted for by safety factors. This approach often yields overly conservative designs, thereby reducing the potential of many advanced composite materials.
Quality assurance programs provide a very effective means to monitor and evaluate medical care. Quality assurance involves: (1) Identify a problem; (2) Determine the source and nature of the problem; (3) Develop policies and methods to effect improvement; (4) Implement those polices; (5) Monitor the methods applied; and (6) Evaluate their effectiveness. Because this definition of quality assurance so closely resembles the Nursing Process, the health unit staff was able to use their knowledge of the nursing process to develop many forms which improve the quality of patient care. These forms include the NASA DFRC Service Report, the occupational injury form (Incident Report), the patient survey (Pre-hospital Evaluation/Care Report), the Laboratory Log Sheet, the 911 Run Sheet, and the Patient Assessment Stamp. Examples and steps which are followed to generate these reports are described.
The emergence of model-based engineering is transforming design and analysis methodologies [5]. A recognized benefit of model-based engineering is the existence of a “single source of truth” about the system that becomes the authoritative source of data and information for designers, analysts, and developers. This promotes consistency and efficiency as the design emerges and can be used to further optimize the design. Integrating System Safety Engineers to the “single source of truth” will ensure that the outputs of their assessments and analyses are relevant to the design as it evolves. Use of an integrated system model enables near immediate evaluation of a design change as well as development of operational processes for risk assessment and communication. Such models can enable efficient and timely analysis of system hazards (e.g., hazard fault tree analysis and procedure simulations) and produce complete, accurate, and more consistent products (e.g., hazard reports and safety requirement evaluations). Therefore, an agency-sponsored team at Goddard Space Flight Center (GSFC) recently completed a System Safety Study of modeling and testing capabilities as part of a Model-Based Safety and Mission Assurance Initiative (MBSMAI). Using an existing model developed for reliability analyses [1], GSFC modeling and system safety experts performed system safety analysis/modeling and produced safety products. The team evaluated model-based feasibility to support System Safety Engineering, developed safety analysis modeling processes, and identified tool capability advancement/development needs. These study results indicate model-based engineering is valid and useable for System
A reassessment of the Assurance Processes regarding spacecraft is underway at JPL. Missions are more difficult, funding is constrained, and development guidelines are different. It is necessary to separate the nice-to-do tasks from the required tasks. We need to determine what we are doing, how well we are doing it, and what we should be doing. Tools to be used are reports of flight anomolies, reports of preflight test anomolies, evaluations of flight performance, and studies of the management of risk during development and performance stages and within programmatic realms.
This report explores the current state of the art of Safety and Mission Assurance (S&MA) in projects that have shifted towards Model Based Systems Engineering (MBSE). Its goal is to provide insight into how NASA’s Office of Safety and Mission Assurance (OSMA) should respond to this shift. In MBSE, systems engineering information is organized and represented in models: rigorous computer-based representations, which collectively make many activities easier to perform, less error prone, and scalable. S&MA practices must shift accordingly. The “Objective Structure Hierarchies” recently developed by OSMA provide the framework for understanding this shift. Although the objectives themselves will remain constant, S&MA practices (activities, processes, tools) to achieve them are subject to change. This report presents insights derived from literature studies and interviews. The literature studies gleaned assurance implications from reports of space-related applications of MBSE. The interviews with knowledgeable S&MA and MBSE personnel discovered concerns and ideas for how assurance may adapt. Preliminary findings and observations are presented on the state of practice of S&MA with respect to MBSE, how it is already changing, and how it is likely to change further. Finally, recommendations are provided on how to foster the evolution of S&MA to best fit with MBSE.
This presentation gives an overview of the technology, methods and processes developed during the TC3 Technical Challenge of the System-Wide Safety (SWS) project. The presentation goes over the motivation for doing this research, gives an overview of the tool, methods and process developed under this program, and describes case studies and impact in industry.
The historical evolution of NASA's interest in quantitative measures of reliability assessment is outlined. The introduction of some quantitative methodologies into the Vehicle Reliability Branch of the Safety, Reliability and Quality Assurance (SR and QA) Division at Johnson Space Center (JSC) was noted along with the development of the Extended Orbiter Duration--Weakest Link study which will utilize quantitative tools for a Bayesian statistical analysis. Extending the earlier work of NASA sponsor, Richard Heydorn, researchers were able to produce a consistent Bayesian estimate for the reliability of a component and hence by a simple extension for a system of components in some cases where the rate of failure is not constant but varies over time. Mechanical systems in general have this property since the reliability usually decreases markedly as the parts degrade over time. While they have been able to reduce the Bayesian estimator to a simple closed form for a large class of such systems, the form for the most general case needs to be attacked by the computer. Once a table is generated for this form, researchers will have a numerical form for the general solution. With this, the corresponding probability statements about the reliability of a system can be made in the most general setting. Note that the utilization of uniform Bayesian priors represents a worst case scenario in the sense that as researchers incorporate more expert opinion into the model, they will be able to improve the strength of the probability calculations.