Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “System safety”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Tracing NASA Contributions Toward Aviation Safety Stakeholder Guidance

The System-Wide Safety project at NASA is developing the concept and a subset of supporting technologies for evolving safety management from a post-accident iterative improvement on safety performed by large commercial operators only to predictive and increasingly autonomous safety functions that are performed during operations across vehicles, airports, and services. The system of interest is the In-time Aviation Safety Management System (IASMS), recommended by the National Academies for NASA to develop the concept in coordination with the broad and diverse community of stakeholders in aviation safety. Because the system context is the airspace and aviation industry, it is important to create and maintain traceability from the research work and system architecture elements developed at NASA to community-created roadmaps and aviation agency guidance.

IASMS↗
NASA NTRS1994

Analyzing Software Errors in Safety-Critical Embedded Systems

This paper analyzes the root causes of safty-related software faults identified as potentially hazardous to the system are distributed somewhat differently over the set of possible error causes than non-safety-related software faults.

Software errors↗
NASA NTRS2013

System Driven Workarounds

The Aviation Safety Reporting System (ASRS) in a partnership between the National Aeronautics and Space Administration (NASA), the Federal Aviation Administration (FAA), participating carriers, and labor organizations. It is designed to improve the National Airspace System by collecting and studying reports detailing unsafe conditions and events in the aviation industry. Employees are able to report safety issues or concerns with confidentiality and without fear of discipline. Safety reports highlighting system driven workarounds for the aviation community highlight the human workaround for the complex aviation system.

aviation safety↗
NASA NTRS2007

NASA's Software Safety Standard

NASA relies more and more on software to control, monitor, and verify its safety critical systems, facilities and operations. Since the 1960's there has hardly been a spacecraft launched that does not have a computer on board that will provide command and control services. There have been recent incidents where software has played a role in high-profile mission failures and hazardous incidents. For example, the Mars Orbiter, Mars Polar Lander, the DART (Demonstration of Autonomous Rendezvous Technology), and MER (Mars Exploration Rover) Spirit anomalies were all caused or contributed to by software. The Mission Control Centers for the Shuttle, ISS, and unmanned programs are highly dependant on software for data displays, analysis, and mission planning. Despite this growing dependence on software control and monitoring, there has been little to no consistent application of software safety practices and methodology to NASA's projects with safety critical software. Meanwhile, academia and private industry have been stepping forward with procedures and standards for safety critical systems and software, for example Dr. Nancy Leveson's book Safeware: System Safety and Computers. The NASA Software Safety Standard, originally published in 1997, was widely ignored due to its complexity and poor organization. It also focused on concepts rather than definite procedural requirements organized around a software project lifecycle. Led by NASA Headquarters Office of Safety and Mission Assurance, the NASA Software Safety Standard has recently undergone a significant update. This new standard provides the procedures and guidelines for evaluating a project for safety criticality and then lays out the minimum project lifecycle requirements to assure the software is created, operated, and maintained in the safest possible manner. This update of the standard clearly delineates the minimum set of software safety requirements for a project without detailing the implementation for those requirements. This allows the projects leeway to meet these requirements in many forms that best suit a particular project's needs and safety risk. In other words, it tells the project what to do, not how to do it. This update also incorporated advances in the state of the practice of software safety from academia and private industry. It addresses some of the more common issues now facing software developers in the NASA environment such as the use of Commercial-Off-the-Shelf Software (COTS), Modified OTS (MOTS), Government OTS (GOTS), and reused software. A team from across NASA developed the update and it has had both NASA-wide internal reviews by software engineering, quality, safety, and project management. It has also had expert external review. This presentation and paper will discuss the new NASA Software Safety Standard, its organization, and key features. It will start with a brief discussion of some NASA mission failures and incidents that had software as one of their root causes. It will then give a brief overview of the NASA Software Safety Process. This will include an overview of the key personnel responsibilities and functions that must be performed for safety-critical software.

Ramsay, Christopher M.↗
NASA NTRS2018

Considerations in Assuring Safety of Increasingly Autonomous Systems

Recent technological advances have accelerated the development and application of increasingly autonomous (IA) systems in civil and military aviation. IA systems can provide automation of complex mission tasks-ranging across reduced crew operations, air-traffic management, and unmanned, autonomous aircraft-with most applications calling for collaboration and teaming among humans and IA agents. IA systems are expected to provide benefits in terms of safety, reliability, efficiency, affordability, and previously unattainable mission capability. There is also a potential for improving safety by removal of human errors. There are, however, several challenges in the safety assurance of these systems due to the highly adaptive and non-deterministic behavior of these systems, and vulnerabilities due to potential divergence of airplane state awareness between the IA system and humans. These systems must deal with external sensors and actuators, and they must respond in time commensurate with the activities of the system in its environment. One of the main challenges is that safety assurance, currently relying upon authority transfer from an autonomous function to a human to mitigate safety concerns, will need to address their mitigation by automation in a collaborative dynamic context. These challenges have a fundamental, multidimensional impact on the safety assurance methods, system architecture, and V&V capabilities to be employed. The goal of this report is to identify relevant issues to be addressed in these areas, the potential gaps in the current safety assurance techniques, and critical questions that would need to be answered to assure safety of IA systems. We focus on a scenario of reduced crew operation when an IA system is employed which reduces, changes or eliminates a human's role in transition from two-pilot operations.

Alves, Erin E.↗
NASA NTRS1995

EVA safety: Space suit system interoperability

The results and the recommendations of the International Academy of Astronautics extravehicular activities (IAA EVA) Committee work are presented. The IAA EVA protocols and operation were analyzed for harmonization procedures and for the standardization of safety critical and operationally important interfaces. The key role of EVA and how to improve the situation based on the identified EVA space suit system interoperability deficiencies were considered.

Skoog, A. I.↗
NASA NTRS2020

Ellicott City Disasters II: Enhancing a Statistical Flood Risk Model to Continue Improving Early Warning Systems and Public Safety in Ellicott City, Maryland

As flooding events in the United States grow in frequency and intensity, the use of technological advancements and applied science are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters II project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, the project improved the original statistical flood risk model, FLuME (Flood Learning Model Environment), programmed by the first DEVELOP term. The enhancements incorporated an additional six years of precipitation and soil moisture data from the North American Land Data Assimilation System (NLDAS), modeled using Aqua Advanced Microwave Scanning Radiometer for EOS and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager. These Earth observations were supplemented by stream gauge data from the OEM and the US Geological Survey. The resultant flood risk model FLASH (Flood Learning Environment and Severity Assessment Hub) was trained to evaluate input variables and predict stage height in Ellicott City in real time. The addition of an advanced deep learning framework known as long short-term memory improved the model’s ability to capture relationships between variables. To assess the effectiveness of the new model, FLASH produced a model efficiency metric of 0.99, a significant improvement over the 0.85 value produced by the previous model. The project assisted the OEM in pursuing the integration of open data and NASA Earth observations into a threat matrix capable of informing near real-time decision making.

Disasters↗
NASA NTRS2020

Ellicott City Disasters II: Enhancing a Statistical Flood Risk Model to Continue Improving Early Warning Systems and Public Safety in Ellicott City, Maryland

As flooding events in the United States grow in frequency and intensity, the use of technological advancements and applied science are increasingly necessary for effective flood monitoring and warning systems. The NASA DEVELOP Ellicott City Disasters II project investigated the use of machine learning for applications in flood risk detection to support the improvement of early warning systems. To strengthen the efforts of the Howard County Office of Emergency Management (OEM) in building a more robust flood monitoring system, the project improved the original statistical flood risk model, FLuME (Flood Learning Model Environment), programmed by the first DEVELOP term The enhancements incorporated an additional six years of precipitation and soil moisture data from the North American Land Data Assimilation System (NLDAS), modeled using Aqua Advanced Microwave Scanning Radiometer for EOS and Tropical Rainfall Measuring Mission TRMM Microwave Imager. These Earth observations were supplemented by stream gauge data from the OEM and the US Geological Survey. The resultant flood risk model FLASH (Flood Learning Environment and Severity Assessment Hub) was trained to evaluate input variables and predict stage height in Ellicott City in real time. The addition of an advanced deep learning framework known as long short-term memory improved the model’s ability to capture relationships between variables. To assess the effectiveness of the new model, FLASH produced a model efficiency metric of 0.99, a significant improvement over the 0.85 value produced by the previous model. The project assisted the OEM in pursuing the integration of open data and NASA Earth observations into a threat matrix capable of informing near real-time decision making.

Disasters↗
NASA NTRS1984

Human factors in aircraft incidents - Results of a 7-year study (Andre Allard Memorial Lecture)

It is pointed out that nearly all fatal aircraft accidents are preventable, and that most such accidents are due to human error. The present discussion is concerned with the results of a seven-year study of the data collected by the NASA Aviation Safety Reporting System (ASRS). The Aviation Safety Reporting System was designed to stimulate as large a flow as possible of information regarding errors and operational problems in the conduct of air operations. It was implemented in April, 1976. In the following 7.5 years, 35,000 reports have been received from pilots, controllers, and the armed forces. Human errors are found in more than 80 percent of these reports. Attention is given to the types of events reported, possible causal factors in incidents, the relationship of incidents and accidents, and sources of error in the data. ASRS reports include sufficient detail to permit authorities to institute changes in the national aviation system designed to minimize the likelihood of human error, and to insulate the system against the effects of errors.

Billings, C. E.↗
NASA NTRS1992

European Workshop Industrical Computer Science Systems approach to design for safety

This paper presents guidelines on designing systems for safety, developed by the Technical Committee 7 on Reliability and Safety of the European Workshop on Industrial Computer Systems. The focus is on complementing the traditional development process by adding the following four steps: (1) overall safety analysis; (2) analysis of the functional specifications; (3) designing for safety; (4) validation of design. Quantitative assessment of safety is possible by means of a modular questionnaire covering various aspects of the major stages of system development.

Zalewski, Janusz↗
NASA NTRS1997

NASA Software Safety Standard

If software is a critical element in a safety critical system, it is imperative to implement a systematic approach to software safety as an integral part of the overall system safety programs. The NASA-STD-8719.13A, "NASA Software Safety Standard", describes the activities necessary to ensure that safety is designed into software that is acquired or developed by NASA, and that safety is maintained throughout the software life cycle. A PDF version, is available on the WWW from Lewis. A Guidebook that will assist in the implementation of the requirements in the Safety Standard is under development at the Lewis Research Center (LeRC). After completion, it will also be available on the WWW from Lewis.

Rosenberg, Linda↗
NASA NTRS2008

Advanced Control System Increases Helicopter Safety

With support and funding from a Phase II NASA SBIR project from Ames Research Center, Hoh Aeronautics Inc. (HAI), of Lomita, California, produced HeliSAS, a low-cost, lightweight, attitude-command-attitude-hold stability augmentation system (SAS) for civil helicopters and unmanned aerial vehicles. HeliSAS proved itself in over 160 hours of flight testing and demonstrations in a Robinson R44 Raven helicopter, a commercial helicopter popular with news broadcasting and police operations. Chelton Flight Systems, of Boise, Idaho, negotiated with HAI to develop, market, and manufacture HeliSAS, now available as the Chelton HeliSAS Digital Helicopter Autopilot.

Source record↗
NASA NTRS2008

Safer Systems: A NextGen Aviation Safety Strategic Goal

The Joint Planning and Development Office (JPDO), is charged by Congress with developing the concepts and plans for the Next Generation Air Transportation System (NextGen). The National Aviation Safety Strategic Plan (NASSP), developed by the Safety Working Group of the JPDO, focuses on establishing the goals, objectives, and strategies needed to realize the safety objectives of the NextGen Integrated Plan. The three goal areas of the NASSP are Safer Practices, Safer Systems, and Safer Worldwide. Safer Practices emphasizes an integrated, systematic approach to safety risk management through implementation of formalized Safety Management Systems (SMS) that incorporate safety data analysis processes, and the enhancement of methods for ensuring safety is an inherent characteristic of NextGen. Safer Systems emphasizes implementation of safety-enhancing technologies, which will improve safety for human-centered interfaces and enhance the safety of airborne and ground-based systems. Safer Worldwide encourages coordinating the adoption of the safer practices and safer systems technologies, policies and procedures worldwide, such that the maximum level of safety is achieved across air transportation system boundaries. This paper introduces the NASSP and its development, and focuses on the Safer Systems elements of the NASSP, which incorporates three objectives for NextGen systems: 1) provide risk reducing system interfaces, 2) provide safety enhancements for airborne systems, and 3) provide safety enhancements for ground-based systems. The goal of this paper is to expose avionics and air traffic management system developers to NASSP objectives and Safer Systems strategies.

Darr, Stephen T.↗
NASA NTRS2014

Bayesian Statistics and Uncertainty Quantification for Safety Boundary Analysis in Complex Systems

The analysis of a safety-critical system often requires detailed knowledge of safe regions and their highdimensional non-linear boundaries. We present a statistical approach to iteratively detect and characterize the boundaries, which are provided as parameterized shape candidates. Using methods from uncertainty quantification and active learning, we incrementally construct a statistical model from only few simulation runs and obtain statistically sound estimates of the shape parameters for safety boundaries.

Active Learning↗
NASA NTRS2019

Urban Area Unmanned Aerial Systems Sensor Capabilities for Ensuring Ground Hazards Safety

Unmanned aerial systems (UASs) in urban areas can pose significant safety risks to dynamic ground objects (DGOs) such as people, pets, and bikes; especially for off-nominal emergency traverses and landings. This paper will examine a framework for evaluating the UAS safety benefits which can be achieved by classifying DGO hazards, modeling their behavior, and assigning collision costs. DGOs are assumed to be any ground objects which are either moving or capable of moving. Safety benefits will be assessed by analyzing metrics computed from UAS and DGO trajectories which take into account intent and uncertainties. This paper will establish the theoretical relationships mapping these trajectories and DGO classifications to safety levels. Sensor capabilities will be mapped to DGO trajectory uncertainties, so that safety can be directly estimated from the sensor specifications for a given UAS trajectory.

Bouyssounouse, Xavier↗
NASA NTRS2018

From Formal Requirements to Highly Assured Software for Unmanned Aircraft Systems

Operational requirements of safety-critical systems are often written in restricted specification logics. These restricted logics are amenable to automated analysis techniques such as model-checking, but are not rich enough to express complex requirements of unmanned systems. This short paper advocates for the use of expressive logics, such as higher-order logic, to specify the complex operational requirements and safety properties of unmanned systems. These rich logics are less amenable to automation and, hence, require the use of interactive theorem proving techniques. However, these logics support the formal verification of complex requirements such as those involving the physical environment. Moreover, these logics enable validation techniques that increase con dence in the correctness of numerically intensive software. These features result in highly-assured software that may be easier to certify. The feasibility of this approach is illustrated with examples drawn for NASA's unmanned aircraft systems.

Munoz, Cesar↗
NASA NTRSDate not supplied

AI/ML Components in Safety-Critical Aviation Systems: Selected Concepts and Underlying Principles

The objective of the AI Roadmap meeting is to engage with all stakeholders in aviation in an open conversation about our approach and the guiding principles that can help us in moving forward in the technological landscape of AI/ML. The objective of the Technical Exchange Meeting is to identify categories of safety concerns associated with having an AI component in the aircraft we identified in the previous Technical Exchange Meetings. The speakers will bring their experience to the discussion to stimulate active participation with all stakeholders.

Design Safety↗