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Bayesian Inference for NASA Probabilistic Risk and Reliability Analysis

This document, Bayesian Inference for NASA Probabilistic Risk and Reliability Analysis, is intended to provide guidelines for the collection and evaluation of risk and reliability-related data. It is aimed at scientists and engineers familiar with risk and reliability methods and provides a hands-on approach to the investigation and application of a variety of risk and reliability data assessment methods, tools, and techniques. This document provides both: A broad perspective on data analysis collection and evaluation issues. A narrow focus on the methods to implement a comprehensive information repository. The topics addressed herein cover the fundamentals of how data and information are to be used in risk and reliability analysis models and their potential role in decision making. Understanding these topics is essential to attaining a risk informed decision making environment that is being sought by NASA requirements and procedures such as 8000.4 (Agency Risk Management Procedural Requirements), NPR 8705.05 (Probabilistic Risk Assessment Procedures for NASA Programs and Projects), and the System Safety requirements of NPR 8715.3 (NASA General Safety Program Requirements).

Dezfuli, Homayoon↗

Addressing Uniqueness and Unison of Reliability and Safety for a Better Integration

Over time, it has been observed that Safety and Reliability have not been clearly differentiated, which leads to confusion, inefficiency, and, sometimes, counter-productive practices in executing each of these two disciplines. It is imperative to address this situation to help Reliability and Safety disciplines improve their effectiveness and efficiency. The paper poses an important question to address, "Safety and Reliability - Are they unique or unisonous?" To answer the question, the paper reviewed several most commonly used analyses from each of the disciplines, namely, FMEA, reliability allocation and prediction, reliability design involvement, system safety hazard analysis, Fault Tree Analysis, and Probabilistic Risk Assessment. The paper pointed out uniqueness and unison of Safety and Reliability in their respective roles, requirements, approaches, and tools, and presented some suggestions for enhancing and improving the individual disciplines, as well as promoting the integration of the two. The paper concludes that Safety and Reliability are unique, but compensating each other in many aspects, and need to be integrated. Particularly, the individual roles of Safety and Reliability need to be differentiated, that is, Safety is to ensure and assure the product meets safety requirements, goals, or desires, and Reliability is to ensure and assure maximum achievability of intended design functions. With the integration of Safety and Reliability, personnel can be shared, tools and analyses have to be integrated, and skill sets can be possessed by the same person with the purpose of providing the best value to a product development.

Huang, Zhaofeng↗

Improving Our Odds: Success through Continuous Risk Management

Launching a rocket, running a business, driving to work and even day-to-day living all involve some degree of risk. Risk is ever present yet not always recognized, adequately assessed and appropriately mitigated. Identification, assessment and mitigation of risk are elements of the risk management component of the "continuous improvement" way of life that has become a hallmark of successful and progressive enterprises. While the application of risk management techniques to provide continuous improvement may be detailed and extensive, the philosophy, ideals and tools can be beneficially applied to all situations. Experiences with the use of risk identification, assessment and mitigation techniques for complex systems and processes are described. System safety efforts and tools used to examine potential risks of the Ares I First Stage of NASA s new Constellation Crew Launch Vehicle (CLV) presently being designed are noted as examples. Recommendations from lessons learned are provided for the application of risk management during the development of new systems as well as for the improvement of existing systems. Lessons learned and suggestions given are also examined for applicability to simple systems, uncomplicated processes and routine personal daily tasks. This paper informs the reader of varied uses of risk management efforts and techniques to identify, assess and mitigate risk for improvement of products, success of business, protection of people and enhancement of personal life.

Greenhalgh, Phillip O.↗

Testing of Advanced Capabilities to Enable In-time Safety Management and Assurance for Future Flight Operations

In order to refine an initial Concept of Operations, explore Concepts of Use, and expose/validate requirements for future In-Time Aviation Safety Management Systems (IASMS), testing architectures were created, along with a set of capabilities and underlying information exchange protocols. These systems were conceived and developed based on hazards associated with two envisioned urban area flight domains: (1) highly autonomous small uncrewed aerial systems (sUAS) operating at low altitudes, and (2) highly autonomous air taxis. The initial scope of this development is described in [1]; this report provides an update, focusing on the subsequent developments and test activities. As stated in [1], it is important to note that there are many capabilities already in use by the industry (or soon to be in use) that will play critical roles in future IASMS designs. Those reported here were developed to address a gap in the current state-of-the-art regarding specific hazards/risks, and/or to allow for investigation of the interplay between and across hazard types — particularly regarding how overall safety risk can be reduced or managed effectively. Results of testing and development activities are organized by the operational phase wherein a particular capability would be employed (i.e., preflight, in-flight, and post-flight/off-line). Pre-flight: A set of capabilities were developed to help mitigate safety risk prior to flight (e.g., during flight and mission planning). Results of testing summarize (1) validation activities to raise the Technology Readiness Level (TRL) and (2) evaluation activities where the capabilities were applied to flight/mission planning procedures and used by operators/pilots. For the latter, flight plans were automatically assessed, and operators/pilots were notified of hazardous flight segments so as to enable adjustment of the flight plan and re-evaluation, and/or to better inform go/no-go decisions. Capabilities addressed hazards associated with power consumption, third-party risk, wind, navigation system performance, radiofrequency interference, and proximity to geo-spatial threats (e.g., buildings, trees, and no-fly zones). In-flight: Flight experiments tested capabilities that detect and respond to hazards encountered during flight. In the first series, safety hazards were monitored and assessed onboard, and system-generated mitigation maneuvers were recorded (but not acted upon by the vehicle). In the second series, mitigation maneuver commands directed the aircraft in response to safety hazards (i.e., auto-mitigation). The sUAS used for testing is described in full, as is the test architecture, which included commercial avionics, research avionics, and onboard software designed to detect, assess, and respond to hazards. The onboard system was designed as a run-time assurance framework, consistent with [2] and supportive of both supervisory and automated modes. The primary functions included: real-time risk assessment (RTRA), auto-pilot monitoring, constraint monitoring, and contingency select/triggering. RTRA performs integrated risk assessment considering data from several hazard-related monitors (e.g., battery, motors, navigation, communications, population density, and loss-of-control). Post-flight/off-line: Data monitored and recorded during flights can enable IASMS capabilities that execute after flights have completed (or “off-line”). These include: (1) the ability to identify anomalies and trends that may only be observable when comparing data spanning a number of similar flights; (2) the ability to update and validate pre-flight and in-flight capabilities and any underlying models to improve their performance; (3) the ability to report anomalies/off-nominals that may indicate design changes or maintenance actions are needed; and (4) the ability for humans involved in operations to report safety-relevant observations to help in understanding the flight data and/or the operational context of a flight. Progress on three such capabilities is summarized; the first investigates anomaly detection given a limited set of flight logs and applies an approach previously used for space operations. The second explores what could be identified using a larger set of flight logs, including from web-based forums where flight logs are posted by sUAS autopilot users. The third creates a new means of collecting information on UAS incidents and accidents via the Aviation Safety Reporting System (ASRS).

sUAS↗

Reliability and Safety Assessment of Urban Air Mobility Concept Vehicles

The primary objective of this research effort is to identify failure modes and hazards associated with several configurations of multicopter concept vehicles supplied by NASA. Functional hazard analyses (FHA) and failure modes and effects criticality analyses (FMECA) are performed for each of the eight vehicle configurations under review. Conceptual design of notional powertrain configurations (turboshaft, electric, hybrid electric), notional thrust control systems (rpm control and collective control), and navigation control systems for the concept vehicles were to support the reliability and safety analysis and to assess whether a mission can be completed safely. Two kinds of analyses are performed: static safety analysis which enable the quantification of the likelihood of individual events, and dynamic safety analyses which allows the investigation of multiple time-dependent failures. Their objective is to quantify the likelihood of catastrophic failures.

Urban Air Mobility↗

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Information about past engineering failures in natural language format presents one possible solution by enabling the retrieval of information that can inform new designs. However, identifying documents containing usable information and extracting the required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing (NLP) framework is proposed to discover relevant knowledge from documents containing failure-related design information. The framework is applied to NASA’s Lessons Learned Information System (LLIS),which is publicly available. Documents containing usable information are filtered using two different NLP-based models. Next, from the identified usable documents, a failure taxonomy is extracted using a partitioned hierarchical topic modeling approach. Partitions of the document describe different sections of the failure taxonomy – i.e., failure, cause of failure, and recommendations – as indicated by the structure of the original document. The extracted failure taxonomy can be leveraged in early design failure assessment methods. Moreover, the framework can be used to identify documents containing usable failure-related design information from other databases and extract relevant information from these documents.

Documentation and Information Science↗

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Information about past engineering failures in natural language format presents one possible solution by enabling the retrieval of information that can inform new designs. However, identifying documents containing usable information and extracting the required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing (NLP) framework is proposed to discover relevant knowledge from documents containing failure-related design information. The framework is applied to NASA’s Lessons Learned Information System (LLIS),which is publicly available. Documents containing usable information are filtered using two different NLP-based models. Next, from the identified usable documents, a failure taxonomy is extracted using a partitioned hierarchical topic modeling approach. Partitions of the document describe different sections of the failure taxonomy – i.e., failure, cause of failure, and recommendations – as indicated by the structure of the original document. The extracted failure taxonomy can be leveraged in early design failure assessment methods. Moreover, the framework can be used to identify documents containing usable failure-related design information from other databases and extract relevant information from these documents.

Documentation and Information Science↗

Liquid and Solid Propulsion Systems Attributes - Unique, Common and Complementary

In this study, attributes are described for solid and liquid propulsion systems based on historical data. This study is not intended to compare liquid and solid propulsion system attributes, rather to present options for their use in various mission scenarios. US launch vehicle data from 1970 to 2008 was analyzed to assess solid and liquid propulsion development cost and schedule characteristics, performance features, and safety and mission success attributes. The study assessed historical trends for liquid and solid systems, and investigated implications of those trends. It was found that the two propulsion technologies have unique, common and complementary attributes that can be leveraged to meet mission requirements.

Cannon, James L.↗

U.S. Space Station Freedom waste fluid disposal system with consideration of hydrazine waste gas injection thrusters

The results are reported of a study of various methods for propulsively disposing of waste gases. The options considered include hydrazine waste gas injection, resistojets, and eutectic salt phase change heat beds. An overview is given of the waste gas disposal system and how hydrozine waste gas injector thruster is implemented within it. Thruster performance for various gases are given and comparisons with currently available thruster models are made. The impact of disposal on station propellant requirements and electrical power usage are addressed. Contamination effects, reliability and maintainability assessments, safety issues, and operational scenarios of the waste gas thruster and disposal system are considered.

Winters, Brian A.↗

NASA Exploration Systems Maintainability Standards for Artemis and Beyond

This assessment was requested by the NASA Engineering and Safety Center (NESC), which, based on findings from the NESC study “Safe Human Expeditions Beyond Low Earth Orbit (LEO)” (Valinia et al., 2022), determined its topic to be an underrecognized critical and urgent Agency need, due to impending Artemis vehicle procurements. The principal objective of this assessment was to review and update current Agency-level maintainability requirements for space systems to support crew on expeditions beyond LEO in both preventive and corrective maintenance. This report contains the results of the NESC assessment.

Orbital Replacement Units↗

Risk-Significant Adverse Condition Awareness Strengthens Assurance of Fault Management Systems

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.

IV&V↗

Risk-Significant Adverse Condition Awareness Strengthens Assurance of Fault Management Systems

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.

Fault management↗

Wind Shear/Turbulence Inputs to Flight Simulation and Systems Certification

The purpose of the workshop was to provide a forum for industry, universities, and government to assess current status and likely future requirements for application of flight simulators to aviation safety concerns and system certification issues associated with wind shear and atmospheric turbulence. Research findings presented included characterization of wind shear and turbulence hazards based on modeling efforts and quantitative results obtained from field measurement programs. Future research thrusts needed to maximally exploit flight simulators for aviation safety application involving wind shear and turbulence were identified. The conference contained sessions on: Existing wind shear data and simulator implementation initiatives; Invited papers regarding wind shear and turbulence simulation requirements; and Committee working session reports.

Bowles, Roland L.↗

Environmental, health and safety assessment of photovoltaics

The environmental, health, and safety (E, H and S) concerns associated with the fabrication, deployment, and decommissioning of photovoltaic (PV) systems in terrestial applications are identified and assessed. Discussion is limited to crystalline silicon technologies. The primary E, H, and S concerns that arise during collector fabrication are associated with occupational exposure to materials of undetermined toxicity or to materials that are known to be hazardous, but for which process control technology may be inadequate. Stricter exposure standards are anticipated for some materials and may indicate a need for further control technology development. Minimizing electric shock hazards is a significant concern during system construction, operation and maintenance, and decommissioning.

Rose, E. C.↗

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Text-based information about past engineering failures presents one possible solution by facilitating the retrieval of information that can inform new designs. However, identifying documents containing relevant information and extracting required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing-based framework is proposed to discover relevant knowledge from documents containing failure-related design information. Documents containing usable information are filtered using sentiment analysis based on a custom lexicon specialized for engineering design and by filtering out documents containing only irrelevant topics. Next, from the identified usable documents, information relating to engineering failures, contributing factors that can be controlled at design time (“risk factors”), and recommended preventative actions are extracted. Semantic similarity is then used to group similar pieces of extracted information for improved generalizability. The proposed framework is applied to NASA’s Lessons Learned Information System (LLIS). The framework can be used to identify documents containing usable failure-related design information from other databases, extract relevant information from these documents, and generalize the acquired knowledge such that it can be applied to novel systems.

Sequoia R. Andrade↗

Closing the Certification Gaps in Adaptive Flight Control Software

Over the last five decades, extensive research has been performed to design and develop adaptive control systems for aerospace systems and other applications where the capability to change controller behavior at different operating conditions is highly desirable. Although adaptive flight control has been partially implemented through the use of gain-scheduled control, truly adaptive control systems using learning algorithms and on-line system identification methods have not seen commercial deployment. The reason is that the certification process for adaptive flight control software for use in national air space has not yet been decided. The purpose of this paper is to examine the gaps between the state-of-the-art methodologies used to certify conventional (i.e., non-adaptive) flight control system software and what will likely to be needed to satisfy FAA airworthiness requirements. These gaps include the lack of a certification plan or process guide, the need to develop verification and validation tools and methodologies to analyze adaptive controller stability and convergence, as well as the development of metrics to evaluate adaptive controller performance at off-nominal flight conditions. This paper presents the major certification gap areas, a description of the current state of the verification methodologies, and what further research efforts will likely be needed to close the gaps remaining in current certification practices. It is envisioned that closing the gap will require certain advances in simulation methods, comprehensive methods to determine learning algorithm stability and convergence rates, the development of performance metrics for adaptive controllers, the application of formal software assurance methods, the application of on-line software monitoring tools for adaptive controller health assessment, and the development of a certification case for adaptive system safety of flight.

Jacklin, Stephen A.↗

Understanding Pilot Breathing – A Case Study in Systems Engineering

This position paper assesses the Pilot Breathing Assessment’s driving requirement to collect missing data on pilot breathing pressure, flow, rate, oxygen and CO2, simultaneously with aircraft data. Repeat measures data were collected over a 2-year period from 5 NASA test-pilots flying 8 flight profiles on NASA F-15 and F/A-18 (A, B) aircraft. This Pilot Breathing Assessment Systems Engineering (PiBASE) position paper serves as a case-study of systems engineering that accommodates the human as a distinct part of the whole. It acknowledges that a successful machine design intended for human use must include human systems biology/physiology as an integral part of planning, design, and implementation.

Pilot Breathing Assessment Systems Engineering↗

Taking the Risk Out of Risk Assessment

The ability to understand risks and have the right strategies in place when risky events occur is essential in the workplace. More and more organizations are being confronted with concerns over how to measure their risks or what kind of risks they can take when certain events transpire that could have a negative impact. NASA is one organization that faces these challenges on a daily basis, as effective risk management is critical to the success of its missions especially the Space Shuttle missions. On July 29, 1996, former NASA Administrator Daniel Goldin charged NASA s Office of Safety and Mission Assurance with developing a probabilistic risk assessment (PRA) tool to support decisions on the funding of Space Shuttle upgrades. When issuing the directive, Goldin said, "Since I came to NASA [in 1992], we've spent billions of dollars on Shuttle upgrades without knowing how much they improve safety. I want a tool to help base upgrade decisions on risk." Work on the PRA tool began immediately. The resulting prototype, the Quantitative Risk Assessment System (QRAS) Version 1.0, was jointly developed by NASA s Marshall Space Flight Center, its Office of Safety and Mission Assurance, and researchers at the University of Maryland. QRAS software automatically expands the reliability logic models of systems to evaluate the probability of highly detrimental outcomes occurring in complex systems that are subject to potential accident scenarios. Even in its earliest forms, QRAS was used to begin PRA modeling of the Space Shuttle. In parallel, the development of QRAS continued, with the goal of making it a world-class tool, one that was especially suited to NASA s unique needs. From the beginning, an important conceptual goal in the development of QRAS was for it to help bridge the gap between the professional risk analyst and the design engineer. In the past, only the professional risk analyst could perform, modify, use, and perhaps even adequately understand PRA. NASA wanted to change this by developing a PRA tool that would be friendlier, more understandable, and more useful to the broader engineering community. This concept ultimately led to the look, feel, and functionality that QRAS has today.

Source record↗