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Designing Graceful Degradation into Complex Systems: The Interaction Between Causes of Degradation and the Association with Degradation Prevention and Recovery
System resilience is critical to safety in air traffic control. An important element of maintaining resilience is the ability of systems to degrade gracefully. Of the available graceful degradation research, a majority of studies have focused primarily on technological causes of degradation only, limiting an ecologically valid understanding of the causes of degradation in air traffic control, and the preventative and mitigative strategies that enable graceful degradation. The current study aimed to address this research gap by investigating causes of degradation in air traffic control across the broad categories of technology, the environment, and the human operator, and the potential interactions between these causes. 12 retired controllers participated in semi-structured interviews focused on previous experience of causes of degradation and mitigation strategies. Findings provide an understanding of causation of degradation in air traffic control, and the prevention and mitigation strategies that moderate the relationship between cause and system effect. Findings confirmed that causes appear to interact to create compound, multiple effects on overall system performance. Findings also revealed prevention and mitigation strategies utilized to moderate the effect of the cause on the system. In order to gain an ecologically valid understanding of the causes of degradation, and effective prevention or mitigation strategies, causes from multiple categories, and the interactions between them, must be identified. Findings have implications for designers of future air traffic control systems to ensure the ability of the system to gracefully degrade, as well as risk assessment and system validation processes.
Designing Graceful Degradation into Complex Systems: Identification of Causes of Degradation, Interactions, and Mitigation of Degradation in Air Traffic Control
System resilience is critical to safety in air traffic control. An important element of maintaining resilience is the ability of systems to degrade gracefully. Of the available graceful degradation research, a majority of studies have focused primarily on technological causes of degradation only, limiting an ecologically valid understanding of the causes of degradation in air traffic control, and the preventative and mitigative strategies that enable graceful degradation. The current study aimed to address this research gap by investigating causes of degradation in air traffic control across the broad categories of technology, the environment, and the human operator, and the potential interactions between these causes. 12 retired controllers participated in semi-structured interviews focused on previous experience of causes of degradation and mitigation strategies. Findings provide an understanding of causation of degradation in air traffic control, and the prevention and mitigation strategies that moderate the relationship between cause and system effect. Findings confirmed that causes appear to interact to create compound, multiple effects on overall system performance. Findings also revealed prevention and mitigation strategies utilized to moderate the effect of the cause on the system. In order to gain an ecologically valid understanding of the causes of degradation, and effective prevention or mitigation strategies, causes from multiple categories, and the interactions between them, must be identified. Findings have implications for designers of future air traffic control systems to ensure the ability of the system to gracefully degrade, as well as risk assessment and system validation processes.
Designing Graceful Degradation into Complex Systems: The Interaction Between Causes of Degradation and the Association with Degradation Prevention and Recovery
System resilience is critical to safety in air traffic control. An important element of maintaining resilience is the ability of systems to degrade gracefully. Of the available graceful degradation research, a majority of studies have focused primarily on technological causes of degradation only, limiting an ecologically valid understanding of the causes of degradation in air traffic control, and the preventative and mitigative strategies that enable graceful degradation. The current study aimed to address this research gap by investigating causes of degradation in air traffic control (ATC) across the broad categories of technology, the environment, and the human operator, and the potential interactions between these causes. 12 retired controllers (ATCOs - Air Traffic Control Officers) participated in semi-structured interviews focused on previous experience of causes of degradation and mitigation strategies. Findings provide an understanding of causation of degradation in air traffic control, and the prevention and mitigation strategies that moderate the relationship between cause and system effect. Findings confirmed that causes appear to interact to create compound, multiple effects on overall system performance. Findings also revealed prevention and mitigation strategies utilized to moderate the effect of the cause on the system. In order to gain an ecologically valid understanding of the causes of degradation, and effective prevention or mitigation strategies, causes from multiple categories, and the interactions between them, must be identified. Findings have implications for designers of future air traffic control systems to ensure the ability of the system to gracefully degrade, as well as risk assessment and system validation processes.
Appreciative Methods Applied to the Assessment of Complex Systems
No abstract available
Supply Chain Research & Analysis: Illuminating Risks in Complex Systems
No abstract available
Complex systems science: A new framework for understanding Earth system models
UNKNOWN
Hybrid Modeling for Complex Systems Health Management
The research work presents application of hybrid physics-informed machine learning to a representative electric powertrain for unmanned aerial vehicles. The model is composed of physics-derived and empirical equations, integrated with connected networks that are strategically placed within the model to substitute equations that are subject to large uncertainty. Polynomial fit driven by heuristics or empirical observations can be substituted by more flexible networks that can minimize the error between model predictions and observations without being restricted to a predefined functional form. This modeling strategy allows training of networks deep inside the model and unknown parameters in a single learning stage. The powertrain model consists of Li-ion batteries, electronic speed controller with pulse-width modulation, and brush-less DC motor with connected propeller. Results obtained from combination of laboratory and simulation tests are discussed in this work.
Seeking Structure in Complex Systems: From Feature Analysis to Space-Time Causal Discovery with Earth Science Applications
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Can an Efficient Nuclear Energy Industry Still be Resilient? On the Nature of Efficiency and Resiliency in Complex Systems
At the time of writing, the nuclear industry is on the precipice of a long-hoped for, but as-yet-unrealized, “nuclear renaissance.” Nuclear power plants in the United States and around the globe are aging, emphasizing the criticality of this moment. The importance of carbon free power sources combined with advancements in nuclear technology and innovation have brought a new potential landscape. As existing reactors and utilities cope with increased economic pressure by seeking out efficiencies the push towards novel nuclear platforms like microreactors and fission batteries will only increase this quest for efficiency gains, potentially at the detriment of safety. This paper argues that the concepts of efficiency and resiliency are fundamentally linked and that the change in one necessarily affects the other. As nuclear power is known for being incredibly resilient, this dichotomy needs attention from the current wave of research towards nuclear power efficiencies. This paper argues for resiliency at any cost. We argue that this resilience-first approach is the right path for nuclear power to take in this net-zero future. The paper is laid out as follows. Section 1 introduces the economic context and resilient nature of nuclear power. Section 2 discusses efficiency, resiliency, and the struggle between the two in nuclear power. Section 3 exemplifies our argument through case studies in the aviation and manufacturing industries and extends the argument to the nuclear industry. Section 4 concludes with a discussion of the implications of this idea.
State analysis requirements database for engineering complex embedded systems
It has become clear that spacecraft system complexity is reaching a threshold where customary methods of control are no longer affordable or sufficiently reliable. At the heart of this problem are the conventional approaches to systems and software engineering based on subsystem-level functional decomposition, which fail to scale in the tangled web of interactions typically encountered in complex spacecraft designs. Furthermore, there is a fundamental gap between the requirements on software specified by systems engineers and the implementation of these requirements by software engineers. Software engineers must perform the translation of requirements into software code, hoping to accurately capture the systems engineer's understanding of the system behavior, which is not always explicitly specified. This gap opens up the possibility for misinterpretation of the systems engineer's intent, potentially leading to software errors. This problem is addressed by a systems engineering tool called the State Analysis Database, which provides a tool for capturing system and software requirements in the form of explicit models. This paper describes how requirements for complex aerospace systems can be developed using the State Analysis Database.
Engineering Complex Embedded Systems with State Analysis and the Mission Data System
It has become clear that spacecraft system complexity is reaching a threshold where customary methods of control are no longer affordable or sufficiently reliable. At the heart of this problem are the conventional approaches to systems and software engineering based on subsystem-level functional decomposition, which fail to scale in the tangled web of interactions typically encountered in complex spacecraft designs. Furthermore, there is a fundamental gap between the requirements on software specified by systems engineers and the implementation of these requirements by software engineers. Software engineers must perform the translation of requirements into software code, hoping to accurately capture the systems engineer's understanding of the system behavior, which is not always explicitly specified. This gap opens up the possibility for misinterpretation of the systems engineer s intent, potentially leading to software errors. This problem is addressed by a systems engineering methodology called State Analysis, which provides a process for capturing system and software requirements in the form of explicit models. This paper describes how requirements for complex aerospace systems can be developed using State Analysis and how these requirements inform the design of the system software, using representative spacecraft examples.
A survey of intelligent tutoring systems: Implications for complex dynamic systems
An overview of the research in the field of intelligent tutorial systems (ITS) is provided. The various approaches in the design and implementation of ITS are examined and discussed in the context of problem solving in an environment of a complex dynamic system (CDS). Issues pertaining to a CDS and the nature of human problem solving especially in light of a CDS are considered. An overview of the architecture of an ITS is provided as the basis for the in-depth examination of various systems. Finally, the implications for the design and evaluation of an ITS are discussed.
The role of reliability graph models in assuring dependable operation of complex hardware/software systems
The complexity of computer systems currently being designed for critical applications in the scientific, commercial, and military arenas requires the development of new techniques for utilizing models of system behavior in order to assure 'ultra-dependability'. The complexity of these systems, such as Space Station Freedom and the Air Traffic Control System, stems from their highly integrated designs containing both hardware and software as critical components. Reliability graph models, such as fault trees and digraphs, are used frequently to model hardware systems. Their applicability for software systems has also been demonstrated for software safety analysis and the analysis of software fault tolerance. This paper discusses further uses of graph models in the design and implementation of fault management systems for safety critical applications.
A conceptual model for evolving run time support of mission and safety critical components in large, complex, distributed systems
Large, complex, distributed systems should be evolved to maximize life cycle support for non-stop operation of mission and safety critical components. This paper outlines the key issues and a recommended approach for tailoring a conceptual model of Ada run time support environments to meet the specific needs of such an application. Prerequisite concepts for this model have been described previously by this author and are summarized. This model proposes upward-compatible extensions to a previously published model of Ada run time environments from the ARTEWG (Ada Run Time Environment Working Group). The first model was used to identify Ada run time requirements, dependencies, issues, features, and options for single processor applications; however, the particular needs for distributed processing were not explicitly described. The purpose of this extended model is to address the needed systems software support for Ada application programs in distributed computing environments.
On the relationship between reliability and linear quadratic optimal control
The linear quadratic optimal control method is used today to solve many complex systems problems. As system complexity increases, and as linear quadratic optimal control is used in more demanding situations, the extension of the design methodology to cover system failures, robustness and reliability is of crucial importance. This paper documents the progress toward a theory which incorporates reliability in the performance index; a linear quadratic control problem is formulated which accounts for system effectiveness and gives an offline procedure for comparing two linear quadratic control systems on the basis of both reliability and performance.
Comparison of Spares Logistics Analysis Techniques for Long Duration Human Spaceflight
As the durations and distances involved in human exploration missions increase, the logistics associated with the repair and maintenance becomes more challenging. Whereas the operation of the International Space Station (ISS) depends upon regular resupply from the Earth, this paradigm may not be feasible for future missions. Longer mission durations result in higher probabilities of component failures as well as higher uncertainty regarding which components may fail, and longer distances from Earth increase the cost of resupply as well as the speed at which the crew can abort to Earth in the event of an emergency. As such, mission development efforts must take into account the logistics requirements associated with maintenance and spares. Accurate prediction of the spare parts demand for a given mission plan and how that demand changes as a result of changes to the system architecture enables full consideration of the lifecycle cost associated with different options. In this paper, we utilize a range of analysis techniques - Monte Carlo, semi-Markov, binomial, and heuristic - to examine the relationship between the mass of spares and probability of loss of function related to the Carbon Dioxide Removal System (CRS) for a notional, simplified mission profile. The Exploration Maintainability Analysis Tool (EMAT), developed at NASA Langley Research Center, is utilized for the Monte Carlo analysis. We discuss the implications of these results and the features and drawbacks of each method. In particular, we identify the limitations of heuristic methods for logistics analysis, and the additional insights provided by more in-depth techniques. We discuss the potential impact of system complexity on each technique, as well as their respective abilities to examine dynamic events. This work is the first step in an effort that will quantitatively examine how well these techniques handle increasingly more complex systems by gradually expanding the system boundary.
Reliability models applicable to space telescope solar array assembly system
A complex system may consist of a number of subsystems with several components in series, parallel, or combination of both series and parallel. In order to predict how well the system will perform, it is necessary to know the reliabilities of the subsystems and the reliability of the whole system. The objective of the present study is to develop mathematical models of the reliability which are applicable to complex systems. The models are determined by assuming k failures out of n components in a subsystem. By taking k = 1 and k = n, these models reduce to parallel and series models; hence, the models can be specialized to parallel, series combination systems. The models are developed by assuming the failure rates of the components as functions of time and as such, can be applied to processes with or without aging effects. The reliability models are further specialized to Space Telescope Solar Arrray (STSA) System. The STSA consists of 20 identical solar panel assemblies (SPA's). The reliabilities of the SPA's are determined by the reliabilities of solar cell strings, interconnects, and diodes. The estimates of the reliability of the system for one to five years are calculated by using the reliability estimates of solar cells and interconnects given n ESA documents. Aging effects in relation to breaks in interconnects are discussed.