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Cathode ray oscilloscope displays curves or contours of complex shapes corresponding to sets of x,y coordinates. It requires few storage facilities and produces a rapid display of complex curves with a fewer number of commands than previous systems.
Fatal accident rates in commercial passenger aviation are at historic lows yet have plateaued and are not showing evidence of further safety advances. Modern aircraft accidents reflect both historic causal factors and new unexpected "Black Swan" events. The ever-increasing complexity of the aviation system, along with its associated technology and organizational relationships, provides fertile ground for fresh problems. It is important to take a proactive approach to aviation safety by working to identify novel causation mechanisms for future aviation accidents before they happen. Progress has been made in using of historic data to identify the telltale signals preceding aviation accidents and incidents, using the large repositories of discrete and continuous data on aircraft and air traffic control performance and information reported by front-line personnel. Nevertheless, the aviation community is increasingly embracing predictive approaches to aviation safety. The "prospective workshop" early assessment tool described in this paper represents an approach toward this prospective mindset-one that attempts to identify the future vectors of aviation and asks the question: "What haven't we considered in our current safety assessments?" New causation mechanisms threatening aviation safety will arise in the future because new (or revised) systems and procedures will have to be used under future contextual conditions that have not been properly anticipated. Many simulation models exist for demonstrating the safety cases of new operational concepts and technologies. However the results from such models can only be as valid as the accuracy and completeness of assumptions made about the future context in which the new operational concepts and/or technologies will be immersed. Of course that future has not happened yet. What is needed is a reasonably high-confidence description of the future operational context, capturing critical contextual characteristics that modulate both the likelihood of occurrence of hazards, and the likelihood that those hazards will lead to negative safety events. Heuristics extracted from scenarios, questionnaires, and observed trends from scanning the aviation horizon may be helpful in capturing those future changes in a way conducive to safety assessment. What is also needed is a checklist of potential sources of emerging risk that arise from organizational features that are frequently overlooked. The ultimate goal is to develop a pragmatic, workable method for using descriptions of the future aviation context, to generate valid predictions of safety risks.
Complex autonomous systems capable of successfully operating independently under ‘known unknowns’ and harsh conditions require paradigm innovation in modern development strategies. In the field of autonomy, developing a system-of-systems which can ostensibly think for itself in the face of ‘unknown unknowns’ is still a field of ongoing research. Maturing the systems architecting and modeling methodologies for developing henceforth named Thinking Autonomous Systems, which are verified with digital mission simulation, can potentially usher in the next generation of artificial intelligence for space exploration. The concept presented in this paper incorporates multiple Model-Based Systems Engineering and simulation methodologies combined as a new paradigm to design a novel, biomimetic thinking autonomy strategy. Anachronistic concepts from classical Kantian philosophy will be leveraged to inspire architectural designs that could be used for complex distributed systems in deep space. To accomplish this, digital transformation of a document-based implementation plan for Thinking Autonomous Systems, generated by experienced NASA software engineers, is implemented for NASA’s Platform for Autonomous Systems by creating descriptive and executable software models in SysML to prototype real-time operating capabilities. This conceptual implementation has been developed by incorporating model-based digital simulations to theorize how a cyberphysical thinking system would achieve specific strategies without crew reliance, while simultaneously being resilient to all operating conditions and remaining functional when devoid of ground communication. Additionally, ensuring that an autonomous system framework is an ethical Artificial Intelligence requires careful consideration of system behavior and accountability, human factors for teaming with a thinking autonomous system, and comparison to other modern approaches used for implementing true autonomy. This paper presents the first steps in formalizing the metacognition required for instantiating a truly Thinking Autonomous System; the approach described symphonizes autonomy characteristics from classical philosophical into a unified software architecture describing human thought. In the future, the foundational models described in this paper can be further leveraged to help advance research into thinking autonomy requirements for future deep space missions as well as for current near-term applications, i.e., living aboard crewed spacecraft like a NASA Gateway cislunar habitat.
Accurate simulation of the effects of integrating new technologies into a complex system is critical to the modernization of our antiquated air traffic system, where there exist many layers of interacting procedures, controls, and automation all designed to cooperate with human operators. Additions of even simple new technologies may result in unexpected emergent behavior due to complex human/ machine interactions. One approach is to create high-fidelity human models coming from the field of human factors that can simulate a rich set of behaviors. However, such models are difficult to produce, especially to show unexpected emergent behavior coming from many human operators interacting simultaneously within a complex system. Instead of engineering complex human models, we directly model the emergent behavior by evolving goal directed agents, representing human users. Using evolution we can predict how the agent representing the human user reacts given his/her goals. In this paradigm, each autonomous agent in a system pursues individual goals, and the behavior of the system emerges from the interactions, foreseen or unforeseen, between the agents/actors. We show that this method reflects the integration of new technologies in a historical case, and apply the same methodology for a possible future technology.
Advanced control technologies are not necessary for the safe, reliable and continuous operation of Advanced Life Support (ALS) systems. ALS systems can and are adequately controlled by simple, reliable, low-level methodologies and algorithms. The automation provided by advanced control technologies is claimed to decrease system mass and necessary crew time by reducing buffer size and minimizing crew involvement. In truth, these approaches increase control system complexity without clearly demonstrating an increase in reliability across the ALS system. Unless these systems are as reliable as the hardware they control, there is no savings to be had. A baseline ALS system is presented with the minimal control system required for its continuous safe reliable operation. This baseline control system uses simple algorithms and scheduling methodologies and relies on human intervention only in the event of failure of the redundant backup equipment. This ALS system architecture is designed for reliable operation, with minimal components and minimal control system complexity. The fundamental design precept followed is "If it isn't there, it can't fail".
A FORTRAN IV computer program for the calculation of the thermodynamic and transport properties of complex mixtures is described. The program has the capability of performing calculations such as:(1) chemical equilibrium for assigned thermodynamic states, (2) theoretical rocket performance for both equilibrium and frozen compositions during expansion, (3) incident and reflected shock properties, and (4) Chapman-Jouguet detonation properties. Condensed species, as well as gaseous species, are considered in the thermodynamic calculation; but only the gaseous species are considered in the transport calculations.
Semi-Markov processes have proved to be an effective and convenient tool to construct models of systems that achieve reliability by redundancy and reconfiguration. These models are able to depict complex system architectures and to capture the dynamics of fault arrival and system recovery. A disadvantage of this approach is that the models can be extremely large, which poses both a model and a computational problem. Techniques are needed to reduce the model size. Because these systems are used in critical applications where failure can be expensive, there must be an analytically derived bound for the error produced by the model reduction technique. A model reduction technique called trimming is presented that can be applied to a popular class of systems. Automatic model generation programs were written to help the reliability analyst produce models of complex systems. This method, trimming, is easy to implement and the error bound easy to compute. Hence, the method lends itself to inclusion in an automatic model generator.
Assurance cases are being increasingly acknowledged as a way to build trust in complex systems with autonomous capabilities [1]. An assurance case is a comprehensive, defensible, and valid justification that a system will function as intended for the specific mission and operating environment. Such justifications for systems with autonomous capabilities are often based on various probabilistic quantifications [2]. Due to the dynamic nature of the environmental conditions in which these systems operate, as well as the changing nature of the autonomous systems themselves, these probabilistic quantifications cannot be simply estimated once during design time. Rather, they need to be continually evaluated during systems operations to ensure that the assurance case justifications are valid. We refer to the assurance case that combines both the static and dynamic elements as a Dynamic Assurance Case (DAC). Such complex systems with autonomous capabilities are often deployed with a Ground Control Software (GCS) component to enable remote operation. Whether the system is composed of a single unit or a fleet of units, deployed distributed or in remote environments, GCS acts as a window into the behavior of the deployed system. It receives telemetry from the system, issues commands to the system and provides various functionalities to visualize the system performance. We propose a dynamic assurance framework where the GCS acts as a relay between the autonomous system and its DAC. GCS can be used to measure both unit-specific as well as system-wide probabilistic quantifications using the incoming telemetry. We embed these quantifications throughout the DAC as variables that can be updated by external sources. We use the GCS to periodically update these variables, which allows us to continually evaluate the formally defined assurance case justifications. We demonstrate our dynamic assurance framework in the NASA Ames project Troupe1 that aims at developing a fleet of rovers capable of au- tonomously mapping their environment. The rovers work cooperatively, each collecting data for different parts of the environment. Each rover runs an identical core Flight System (cFS) [4] application. Troupe1 uses OpenC3 Cosmos [5] as the ground system, and AdvoCATE [3] to capture the system DAC. We show how we can measure both rover-specific and system-wide quantifications in Cosmos using its Ruby scripting editor and pass them into the DAC modelled in AdvoCATE. Then, we show how these incoming variables can be embedded in different parts of the DAC and how effects of their updates can be observed
Control of vehicles and other complex systems is a high-level integrative function of the central nervous system (CNS). It requires well-functioning subsystem performance, including good visual acuity, eye-hand coordination, spatial and geographic orientation perception, and cognitive function. Evidence from space flight research demonstrates that the function of each of these subsystems is altered by removing gravity, a fundamental orientation reference, which is sensed by vestibular, proprioceptive, and haptic receptors and used by the CNS for spatial orientation, posture, navigation, and coordination of movements. The available evidence also shows that the degree of alteration of each subsystem depends on a number of crew- and mission-related factors. There is only limited operational evidence that these alterations cause functional impacts on mission-critical vehicle (or complex system) control capabilities. Furthermore, while much of the operational performance data collected during space flight has not been available for independent analysis, those that have been reviewed are somewhat equivocal owing to uncontrolled (and/or unmeasured) environmental and/or engineering factors. Whether this can be improved by further analysis of previously inaccessible operational data or by development of new operational research protocols remains to be seen. The true operational risks will be estimable only after we have filled the knowledge gaps and when we can accurately assess integrated performance in off-nominal operational settings (Paloski et al. 2008). Thus, our current understanding of the Risk of Impaired Control of Spacecraft/Associated Systems and Decreased Mobility Due to Vestibular/Sensorimotor Alterations Associated with Space flight is limited primarily to extrapolation of scientific research findings, and, since there are limited ground-based analogs of the sensorimotor and vestibular changes associated with space flight, observation of their functional impacts is limited to studies performed in the space flight environment. Fortunately, many sensorimotor and vestibular experiments have been performed during and/or after space flight missions since 1959 (Reschke et al. 2007). While not all of these experiments were directly relevant to the question of vehicle/complex system control, most provide insight into changes in aspects of sensorimotor control that might bear on the physiological subsystems underlying this high-level integrated function.
Program is numerical procedure for calculating radiation/geometrical configuration factors and/or space-environmental heat-flux histories. System can accomodate complex systems of diverse geometric shapes residing in unlimited variety of mutual shadow conditions. Basic analytical device is finite-difference employment of unit-sphere method of calculating configuration factors.
The OAO was successfully operating for approximately 11 months and has made over 2500 stellar observations. The OAO control system was a complex system which takes the 4500-lb vehicle through initial stabilization to star tracker control where a pointing accuracy of less than 1 arc minute was achieved. To obtain this pointing accuracy, the system used six orthogonally mounted gimbaled star trackers. The trackers were two gimbaled devices, having a 1-deg field of view with a + or - 43 deg gimbal excursion. The tracker could recognize and track 2.0 magnitude stars or brighter. The flight results indicated spacecraft pointing accuracies of less than 1 arc minute after tracker calibration with spacecraft jitter less than 3 arc seconds.
Accurate dynamic models for propulsion system behavior are critical to successful synthesis of STOL autothrottle/autoland control systems. This paper describes the development of a nonlinear dynamic model for the response of a STOL aircraft in the landing/approach configuration. The model is based upon an analysis of the throttle, governor, and turbofan engine components. Model parameters are directly identified from data acquired during a flight of the NASA Augmentor Wing Jet STOL research aircraft. The accuracy of the model and a comparison of results for two engines are described. Various approaches to modeling propulsion system response for complex systems representative of current and near-term aircraft are discussed.
Demands for nonlinear time history simulations of large, flexible multibody dynamic systems has created a need for efficient interfaces between finite-element modeling programs and time-history simulations. One such interface, TREEFLX, an interface between NASTRAN and TREETOPS, a nonlinear dynamics and controls time history simulation for multibody structures, is presented and demonstrated via example using the proposed Space Station Mobile Remote Manipulator System (MRMS). The ability to run all three programs (NASTRAN, TREEFLX and TREETOPS), in addition to other programs used for controller design and model reduction (such as DMATLAB and TREESEL, both described), under a UNIX Workstation environment demonstrates the flexibility engineers now have in designing, developing and testing control systems for dynamically complex systems.
Deceit, a distributed file system (DFS) being developed at Cornell, focuses on flexible file semantics in relation to efficiency, scalability, and reliability. Deceit servers are interchangeable and collectively provide the illusion of a single, large server machine to any clients of the Deceit service. Non-volatile replicas of each file are stored on a subset of the file servers. The user is able to set parameters on a file to achieve different levels of availability, performance, and one-copy serializability. Deceit also supports a file version control mechanism. In contrast with many recent DFS efforts, Deceit can behave like a plain Sun Network File System (NFS) server and can be used by any NFS client without modifying any client software. The current Deceit prototype uses the ISIS Distributed Programming Environment for all communication and process group management, an approach that reduces system complexity and increases system robustness.
Teleoperation of land vehicles allows the removal of the operator from the vehicle to a remote location. This can greatly increase operator safety and comfort in applications such as security patrol or military combat. The cost includes system complexity and reduced system performance. All feedback on vehicle performance and on environmental conditions must pass through sensors, a communications channel, and displays. In particular, this requires vision to be transmitted by close-circuit television with a consequent degradation of information content. Vehicular teleoperation, as a result, places severe demands on the operator. Teleoperated land vehicles have been built and tested by many organizations, including Sandia National Laboratories (SNL). The SNL fleet presently includes eight vehicles of varying capability. These vehicles have been operated using different types of controls, displays, and visual systems. Experimentation studying the effects of vision system characteristics on off-road, remote driving was performed for conditions of fixed camera versus steering-coupled camera and of color versus black and white video display. Additionally, much experience was gained through system demonstrations and hardware development trials. The preliminary experimental findings and the results of the accumulated operational experience are discussed.
Interdiffusion and interdiffusion-related phenomena in metal and intermetallic matrix composites can be of crucial interest for the prolonged application of these systems at high temperature. The level of complication that these effects can have can vary significantly from system to system. Reviewed herein are recent efforts to address interdiffusion and reaction kinetics for both a simple system, the single phase W/Nb system, and more complex systems such as tungsten fiber reinforced superalloys (TFRS) and beryllide reinforced aluminides. Additionally, recent work on inhibiting interdiffusion in MMCs via ion-implanted diffusion barriers will be presented.
Incorporating a state-of-the-art process control and instrumentation system into a complex system for thermal vacuum testing is discussed. The challenge was to connect several independent control systems provided by various vendors to a supervisory computer. This combination will sequentially control and monitor the process, collect the data, and transmit it to color a graphic system for subsequent manipulation. The vacuum system upgrade included: replacement of seventeen diffusion pumps with eight cryogenic pumps and one turbomolecular pump, replacing a relay based control system, replacing vacuum instrumentation, and upgrading the data acquisition system.
A ground based (1-g) experiment is in progress that will measure the turbidity of a density-matched, binary fluid mixture extremely close to its liquid-liquid critical point. By covering the range of reduced temperatures t equivalent to (T-T(sub c)) / T(sub c) from 10(exp -8) to 10(exp -2), the turbidity measurements will allow the critical exponent eta to be determined. No experiment has precisely determined a value of the critical exponent eta, yet its value is significant to theorists in critical phenomena. Relatively simple critical phenomena, as in the liquid-liquid system studied here, serve as model systems for more complex systems near a critical point.