Electronics designed for use in aerospace vehicles.
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The objective of this research is to create tools to manage uncertainty in the design and certification process of safety-critical aviation systems. The research focuses on three innovative ideas to support this objective. First, probabilistic techniques will be introduced to specify system-level requirements and bound the performance of dynamical components. These will reduce the design costs associated with complex aviation systems consisting of tightly integrated components produced by many independent engineering organizations.
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This project addresses the management of the air traffic system, a cyber-physical sys- tem where the need for a tight connection between the computational algorithms and the physical system is critical to safe, reliable and efficient performance. Indeed, the lack of this tight connection is one of the reasons current systems are overwhelmed by the ever increasing traffic and suffer when there is any deviation from the expected (e.g., changing weather).
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Effective engineering of complex devices often depends on the ability to encapsulate responsibility for tasks into modular components with specific responsibilities and clearly defined lines of communication. Under such conditions, one can determine what components or lines of communication are at fault for poor system performance because the system can be checked against modularized model specifications.
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Transforming the traditional, single-vehicle-based safety and efficiency control, next-generation vehicles are expected to form platoons for optimizing roadway usage and fuel efficiency while ensuring transportation safety. Two basic enablers of vehicle platooning are vehicular wireless networking and platoon control.
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Cyber-Physical Systems (CPS) are deployed in a wide variety of safety critical applications from avionics, medical, and automotive domains. For these applications, it is essential to create a precise specification and formally verify that the implementation behaves as specified. The formal verification of these systems presents a wide variety of challenges. Models of these systems must represent the physical world, analog sensors and actuators, computer hardware and software, networks, and feedback control.
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Fault tolerance is vital to ensuring the integrity and availability of safety critical systems. Current solutions are based almost exclusively on physical redundancy at all levels of the design. The use of physical redundancy, however, dramatically increases system size, complexity, weight, and power consumption.
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Multicore platforms have the potential of revolutionizing the capabilities of embedded cyber-physical systems but lack predictability in execution time due to shared resources. Safety-critical systems require such predictability for certification. This research aims at resolving this multicore "predictability problem.'' It will develop methods that enable to share hardware resources to be allocated and provide predictability, including support for real-time operating systems, middleware, and associated analysis tools.
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Processors in cyber-physical systems are increasingly being used in applications where they must operate in harsh ambient conditions and a computational workload which can lead to high chip temperatures. Examples include cars, robots, aircraft and spacecraft. High operating temperatures accelerate the aging of the chips, thus increasing transient and permanent failure rates. Current ways to deal with this mostly turn off the processor core or drastically slow it down when some part of it is seen to exceed a given temperature threshold.
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As technology pushes automation to greater degrees of autonomy, the verification and validation burden becomes more cost and time prohibitive. It has been well established that, as stated in AF Technology Horizons 2010, "It is possible to develop systems having high levels of autonomy, but it is the lack of suitable V&V methods that prevents all but relatively low levels of autonomy from being certified for use." This increased move towards further levels of autonomy has brought the certification need to a national level.
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Growing demands on our civil infrastructure have heightened the need for smart structural components and systems whose behavior and performance can be controlled under a variety of loading scenarios such as high winds and earthquakes.
