This paper describes a model-driven analysis to assess the mission effectiveness of specific Communication Navigation Surveillance/Air Traffic Management (CNS/ATM) capabilities to support the U.S. Air Force (USAF). Two layers of interactions were investigated: first, within the USAF enterprise, between the Combat Air Forces and the Mobility Air Forces, and second, between the USAF and civilian ATM.The analysis sought to answer the following question: "What is the degradation in mission effectiveness, assuming delays in planned avionics upgrades, in light of current and continuing denial of military-preferred routings and altitudes in civil European airspace?" Two hypothetical scenarios were considered, each with different forward basing of fighters. In each scenario, CNS enabled and CNS not-enabled aircraft were examined for mission effectiveness. Also presented are the effects of missed strike packages on the Air Operations Center (AOC) and on tanker utilization.
In this paper major factors contributing to system migration failures are reviewed. We highlight the need for a comprehensive system engineering approach that can address the inherent complexities of migrating mission critical systems. To address this need, a model-based approach supported by tools is presented. Central to this approach is the use of a new type of system architecture model called "Loop Relationship (LR) Models." These models are used to recover the legacy system design, specify the migrated system requirements and proposed system design; and analyze the performance implications of proposed modifications to the legacy system. Finally we will discuss our experience in forming a team to apply the above approach on a number of system migration projects.
A commonly held view is that system and human vulnerabilities can form links in a chain of events and result in an undesirable outcome. However, this truism has led to only limited success in the development of better techniques to analyze this progression. In this study the evolution of air traffic operational errors (OEs) was of particular interest. While it is generally accepted that OEs evolve over time, the temporal characteristics of OEs have received little attention. By better understanding these temporal characteristics, we will be better able to understand how vulnerabilities become links in a chain so that resources can be allocated effectively to develop mitigation strategies. To better understand how vulnerabilities become links in a chain, two activities were conducted. The first study developed a temporal markers (TMs) definition and sequencing framework. The second study provided an initial assessment of the framework using a small sample of OEs which were readily available in a local archive. Initial results suggest that temporal profiling of OEs may be useful in uncovering trends that are not currently being systematically examined. However, further validation of the framework using a larger set of OEs is required to achieve the goal of developing information that can be routinely used to mitigate OE occurrence. U.S. Air Force in European Airspace: Planning Future CNS/ATM Capabilities
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