Resilience is the ability of a system to react to and recover from disturbances with minimal effect on its dynamic stability. While resilience has been the focus of research in several fields, in the case of systemsof-systems (SoSs), addressing resilience is particularly interesting and challenging. As infrastructure SoSs, such as power, transportation, and communication networks, grow in complexity and interconnectivity, measuring and improving the resilience of these critical SoSs is vital in terms of safety and providing uninterrupted services. While the resilience of SoSs depends on the reliability of their constituent systems, traditional reliability and risk assessment approaches cannot adequately quantify their resilience. In this paper, we provide an evaluation of the various methods available and challenges associated with designing resilient SoSs by (1) indicating important differences between resilience and various related system attributes, (2) providing a critical assessment of the current reliability and risk techniques in addressing SoS resilience, and (3) discussing the application of recent multidisciplinary research that can guide the design of resilient SoS. Finally, we highlight key challenges in this design process and propose a series of research themes that can shape future research in this field. C⃝ 2015 Wiley Periodicals, Inc. Syst Eng 18: 491-510, 2015

The removal of noise and outliers from health signals is an important problem in jet engine health monitoring. Typically, health signals are time series of damage indicators, which can be sensor measurements or features derived from such measurements. Sharp or sudden changes in health signals can represent abrupt faults and long term deterioration in the system is typical of gradual faults. Simple linear filters tend to smooth out the sharp trend shifts in jet engine signals and are also not good for outlier removal. We propose new optimally designed nonlinear weighted recursive median filters for noise removal from typical health signals of jet engines. Signals for abrupt and gradual faults and with transient data are considered. Numerical results are obtained for a jet engine and show that preprocessing of health signals using the proposed filter significantly removes Gaussian noise and outliers and could therefore greatly improve the accuracy of diagnostic systems.

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Changing aircraft operational procedures is one way of mitigating the environmental impacts of aviation in relatively short timeframes with existing aircraft types. However, to date these mitigations have not been evaluated or compared in a systematic manner that considers both their environmental impact reduction potential and their ability to be successfully implemented. This article presents a comprehensive identification and systematic evaluation of potential near-term operational changes to determine their relative environmental mitigation benefits. The research also evaluated the potential for successful implementation by identifying possible barriers to implementation for each mitigation. The analysis identifies the most promising mitigations offering a combination of environmental impact reduction and ease of implementation.