Operating unmanned aerial vehicles (UAVs) over inhabited areas requires mitigating the risk to persons on the ground. Because the risk depends upon the flight path, UAV operators need approaches that can find low-risk flight paths between the mission's start and finish points. Because the flight paths with the lowest risk could be excessively long and indirect, UAV operators are concerned about the tradeoff between risk and flight time. This paper presents a risk assessment technique and bi-objective optimization methods to find low-risk and time (flight path) solutions and computational experiments to evaluate the relative performance of the methods (their computation time and solution quality). The methods were a network optimization approach that constructed a graph for the problem and used that to generate initial solutions that were then improved by a local approach and a greedy approach and a fourth method that did not use the network solutions. The approaches that improved the solutions generated by the network optimization step performed better than the optimization approach that did not use the network solutions.

The aim of this research has been to develop a project risk management lesson that is, capable to take into account practical challenges that project managers have to deal with during managing project risks. Interviews were conducted with the project managers experienced in project risk management. The list of challenges and associated tactics to deal with these challenges were mapped into ten requirements representing the intended learning outcome of the lesson. The requirements were then mapped onto the design using the four instructional methods; a briefing lecture, team-based assignment, a computer simulation, and a debriefing lecture. All these methods are linked by a real life project case, and executed in a gaming context in order to improve motivation and engagement. The uniqueness and strength of the design comes from its ability to engage the students actively in the entire risk management process. The design also provides students with ability to simulate some of the risks they have identified themselves during the team-assignment. This gave the students a feeling of ownership to risk management process during simulation.

Integrated Systems Health Management (ISHM) is an evolving technology used to detect, assess, and isolate faults in complex systems to improve safety. At the conceptual design level, system-level engineers must make decisions regarding the inclusion of ISHM and the extent and type of the sensing technologies used in various subsystems. In this paper, we propose an ISHM design tool to be used in conjunction with standard system modeling methods to help with the integration of ISHM into the system design process. The key to this analysis is the formulation of an objective function that explicitly quantifies the value derived by integrating the ISHM technology in various subsystems. Ultimately, to determine the best ISHM system configuration, an objective function is formulated, referred to as profit, which is expressed as the product of system availability ( A S ) and revenue per unit availability ( R ) , minus the sum of cost of detection ( C D ) and cost of risk ( C R ) . The analysis is conducted at the system functional level appropriate for conceptual design using standard system functional modeling methods, and ISHM is allocated to the functional blocks using the ISHM design tool. The proposed method is demonstrated using a simplified aerospace system design problem resulting in a configuration of sensors, which optimizes the value of the ISHM system for the given input parameters. In this problem, profit was increased by 11%, inspection interval increased by a factor of 1.5 and cost of risk reduced by a factor of 2.4 over a system with no ISHM.