Urban Air Mobility (UAM) is increasingly becoming popular for Passenger or Cargo movement in dense smart cities. Several researches so far are focused on individual vehicle architectures such as multirotor or tiltrotor etc., but not much effort in a System of Systems (SoS) point of view where a homogenous fleet of vehicle with different passenger capacity, speed, and propulsive energy concepts are assessed in a framework for a successful UAM operations in a given city. An effort is made in this paper wherein, vehicle architecture is derived from the Concept of Operations (CONOPS) of scenarios such as urban and suburban operations and as well as propulsion subsystem for sustainable UAM. This paper approaches UAM aircraft design driven by SoS approach and an agent-based simulation supports the vehicle architecture evaluation and fleet definition. The outcome of this study is: multiple aircraft design with subsystem architectures, ideal fleet size for the respective operational scenarios, autonomy and battery technology effectiveness on UAM throughput (to efficiently provide UAM on-demand service maximum passengers within 15 min wait time), and importantly, sustainability metrics such as total fleet energy required. Several System of Systems, system and subsystem level sensitivity research questions are addressed to understand the interlevel coupling.

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Can Urban Air Mobility (UAM) systems constitute viable and sustainable mobility solutions? This question has increasingly been concerning scientists, companies, policy makers, and authorities as more and more UAM vehicle concepts are seeing the light of day. In order to come closer to answering this question and to demonstrate the dependencies and impacts of the numerous parameters used to describe a highly complex system of a fleet of UAM vehicles operating in an urban environment, this paper employs a System of Systems (SoS) approach. A collaborative SoS framework with an agent-based simulation is introduced, which connects the UAM vehicle design, fleet performance, vertiport network, and reenergizing infrastructure with a Life-Cycle Assessment (LCA). The framework is used to simulate four exemplary UAM fleet-operation scenarios based on two cities and two operational modes, namely urban and suburban operations. Different vehicle design configurations, e.g. multirotor and lift + cruise vehicles, are evaluated in each scenario based on respectively realistic Concepts of Operations (CONOPS). Additionally, two different points in time, namely 2025 and 2050, are considered and assessed for powering the vehicles by taking into account the characteristics of batteries as well as the underlying electricity mix for their operation. Lithium nickel manganese cobalt oxide battery and lithium-sulfur (Li-S) batteries are considered. The SoS framework helps to asses various UAM metrics such as the average wait time for a passenger, the ideal number of aircraft needed for transporting all passengers within given time, the energy required on a vehicle and fleet level, sustainability metrics, e.g. the global warming potential associated with the energy carriers and many more. The capability to explore a wide design space and to visualize the dependencies between the system parameters and their impacts on different SoS metrics provides stakeholders with a helpful tool for their decision making.

Large wildfires are increasingly occurring phenomenon in several since the past few years. The suppression of wildfires is complex considering heterogeneous independent constituent systems operating together to monitor, mitigate, and suppress the fire. In addition, the management of the disaster response involve multiple institutions in collaboration. Recognition of this wildfire fighting scenario, as a System of Systems (SoS) is valid. Aerial vehicles may play a big role in firefighting considering monitoring and suppression at early stages when the fire is still small. Thus, there is scope for designing a new Unmanned Aerial Vehicle (UAV) with a payload of 250 kg to 500 kg for aerial forest fire suppression, using a SoS wildfire simulation driven aircraft design approach, where the individual optimum performance of a system, especially of a new aircraft for firefighting, does not guarantee optimum overall firefighting mission effectiveness. Whereas an optimum combinationof fleet, technology and operational tactics can effectively suppress fire. For this reason, this research focuses on four different aspects: 1) Applying the inverse design paradigm to a wildfire suppression air vehicle by coupling a fire propagation cellular automata model with a stochastic agent-based simulation of an evolved firefighting SoS. An efficient SoS framework to Evaluate fleet performance. 2) Four System of systemssystemsubsystem interlinking research questions are addressed with corresponding sensitivity results. The impact of wildfire based on vehicle fleet size, vehicle architecture (Tiltrotor, Compound Heli, Multirotor or Lift cruise), payload carrying capability, response time and cruise speed. 3) The evolution of perfect combination of aerial vehicle fleet with different vehicle architectures, technologies and performances using simulations. 4) Obtaining a set of system level (aircraft level) Measures of Performance (MoP) for the large suppression UAVs that produce improved SoS-level Measures of Effectiveness (MoE) during an initial attack quantified by containment time and total fire burnt area. As addressed by research questions and results. The response time and Number of Aircraft has large impact on success of the firefighting mission. As the time advantage deteriorate, the wild fire expands exponentially.

This paper presents an extendable approach to the modelling and simulation of Urban Air Mobility (UAM), and dissemination criteria for system of systems simulation driven studies. UAM involves a multitude of complexities including the airspace, fleet, demand, and vertidrome management. Simulation is a key enabler for understanding these complexities and the interaction of the different stakeholders within the UAM paradigm. This work builds upon past research of the authors and presents a framework for simulation and modelling which includes the modelling of passenger demand, passenger mode choice, vehicle allocation for heterogenous fleets, route planning, deadheading, vertidrome scheduling, and flight scheduling with stop-overs. The approach presented in this work can be used to model both on-demand and scheduled operations, while the primary focus is placed on the former. Moreover, different methods can be implemented for the detailed modelling of the stakeholders, in addition to parametrically varying aspects such as the fleet size, number of vertidromes, and others. The aims of this paper are two, firstly to offer a framework for the modelling of UAM by breaking down its complexity systematically to simpler blocks, namely the stakeholders, the processes and interaction, through which the emergent behavior of the system of systems simulation may be more easily observed or understood. Secondly, it is to provide a clear method for dissemination of the modelling and simulation with the goal of establishing a common standard, demonstrated through the dissemination of the authors’ simulation to the reader.