System of Systems Simulation Driven Wildfire Fighting Aircraft Design and Fleet Assessment

Abstract

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 combination of 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 systems – system – subsystem 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.