In the field of System-of-Systems (SoS) engineering, the study of interactions between complex systems froma holistic point of view is important for finding emerging behaviours. To observe as many behaviours aspossible, especially when field testing is not a viable option, simulations play an important role in design spaceexploration and formulation for the Firefighting SoS framework. The presented work describes an AgentBased Model (ABM) approach for simulation of wildfire spread and its detection using collaborating vehicles:Unmanned Aerial Vehicles (UAVs), or partly autonomous air- and land-based vehicles. Implemented in theopen-source software NetLogo, the usage of its Geographic Information System (GIS) extension allows tosimulate scenarios at specific locations. This ABM will be used in the future for Agent-Based Simulations(ABS) for the study of an SoS framework oriented to firefighting, including design and optimization of the SoS,constituent systems and their subsystems.

The increasing interest in System-of-Systems (SoS) for engineering applications are introducing new challenges that must be overcome at an early design stage. One of these is the integration of different tools that can be used to make predictions about a system under development and how these together can be used to predict SoS performances by comparison of parameter spaces.The purpose of this paper is therefore to illustrate how different SoS architectures can be modeled, simulated, and evaluated throughout different scenarios by different teams of researchers following a common workflow.An ontology is used as an overarching knowledge base where information about entities, such as scenario details, can be extracted and used for the setup of Agentbased Simulations(ABS) through a tool integration software acting as master that controls the correct execution of the defined workflow.The tool integration software also enables additional modelling capabilities, such as a Design of Experiments (DOE) definition for design space explorations, an Optimizer with different algorithms, user-defined Python scripts, etc. 

The System of Systems (SoS) framework plays a pivotal role in delimiting aircraft design spaces by examininginteractions among its Constituent Systems (CS). Each CS has a distinct collection of capabilities, some of which may be shared with other CS. The framework explores emergent behaviours that arise from communication between the CS within the SoS. These emergent behaviours are characterized by their unattainability by any individual CS and result from their collaborative nature. The identification of these emergent behaviours enablesSystem of Systems Engineering (SoSE) to pinpoint the most valuable configurations of the SoS, thereby maximizing the collective value. Furthermore, these emergent behaviours aid in stipulating design requirements for new systems based on the capabilities outlined in the SoS study. To map the relationship between needs, capabilities, requirements, and behaviours, maintaining traceability throughout the study is paramount. This research employs workflows created using the Remote Component Environment (RCE), a specialized tool for structured and automated task development. The objective is to showcase RCE's integration capabilitiesspecifically for software tools and Python scripts- with task scheduling. This integration enables swift extraction of results, making them available at every step, thus augmenting analysis efficiency. The study focuses on the perspective of an aircraft designer during the early concept generation phase, specifically applied to the development of an electric Unmanned Aerial Vehicle (UAV) concept for wildfire detection.