336 research outputs found

    Spread and defend infection in graphs

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    The spread of an infection, a contagion, meme, emotion, message and various other spreadable objects have been discussed in several works. Burning and firefighting have been discussed in particular on static graphs. Graph burning simulates the notion of the spread of "fire" throughout a graph (plus, one unburned node burned at each time-step); graph firefighting simulates the defending of nodes by placing firefighters on the nodes which have not been already burned while the fire is being spread (started by only a single fire source). This article studies a combination of firefighting and burning on a graph class which is a variation (generalization) of temporal graphs. Nodes can be infected from "outside" a network. We present a notion of both upgrading (of unburned nodes, similar to firefighting) and repairing (of infected nodes). The nodes which are burned, firefighted, or repaired are chosen probabilistically. So a variable amount of nodes are allowed to be infected, upgraded and repaired in each time step. In the model presented in this article, both burning and firefighting proceed concurrently, we introduce such a system to enable the community to study the notion of spread of an infection and the notion of upgrade/repair against each other. The graph class that we study (on which, these processes are simulated) is a variation of temporal graph class in which at each time-step, probabilistically, a communication takes place (iff an edge exists in that time step). In addition, a node can be "worn out" and thus can be removed from the network, and a new healthy node can be added to the network as well. This class of graphs enables systems with high complexity to be able to be simulated and studied

    Validation of flacs code for risk analysis of hydrocarbon pool fires

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    Fires have been object of study over the last decades due to their destructive power. Fire’s hazardous nature and its ability to inflict damage to property, the environment and people, has produced a need to understand how it works in every aspect. Currently, the main focus is to estimate the fire characteristics and main effects, in order to accurately design emergency plans and prevention measures. Due to the needs previously stated, fires have been studied and analyzed mainly from an experimental point of view. However, experimental data is arduous and extremely expensive to obtain due to the amount of resources needed. Additionally, small-scale models, which are generally easier to be undertaken, cannot be extrapolated to full-scale models. Considering this, semi-empirical methods were developed, but can only be applied to simple scenarios and they cannot fully model them. To achieve complete models of fires, CFD (Computational Fluid Dynamics) modeling has been recently used as a way to achieve a cheaper and easier method to study the fire development of full-scale fires in a wide range of conditions. Nevertheless, CFD models require a huge validation effort before they could be widely applied. The main objective of this thesis is to analyze the performance and if possible validate the CFD code FLACS-Fire v10.5 (Flame Accelerator Simulator) for pool-fires. FLACS is a Computational Fluid Dynamic (CFD) program, which solves the compressible conservation equations for mass, momentum, enthalpy, and mixture fraction using a finite volume method. To model a fire it is necessary to include, among others, processes that involve submodels for: turbulence, combustion, thermal radiation, and soot generation. It is of utmost importance, while developing fire models, to validate them against experimental data in pursuance of being able to conclude whether the simulation is valid or not, and to determine the inherent error in comparison with reality. This process consists in a replication of the experimental setup in the CFD, in this case FLACS, and compare it with experimental data previously available. In the present work, gasoline and diesel fuel experimental pool fires were modeled with FLACS-Fire v10.5 code. Simulations considered different pool fire experiments with diameters ranging from 1.5 to 4 meters. In addition, simulations were run with the Eddy Dissipation Concept (EDC) as combustion model; with the κ-ε model as turbulence model; and with the Discrete Transfer Model (DTM) as the radiation model. The predicted results of temperature’s evolution at different heights, burning rate, and thermal radiation were compared with experimental measurements. The results for gasoline and diesel pool fires indicate that FLACS-Fire v10.5 is able to model pool fires. Pool model 3 (PM3) was able to run all simulations, and Pool Model 1 (PM1) does not perform well with pool diameters higher than 1.5m. Predicted values of the proposed parameters are in a fair concordance with experimentally obtained values. Temperatures measured at the centerline of the flame are in most cases overestimated. Burning rates are well approximated with small and large pool fires (0.15 kg/s-0.5kg/s) but largely over predicted in gasoline pool fires of medium size. Thermal radiation is also forecasted with values larger than their experimental counterparts. Chapter 1, contains a brief introduction to the master thesis. It gives a general understanding of the importance of pool fires in the industry. It also gives a global introduction to Computational Fluid Dynamics (CFD), and its relevancy in the study of accidents, especially in the case of pool fires. Chapter 2, consists of a theoretical background of fire phenomena and the combustion process, with a special focus on pool fires. First, a brief and simple explanation of the combustion process is given. Then, an introduction to heat transfer is provided, in order to show the essentials of how thermal energy is transferred and how it affects pool fires. Finally, an introduction to pool fires characteristics and their mechanisms is given, with an emphasis on the zones composing the fire as well as its main features. Chapter 3, mainly covers the existing work concerning the ongoing topic. It covers authors who have worked with pool fires, especially in the validation of FLACS-Fire; as well as others who gather experimental data. Chapter 4, comprises the crucial elements in fire modeling using FLACS-Fire v10.5. Principally, it contains the submodels FLACS uses for: fluid flow, turbulence, radiation, combustion, soot formation, and pool modeling. This chapter shows a theoretical understanding and the basis from which the simulations are later performed. Chapter 5, is constituted by a detailed explanation of the experimental data used in the present thesis. Instrumentation used in the experiments is thoroughly analyzed, as well as the fuels used and the experiments performed. Chapter 6, includes the simulations performed in the present thesis, as well as, a comprehensive analysis of the data obtained. Initial simulations studying various variables such as grid, radiation model and pool model are studied. Final simulations are also evaluated, which especial emphasis on the discrepancies with the experimental data

    CONTROLLER SYNTHESIS AND FORMAL BEHAVIOR INFERENCE IN AUTONOMOUS SYSTEMS

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    Autonomous systems are widely used in crucial applications such as surveillance,defense, reghting, and search & rescue operations. Many of these application require systems to satisfy user-dened requirements describing the desired system behavior. Given high-level requirements, we are interested in the design of controllers that guarantee the compliance of these requirements by the system. However, ensuring that these systems satisfy a given set of requirements is challenging for many reasons, one of which is the large computational cost incurred by having to account for all possible system behaviors and environment conditions. These computational diculties are exacerbated when systems are required to satisfy requirements involving large numbers of tasks emerging from dynamic environments. In addition to computational diculties, scalability issues also arise when dealing with multi-agent applications, in which agents require coordination and communication to satisfy mission requirements. This dissertation is an eort towards addressing the computational and scalability challenges of designing controllers from highlevel requirements by employing reactive synthesis, a formal methods approach, and combining it with other decision-making processes that handle coordination among agents to alleviate the load on reactive synthesis. The proposed framework results in a more scalable solution with lower computational costs while guaranteeing that high-level requirements are met. The practicality of the proposed framework is demonstrated through various types of multi-agent applications including reghting, re monitoring, rescue, search & rescue and ship protection scenarios. Our approach incorporates methodology from computer science and control, including reactive synthesis of discrete systems, metareasoning, reachability analysis and inverse reinforcement learning. This thesis consists of two key parts: reactive synthesis from linear temporal logic specications and specication inference from demonstrations of formal behavior. First, we introduce the reactive synthesis problem for which the desired system behavior species the method by which a multi-agent system solves the problem of decentralized task allocation depending on communication availability conditions. Second, we present the synthesis problem formulated to obtain a high-level mission planner and controller for managing a team of agents ghting a wildre. Third, we present a framework for inferring linear temporal logic specications that succinctly convey and explain the observed behavior. The gained knowledge is leveraged to improve motion prediction for agents behaving according to the learned specication. The eectiveness of the inference process and motion prediction framework are demonstrated through a scenario in which humans practice social norms commonly seen in pedestrian settings

    Aerial Drone-based System for Wildfire Monitoring and Suppression

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    Wildfire, also known as forest fire or bushfire, being an uncontrolled fire crossing an area of combustible vegetation, has become an inherent natural feature of the landscape in many regions of the world. From local to global scales, wildfire has caused substantial social, economic and environmental consequences. Given the hazardous nature of wildfire, developing automated and safe means to monitor and fight the wildfire is of special interest. Unmanned aerial vehicles (UAVs), equipped with appropriate sensors and fire retardants, are available to remotely monitor and fight the area undergoing wildfires, thus helping fire brigades in mitigating the influence of wildfires. This thesis is dedicated to utilizing UAVs to provide automated surveillance, tracking and fire suppression services on an active wildfire event. Considering the requirement of collecting the latest information of a region prone to wildfires, we presented a strategy to deploy the estimated minimum number of UAVs over the target space with nonuniform importance, such that they can persistently monitor the target space to provide a complete area coverage whilst keeping a desired frequency of visits to areas of interest within a predefined time period. Considering the existence of occlusions on partial segments of the sensed wildfire boundary, we processed both contour and flame surface features of wildfires with a proposed numerical algorithm to quickly estimate the occluded wildfire boundary. To provide real-time situational awareness of the propagated wildfire boundary, according to the prior knowledge of the whole wildfire boundary is available or not, we used the principle of vector field to design a model-based guidance law and a model-free guidance law. The former is derived from the radial basis function approximated wildfire boundary while the later is based on the distance between the UAV and the sensed wildfire boundary. Both vector field based guidance laws can drive the UAV to converge to and patrol along the dynamic wildfire boundary. To effectively mitigate the impacts of wildfires, we analyzed the advancement based activeness of the wildfire boundary with a signal prominence based algorithm, and designed a preferential firefighting strategy to guide the UAV to suppress fires along the highly active segments of the wildfire boundary

    Multi-Agent Pathfinding in Mixed Discrete-Continuous Time and Space

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    In the multi-agent pathfinding (MAPF) problem, agents must move from their current locations to their individual destinations while avoiding collisions. Ideally, agents move to their destinations as quickly and efficiently as possible. MAPF has many real-world applications such as navigation, warehouse automation, package delivery and games. Coordination of agents is necessary in order to avoid conflicts, however, it can be very computationally expensive to find mutually conflict-free paths for multiple agents – especially as the number of agents is increased. Existing state-ofthe- art algorithms have been focused on simplified problems on grids where agents have no shape or volume, and each action executed by the agents have the same duration, resulting in simplified collision detection and synchronous, timed execution. In the real world agents have a shape, and usually execute actions with variable duration. This thesis re-formulates the MAPF problem definition for continuous actions, designates specific techniques for continuous-time collision detection, re-formulates two popular algorithms for continuous actions and formulates a new algorithm called Conflict-Based Increasing Cost Search (CBICS) for continuous actions

    e-Sanctuary: open multi-physics framework for modelling wildfire urban evacuation

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    The number of evacuees worldwide during wildfire keep rising, year after year. Fire evacuations at the wildland-urban interfaces (WUI) pose a serious challenge to fire and emergency services and are a global issue affecting thousands of communities around the world. But to date, there is a lack of comprehensive tools able to inform, train or aid the evacuation response and the decision making in case of wildfire. The present work describes a novel framework for modelling wildfire urban evacuations. The framework is based on multi-physics simulations that can quantify the evacuation performance. The work argues that an integrated approached requires considering and integrating all three important components of WUI evacuation, namely: fire spread, pedestrian movement, and traffic movement. The report includes a systematic review of each model component, and the key features needed for the integration into a comprehensive toolkit

    Development of a dynamic model of a ducted fan VTOL UAV

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    The technology of UAV (Unmanned Aerial Vehicle) has developed since its conception many years ago. UAVs have several features such as, computerised and autonomous control without the need for an on-board pilot. Therefore, there is no risk of loss of life and they are easier to maintain than manned aircraft. In addition, UAVs have an extended range/endurance capability, sometimes for several days. This makes UAVs attractive for missions that are typically "dull, dirty and dangerous". With the development of technology, the application of UAVs is becoming commonplace for both military and civil missions. Examples of this are reconnaissance, surveillance, environmental monitoring, disaster observation, etc. The School of Aerospace, Mechanical and Manufacturing Engineering (SAMME) at RMIT University has designed a novel concept for a ducted-fan UAV with vertical takeoff and landing capability and the option to transition to horizontal flight. The aerodynamic analysis, preliminary and detailed design, of this ducted-fan VTOL UAV, is the first and most important step. To optimize the aerodynamic characteristics, evaluating aerodynamic coefficients and analyzing the flow patterns around the vehicle at different speeds and angles of attack is necessary. In this project, CFD plays an important role in predicting the longitudinal and lateral stability and control characteristics of a full-scale model of ducted fan VTOL UAV at both vertical and horizontal flight without any prior knowledge of existing wind tunnel or flight test data. Prior to carrying out experiments in the wind tunnel, the manufacture of ducted fan VTOL UAV was focused on. Particular attention was paid to the propulsion system as the key point. The full-scale model of UAV was produced using the Rapid Prototyping Facility at SAMME to ensure its accurate geometric shape for testing in the wind tunnel. The experiments of the full-scale UAV model with engines was conducted in RMIT's Industrial Wind Tunnel where its aerodynamic characteristics and its properties of counter-rotating propulsion system were tested. In addition, the correlation between experimental data and CFD results was evaluated and the accuracy of the dynamic model of ducted fan VTOL UAV was improved. Flight dynamics is concerned with the motion of an aircraft due to internally or externally generated forces. The ducted fan VTOL UAV stability and control derivatives are determined and used as a basis in a flight simulation environment. This simulation showed that the vehicle is stable and controllable for a range of flight speeds. Finally, a MIMO linear control system was designed to control the vehicle in hovering and low-speed slide flight. The real-time simulation and modeling in MATLAB combined with a flight-simulator showed several animations and trajectories of UAV missions with or without crosswind effect during flight. These simulations were very helpful in determining the dynamic behaviour of the vehicle under various flight conditions
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