<p>The use of lower airspace for air taxi and cargo applications opens up exciting prospects for futuristic Unmanned Aircraft Systems (UAS). However, ensuring the safety and security of these UAS within densely populated urban areas presents significant challenges. Most modern aircraft systems, whether unmanned or otherwise, rely on the Global Navigation Satellite System (GNSS) as a primary sensor for navigation. From satellite navigations point of view, the dense urban environment compromises positioning accuracy due to signal interference, multipath effects, etc. Furthermore, civilian GNSS receivers are susceptible to spoofing attacks since they lack encryption capabilities. Therefore, in this thesis, we focus on examining the safety and cybersecurity assurance of UAS in dense urban environments, from both theoretical and experimental perspectives. </p> <p>To facilitate the verification and validation of the UAS, the first part of the thesis focuses on the development of a realistic GNSS sensor emulation using a Gazebo plugin. This plugin is designed to replicate the complex behavior of the GNSS sensor in urban settings, such as multipath reflections, signal blockages, etc. By leveraging the 3D models of the urban environments and the ray-tracing algorithm, the plugin predicts the spatial and temporal patterns of GNSS signals in densely populated urban environments. The efficacy of the plugin is demonstrated for various scenarios including routing, path planning, and UAS cybersecurity. </p> <p>Subsequently, a robust state estimation algorithm for dynamical systems whose states can be represented by Lie Groups (e.g., rigid body motion) is presented. Lie groups provide powerful tools to analyze the complex behavior of non-linear dynamical systems by leveraging their geometrical properties. The algorithm is designed for time-varying uncertainties in both the state dynamics and the measurements using the log-linear property of the Lie groups. When unknown disturbances are present (such as GNSS spoofing, and multipath effects), the log-linearization of the non-linear estimation error dynamics results in a non-linear evolution of the linear error dynamics. The sufficient conditions under which this non-linear evolution of estimation error is bounded are derived, and Lyapunov stability theory is employed to design a robust filter in the presence of an unknown-but-bounded disturbance. </p>

<p dir="ltr">In the context of a Human-in-the-Loop (HITL) system, the accuracy of reachability analysis plays a significant role in ensuring the safety and reliability of HITL systems. In addition, one can avoid unnecessary conservativeness by explicitly considering human control behavior compared to those methods that rely on the system dynamics alone. One possible approach is to use a Gaussian Mixture Model (GMM) to encode human control behavior using the Expectation-Maximization (EM) algorithm. However, relatively few works consider the admissible control input ranges due to physical limitations when modeling human control behavior. This could make the following reachability analysis overestimate the system's capability, thereby affecting the performance of the HITL system. To address this issue, this work presents a constrained stochastic reachability analysis algorithm that can explicitly account for the admissible control input ranges. By confining the ellipsoidal confidence region of each Gaussian component using Sequential Quadratic Programming (SQP), we probabilistically constrain the GMM as well as the corresponding stochastic reachable sets. A comprehensive mathematical analysis of how the constrained GMM can affect the stochastic reachable sets is provided in this work. Finally, the proposed stochastic reachability analysis algorithm is validated via an illustrative numerical example.</p>

<p dir="ltr">The use of autonomous vehicles, such as Unmanned Aerial Systems (UASs), Unmanned Ground Vehicles (UGVs), and Unmanned Surface Vessels (USVs), has globally increased in various applications. Their rising popularity and high accessibility have also increased the use of UASs in criminal or hazardous actions.</p><p dir="ltr">It is beneficial to rapidly compute possible surveillance system evasive paths to evaluate the effectiveness of a given sensor deployment scheme. To find these evasive trajectories, we assume full knowledge of the current and future state of the surveillance system. This assumption allows the defender to identify worst-case trajectories to counteract. The surveillance system path planning presented in this work can be leveraged for game theoretic sensor deployment.</p><p dir="ltr">A sensor deployment scheme determines the overall surveillance efficiency. Through redeployment after each assessment, it aims to approach an equilibrium that maximizes defense capabilities. Therefore, a method of evaluation that models mobile, directional sensors is demanded.</p><p dir="ltr">In response to this demand, this thesis explores the design of a computationally efficient path-planning algorithm for the space-time domain. The Space-Time Parallel RRT* (STP-RRT*) algorithm obtains multiple goal candidates, drawn from a uniform distribution over the time horizon. A set of parallel RRT* trees is simultaneously populated by each goal candidate. By leveraging a connect heuristic from RRT-Connect, parallel goal trees converge to an RRT* tree populated from a start point. This simultaneous tree growth structure returns a computation complexity of O(N log(N)), where N is the number of random samples.</p><p dir="ltr">Due to its low complexity, the STP-RRT* algorithm is suitable to be used as an evaluation metric that computes the cost of the infiltration path of a malicious autonomous system to assess the performance of the deployment layout. The feedback assessment can be used for the surveillance system redeployment to strengthen the vulnerability.</p><p dir="ltr">To identify potential and existing bottlenecks in the algorithm, a computation complexity analysis is conducted, and complexity reduction techniques are employed. Given that surveillance system characteristics are known, 1-dimensional and 2-dimensional environments are generated where positions and surveillance patterns of stationary and dynamic obstacles are randomly selected. In each randomized environment, the STP-RRT*, RRT*, and ST-RRT* are evaluated by comparing success rate, computation time, tree size, and normalized cost through 100-trial Monte Carlo simulations. Under the provided conditions, the proposed STP-RRT* algorithm outperforms two other algorithms with an improved mean success rate and reduced mean computation time by 10.02% and 12.88%, respectively, while maintaining a similar cost level, showing its potential application in surveillance-evasive path-planning problems for surveillance deployment evaluation. Finally, we integrate our algorithm with Nav2, an open-source navigation stack for various robotics applications, including UAV, UGV, and USV. We demonstrate its effectiveness via software-in-the-loop (SiTL) experiments utilizing open-source autopilot software.</p>

<p dir="ltr">I conducted an in-depth analysis of the frequency and severity of external load accidents involving Chinook helicopters over a period of 30 years. The literature review encompassed General Aviation (GA) and ground-based safety organizations, while the data analysis predominantly relied on secondary data from the Army Combat Readiness Center (ACRC). In conducting this study, I aimed to identify key trends, causes, and effects of these accidents, particularly emphasizing material failures, human errors, and the substantial impact of rotor downwash as horizontal wind velocities in proximity to the ground. The study's goal was to improve safety and operational efficiency in Chinook external load operations by identifying frequency and severity of accidents over a 30-year period. The hope was that this would provide valuable insights for improvements in risk mitigation techniques.</p><p dir="ltr">By using an exploratory secondary data analysis of both publicly available U.S. Army accidents and accident data provided by the U.S. ACRC, I found that Chinook rotor downwash, which manifests as horizontal wind velocity when in close proximity to the ground, is the most significant and underreported factor. Based on the findings of this research, I recommend improved classification and documentation of such accidents. The findings highlighted the urgency of updating training and operational procedures to effectively address the unique challenges posed by rotor downwash and high gross weights in proximity to the ground, typical of Chinook external load Pickup and Landing Zone (PZ/LZ) operations. Implementing these recommendations is expected to enhance safety measures in both training and practical operations, ultimately reducing future accidents and improving safety standards in the aviation industry.</p>

<p>In Chapter 2 an experiment has been conducted to measure the quenching distance of a premixed fuel-air mixture. Quenching distance refers to the physical limit below which combustion of a fuel and an oxidizer, even if present in sufficient proportions, cannot maintain combustion and propagate a flame. It is dependent on the physical area that is present for the flame to travel through, the temperature and pressure conditions, the thermal conductivity of the walls, and the specific fuel and oxidizer present. Applicable in a wide variety of industries from the automotive industry to the aerospace industry, the ability to control a combustion reaction and where it occurs can lead to increased safety and efficiency in devices such as injectors, mixing chambers, engine pistons, combustors, propellant turbopumps, and fuel-air heat exchangers. Currently, little to no quenching distance data exists for heavier-than-air hydrocarbons. Using a parallel ceramic plate setup with spark rods inside a pressure vessel to contain the initial combustion reaction, the quenching distances of the hydrocarbons is measured and a relationship with equivalence ratio is found. This relationship is used to construct a model to apply to heavier-than-air hydrocarbons.</p> <p>Chapter 3 focuses on an experiment designed to measure the flow rates of leaks in fuel-air heat exchangers. The ability to accurately quantify and understand these flow rates is crucial for assessing the performance and safety of such systems. Furthermore, the obtained flow rate data will be compared with a Computational Fluid Dynamics (CFD) model developed for micro-scale flows resulting from fuel leakage into a cross-flow of heated air within the heat exchanger. These flow rates provide a model of the volume and rate of fuel being injected into the air channels, aiding in the assessment of potential risks and hazards associated with the leakage. To validate the accuracy and reliability of the model developed for micro-scale flow, the measured flow rates obtained from the experimental setup are compared against the corresponding predictions of the model. By establishing a correlation between the experimental data and the model results, the validity of the model can be confirmed, ensuring its efficacy for future simulations and analyses.</p> <p>Chapter 4 details the creation and analysis of a program developed in Python and MATLAB for assessing combustion risk in microscale fuel-air heat exchanger channels. The Safety Net for Unquenched Flame Fronts (SNUFF) is designed as a design assistance tool for microscale flows of fuel and oxidizer, specifically for heat exchangers. This application helps analyze combustion risks in these microscale flow channels due to leaks or unintended flows caused by damage or manufacturing defects. SNUFF integrates REFPROP and flame simulation data with the models for quenching distance and microscale flow from previous chapters to generate sensitivity plots for various design parameters. This tool enables engineers to assess combustion risks in fuel-air channels, allowing them to design processes that accommodate manufacturing limitations in numerous microscale channel applications.</p>

<p dir="ltr">Managing transient heat loads has become more challenging with the increasing electrification of ground, air, and marine vehicles. Doing so requires novel designs of thermal management systems, or in some cases, novel retrofits of legacy TMSs to accommodate the addition of more electrified subsystems. However, design tools that are well suited for examining and optimizing the dynamic response of TMS over candidate operation or mission profiles are limited. In this thesis, a principled methodology and associated tools for the enumeration and dynamic optimization of all feasible architectures of an air cycle machine are presented. Graph-based modeling is pivotal for exploring and optimizing ACM architectures, providing a structured representation of system components and interactions. By modeling the ACM as a graph, with vertices and edges representing components and interactions, respectively, various component configurations and performance metrics can be systematically analyzed. This approach enables efficient exploration of design alternatives and consideration of dynamic boundary conditions (representing, for example, a complex mission profile) during optimization. Another unique contribution of this thesis is a novel application of a multi-state graph-based modeling approach for developing dynamic models of turbomachinery components. By representing multiple states within each control volume or component and connecting them through power flows, this approach accurately captures both first and second law dynamics, enabling the computation of dynamic entropy generation rates. A detailed case study demonstrates the optimization of ACM architectures based on entropy generation minimization and dynamic bleed air flow rate minimization. This study highlights the trade-offs between different optimization criteria and the potential for generalizing the tool to more complex thermofluid systems in thermal management applications. The results underscore the importance of entropy-based analysis in comparing the thermodynamic losses across various system architectures.</p>

International Telemetering Conference Proceedings / October 17-20, 1994 / Town & Country Hotel and Conference Center, San Diego, California / The Aircraft Research and Development Unit (ARDU) of the Royal Australian Air Force (RAAF) is the only agency in Australia that performs the full spectrum of military flight testing and is the new custodian of the instrumented weapons range at Woomera. Receiving early attention will be the upgrade and integration of ARDU's telemetry systems with the meteorological and tracking data acquisition capabilities at Woomera to minimize overhead and data turnaround time. To achieve these goals, maximum modularity, extensibility, and product interoperability is being sought in the proposed architecture of all the systems that will need to cooperate on the forecast test programmes. These goals are also driven by the need to be responsive to a wide variety of tasks which presently include structural flight testing of fighter and training aircraft, weapons systems performance evaluation on a variety of combatant aircraft, and a host of other tasks associated with all fixed and rotary wing aircraft in the Army and Air Force inventory. Of all these tasks however, ARDU sees that responsiveness to future testing of F-111Cs fitted with unique Digital Flight Control Systems along with USAF standard F-111Gs may place the most significant demands on data handling —particularly in regard to providing an avionics bus diagnostic capability when performing Operational Flight Programme (OFP) changes to the mission computers. With the timely assistance and advice of Loral Test & Information Systems, who has long-term experience in supporting USAF F-111 test programmes, ARDU is confident of making wise design decisions that will provide the desired flexibility and, at the same time, minimize life-cycle costs by ensuring compliance with the appropriate telemetry and open systems standards. As well, via cooperative agreements with the USAF, the potential exists to acquire proven software products without needing to fund the development costs already absorbed by the USAF. This paper presents ARDU's perception of future needs, a view by LTIS of how best to meet those needs, and, based on ARDU data, a view of how LTIS' proposal will satisfy the requirement to provide maximum extensibility with minimum life-cycle costs.

Dans les systèmes embarqués critiques, assurer la sûreté de fonctionnement est primordial du fait, à la fois, des exigences en sûreté dictées par les autorités de certification et des contraintes en sûreté de ces systèmes où des défaillances pourraient conduire à des évènements catastrophiques, voire la perte de vies humaines. Les architectures de ces systèmes sont aujourd'hui de plus en plus distribuées, s'appuyant sur des réseaux numériques complexes, ce qui pose la problématique de l'intégrité des communications. Dans ce contexte, nous proposons une approche bout en bout pour l'intégrité des communications, basée sur le concept du " canal noir " introduit par l'IEC 61508. Elle utilise les codes détecteurs d'erreurs CRC, Adler et Fletcher. Selon le niveau de redondance des systèmes, nous proposons une approche multi-codes (intégrité jugée sur un lot de messages) pour les systèmes dotés d'un niveau de redondance important et une approche mono-code (intégrité jugée sur chaque message) pour les autres cas. Nous avons validé ces propositions par des expérimentations évaluant le pouvoir de détection intrinsèque de chaque code détecteur et la complémentarité entre ces code en termes de pouvoir de détection, ainsi que leurs coûts de calcul avec une analyse de l'impact du type de leur implémentation et de l'environnement matériel (standard et embarqué : processeurs i7, STM32, TMS320C6657 et P2020). L'approche mono-code a été appliquée à un cas d'étude industriel : les futurs systèmes de commande de vol d'Airbus Helicopters. / In critical embedded systems, ensuring dependability is crucial given both dependability requirements imposed by certification authorities and dependability constraints of these systems where failures could lead to catastrophic events even loss of human lives. The architectures of these systems are increasingly distributed deploying complex digital networks which raise the issue of communication integrity. In this context, we propose an end to end approach for communication integrity. This approach is based on the "black channel" concept introduced by IEC 61508. It uses error detection codes particularly CRC, Adler and Fletcher. Depending on the redundancy level of targeted systems, we propose a multi-codes approach (integrity of a set of messages) for systems with an important redundancy level and a single- code approach (integrity per message) for the other cases. We validated our proposals through experiments in order to evaluate intrinsic error detection capability of each error detection code, their complementarity in terms of error detection and their computational costs by analyzing the impact of the type of implementation and the hardware environment (standard or embedded: i7, STM32, TMS320C6657 and P2020 processors). The single-code approach was applied to an industrial case study: future flight control systems of Airbus Helicopters.

<p dir="ltr">This thesis concentrates on the improvement of the quality of shock-dominated flows in supersonic inlets by controlling shock wave / boundary layer interactions (SWBLIs). SWBLI flow control has been a major issue relevant to scramjet-associated endeavors for many years. The ultimate goal of this study is to numerically investigate SWBLI flow control through the application of steady-state thermal sources --- which were defined to replicate the Joule heating effect produced by Quasi-DC electric discharges --- and compare the results with data obtained from previous experiments.</p><p dir="ltr">Numerical solutions were obtained using both a three-dimensional, unsteady Reynolds-averaged Navier-Stokes (RANS) solver with a Spalart-Allmaras (SA) Detached Eddy Simulation (DES) turbulence modeling method and also a simple three-dimensional, compressible RANS solver with a SA turbulence model. Computations employed an ideal gas thermodynamic model. The numerical code is Stanford University Unstructured (SU2), an open-source, unstructured grid, computational fluid dynamics code. The SU2 code was modified to include volumetric thermal source terms to represent the Joule heating effect of electric current flowing through the gas. The computational domain, source term configuration, and flow conditions were defined in accordance with experiments carried out at the University of Notre Dame. Mach 2 flow enters the three-dimensional test domain with a stagnation pressure of 1.7 bar. The test domain is contained by four isothermal side walls maintained at room temperature, as well as an inlet and outlet. A shock wave (SW) generator, a symmetric 10 degree wedge, is positioned on the upper surface of the test domain. The overall length of the test sections is 910 mm and inlet length of the computational domain is increased prior to the location of shock wave generator in order to allow for adequate boundary layer growth. Volumetric heating source terms were positioned on the lower surface of the test domain in the reflected SW region.</p><p dir="ltr">Experimental results show that the thermal sources create a new shock train within the duct and do not initiate significant additional pressure losses. What remains to be explored is the overall characterization of the 3D flow features and dynamics of the thermally induced SW and the effect of gas heating on total pressure losses in the test section.</p><p dir="ltr">Numerical solutions validate what is observed experimentally, and offer the ability to gather more temporally and spatially-resolved measurements to better understand and characterize shock-dominated flow control in a supersonic inlet or duct. Although thermally driven SWBLI flow control requires additional research, this study alleviates the dependency on experimentally driven data and adds insight into the nature of the complex unsteady, three-dimensional flowfield.</p>

<p dir="ltr">Methodologies for optimizing UAVs' control for varied environmental conditions have become crucial in the recent development for UAV control sector, yet they are lacking. This research focuses on the dynamism of the Gazebo simulator and PX4 Autopilot flight controller, frequently referenced in academic sectors for their versatility in generating close-to-reality digital environments. This thesis proposed an integrated simulation system that ensures realistic wind and gust interactions in the digital world and efficient data extraction by employing an industrial standard control communication protocol called MAVLink with the also the industry standard ground control software QGroundControl, using real and historical weather information from NOAA database. This study also looks into the potential of reinforcement learning, namely the DDPG algorithm, in determining optimal UAV safety distance, trajectory prediction, and mission planning under wind disruption. The overall goal is to enhance UAV stability and safety in various wind-disturbed conditions. Mainly focusing on minimizing potential collision risks in areas such as streets, valleys, tunnels, or really anywhere has winds and obstacles. The ROS network further enhanced these components, streamlining UAV response analysis in simulated conditions. This research presents a machine-learning approach to UAV flight safety and efficiency in dynamic environments by synthesizing an integrated simulation system with reinforcement learning. And the results model has a high accuracy, reaching 91%, 92%, and 97% accuracy on average in prediction of maximum shifting displacement, and left/right shifting displacement, when testing with real wind parameters from KLAF airport. </p>