At Saab Training & Simulation, there are set strength requirements in the form of quality testing for its products through vibration testing. This is done to ensure the quality of the products, but the vibration machine can only test products up to a set weight limit. The purpose is to investigate the possibility of weight reduction for a fixture used in vibration testing through simulation, with the goal of testing heavier products. As part of this, the tools of topology optimization and design of experiments have been explored in an iterative process to develop design proposals. These design proposals have been evaluated through finite element analysis. The result is the development of three design proposals, out of which the proposal that advanced is presented with a weight reduction of 32,41%.

No description available.

Les deux méthodes principales pour mesurer la constante de Hubble, soit le taux d’expansion actuel de l’Univers, trouvent des valeurs différentes. L’une d’elle s’appuie lourdement sur le modèle cosmologique aujourd’hui accepté pour décrire le cosmos et l’autre, sur une mesure directe. Le désaccord éveille donc des soupçons sur l’existence d’une nouvelle physique en dehors de ce modèle. Si une autre méthode, indépendante des deux en conflit, soutenait une des deux valeurs, cela orienterait les efforts des cosmologistes pour résoudre la tension. Les lentilles gravitationnelles fortes comptent parmi les méthodes candidates. Ce phénomène se produit lorsqu’une source lumineuse s’aligne avec un objet massif le long de la ligne de visée d’un télescope. La lumière dévie de sa trajectoire sur plusieurs chemins en traversant l’espace-temps déformé dans le voisinage de la masse, résultant en une image déformée, gros- sie et amplifiée. Dans le cas d’une source lumineuse ponctuelle, deux ou quatre images se distinguent nettement. Si cette source est aussi variable, une de ses fluctuations apparaît à différents moments sur chaque image, puisque chaque chemin a une longueur différente. Le délai entre les signaux des images dépend intimement de la constante de Hubble. Or, cette approche fait face à de nombreux défis. D’abord, elle requiert plusieurs jours à des spécialistes pour exécuter la méthode de Monte-Carlo par chaînes de Markov (MCMC) qui évalue les paramètres d’un seul système de lentille à la fois. Avec les détections de milliers de systèmes prévues par l’observatoire Rubin dans les prochaines années, cette approche est inconcevable. Elle introduit aussi des simplifications qui risquent de biaiser l’inférence, ce qui contrevient à l’objectif de jeter la lumière sur le désaccord entre les mesures de la constante de Hubble. Ce mémoire présente une stratégie basée sur l’inférence par simulations pour remédier à ces problèmes. Plusieurs travaux antérieurs accélèrent la modélisation de la lentille grâce à l’ap- prentissage automatique. Notre approche complète leurs efforts en entraînant un estimateur neuronal de ratio à déterminer la distribution de la constante de Hubble, et ce, à partir des produits de la modélisation et des mesures de délais. L’estimateur neuronal de ratio s’exécute rapidement et obtient des résultats qui concordent avec ceux de l’analyse traditionnelle sur des simulations simples, qui ont une cohérence statistique acceptable et qui sont non-biaisés. / The two main methods to measure the Hubble constant, the current expansion rate of the Universe, find different values. One of them relies heavily on today’s accepted cosmological model describing the cosmos and the other, on a direct measurement. The disagreement thus arouses suspicions about the existence of new physics outside this model. If another method, independent of the two in conflict, supported one of the two values, it would guide cosmologists’ efforts to resolve the tension. Strong gravitational lensing is among the candidate methods. This phenomenon occurs when a light source aligns with a massive object along a telescope line of sight. When crossing the curved space-time in the vicinity of the mass, the light deviates from its trajectory on several paths, resulting in a distorted and magnified image. In the case of a point light source, two or four images stand out clearly. If this source is also variable, the luminosity fluctuations will appear at different moments on each image because each path has a different length. The time delays between the image signals depend intimately on the Hubble constant. This approach faces many challenges. First, it requires several days for specialists to perform the Markov Chain Monte-Carlo (MCMC) which evaluates the parameters of a single lensing system at a time. With the detection of thousands of lensing systems forecasted by the Rubin Observatory in the coming years, this method is inconceivable. It also introduces simplifications that risk biasing the inference, which contravenes the objective of shedding light on the discrepancy between the Hubble constant measurements. This thesis presents a simulation-based inference strategy to address these issues. Several previous studies have accelerated the lens modeling through machine learning. Our approach complements their efforts by training a neural ratio estimator to determine the distribution of the Hubble constant from lens modeling products and time delay measurements. The neural ratio estimator results agree with those of the traditional analysis on simple simulations, have an acceptable statistical consistency, are unbiased, and are obtained significantly faster.

The current thesis investigates data-driven simulation decision-making with field-quality consumer data. This is accomplished by outlining the benefits and uses of combining machine learning and simulation in the literature and by locating barriers to the use of machine learning (ML) in the simulation subsystems at a case study organization. Additionally, an implementation is carried out to demonstrate how Scania departments can use this technology to analyze their current data and produce results that support the exploration of the simulation space and the identification of potential design issues so that preventative measures can be taken during concept development. The thesis' findings provide an overview of the literature on the relationship between machine learning and simulation technologies, as well as limitations of using machine learning in simulation systems at large scale manufacturing organizations. Support vector machines, logistic regression, and Random Forest classifiers are used to demonstrate one possible use of machine learning in simulation.

Transit system have a large importance in modern urban cities, with urban rail often acting as the central system with it efficient travel time and great capacity. As cities grow in population, so to does the usage of urban rail resulting in increased crowding on the platform and in the trains. Since crowding level is directly correlated to the experience of travel as well as a safety issue, much research has been done to improve it. Currently its common to utilise transit assignment models (TAM) to evaluate and research transit system but for them to work optimally requires weight parameters connected to perceived time spent on the journey. To get the weight parameters for a system requires surveys to be preformed which is costly and not always possible. Therefor its attractive to find these weights through optimisation using available data. Most transit system uses automated fare collection (AFC), which can be used to create origin-destination (OD) data, and automated vehicle location (AVL) together with link-load data. This project aims to develop a simulation-based optimisation (SBO) that automatically finds the weights for a frequency-based assignment model using OD and link-load as input arguments. The SBO will evaluate five different algorithm, genetic algorithm (GA), simulated annealing (SA), Nelder-Mead method (NM), simultaneous perturbation stochastic approximation (SPSA), and Bayesian optimisation (BO), using a fitness model based on KolmogorovSmirnov test. Synthetic data was implemented to evaluate the algorithms where result needed to be within a margin of error of the set weight. No algorithm was however able to converge during the simulation, therefor not optimising the weights to within the margin of error. A longer simulation was evaluated to see if the length needed to reach convergence was to short but achieved the same results. While the cause was not found, the standard deviation of the TAM could be the problem since the deviation was larger than the change of weight parameters achieved. Even if this project could not achieve its objective of developing a SBO method, it can be used for future research and work as a guide on further development on TAM research. / Transportsystem har en stor påverkan i moderna städer, specifikt tunnelbanan som ofta agerar som det centrala systemet med dess snabba transport samt stora kapacitet. Alltmedan städer växer i befolkning så ökar användandet av tunnelbanan vilket resulterar till trängsel både på plattformen och på tåget. Trängsel är väl studerat inom forskningen då den direkt påverkar den upplevda trivseln samt säkerheten på plattformen. Nuförtiden är det vanligt att använda sig av transport modeller för att undersöka och forska om transportsystemet men modellerna kräver viktparametrar kopplade till den uppfattade tiden man har för att fungera. Vanligtvis behöver man utföra undersökningar för att ta reda på vad viktparametrarna är men det är både dyrt och komplicerat. Därför vill man kunna få fram dessa vikter genom att optimera kända data. De flesta transportsystem använder sig av automatiska biljettsystem (AFC), vilket kan användas för att skapa start-stop (OD) data, och automatisk fordonslokalisering (AVL) tillsammans med länk-belastningsdata. Detta projekts syfte är att utveckla en simuleringsbaserad optimering (SBO) som automatiskt hittar vikterna för en frekvensbaserad transportmodell genom att använda OD- och länk-belastningsdata som argument. SBO kommer att undersöka fem olika algoritmer, genetic algorithm (GA), simulated annealing (SA), Nelder-Mead method (NM), simultaneous perturbation stochastic approximation (SPSA), and Bayesian optimisation (BO), tillsammans med en objektfunktion baserad på Kolmogorov-Smirnov testet. Syntetiskt data användes för att utvärdera algoritmerna, där resultatet behövde vara inom en viss marginal av de satta vikterna. Inga algoritmer konvergerade vilket resulterade att deras resultat inte var inom marginalen. Ett längre test var utfört då konvergensen kunde ha skett senare men det blev samma resultat som tidigare. Anledningen kunde inte finnas men sannolikt var det TAM standardavvikelse som var del av felet då den var större än en förändring av viktparametrarna skapade. Även om detta projekt inte kunde uppnå sitt mål kan den användas för fortsatt arbete inom området och vara som guide för framtida utvecklingar.

This thesis work has been part of an effort to improve the after-action reviews of the air combat simulator training sessions conducted at the Swedish Air Force Combat Simulation Centre (FLSC). Initial studies identified three main needs regarding the evaluation of air-to-air missile shots during beyond-visual-range combat simulation. These needs included an improved detection of where and when in the simulation playback a missile shot took place, a collected view of flight parameters to prevent confusion and cross-referencing between the various displays, as well as the ability to review an aircraft’s flight parameters over time in order to discuss alternative shooting opportunities or maneuvering patterns. To fulfill these three needs, design studies were performed iteratively in collaboration with staff at the FLSC. This work has resulted in a design proposal with a prototype based on the design guidelines and recommendations of the study's participants. The purpose of the visualization is to provide support for instructors and promote the individual learning of pilots. Hopefully, this can ultimately help in answering the question regarding why a missile missed its target. For instructors and air units such aids could mean that operating errors can be more easily identified and also form a basis for discussion during the assessment briefings. / Detta examensarbete har haft som syfte att förbättra utvärderingen av luftstridssimuleringar som bedrivs vid det svenska flygvapnets luftstridssimuleringscentrum, FLSC. Inledande studier identifierade tre huvudsakliga behov för utvärderingen av flygplansburna robotskott avfyrade mot luftmål utom synhåll, på långa avstånd. Dessa behov inkluderar en förbättring när det gäller att upptäcka var och när i en simuleringsuppspelning som ett robotskott har skett, en samlad vy över flygparametrar för att förhindra förvirring och korsreferering mellan olika skärmar, samt möjligheten att utvärdera ett flygplans flygparametrar över tid för att kunna diskutera alternativa avfyrningsmöjligheter eller manövreringsmönster. För att fylla dessa tre behov har iterativa designstudier utförts i samarbete med personalen på FLSC. Detta har resulterat i ett designförslag med en prototyp baserad på de designriktlinjer och -rekommendationer som studiens deltagare delgett. Syftet med visualiseringen är att ge stöd till instruktörer och främja piloters individuella inlärning. Förhoppningsvis kan detta i slutändan bidra till att svara på frågan om varför en robot missade sitt mål. För instruktörer och flygförband kan ett sådant hjälpmedel underlätta identifiering av felmanövreringar och även ligga till grund för värdefulla diskussioner under analysen av genomförda luftsstridsimuleringar.

Automated vehicles are assumed to play an important role in the future of mobility, but their operation must be provably safe. They consist of automated driving systems (ADSs) that perform various automated driving tasks without the active participation of a human driver. These automated driving tasks can be mainly categorized as perception, decision-making, and motion control. These tasks must be accomplished by the components of an ADS, which must be seamlessly integrated to ensure safety. The complexity of the ADS architecture makes the safety assessment rather challenging. This complexity is further exacerbated when automated vehicles need to interact in different traffic situations. Design, verification, and testing of ADSs as simulation models provide a safer and cost-efficient early development opportunity compared to real-world testing. To this end, a capable simulation framework that incorporates the simulation models of ADSs must be developed for designing, implementing, and testing these models in a traffic simulation. The main contributions of this thesis are denoted as (i), (ii), and (iii). Safety assessment of ADS can be done either experimentally by (i) simulation-based testing in (ii) a simulation framework or theoretically (iii) using formal methods. Simulation-based testing requires two components: (i) efficient testing strategies for different ADS components and (ii) a simulation framework containing the models of ADS components for applying these testing strategies. Simulation-based testing alone cannot prove or guarantee safety. In order to complement the safety assessment process, whenever applicable, (iii) formal methods must be utilized to derive theoretical safety proofs for certain types of systems for a set of assumptions. Formal methods for synthesis include methods such as correct-by-construction of control protocols and reachability analysis for dynamic systems, which can be used to design provably safe decision-making and control algorithms. The correct-by-construction synthesis of discrete control protocols can be used as safety filters for decision-making algorithms, such as autonomous intersection management algorithms, to verify the safety of taken actions. The reachability analysis is useful for predicting trajectories for possible maneuvers in a finite time horizon for an automated vehicle on a highway. By over-approximating these ego vehicle trajectories, safety verification of possible maneuvers can be done by comparing them to the possible trajectories of other vehicles. A game-theoretical decision-making approach, such as minimax, can augment safety in maneuver planning by considering the worst-case situations up to a finite time horizon. Such an online maneuver planning algorithm reconsiders the maneuvers at each planning cycle in a receding horizon fashion. However, to apply formal methods, certain assumptions must be made about complex parts of ADSs, and therefore, simulation-based testing is still needed to check the validity of these assumptions in simulation models. Safety assessment with a holistic approach is presented that combines the previously mentioned contributions of this thesis (i), (ii), and (iii) into a workflow of modeling, design/synthesis, and testing. Such an approach is essential for developing safe algorithms for ADSs in a simulation framework.:Kurzfassung v Abstract vii Contents ix 1 Introduction 1 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Scope of the Thesis . . . . . . . . . . . . . . . . . . . . . . . 1 1.3 Research Questions . . . . . . . . . . . . . . . . . . . . . . . 2 1.4 Structure of the Thesis . . . . . . . . . . . . . . . . . . . . . 3 2 Safety Assessment of Automated Driving Systems - State of the Art 5 2.1 State of the Art . . . . . . . . . . . . . . . . . . . . . . . . . 5 2.1.1 Definition of ADS . . . . . . . . . . . . . . . . . . . . 5 2.1.2 Meaning of Safety for ADS . . . . . . . . . . . . . . . 8 2.1.3 Testing for Safety . . . . . . . . . . . . . . . . . . . . 12 2.1.4 Simulation Frameworks for ADSs and AVs . . . . . . 14 2.1.5 Roles of Formal Methods . . . . . . . . . . . . . . . . 16 2.2 Challenges and Contributions . . . . . . . . . . . . . . . . . 18 2.2.1 Challenges in the State-of-the-Art . . . . . . . . . . . 18 2.2.2 The Contributions . . . . . . . . . . . . . . . . . . . 21 3 Simulation-based Testing using Fault Injection 23 3.1 Related Work and Preliminaries . . . . . . . . . . . . . . . . 24 3.1.1 Fault Injection . . . . . . . . . . . . . . . . . . . . . 24 3.1.2 Fault Types and Parameters . . . . . . . . . . . . . . 27 3.1.3 Testing for ADS safety using FI . . . . . . . . . . . . 30 3.1.4 Metrics and Specifications for Safety Evaluation . . . 33 3.1.5 Simulative Error Propagation Analysis . . . . . . . . 35 3.2 Developing a Testing Strategy using Fault Injection . . . . . 36 3.2.1 Automated Testing . . . . . . . . . . . . . . . . . . . 37 3.2.2 Using Domain-specific Knowledge . . . . . . . . . . . 40 3.2.3 Smart Testing Strategy . . . . . . . . . . . . . . . . . 41 3.3 Application of Testing Strategies . . . . . . . . . . . . . . . 42 3.3.1 Testing of ACC Systems for Fault Tolerance using Fault Injection . . . . . . . . . . . . . . . . . . . . . . . . . 43 3.3.2 Discovering Fault Parameter Space using Smart Testing Strategy . . . . . . . . . . . . . . . . . . . . . . . 48 3.4 General Functionalities for Efficient Tools . . . . . . . . . . . 52 3.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 4 A Framework for Simulating Automated Driving Systems in Traffic 55 4.1 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . . 56 4.1.1 Levels of Detail in Traffic Simulation . . . . . . . . . 56 4.1.2 Traffic Simulations and Scenario-based Testing . . . . 59 4.1.3 Generic ADS Architecture . . . . . . . . . . . . . . . 64 4.2 Preliminaries and Definitions . . . . . . . . . . . . . . . . . . 65 4.2.1 Map and Path Planning . . . . . . . . . . . . . . . . 66 4.2.2 Decision Making and Trajectories . . . . . . . . . . . 67 4.2.3 Vehicle Motion Control . . . . . . . . . . . . . . . . . 68 4.3 Mapping the ADS structure into a Simulation Model . . . . 72 4.3.1 Sensor-based Perception . . . . . . . . . . . . . . . . 72 4.3.2 V2X Communication . . . . . . . . . . . . . . . . . . 73 4.3.3 Global Path Planner . . . . . . . . . . . . . . . . . . 75 4.3.4 Behavioral Planner/Maneuver Planner . . . . . . . . 78 4.3.5 Longitudinal and Lateral Motion Control . . . . . . . 80 4.4 Interfaces and Layering between Modules . . . . . . . . . . . 81 4.4.1 Relations between Discrete Decision-Making and Continuous Control . . . . . . . . . . . . . . . . . . . . . 82 4.4.2 Vehicles and the Infrastructure - Autonomous Intersection Management . . . . . . . . . . . . . . . . . . . . 83 4.5 Instantiating a Model-based Traffic Simulation . . . . . . . . 86 4.5.1 Traffic Simulation Environment Architecture . . . . . 88 4.5.2 Road Network and the Map Format . . . . . . . . . . 91 4.5.3 Scenario-based Traffic Simulation as Test Cases . . . 95 4.5.4 Overview of the Simulation Framework with Fault Injection . . . . . . . . . . . . . . . . . . . . . . . . . . 97 4.6 Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 4.6.1 Urban Traffic Simulations . . . . . . . . . . . . . . . 101 4.6.2 Fault-Error-Failure Chain Analysis for Safety Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 4.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 5 Using Formal Methods for Safe Algorithms Design 111 5.1 Control Protocol Synthesis . . . . . . . . . . . . . . . . . . . 111 5.1.1 Related Work and Preliminaries . . . . . . . . . . . . 111 5.1.1.1 Finite State Transition Systems . . . . . . . 112 5.1.1.2 Linear Temporal Logic and Büchi Automaton 113 5.1.1.3 Correct-by-Construction Control Protocol Synthesis . . . . . . . . . . . . . . . . . . . 114 5.1.2 Application in an Autonomous Intersection Management Algorithm . . . . . . . . . . . . . . . . . . . . . 116 5.1.2.1 Modeling the Intersection and the Behaviors of the Vehicles . . . . . . . . . . . . . . . . 116 5.1.2.2 Specifications for Synthesis . . . . . . . . . 120 5.1.2.3 Algorithm for Safe Decision-Making for AIM 122 5.2 Game-Theoretical Decision-Making and Trajectory Verification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 5.2.1 Related Work and Preliminaries . . . . . . . . . . . . 125 5.2.1.1 Game-Theoretical Minimax Decision-Making 126 5.2.1.2 Reachability Analysis for Trajectory Generation . . . . . . . . . . . . . . . . . . . . . . 127 5.2.1.3 Motion in Frenet Coordinates . . . . . . . . 130 5.2.1.4 Modeling of AVs and Maneuvers . . . . . . 132 5.2.2 Application in a Safe Maneuver Planning Algorithm . 137 5.2.2.1 Fixed Abstraction and the Over- Approximation of Trajectories . . . . . . . . 138 5.2.2.2 Safety Quantification of Maneuvers . . . . . 140 5.2.2.3 Minimax Decision-Making for Safe Maneuver Planning . . . . . . . . . . . . . . . . . . . 143 5.3 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 6 Safety Assessment with a Holistic Approach 151 6.1 Overview and the Application of the Approach . . . . . . . . 152 6.2 Case Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . 154 6.2.1 Case Study 1: Safety of an Autonomous Intersection Management Algorithm . . . . . . . . . . . . . . . . 155 6.2.1.1 Modeling . . . . . . . . . . . . . . . . . . . 155 6.2.1.2 Design/Synthesis . . . . . . . . . . . . . . . 157 6.2.1.3 Testing and Results . . . . . . . . . . . . . 159 6.2.1.4 Conclusion . . . . . . . . . . . . . . . . . . 161 6.2.2 Case Study 2: Safety of a Maneuver Planning Algorithm for Highway Driving . . . . . . . . . . . . . . . 162 6.2.2.1 Modeling . . . . . . . . . . . . . . . . . . . 163 6.2.2.2 Design/Synthesis . . . . . . . . . . . . . . . 163 6.2.2.3 Testing and Results . . . . . . . . . . . . . 167 6.2.2.4 Conclusion . . . . . . . . . . . . . . . . . . 175 7 Conclusions 177 7.1 Main Findings . . . . . . . . . . . . . . . . . . . . . . . . . . 178 7.2 Answers to the Research Questions . . . . . . . . . . . . . . 179 7.3 Possible Future Directions . . . . . . . . . . . . . . . . . . . 181 Appendix A Additional Details 185 A.1 Rigid Bodies of the Vehicles . . . . . . . . . . . . . . . . . . 185 A.2 Collision Detection . . . . . . . . . . . . . . . . . . . . . . . 186 A.3 Trajectory Tracking in Frenet Coordinates . . . . . . . . . . 187 References 189

This study selects several new advanced topics in power systems, and verifies their usefulness using the simulation. In the study on ratio of the equivalent reactance and resistance of the bulk power systems, the simulation results give us the more correct value of X/R of the bulk power system, which can explain why the active power compensation is also important in voltage flicker mitigation. In the application study of the Energy Storage System(ESS) to the wind power, the new model implementation of the ESS connected to the wind power is proposed, and the control effect of ESS to the intermittency of the wind power is verified. Also this study conducts the intensive simulations for clarifying the behavior of the wide-area power system frequency as well as the possibility of the on-line instability detection. In our POWER IT Laboratory, since 2003, the U.S. national frequency monitoring network (FNET) has been being continuously operated to monitor the wide-area power system frequency in the U.S. Using the measured frequency data, the event of the power system is triggered, and its location and scale are estimated. This study also looks for the possibility of using the simulation technologies to contribute the applications of FNET, finds similarity of the event detection orders between the frequency measurements and the simulations in the U.S. Eastern power grid, and develops the new methodology for estimating the event location based on the simulated N-1 contingencies using the frequency measurement. It has been pointed out that the simulation results can not represent the actual response of the power systems due to the inevitable limit of modeling power systems and different operating conditions of the systems at every second. However, in the circumstances that we need to test such an important infrastructure supplying the electric energy without taking any risk of it, the software based simulation will be the best solution to verify the new technologies in power system engineering and, for doing this, new models and better application of the simulation should be proposed. Conducting extensive simulation studies, this dissertation verified that the actual X/R ratio of the bulk power systems is much lower than what has been known as its typical value, showed the effectiveness of the ESS control to mitigate the intermittence of the wind power from the perspective of the power grid using the newly proposed simulation model of ESS connected to the wind power, and found many characteristics of the wide-area frequency wave propagation. Also the possibility of using the simulated responses of the power system for replacing the measured data could be confirmed and this is very promising to the future application of the simulation to the on-line analysis of the power systems based on the FNET measurements. / Ph. D.

This thesis explores the development and validation of advanced Machine Learning (ML) and Deep Learning (DL) algorithms for detecting Distributed Denial of Service (DDoS) attacks within 5th Generation (5G) telecommunications networks. As 5G technologies expand, the vulnerability of these networks to cyber threats that compromise service integrity increases, necessitating robust detection mechanisms. The primary aim of this research is to develop and validate ML and DL algorithms that effectively detect DDoS attacks within 5G telecommunications networks. These algorithms will leverage real-time data processing to enhance network security protocols and improve resilience against cyber threats. A robust simulated environment using free 5GC and UERANSIM was established to mimic the complex dynamics of 5G networks. This facilitated the controlled testing of various ML and DL models under both normal and attack conditions. The models developed and tested include Bidirectional Encoder Representations from Transformer (BERT), Bidirectional Long Short-Term Memory (BiLSTM), Multilayer Perceptron (MLP), a Custom Convolutional Neural Network (CNN), Random Forest, Support Vector Machine (SVM), and XGBoost. The ensemble model combining Random Forest and XGBoost showed superior performance, making it suitable for the dynamic 5G environment. However, the study also highlights the complications of ensemble models, such as increased computational complexity and resource demands, which may limit their practicality in resource-constrained settings. This thesis addresses a critical research gap by evaluating modern DL techniques, traditional ML models, and ensemble methods within a simulated 5G environment. This comparative analysis helps identify the most effective approach for real-time DDoS detection, balancing accuracy, complexity, and resource efficiency. The findings indicate that the tailored ML, DL and Ensemble models developed are highly effective in detecting DDoS attacks, demonstrating high accuracy and efficiency in real-time threat detection. This highlights the potential for these models to be adapted for real-world applications in modern telecommunications infrastructures. In conclusion, this thesis contributes substantially to the field of cybersecurity in 5G networks by demonstrating that ML and DL models, developed and tested in a sophisticated simulated environment, can significantly enhance network security protocols. These models offer promising approaches to securing emerging telecommunications infrastructures against continuously evolving cyber threats, thus supporting the stability and reliability of 5G networks globally.

We consider a class of periodic preventive maintenance (PM) optimization problems, for a single piece of equipment that deteriorates with time or use, and can be repaired upon failure, through corrective maintenance (CM). We develop analytical and simulation-based optimization models that seek an optimal periodic PM policy, which minimizes the sum of the expected total cost of PMs and the risk-averse cost of CMs, over a finite planning horizon. In the simulation-based models, we assume that both types of maintenance actions are imperfect, whereas our analytical models consider imperfect PMs with minimal CMs. The effectiveness of maintenance actions is modeled using age reduction factors. For a repairable unit of equipment, its virtual age, and not its calendar age, determines the associated failure rate. Therefore, two sets of parameters, one describing the effectiveness of maintenance actions, and the other that defines the underlying failure rate of a piece of equipment, are critical to our models. Under a given maintenance policy, the two sets of parameters and a virtual-age-based age-reduction model, completely define the failure process of a piece of equipment. In practice, the true failure rate, and exact quality of the maintenance actions, cannot be determined, and are often estimated from the equipment failure history. We use a Bayesian approach to parameter estimation, under which a random-walk-based Gibbs sampler provides posterior estimates for the parameters of interest. Our posterior estimates for a few datasets from the literature, are consistent with published results. Furthermore, our computational results successfully demonstrate that our Gibbs sampler is arguably the obvious choice over a general rejection sampling-based parameter estimation method, for this class of problems. We present a general simulation-based periodic PM optimization model, which uses the posterior estimates to simulate the number of operational equipment failures, under a given periodic PM policy. Optimal periodic PM policies, under the classical maximum likelihood (ML) and Bayesian estimates are obtained for a few datasets. Limitations of the ML approach are revealed for a dataset from the literature, in which the use of ML estimates of the parameters, in the maintenance optimization model, fails to capture a trivial optimal PM policy. Finally, we introduce a single-stage and a two-stage formulation of the risk-averse periodic PM optimization model, with imperfect PMs and minimal CMs. Such models apply to a class of complex equipment with many parts, operational failures of which are addressed by replacing or repairing a few parts, thereby not affecting the failure rate of the equipment under consideration. For general values of PM age reduction factors, we provide sufficient conditions to establish the convexity of the first and second moments of the number of failures, and the risk-averse expected total maintenance cost, over a finite planning horizon. For increasing Weibull rates and a general class of increasing and convex failure rates, we show that these convexity results are independent of the PM age reduction factors. In general, the optimal periodic PM policy under the single-stage model is no better than the optimal two-stage policy. But if PMs are assumed perfect, then we establish that the single-stage and the two-stage optimization models are equivalent. / text