Developing high-end aerospace components is a complex and highly competitive business. Hence methods for decreasing lead-time, while still providing the same quality and at a lower cost, has to be developed. This thesis is conducted at Research & Technology - GKN Aerospace in Trollhättan Sweden. A multidisciplinary analysis system known internally as Engineering Workbench, forms the base for implementation of the methods and tools developed in this thesis work. The system applies set-based engineering approach to develop new components. The evaluation of the design space is performed through parametric studies to find relations between the design parameters and performance metrics of the design. The engineering workbench allows GKN to define and evaluate a large design space within a limited timeframe. This thesis will look to improve the current producibility assessment system within the EWB by increasing the robustness and flexibility of the system. This is done by re-designing the producibility analysis part system and into a modular knowledge-based system that implements various techniques to increase the robustness and flexibility of the system. The re-designed system is automated, flexible and robust and is able to perform user defined weld assessments on a various designs and provides GKN with weld producibility data.

Network growing mechanisms are used to construct random networks that have structural behaviors similar to existing networks such as genetic networks, in efforts of understanding the evolution of complex topologies. Popular mechanisms, such as preferential attachment, are capable of preserving network features such as the degree distribution. However, little is known about such randomly grown structures regarding robustness to disturbances (e.g., edge deletions). Moreover, preferential attachment does not target optimizing the network's functionality, such as information flow. Here, we consider a network to be optimal if it's natural functionality is relatively high in addition to possessing some degree of robustness to disturbances. Specifically, a robust network would continue to (1) transmit information, (2) preserve it's connectivity and (3) preserve internal clusters post failures. In efforts to pinpoint features that would possibly replace or collaborate with the degree of a node as criteria for preferential attachment, we present a case study on both; undirected and directed networks. For undirected networks, we make a case study on wireless sensor networks in which we outline a strategy using Support Vector Regression. For Directed networks, we formulate an Integer Linear Program to gauge the exact transcriptional regulatory network optimal structures, from there on we can identify variations in structural features post optimization.

Les structures mécaniques complexes résultent de l’assemblage de plusieurs composants, possédant souvent des propriétés mécaniques différentes, reliés à leurs interfaces par différents types de jonctions. L’hétérogénéité des comportements dynamiques de ces sous-structures et leurs sollicitations extérieures vont générer des efforts sur la structure principale et des accélérations importantes au niveau des équipements embarqués, affectant leur fonctionnement, leur fiabilité, leur sécurité. Il est alors nécessaire de les protéger en les isolant du reste de la structure.Ces travaux concernent la maîtrise des niveaux vibratoires et visent à fournir une méthode de caractérisation dynamique des interfaces entre différentes sous-structures. Celle-ci est ensuite intégrée dans une démarche visant à minimiser la puissance transmise entre des sous-structures sources et réceptrices.Une méthode de modes de flux de puissance a été développée, dont les valeurs et efforts propres fournissent, respectivement, des informations quantitatives et qualitatives sur les flux de puissance à l’intérieur d’une structure. Son application à l’étude de la puissance transmise entre deux sous-structures permet d’identifier les directions et les participations des principaux chemins de puissance transitant par les jonctions.Ces résultats ont été appliqués afin de proposer une méthodologie de conception robuste des interfaces de structures. Deux démarches d’optimisation ont été comparées visant à minimiser la puissance transmise par rapport aux paramètres de raideurs des jonctions. L’importance de considérer la robustesse de ces solutions a été soulignée par une approche complémentaire non-probabiliste. / Complex mechanical structures are composed of an assembly of several components, often exhibiting different mechanical properties and joined at their interfaces by different junction types. The various dynamic behaviours of these substructures and the applied external loadings generate important efforts on the main structure, resulting in high acceleration responses of the on-board equipments, affecting their performance, reliability and security. It is therefore necessary to protect them from these harsh conditions by isolating them from the rest of the structure.These researches are related to structural vibration control and aim at proposing a new method to dynamically characterize interfaces between different substructures. This method is then integrated to a robust design approach to minimize the power transmitted between a source and a receiver substructure. A power flow mode method has been developed, which allows determining eigenvalues and eigenvectors respectively representing qualitative and quantitative information on the power flowing inside the structure. This has been further applied to study the power transmitted at the interface, making it possible to identify the direction associated to the dominant power flow pattern and to quantify their contribution.These results have been applied to propose a robust design approach of structural interfaces. Optimization procedures have been implemented and compared to minimize the power transmitted between with respect to the interface stiffness parameters. The importance of considering the robustness of these solutions has been underlined by performing a complementary analysis based on a non-probabilistic approach.

Doctor of Philosophy / Department of Electrical and Computer Engineering / Caterina Scoglio / Critical infrastructures are repeatedly attacked by external triggers causing tremendous amount of damages. Any infrastructure can be studied using the powerful theory of complex networks. A complex network is composed of extremely large number of different elements that exchange commodities providing significant services. The main functions of complex networks can be damaged by different types of attacks and failures that degrade the network performance. These attacks and failures are considered as disturbing dynamics, such as the spread of viruses in computer networks, the spread of epidemics in social networks, and the cascading failures in power grids. Depending on the network structure and the attack strength, every network differently suffers damages and performance degradation. Hence, quantifying the robustness of complex networks becomes an essential task. In this dissertation, new metrics are introduced to measure the robustness of technological and social networks with respect to the spread of epidemics, and the robustness of power grids with respect to cascading failures. First, we introduce a new metric called the Viral Conductance ($VC_{SIS}$) to assess the robustness of networks with respect to the spread of epidemics that are modeled through the susceptible/infected/susceptible ($SIS$) epidemic approach. In contrast to assessing the robustness of networks based on a classical metric, the epidemic threshold, the new metric integrates the fraction of infected nodes at steady state for all possible effective infection strengths. Through examples, $VC_{SIS}$ provides more insights about the robustness of networks than the epidemic threshold. In addition, both the paradoxical robustness of Barab\'si-Albert preferential attachment networks and the effect of the topology on the steady state infection are studied, to show the importance of quantifying the robustness of networks. Second, a new metric $VC_$ is introduced to assess the robustness of networks with respect to the spread of susceptible/infected/recovered ($SIR$) epidemics. To compute $VC_$, we propose a novel individual-based approach to model the spread of $SIR$ epidemics in networks, which captures the infection size for a given effective infection rate. Thus, $VC_$ quantitatively integrates the infection strength with the corresponding infection size. To optimize the $VC_$ metric, a new mitigation strategy is proposed, based on a temporary reduction of contacts in social networks. The social contact network is modeled as a weighted graph that describes the frequency of contacts among the individuals. Thus, we consider the spread of an epidemic as a dynamical system, and the total number of infection cases as the state of the system, while the weight reduction in the social network is the controller variable leading to slow/reduce the spread of epidemics. Using optimal control theory, the obtained solution represents an optimal adaptive weighted network defined over a finite time interval. Moreover, given the high complexity of the optimization problem, we propose two heuristics to find the near optimal solutions by reducing the contacts among the individuals in a decentralized way. Finally, the cascading failures that can take place in power grids and have recently caused several blackouts are studied. We propose a new metric to assess the robustness of the power grid with respect to the cascading failures. The power grid topology is modeled as a network, which consists of nodes and links representing power substations and transmission lines, respectively. We also propose an optimal islanding strategy to protect the power grid when a cascading failure event takes place in the grid. The robustness metrics are numerically evaluated using real and synthetic networks to quantify their robustness with respect to disturbing dynamics. We show that the proposed metrics outperform the classical metrics in quantifying the robustness of networks and the efficiency of the mitigation strategies. In summary, our work advances the network science field in assessing the robustness of complex networks with respect to various disturbing dynamics.

Le point de départ pour les systèmes décentralisés a été l’échange des fichiers, en utilisant cet approche i) pour distribuer la bande passante entre tous les nœuds concernés et ii) pour augmenter la robustesse en éliminant autant que possible les points individuels de défaillance et de contrôle et iii) en partageant également les responsabilités entre les nœuds. Si les approches le plus décentralisés sont très efficaces en termes de résilience aux pannes, pour la même raison, les performances sont limités et difficiles à analyser quand on observe plusieurs réseaux interconnectés entre eux, configurations qui peuvent être analysés à travers des outils de simulation, souvent peu efficaces dans l’analyse de l’espace de possibilités. Dans cette thèse on a développé un modèle mathématique pour la modélisation de l’interconnexion des réseaux en permettant l’étude et l’exploration d’équilibres qui grâce à l’abstraction du modèle peuvent s’appliquer à l’interconnexion des réseaux de communications, réseaux de distribution de marchandise ou réseaux de distribution d’eau. La thèse se focalise aussi sur les réseaux décentralisés MANET, ou` la communication entre nœuds mobiles est purement ≪ ad-hoc ≫ (ex: deux voitures communiquant entre eux quand ils sont proches) en utilisant i) des ≪ rateless coding ≫ pour augmenter la robustesse et minimiser la perte ou la corruption de données causées par la non fiabilité du moyen de transmission et ii) des algorithmes de ≪ pollution détection ≫, par exemple de détection de nœuds malveillants ou de paquets corrompus, cette détection et prévention étant très difficile dans des environnements fortement distribués. / The original “selling point” for decentralized networks has been file exchange, using the decentralized approach to diffuse the bandwidth cost between all the participating nodes, augmenting the robustness by avoiding single point of failures and control by sharing the responsibility between all nodes. While the most decentralized approaches are very efficient in terms of resilience they are, by the same reason, more performance limited and harder to analyze. This analysis is usually the sole realm of simulation tools, a quite in- efficient way to analyze the possibility space. We thus developed and present here a mathematical model for network interconnection, enabling the study and exploration of equilibriums and, by virtue of the abstraction of the model, perfectly applicable to any interconnection of networks, be them communication networks, social networks or, for example, water distribution networks. We also focused on decentralized networks, called MANETs, where communication between mobile nodes is purely ad-hoc based (eg.: two cars passing each other and communicating while in range), exploit- ing rateless coding to increase their robustness by minimizing data loss due to transmission unreliability, and detecting malicious nodes sending corrupted packets, a hard to detect and prevent problem in a strongly distributed environments, using SIEVE, a custom developed algorithm.

EUROPEAN AIR HUBS IN THE CONTEXT OF NETWORK AND ITS RESISTANCE AGAINST DISTURBANCES Abstract The submitted master thesis is addressing the theme of connectivity of European Air Transport Network, its properties and resistance against negative influences based on data from flight schedules for winter season 2018. The main objective of the thesis is to analyse European Air Transport Network from the point of connectivity in order to find out the most important airport hubs according to their geographic conditions, community structure and resistance of the whole network. Used methods are based on the Graph Theory and the centrality measures as indicators of connectivity. The empiric part of the thesis is divided into three parts. The aim of the first part is to find out, what airports are the most important in the European Air Transport Network. In the second part are explored properties and structure of the network. The last part is aiming to analyse the resistance of the European Air Transport Network from the view of robustness and resilience. Among the most important air hubs in Europe belong airports, that are serving world cities and tourist attractive localities. There is a strong dominance of the Schiphol airport in Amsterdam, the El Prat airport in Barcelona and the Frankfurt Airport. The European Air...

<div>"Can machines think?", the question brought up by Alan Turing, has led to the development of the eld of brain-inspired computing, wherein researchers have put substantial effort in building smarter devices and technology that have the potential of human-like understanding. However, there still remains a large (several orders-of-magnitude) power efficiency gap between the human brain and computers that attempt to emulate some facets of its functionality. In this thesis, we present design techniques that exploit the inherent variability in the difficulty of input data and the correlation of characteristic semantic information among inputs to scale down the computational requirements of a neural network with minimal impact on output quality. While large-scale artificial neural networks have achieved considerable success in a range of applications, there is growing interest in more biologically realistic models, such as, Spiking Neural Networks (SNNs), due to their energy-efficient spike based processing capability. We investigate neuroscientific principles to develop novel learning algorithms that can enable SNNs to conduct on-line learning. We developed an auto-encoder based unsupervised learning rule for training deep spiking convolutional networks that yields state-of-the-art results with computationally efficient learning. Further, we propose a novel "learning to forget" rule that addresses the catastrophic forgetting issue predominant with traditional neural computing paradigm and offers a promising solution for real-time lifelong learning without the expensive re-training procedure. Finally, while artificial intelligence grows in this digital age bringing large-scale social disruption, there is a growing security concern in the research community about the vulnerabilities of neural networks towards adversarial attacks. To that end, we describe discretization-based solutions, that are traditionally used for reducing the resource utilization of deep neural networks, for adversarial robustness. We also propose a novel noise-learning training strategy as an adversarial defense method. We show that implicit generative modeling of random noise with the same loss function used during posterior maximization, improves a model's understanding of the data manifold, furthering adversarial robustness. We evaluated and analyzed the behavior of the noise modeling technique using principal component analysis that yields metrics which can be generalized to all adversarial defenses.</div>

Les travaux de cette thèse portent sur l’analyse de stabilité et la synthèse de commandes robustes pour les systèmes linéaires à commutation en temps discret avec des incertitudes polytopiques et des incertitudes sur la loi de commutation. On considère des lois de commutations arbitraires et on montre que l’utilisation des fonctions de Lyapunov commutées dépendant de paramètres permet de déterminer des critères de stabilité et de stabilisation robuste moins conservatifs. Ensuite, des conditions de stabilité robuste pour les systèmes en temps discret avec une loi de commutation incertaine sont présentées en termes de temps minimum de séjour. Les résultats obtenus s’avèrent utiles dans le contexte de la commande numérique des systèmes continus en présence d’imprécisions sur les instants d’échantillonnage et d’application des commandes. Nous montrons comment une modélisation à base d’évènements permet de ramener le problème original à un problème spécifique aux systèmes à commutation avec des incertitudes polytopiques. Les résultats sont étendus au cas des systèmes à commutation continus commandés par des correcteurs numériques / This PhD thesis is dedicated to the study of robust stability analysis and control synthesis for discrete time uncertain switching systems under arbitrary switching. Polytopic uncertainties are considered. We show that Lyapunov functions that depend on the uncertain parameter and that take into account the structure of the system may be used in order to reduce the conservatism related to uncertainty problems. Next, we consider the case of discrete time switched systems that are stabilized by a switched state feedback for which the switching signal may be temporary uncertain. Dwell time conditions for stability analysis of such systems are given. These results are usefull in the context of continuous time are stabilized via a computer when uncertainties occur on the sampling and actuation events. We present a new event based discrete-time model and we show that the stabilizability of this system can be achieved by finding a control for a switched polytopic system. The methodology is extended to the case of switched system

Timber has become more popular as a construction material during recent years. Engineered wood products, such as glued laminated timber and cross-laminated timber, have enabled the construction of multi-storey buildings. Tall buildings with many occupants need to resist a disproportional collapse in case of unexpected exposures, e.g. accidents or terrorism. Structural robustness can improve the collapse resistance of a building. The literature about robustness is comprehensive concerning concrete and steel buildings, but it is rather limited regarding timber. A robust building can mobilise alternative load paths in the structure after the removal of bearing building components. Alternative load paths rely primarily on the connections between components. For timber buildings, few investigations exist to evaluate the alternative load paths after a removal. Analyses usually do not take into account non-linear effects which could influence the capacity of alternative load paths, such as damage of single fasteners, friction,  timber crushing and brittle failure. In particular, the alternative load paths in platform-framed cross-laminated timber buildings are not well understood.  The goals of this thesis are to i) review the concept of robustness in general and determine the state of the art concerning timber buildings in particular, ii) develop a method to analyse the alternative load paths in a platform-framed CLT building taking into account relevant non-linearities, iii) use the method to elicit the alternative load paths in a building after a wall removal, and iv) study the effects of probabilistic variations of model parameters.  The thesis first introduces tall timber buildings and then presents a summary of structural robustness in a collapse resistance framework. The summary includes established analysis methods and specific considerations for timber, whereof a detailed review is provided in Paper I. Paper III additionally provides results of a survey on contemporary practices of professionals around the world concerning robustness.  In the subsequent chapter, the studied 8-storey case building made of platform-framed cross-laminated timber is described including the modelling abstractions. Additionally, the setup of a validation experiment for the modelling approach is described. The following chapter introduces the modelling approach for an alternative load path analysis after a wall removal. The approach is based on the finite element method using the commercial software Abaqus. The deterministic part of the approach includes a non-linear static pushdown analysis of single storeys in a bay and elicits the alternative load paths and their capacity. Finite connector elements in the model substitute single fasteners including their elastic, plastic, damage and rupture behaviour. The 3D models of the walls and floors account for timber crushing, brittle failure and contact friction. A simplified non-linear dynamic model of the entire bay uses the pushdown results as inputs and evaluates the collapse progression among storeys after a sudden element removal. The probabilistic part of the approach models the uncertainty of the input parameters of the dynamic model by varying the parameter values in a Monte Carlo simulation, to evaluate the probability of a collapse.  Paper II applies the approach for a simple pushdown of a single storey and Paper IV applies the pushdown and the dynamic analysis to elicit the alternative load paths after a single wall removal. The thesis shows furthermore the results of a double wall removal in the example building and the results of the Monte Carlo analysis for the single and double wall removal.  For the assumed removals, the developed approach could identify the alternative load paths, determine their capacities and estimate the probability of a collapse under probabilistic variations. The approach might be used to classify various removal scenarios in platform-framed multi-storey cross-laminated timber buildings specifically and predetermine design solutions which could provide a desired level of robustness. The approach might be generalised for multi-storey timber buildings of various construction types.

Les travaux de cette thèse portent sur la stabilisation des systèmes affines commutés. Ces systèmes appartiennent à la classe des systèmes dynamiques hybrides. Ils possèdent de plus la particularité d'avoir des points de fonctionnement non auto-maintenables : il n'existe pas de loi de commutations permettant de maintenir l'état du système en ce point. De ce fait, la stabilisation de ces systèmes en imposant à la loi de commutations une durée minimale entre chaque commutation aboutit à une convergence des trajectoires dans une région de l'espace d'état. Après avoir synthétisé différentes stratégies de commutations échantillonnées construites à partir d'une fonction de commande de Lyapunov en temps continu, nous cherchons à déterminer la région de l'espace dans laquelle converge asymptotiquement l'ensemble des trajectoires du système. Par la résolution d'un problème d'optimisation, une estimation de la taille de cette région est donnée et un lien avec les incertitudes du système y est établi. Un second problème de stabilisation est étudié dans cette thèse, en considérant une stratégie de commande basée observateur par retour de sortie. Cependant, du fait de la nature hybride du système, son observabilité est directement liée à la séquence de commutations. Il est alors nécessaire de garantir à la fois l'observabilité, par une condition algébrique, et la convergence du système vers un point de fonctionnement, par l'existence d'une fonction de commande de Lyapunov / This PhD thesis deals with the stabilization of switched affine systems. These systems belong to the class of hybrid dynamical systems. They exhibit a particular behavior: no switching law exists such that the state can be maintained on a chosen operating point. Hence, assuming a dwell time condition on switchings exists, the stabilization of these systems leads to a convergence of the trajectories to a region of the state space. Based on a control Lyapunov function in continuous time, we synthesize several sampled-data switching strategies. The whole trajectories asymptotically converge to a region which we attempt to determine. Solving an optimization problem, an estimation of the size of this region is given. A link with the system uncertainties is also established. This PhD thesis is dedicated to a second stabilization issue: observer-based output-feedback synthesis. By its hybrid nature, the observability of the system is connected to the switching sequence. Therefore, the synthesis of the switching strategy must respect an observability condition and guarantee the convergence to the operating point. The observability is achieved thanks to an algebraic condition. The convergence property is based on the existence of a control Lyapunov function