Winter Storm Uri damaged parts of the United States, Mexico, and Canada in February of 2021. The State of Texas was heavily affected due to the institutional failure of Texas's primary power provider, the Electric Reliability Council of Texas (ERCOT). Despite similar previous storms that exposed weaknesses in the state's power grid system in 1999 and 2011, ERCOT did not make the necessary changes to prevent a future disaster. The purpose of this study is to advance the understanding of the concept of recreancy through the exploration of eight different dimensions of the concept: trust or distrust in institutions; institutional responsibility for disaster preparedness; responsibility for impacts of a disaster; effectiveness or ineffectiveness of institutions in responding to a disaster; an institution's capability of preventing a similar event in the future; an institution's willingness to make changes in their actions or behavior; confidence that an institution will prevent a similar event in the future; and responsibility for compensation for impacts of a disaster. To examine the composition of the concept of recreancy, I analyzed survey data collected in Texas during April and May of 2022. I aggregated and coded survey data according to the level respondents reported to agree with the survey indicators measuring dimensions of recreancy. I utilized Confirmatory Factor Analysis to analyze if the derived dimensions of recreancy measure recreancy, and if some are more salient than others. Confirmatory Factor Analysis revealed variability in the importance of different dimensions of recreancy, suggesting that some dimensions are more salient than others in shaping residents' perceptions of recreancy in the context of Winter Storm Uri. Further analysis revealed a preliminary model to operationalize recreancy, however further analysis is needed. / Master of Science / In February 2021, Winter Storm Uri devasted regions of the United States, Mexico, and Canada. The state of Texas experienced significant storm impacts due to the failure of its primary power provider, the Electric Reliability Council of Texas (ERCOT). ERCOT is responsible for overseeing and managing the state's power grid. Similar storms in 1999 and 2011 revealed weaknesses in the power grid's infrastructure—state officials mandated but did not require weatherization precautions to prevent future grid failures. ERCOT did not implement the suggested changes and the power grid failure during Winter Storm Uri left millions of Texas residents without access to power, heat, water, and other necessary services. This thesis explores residents' perceptions of ERCOT's institutional failure—recreancy—and aims to understand the concept of recreancy through the examination of eight dimensions: trust or distrust in institutions; institutional responsibility for disaster preparedness; responsibility for impacts of a disaster; effectiveness or ineffectiveness of institutions in responding to a disaster; an institution's capability of preventing a similar event in the future; an institution's willingness to make changes in their actions or behavior; confidence that an institution will prevent a similar event in the future; and responsibility for compensation for impacts of a disaster. I analyzed survey respondents' levels of agreement with each dimension and utilized Confirmatory Factor Analysis to assess the relative importance of the dimensions and if they accurately capture recreancy.

Due to power system deregulations, transmission expansion not keeping up with the load growth, and higher frequency of natural hazards resulting from climate change, major blackouts are becoming more frequent and are spreading over larger regions, entailing higher losses and costs to the economy and the society of many countries in the world. Large-scale blackouts typically result from cascading failure originating from a local event, as typified by the 2003 U.S.-Canada blackout. Their mitigation in power system planning calls for the development of methods and algorithms that assess the risk of cascading failures due to relay over-tripping, short-circuits induced by overgrown vegetation, voltage sags, line and transformer overloading, transient instabilities, voltage collapse, to cite a few. How to control the economic losses of blackouts is gaining a lot of attention among power researchers. In this research work, we develop new Monte Carlo methods and algorithms that assess and manage the risk of cascading failure in composite reliability of deregulated power systems. To reduce the large computational burden involved by the simulations, we make use of importance sampling techniques utilizing the Weibull distribution when modeling power generator outages. Another computing time reduction is achieved by applying importance sampling together with antithetic variates. It is shown that both methods noticeably reduce the number of samples that need to be investigated while maintaining the accuracy of the results at a desirable level. With the advent of microgrids, the assessment of their benefits in power systems is becoming a prominent research topic. In this research work, we investigate their potential positive impact on power system reliability while performing an optimal coordination among three energy sources within microgrids, namely renewable energy conversion, energy storage and micro-turbine generation. This coordination is modeled when applying sequential Monte Carlo simulations, which seek the best placement and sizing of microgrids in composite reliability of a deregulated power system that minimize the risk of cascading failure leading to blackouts subject to fixed investment budget. The performance of the approach is evaluated on the Roy Billinton Test System (RBTS) and the IEEE Reliability Test System (RTS). Simulation results show that in both power systems, microgrids contribute to the improvement of system reliability and the decrease of the risk of cascading failure. / Ph. D.

Yes / This paper presents the development and implementation of an Analytical Target Cascading (ATC) Multi-disciplinary Design Optimisation (MDO) framework for the steady state engine calibration optimisation problem. The case is made that the MDO / ATC offers a convenient framework for the engine calibration optimisation problem based on steady state engine test data collected at specified engine speed / load points, which is naturally structured on 2 hierarchical levels: the “Global” level, associated with performance over a drive cycle, and “Local” level, relating to engine operation at each speed / load point. The case study of a gasoline engine equipped with variable camshaft timing (VCT) was considered to study the application of the ATC framework to a calibration optimisation problem. The paper describes the analysis and mathematical formulation of the VCT calibration optimisation as an ATC framework, and its Matlab implementation with gradient based and evolutionary optimisation algorithms. The results and performance of the ATC are discussed comparatively with the conventional two-stage approach to steady state calibration optimisation. The main conclusion from this research is that ATC offers a powerful and efficient approach for engine calibration optimisation, delivering better solutions at both “Global” and “Local” levels. Further advantages of the ATC framework is that it is flexible and scalable to the complexity of the calibration problem, and enables calibrator preference to be incorporated a priori in the optimisation problem formulation, delivering important time saving for the overall calibration development process. / The research work presented in this paper was funded by UK Technology Strategy Board (TSB) through the CREO (Carbon Reduction through Engine Optimisation) project.

No / This paper presents the development of an Analytical Target Cascading (ATC) Multidisciplinary Design Optimization (MDO) framework for a steady-state engine calibration optimization problem. The implementation novelty of this research is the use of the ATC framework to formulate the complex multi-objective engine calibration problem, delivering a considerable enhancement compared to the conventional 2-stage calibration optimization approach [1]. A case study of a steady-state calibration optimization of a Gasoline Direct Injection (GDI) engine was used for the calibration problem analysis as ATC. The case study results provided useful insight on the efficiency of the ATC approach in delivering superior calibration solutions, in terms of “global” system level objectives (e.g. improved fuel economy and reduced particulate emissions), while meeting “local” subsystem level requirements (such as combustion stability and exhaust gas temperature constraints). The ATC structure facilitated the articulation of engineering preference for smooth calibration maps via the ATC linking variables, with the potential to deliver important time saving for the overall calibration development process.

The External Enablers framework was developed to provide structure and terminology for the analysis of entrepreneurial opportunities. External Enablers (EEs) refer to changes in the environment such as regulatory changes, demographic shifts, or new technologies that enable an individual to create and develop ventures (Davidsson, 2015; Davidsson et al., 2020; Kimjeon & Davidsson, 2021). The framework aims to explain the cause-effect relationships between environmental changes and benefits that ventures experience, via EE mechanisms. EE mechanisms connect to responses in entrepreneurs through relational qualities called opacity and agency intensity. However, recent studies have found that entrepreneurs may ignore significant external changes in the environment, regardless of opacity and agency intensity considerations. Consequently, something else might explain agents’ engagement in venture creation. Another shortcoming of the framework is that it has yet to integrate the possibility that EEs might trigger consecutive EEs, in addition to agents acting on them through, for example, cascading effects. This thesis explores entrepreneurial action and its interplay with external enablers. We investigate why certain individuals act entrepreneurially upon multiple EEs. Previous research has stated that entrepreneurs may ignore opacity and agency intensity considerations. Hence, opacity and agency intensity may not be enough to explain why agents act on EEs. We conducted a qualitative multicase study, to identify patterns and relationships for theory building adhering to grounded theory traditions. Four cases from the Swedish wine industry were chosen, two “pioneers” (that is, early entrants in the wine industry in Sweden) and two “followers” (that is, later entrants). The industry serves as an appropriate empirical setting due to its novelty, where the environment changed rapidly, enabling a new industry to emerge from the 90s. Archival material and semi-structured interviews were combined, where a total of 21 interviews were conducted with vineyard founders, owners, and one expert. The findings show that the pioneers faced high opacity and agency intensity. Therefore, we introduce a third relational quality called Enthusiasm Fit. A high enthusiasm fit helps the pioneers “see through” a high opacity and overcome agency intensity, resulting in acting upon multiple and consecutive EEs. We also found that pioneers contribute to creating other EEs, resulting in cascading effects, where one EE generates reactions in another. Moreover, the followers don’t require a high enthusiasm fit but need the cascading effects produced by pioneers, to lower opacity and agency intensity considerations.

This diploma thesis covers a solution of designing the information system for HNS mechanix ltd. This company provides auditorial services of optical products. During the desining not only the requirements of functionality and attributes of the system itself but also implementation and developing tools are necessary to be followed. The system is required to be available as WWW service with multilevel user access.

An den automobilen Entwicklungsprozess werden zunehmend Anforderungen hinsichtlich der Verkürzung von Entwicklungszeiten, der Verringerung von Entwicklungskosten sowie der Verlagerung der Entwicklung hin zu frühen Entwicklungsphasen gestellt. Um diese Anforderungen zukünftig erfüllen zu können, ist es notwendig, geeignete Prozesse und Entwicklungsmethoden zu erarbeiten, die bereits in frühen Entwicklungsphasen zu robusten Konzepten führen. In der vorliegenden Arbeit wird dazu eine Fahrwerkauslegungsmethode für die Konzeptphase entwickelt, mit der es entsprechend des V-Entwicklungsmodells innerhalb von zwei Auslegungsschritten möglich ist, aus Gesamtfahrzeugeigenschaftszielen für Fahrdynamik und Fahrkomfort Subsystemziele für den Reifen, die Achskinematik und Achselastokinematik sowie für die Lenkung abzuleiten. Die entwickelte Auslegungsmethode basiert auf dem Target-Cascading-Ansatz und nutzt effektive Achscharakteristika, um die Wirkzusammenhänge innerhalb des Fahrwerks während der Auslegung aufzuzeigen. Mithilfe der in dieser Arbeit entwickelten Auslegungsmethodik ist ein wichtiger Beitrag zur zielgerichteten Ableitung von Fahrwerkeigenschaften geschaffen, der eine deutliche Verkürzung der Entwicklungszeiten und der damit einhergehenden Entwicklungskosten innerhalb der frühen Entwicklungsphase des Fahrwerks ermöglicht.:Vorwort und Danksagung Kurzfassung und Abstract Nomenklatur 1. Einführung 1.1. Motivation zur Entwicklung einer Fahrwerkauslegungsmethode für die Konzeptphase 1.2. Zielstellung und Struktur der Arbeit 1.3. Eingrenzung der Aufgabenstellung 2. Wissenschaftliche Grundlagen 2.1. Konzeptphase im Automobil-Entwicklungsprozess 2.2. Arbeitsraum des Fahrzeugs eines Normalfahrers 2.2.1. Fahrgeschwindigkeiten 2.2.2. Längs- und querdynamischer Arbeitsraum 2.2.3. Vertikaldynamischer Arbeitsraum 2.3. Objektivierung des Fahrverhaltens 2.3.1. Objektivierung der Längs- und Querdynamik 2.3.2. Objektivierung der Vertikaldynamik 2.4. Stand der Technik hinsichtlich Achsauslegungsmethoden 2.4.1. Klassische Auslegungsmethoden 2.4.2. Auslegungsmethoden auf Basis von Optimierungsalgorithmen 2.4.3. Wissensbasierte und strukturelle Auslegungsmethoden 2.4.4. Mischansätze 2.5. Zusammenfassung und Diskussion 3. Identifikation und Analyse relevanter Fahrwerkeigenschaften zur Integration in die Auslegungsmethode 3.1. Untersuchung der Subsystemeigenschaften der elektromechanischen Lenkung 3.2. Untersuchung der Subsystemeigenschaften der Achsen 3.2.1. Kinematische Achseigenschaften 3.2.2. Elastokinematische Achseigenschaften 3.2.3. Dämpfungseigenschaften der Achse 3.3. Untersuchung der Subsystemeigenschaften des Reifens 3.4. Zusammenfassung 4. Aufbau eines analytisch-physikalischen Wirkkettenverständnisses zwischen Gesamtfahrzeug- und Subsystemverhalten 4.1. Ableitung von Einfachmodellen zur Beschreibung der analytischen Wirkzusammenhänge 4.1.1. Einfachmodell zur Beschreibung der querdynamischen Wirkzusammenhänge 4.1.2. Einfachmodell zur Beschreibung der längs- und vertikaldynamischen Wirkzusammenhänge 4.2. Validierung der Einfachmodelle 4.2.1. Validierung des Einfachmodells zur Beschreibung der Querdynamik 4.2.2. Validierung des Einfachmodells zur Beschreibung der Längs- und Vertikaldynamik 4.3. Zusammenfassung 5. Entwicklung einer Achsauslegungsmethode für die Konzeptphase der Fahrwerkentwicklung 5.1. Strukturierung des Auslegungsprozesses 5.1.1. Definition und Herleitung der effektiven Achscharakteristika 5.1.2. Aufbau und Eigenschaften der effektiven Achscharakteristika 5.2. Detaillierung der Auslegungsmethode 5.2.1. Definition der objektiven Gesamtfahrzeugeigenschaften 5.2.2. Auslegung in Schritt 1 5.2.3. Auslegung in Schritt 2 5.2.4. Umsetzbarkeit der abgeleiteten Subsystemeigenschaften 5.3. Erweiterung und Automatisierung der Auslegungsmethode 5.3.1. Grundprinzip des Solution-Space-Algorithmus 5.3.2. Anpassung und Integration des Solution-Space-Algorithmus in die Achsauslegungsmethode 5.4. Zusammenfassung 6. Untersuchung und Evaluation der Achsauslegungsmethode anhand einer Beispielauslegung 6.1. Zielwertdefinition auf Basis einer Wettbewerbsanalyse 6.1.1. Längsdynamik 6.1.2. Querdynamik 6.1.3. Vertikaldynamik 6.1.4. Zusammenfassung der Zielanforderungen 6.2. Beispielauslegung auf Basis der manuellen Achsauslegungsmethode 6.2.1. Auslegung in Schritt 1 6.2.2. Auslegung in Schritt 2 6.2.3. Ergebnis der Auslegung, Umsetzbarkeit und Zielerreichung 6.3. Beispielauslegung auf Basis der erweiterten automatisierten Achsauslegungsmethode 6.3.1. Auslegung in Schritt 1 6.3.2. Auslegung in Schritt 2 6.4. Vergleich zu bisherigen Methoden 6.5. Zusammenfassung 7. Zusammenfassung und Handlungsempfehlung Literaturverzeichnis Abbildungsverzeichnis Tabellenverzeichnis Anhang A.1. Konzepteigenschaften des Beispielfahrzeugs A.2. Kinematische Achseigenschaften des Beispielfahrzeugs A.3. Elastokinematische Achseigenschaften des Beispielfahrzeugs A.3.1. Einfluss der Längskraft auf die Radstellung A.3.2. Einfluss des Spinmoments auf die Radstellung A.3.3. Einfluss der Seitenkraft und des Sturzmoments auf die Radstellung A.3.4. Einfluss des Rückstellmoments auf die Radstellung A.3.5. Einfluss der Vertikalkraft auf die Radstellung A.4. Erstellung eines Allgemeinmodells zur Beschreibung des Fahrverhaltens A.5. Herleitung der verwendeten Simulationsmodelle A.5.1. Einfachmodell zur Beschreibung der Querdynamik A.5.2. Einfachmodell zur Beschreibung der Längs- und Vertikaldynamik A.6. Ableitung der Übersetzungen und Nachgiebigkeiten A.7. Vergleich des Fahrzeugverhaltens vor und nach der Auslegung mithilfe der entwickelten Auslegungsmethode

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.

This thesis evaluates and develops a method for studying the occurrence of cascading effects between critical infrastructures. The thesis also analyzes how the results of previous research using the method may have been affected by certain aspects of the method. Applying different inclusion thresholds and exploring how material could be gathered differently, the thesis provides some tentative answers to the value of using newspaper articles when studying cascading effects. In addition, the thesis offers recommendations for future research and policy on the protection of critical infrastructures.

This thesis evaluates and develops a method for studying the occurrence of cascading effects between critical infrastructures. The thesis also analyzes how the results of previous research using the method may have been affected by certain aspects of the method. Applying different inclusion thresholds and exploring how material could be gathered differently, the thesis provides some tentative answers to the value of using newspaper articles when studying cascading effects. In addition, the thesis offers recommendations for future research and policy on the protection of critical infrastructures.