This thesis explores barriers to widespread adoption of electric vehicles and proposes possible policy solutions. It analyzes main barriers including awareness, upfront cost, and range anxiety, as well as existing policy solutions, and a detailed case study examining policy differences in high adopting versus low adopting states. Awareness and eduction surrounding electric vehicles and their capabilities, financial incentives and market mechanisms for reducing costs, and charging infrastructure and efficiency improvements are examined. Conclusions were formed through interviews with various experts as a method of data collection. It was found that many existing state and local level policies could be scaled to a national level to facilitate rapid reductions in transportation emissions through electrification of the transportation sector.

This thesis deals with the design of extending the ICT infrastructure in Aumeto s.r.o. There are theoretical points, techniques and methods that are used later. The analysis of current data network in Aumeto s.r.o. was the goal of the first part. Designed part is based on that analysis.

Diploma thesis deals with monitoring critical infrastructure, critical information infrastructure and network monitoring in energetic industry. The goal is to create analytical environment for processing logs from the network, to map the most critical segments of the network and implementation of monitoring and network devices, that increase security and mitigate risks of security events or security incidents

This study examines the subsurface infrastructure in the Swedish city of Norrköping from an urban mining perspective. Urban mining is a broadly defined term for different strategies that regard the built environment as a resource base for materials. In this study, the focus is on three base metals that exist in large quantities in infrastructure parts: iron, copper and aluminium. A special focus is given to the parts of Norrköping’s infrastructure that are not in-use and thus constitute a ”hibernating stock” that contains recyclable metals. The main results of this study are twofold. First, a quantitative assessment of the hibernating stocks of urban infrastructure gives answers to how large the stocks are and where in Norrköping they are located. This was performed using a spatially informed Material Flow Analysis to arrive at a recycling potential in terms of weight and spatial concentration. Second, a qualitative assessment was made regarding how these hibernating stocks of urban infrastructure come into existence. An infrastructure studies perspective was used to outline three patterns with their own sets of ”hibernation” logics. These logics give rise to different prerequisites for the implementation of urban mining in practice. A main argument of this study’s cover essay is that both of the above outlined kinds of knowledge are needed to engage in urban mining with confidence. Thus, the main focus of the cover essay text is to describe how the two different perspectives of Material Flow Analysis and infrastructure studies were combined into a coherent research approach.

La résilience concerne une capacité importante d'un système à résister et à se remettre des événements perturbateurs. L'objectif de cette thèse est de construire un cadre d'analyse et d'optimisation de la résilience des infrastructures critiques interconnectées (ICIs). Dans ce travail, les contributions scientifiques originales comprennent: 1) une approche de modélisation générique pour décrire le comportement dynamique et les processus d'échec en cascade dans les ICIs. 2) basé sur le modèle proposé, une approche quantitative d'évaluation de la résilience de ICIs est développée, où les aspects d'atténuation et de récupération sont évalués; 3) afin de réduire le coût de calcul dans le cas de systèmes à grande échelle, trois méthodes Différentes échelle, trois méthodes différentes d'analyse de sensibilité globale (ANN estimation, ensemble-based, given-data estimation), sont mis en place pour identifier les paramètres de modèle les plus pertinents affectant la résilience du système, puis les performances de ces méthodes sont comparées;4) un modèle hiérarchique est développé pour caractériser les facteurs de stratégies d'amélioration de la résilience. Un problème d’optimisations multi-objectif est formulé et résolu par l'algorithme NSGA-II, afin de fournir un plan optimal pour l'amélioration de la résilience du système. Les méthodes proposées sont mises en œuvre dans les applications, par exemple, un réseau d'alimentation en gaz et un réseau électrique. / Resilience is the ability of a system to resist to and recover from disruptive events. The objective of this thesis is to build a framework of analysis and optimization of interconnected critical infrastructures (ICIs) resilience. In this work, the original scientific contributions include: 1) a generic modeling approach to describe the dynamic behavior and the physical cascading failure processes in ICIs.2) on the basis of the model, a quantitative resilience assessment approach for ICIs is proposed, where both the mitigation and recovery aspects of system resilience are evaluated; 3) in order to reduce the computational cost in the case of large-scale systems, three different global sensitivity analysis methods (ANN estimation, ensemblebased, give-data estimation) are implemented to identify the most relevant model parameters affecting the system resilience, and then the performance of these methods are compared; 4) a hierarchical model is developed to characterize the factors of resilience improvement strategies. A multi-objectives optimization problem is formulated and solved by NSGA-II algorithm, to provide the optimal plan for system resilience improvement. The methods proposed are implemented to applications, e.g., a gas supply network and an electrical power grid.

abstract: This dissertation advances the capability of water infrastructure utilities to anticipate and adapt to vulnerabilities in their systems from temperature increase and interdependencies with other infrastructure systems. Impact assessment models of increased heat and interdependencies were developed which incorporate probability, spatial, temporal, and operational information. Key findings from the models are that with increased heat the increased likelihood of water quality non-compliances is particularly concerning, the anticipated increases in different hardware components generate different levels of concern starting with iron pipes, then pumps, and then PVC pipes, the effects of temperature increase on hardware components and on service losses are non-linear due to spatial criticality of components, and that modeling spatial and operational complexity helps to identify potential pathways of failure propagation between infrastructure systems. Exploring different parameters of the models allowed for comparison of institutional strategies. Key findings are that either preventative maintenance or repair strategies can completely offset additional outages from increased temperatures though-- improved repair times reduce overall duration of outages more than preventative maintenance, and that coordinated strategies across utilities could be effective for mitigating vulnerability. / Dissertation/Thesis / Doctoral Dissertation Civil, Environmental and Sustainable Engineering 2019

De aktuella klimatförändringarna skapar utmaningar för västkustens kommuner. Detta skapar möjligheter för den blå-gröna infrastrukturen att samspela med de traditionella dagvattenledningsystemen för att skapa en mer hållbar dagvattenhantering. Syftet med denna studie är därför att undersöka hur Kungsbacka, Halmstads och Varbergs kommun arbetar med hållbar dagvattenhantering i praktiken för att motverka framtida översvämningar samt att undersöka vilka faktorer som påverkar kommunernas arbete med blå-grön infrastruktur. Studien har en kvalitativ tillvägagångsmetod i form av dokumentanalys samt semistrukturerade intervjuer. Med utgångspunkt i hållbarhetsövergångsteorin Multi-level perspective har de framtagna dokumenten och intervjuerna analyserats vilket konstaterar att politikerna ofta försvårar utvecklingen av blå-grön infrastruktur. Även utmaningar som geotekniska förutsättningar och markbrist påverkar den blå-gröna infrastrukturens möjlighet att frodas. Den breda tolkningen som kommunerna har av begreppet hållbar dagvattenhantering bidrar till en vidareutveckling av den blå-gröna infrastrukturen. Även klimathändelser påverkar den blå-gröna infrastrukturens förutsättning för genomslag hos den traditionella dagvattenhanteringen. / Climate change is creating challenges for the municipalities on the West Coast. This provides opportunities for blue-green infrastructure to collaborate with traditional stormwater management systems to create more sustainable stormwater management. The purpose of this study is therefore to investigate how the municipalities of Kungsbacka, Halmstad, and Varberg are working with sustainable stormwater management to counteract future flooding, and to examine the factors that affect the municipalities' work with blue-green infrastructure. Based on the sustainability transition theory Multi-level perspective, the documents and interviews have been analyzed, which states that politicians often hinder the development of blue-green infrastructure. Challenges such as geotechnical conditions and land shortage also affect the blue-green infrastructure's ability to thrive. Municipalities' broad interpretation of sustainable stormwater management promotes the sustainable stormwater management and therefore blue-green infrastructure development. Climate events affect the conditions for breakthroughs in traditional stormwater management.

The aim of this paper was to investigate whether infrastructure could be modelled in order to find critical points using network science and graph theory. Since a lot of information about ourinfrastructures is publicly available, an attacker might exploit this to find vulnerabilities in our systems. With that in mind, the methods of this paper were implemented from an attackers point of view who’d want to maximize harm with minimal effort. The Swedish railway network served as an example and starting point for the optimization of the methods. The data for the network was obtained from the Swedish Transport Agency’s website and was implemented in Networkx using Python. Different centrality metrics were used to identify and remove critical nodes in the network. The centrality metrics were also used to rank the nodes and to remove them after order of importance as the size of the largest component was recorded. This was done both with no recalculation and with a recalculation after each removal. The results were compared with the random removal of nodes, and it showed that without a recalculation the random removal performed better but with recalculation all the centrality metrics performed significantly better. The Swedish railway network is a sensitive network in terms of how it is connected. Targeting a few nodes could completely cut off parts of the graph, creating two sub components with no way of traveling between them. Many different methods can identify these nodes, but only a few are suitable in terms of generic results that could work on other networks as well. The most prominent one being the one dealing with degree and connectivity. The nodes that had a higher degree than connectivity between themselves and the source, identified nodes that would completely disrupt the network, leaving two subcomponents. Infrastructures can be seen as highly intertwined systems, where the physical-, cyber- and human parts all affect and interact with each other.

Over the past several decades, flooding events in the United States have become the most frequent and costliest natural disaster. In the US, city and regional leaders are planning new water and flood mitigation infrastructure in response to the challenges of flooding, uneven urbanization, and racialized exclusion. Historically, projects to keep water out have never been universal or evenly applied. Yet, ‘learning to live’ with water, a key tagline in current sustainable development paradigms, masks how histories of racialized land development are entangled with contemporary water infrastructure projects and are productive of regional planning power. This dissertation centers racial capitalism in analysis of how contemporary water infrastructure projects are entangled with, and informed by, histories of racialized land development in the mid-Mississippi River Region. Through two case studies on flood mitigation infrastructure in eastern Missouri, I trace the historic development of infrastructures that shape the ongoing racialization of space, infrastructure (re)development and community vulnerability to flooding today. The case studies draw from a range of data, including archival research on histories of land and infrastructure development, participant observation of planning meetings, professional conferences, and local neighborhood initiatives, and field observations of the built environment. I argue that 1) scholarship concerned with social-environmental inequities should engage racial capitalism as a framework to “provincialize” urban theory and environmental racism as a means to theorize uneven infrastructural provisioning as a mode of urbanization that (re)produces social difference and value creation under racial capitalism, 2) the historical development of flood control in the Mississippi region was fundamental to the development of racial capitalism because it consolidated regional planning power through methods of social and environmental domination, and 3) contemporary infrastructural redevelopment and flood mitigation projects must contend with the path dependencies of structural racism to disrupt existing cycles of marginalization across social differences to deliver meaningfully on equity goals. Ultimately, this study finds that flood-mitigation infrastructures, including levees, floodways, and dams, on the Missouri River and gray and green stormwater infrastructure (GSI) in the City of St. Louis are embedded in broader social-environmental networks and regional power blocs, whose regional history and dynamics have created distinct patterns of uneven urbanization and vulnerability to flooding disasters. Because infrastructure projects are embedded in the built environment for decades, the social relations comprising their implementation, or lack thereof, reach into present and future development considerations. Thus, when planning projects fail to grapple with path dependencies of past infrastructure projects, they may reproduce structural racism and re-create patterns of uneven urbanization and vulnerability to flooding disasters. / Geography

The U.S. Air Force (USAF) estimates it has a $33 billion (about 10 percent is airfield pavements) deferred maintenance backlog within its $263 billion infrastructure portfolio. Given the scope of this backlog and the importance of airfields, the USAF has a vested interest in finding strategies to help reverse this growing trend. Without an increase in funding, divestiture of excess infrastructure, or change in strategy, this backlog is estimated to climb to over $50 billion by 2030. Reversing the growing infrastructure backlog trend requires new methods and strategies to rethink how the USAF invests in its infrastructure. As such, the overall goal of this research is to develop a comprehensive and practical asset management approach to reduce the total cost of ownership of USAF airfield pavements. By reducing the cost of ownership, the goal is to reverse the growing maintenance backlog while maintaining a pavement portfolio capable of supporting USAF flying operations into the future. While this research is particularly relevant to the USAF, it seeks to fill research gaps within the current body of knowledge related to pavement management strategies for other agency types by presenting a practical, simulation-based methodology for work planning and budget allocation across a large pavement portfolio over a thirty-year period. The dissertation presents the development of the BEAST and RAMPSS algorithms. The BEAST algorithm is a simulation tool capable of modeling behaviors and decisions of 109 organizations managing a global network of airfield pavements over thirty years. Additionally, the BEAST is used to forecast outcomes of USAF investment decisions utilizing its current management strategies and historical behaviors. The RAMPSS is a simulation algorithm designed to select the most economical maintenance strategy for each pavement section in the USAF’s portfolio (i.e., individualized maintenance recommendation strategy for each pavement section). Analysis from the RAMPSS algorithm of the USAF’s pavement portfolio suggests that airfields are generally more cost-effective to maintain if kept in better conditions with strategies other than localized preventative maintenance. The USAF’s current maintenance strategy is unsustainable; however, switching to recommendations from RAMPSS (incorporated and modeled in the BEAST) provides a potentially significant course correction.