Civil infrastructure systems form the backbone of modern civilization, providing the basic services that allow society to function. Effective management of these systems requires decision-making about the allocation of limited resources to maintain and repair infrastructure components and to replace failed or obsolete components. Making informed decisions requires an understanding of the state of the system; such an understanding can be achieved through a computational or conceptual system model combined with information gathered on the system via inspections or sensors. Gathering of this information, referred to generally as sensing, should be optimized to best support the decision-making and system management processes, in order to reduce long-term operational costs and improve infrastructure performance. In this work, an approach to optimal sensing in infrastructure systems is developed by combining probabilistic graphical models of infrastructure system behavior with the value of information (VoI) metric, which quantifies the utility of information gathering efforts (referred to generally as sensor placements) in supporting decision-making in uncertain systems. Computational methods are presented for the efficient evaluation and optimization of the VoI metric based on the probabilistic model structure. Various case studies on the application of this approach to managing infrastructure systems are presented, illustrating the flexibility of the basic method as well as various special cases for its practical implementation. Three main contributions are presented in this work. First, while the computational complexity of the VoI metric generally grows exponentially with the number of components, growth can be greatly reduced in systems with certain topologies (designated as cumulative topologies). Following from this, an efficient approach to VoI computation based on a cumulative topology and Gaussian random field model is developed and presented. Second, in systems with non-cumulative topologies, approximate techniques may be used to evaluate the VoI metric. This work presents extensive investigations of such systems and draws some general conclusions about the behavior of this metric. Third, this work presents several complete application cases for probabilistic modeling techniques and the VoI metric in supporting infrastructure system management. Case studies are presented in structural health monitoring, seismic risk mitigation, and extreme temperature response in urban areas. Other minor contributions included in this work are theoretical and empirical comparisons of the VoI with other sensor placement metrics and an extension of the developed sensor placement method to systems that evolve in time. Overall, this work illustrates how probabilistic graphical models and the VoI metric can allow for efficient sensor placement optimization to support infrastructure system management. Areas of future work to expand on the results presented here include the development of approximate, heuristic methods to support efficient sensor placement in non-cumulative system topologies, as well as further validation of the efficient sensing optimization approaches used in this work.

The safety of dams is crucial in ensuring the continual availability of water, safety of the surrounding communities and infrastructure. Surveillance systems are implemented to monitor the structural integrity of certain dams which have a safety risk. The components and extent of the surveillance systems adopted depends on many factors, which include the type of dam wall structure used to impound the reservoir, geotechnical and environmental conditions. The case study used for this thesis is Kouga Dam located in the Eastern Cape Province of South Africa. It is a double curvature, concrete arch dam which supplies water for domestic, irrigation and industrial use to the Gamtoos River Valley and Nelson Mandela Metropolitan. During construction the stability of the right flank was questioned and subsequently, remedial measures were taken in order to increase the shear resistance of this flank. Previous dam safety evaluations also noted the possibility of Alkali Silica Reaction (ASR) occurring within the structure which resulted in concrete swelling and loss of strength. Due to these factors and the large hazard potential rating associated with this dam an intensive surveillance system has been used to monitor the dam's behaviour during operation. In this thesis the results of the surveillance system is analysed. A strong linear relationship exists between the temperature loading and displacement response of the dam wall. Changes in temperature initiate the response of the structure almost instantaneously. A more complex relationship exists between hydrostatic loading and the displacement response of the structure. A phase lag of approximately one to three months is evident between these two variables. Since construction the displacement and strain rates in the upstream (y) and upward (z) directions are 0.3mm/annum and 8.6με/annum respectively. However, since 1989 there has been a reduction in the average displacement and strain rates in all directions by approximately 70%. This may suggest that the ASR has stabilized. The vertical construction joints, especially the central and upper joints, are relatively open during low water levels. The structure is found to transfer the imposed loading mainly to the central foundation via dominant cantilever action. As a result the reaction forces on the upper foundation have been found to be relatively low, lowering the risk of potential shear failure of the right foundation. Small foundation movements of less than 0.3mm have been observed within the foundation downstream of the dam wall on the right flank. These movements are between 10 and 40m within the foundations.

Abstract This thesis deals with the process of server consolidation, which is tightly connected to IT infrastructure of virtually any organization. Moreover it is dealt in some respect with the way the organization runs and with linking these two particular areas together. The goal of this thesis is to identify consequences or impacts of server consolidation process on the way the organization functions and on methods how to measure these impacts. One of the steps towards this goal is unmistakably analyzing the planning and deployment of server consolidation including virtualization technology. Server consolidation is characterized as a process leading to simplified and more effective IT infrastructure of an organization. To analyze the IT infrastructure in complete and systematic way it is used framework called IT Infrastructure Library respectively part of it called ICT Infrastructure Management. Because of that linking of the server consolidation process progress to organization's global goals is granted. Contribution of this thesis can be seen in complex analysis of the consequences of the server consolidation process to the functioning of an organization. Especially in areas that are usually not being considered in connection with server consolidation, which is considered to be IT matter, such as human resources and social enviroment. Key words: server consolidation, server consolidation consequences, ICT Infrastructure Management, Virtualization

Thesis (MEng)--Stellenbosch University, 2015. / ENGLISH ABSTRACT: The Department of Water Affairs and Forestry infrastructure has shown a decline in condition from 2006 to 2011, according to the Infrastructure Report Card. With the increase in population, the additional demand placed on the already ageing infrastructure together with inadequate maintenance exacerbates the deterioration of these structures. Much has been done to improve the provision of basic water services to South Africans, however to ensure that basic water services remain intact, maintenance of the existing structures is of paramount importance. The storage of potable water in a hygienic manner is essential to the water provision network, thus focus is placed on water reservoirs (in particular reinforced concrete water reservoirs). It has been identified that there is a lack of appropriate policies, practices, procedures and guidelines related to the maintenance of municipal water reservoirs. The solution that this study proposes is to develop a maintenance prioritization method for reinforced concrete water reservoirs. This method specifically provides the user (i.e facility manager) with a systematic approach to assessing and allocating a condition value to the reservoir, which is used to prioritize maintenance activities. This method follows the approach used by the TRH/TMH manuals and bridge management systems that are implemented throughout South Africa. This method includes, the breakdown of essential reservoir components thus facilitating the development of future asset registers, the deterioration mechanisms that affect these reservoirs along with the appropriate identification methodologies and the percentage contributions of each component to the overall condition of the facility. The research for the prioritization method is conducted by combining literature with feedback from industry professionals. The literature featured investigation of the components of concrete reservoirs and deterioration mechanisms that affect these components. The results of the feedback from the industry professionals indicated that some of the components contribute more to the overall condition of the facility than others. This contribution is based on the importance of the component with regard to the provision of service and safety. Thus, in the case of a concrete reservoir, the walls are more essential to the provision of service and safety than the access components, thus its contribution percentage is higher. The research suggests that if the prioritization method could successfully be implemented, it will provide the users additional information that can be used to prioritise maintenance activities at both component and network level. Further, it may allow for the development of a comprehensive asset register of concrete reservoirs and may also aid in the financial planning related to the maintenance of these structures. / AFRIKAANSE OPSOMMING: Die Departement van Waterwese en Bosbou se infrastruktuur het n afname in kondisie gradering getoon van 2006 tot 2011 volgens die Infrastruktuur Verslag Kaart. Die toename in die bevolking veroorsaak bykomende druk op die reeds verouderende infrastruktuur wat tesame met swak instandhouding die agteruitgang van hierdie strukture vererger. Baie is gedoen om die voorsiening van basiese waterdienste aan Suid-Afrikaners te verbeter, maar dit is uiters noodsaaklik dat bestaande strukture in stand gehou word om te verseker dat basiese waterdienste beskikbaar bly. Die berging van drinkwater op ’n higiëniese wyse is noodsaaklik vir die watervoorsieningsnetwerk met die gevolg dat daar op waterreservoirs, spesifiek gewapende beton waterreservoirs, gefokus word. Daar is vasgestel dat daar nie toepaslike praktyke, prosedures en riglyne met betrekking tot die instandhouding van van munisipale waterreservoirs bestaan nie. Die oplossing wat deur hierdie studie voorgestel word, is om ’n onderhoud prioritisering metode vir gewapende beton waterreservoirs te ontwikkel. Hierdie metode bied spesifiek aan die gebruiker (reservoir bestuurder) ’n sistematiese benadering om ’n toestandwaarde ten opsigte van die reservoir te bepaal en toe te wys, wat gebruik word om instandhoudingsaktiwiteite te prioritiseer. Hierdie metode volg die benadering van die TRH/TMH en brug bestuur sisteme, wat geimplimenteer word reg deur Suid Afrika. Hierdie metode sluit in die klassifiseering van hoof komponente van ’n gewapende beton reservoir wat die ontwikkeling van toekomstige bateregisters, die degenerasiemeganismes wat hierdie reservoirs beïnvloed tesame met die gepaste identifiseringsmeganismes en die bydrae volgens persentasie van elke komponent tot die algehele toestand van die fasiliteit, fasiliteer. Die navorsing ten opsigte van die prioritiserings metode is uitgevoer deur literatuur met terugvoer van bedryfskundiges te kombineer. Die literatuur wat geraadpleeg is handel oor die ondersoek na die komponente van gewapende beton reservoirs en degenerasiemeganismes wat hierdie komponente beïnvloed. Die studie dui aan dat, aan die hand van die bedryfskundiges se terugvoer, sommige komponente meer as ander tot die algehele toestand van die fasiliteit bydra. Hierdie bydrae is gebaseer op die belangrikheid van die komponent in terme van die voorsiening van dien ek veiligheid. Dus, is die geval van n beton reservoir, is die mure meer van beland as die toegans komponente in terme van voorsiening van diens en veiligheid. Die navorsing gee te kenne dat indien die prioritiserings metode suksesvol geïmplementeer kan word, dit die gebruiker bykomende inligting kan gee wat gebruik kan word om die instandhoudingsaktiviteite te prioritiseer op beide netwerk en komponente vlak. Verder, mag daar ’n omvattende bateregister van gewapende beton reservoirs ontwikkel kan word wat dus sal help met die finansiële beplanning rondom die instandhouding van hierdie strukture.

As infrastructure networks grow more complex, regulatory requirements become greater, populations grow, budgets become more limited, and the expectations of customers increase, municipalities are progressively being required to provide more for less. This is presenting some particular challenges to the long-term sustainability of buried water and wastewater infrastructure in Ontario. In response, municipalities are increasingly seeking to improve their business processes and asset management capabilities as a path to optimize the lifecycle of their infrastructure assets and ensure public safety, community development, and financial sustainability. This thesis presents an organizational performance measurement framework for municipal infrastructure asset management which was validated through interviews and surveys with international discipline experts. The resultant framework provides a high-level outline and suggestions for implementation of key objectives, 11 core critical success factors, and 135 quantitative performance indicators for municipal water and wastewater asset management organizations.

As infrastructure networks grow more complex, regulatory requirements become greater, populations grow, budgets become more limited, and the expectations of customers increase, municipalities are progressively being required to provide more for less. This is presenting some particular challenges to the long-term sustainability of buried water and wastewater infrastructure in Ontario. In response, municipalities are increasingly seeking to improve their business processes and asset management capabilities as a path to optimize the lifecycle of their infrastructure assets and ensure public safety, community development, and financial sustainability. This thesis presents an organizational performance measurement framework for municipal infrastructure asset management which was validated through interviews and surveys with international discipline experts. The resultant framework provides a high-level outline and suggestions for implementation of key objectives, 11 core critical success factors, and 135 quantitative performance indicators for municipal water and wastewater asset management organizations.

The task of preserving and improving infrastructure systems is becoming extremely challenging because these systems are decaying due to aging and over utilization, have limited funding, and are complex in nature (geographically spread, and affect and are affected by technological, environmental, social, security, political, and economic factors). The infrastructure management paradigm has emerged to assist in the challenging task of managing infrastructure systems in a systematic and cost-effective manner. Infrastructure management is a data-driven process. It relies on large databases that contain information on the system’s inventory, condition, maintenance and rehabilitation (M&R) history, utilization, and cost. This data feeds into analytical models that assess infrastructure current conditions, predict future conditions, and develop optimal M&R strategies. Thus, complete and accurate data is essential to a reliable infrastructure management system. This study contributes to advancing the infrastructure management paradigm (with focus on pavement management) in two primary ways: (a) it provides in-depth understanding of the impact of errors in condition data on the outputs of infrastructure management systems, and (b) it provides efficient computational methods for improving infrastructure data quality. First, this research provides a quantitative assessment of the effects of error magnitude and type (both systematic and random) in pavement condition data on the accuracy of PMS outputs (i.e., forecasted needed budget and M&R activities in a multi-year planning period). Second, a new technique for detecting gross outliers and pseudo outliers in pavement condition data was developed and tested. Gross outliers are data values that are likely to be erroneous, whereas pseudo outliers are pavement sections performing exceptionally well or poor due to isolated local conditions. Third, a new technique for estimating construction and M&R history data from pavement condition data was developed and tested. This technique is especially beneficial when M&R data and condition data are stored in disparate heterogeneous databases that are difficult to integrate (i.e., legacy databases). The main merit of the developed techniques is their ability to integrate methods and principles from Bayesian and spatial statistics, GIS, and operations research in an efficient manner. The application of these techniques to a real-world cases study (pavement network in Bryan district) demonstrated the potential benefits of these techniques to infrastructure managers and engineers.

This research addresses the infrastructure maintenance scheduling problems under budget uncertainty. Infrastructure agencies usually face budget uncertainties that will eventually lead to suboptimal planning if maintenance decisions are made without taking the uncertainty into consideration. It is important for decision makers to adopt maintenance scheduling policies that take future budget uncertainty into consideration. The author proposes a multistage, stochastic linear programming model to address this problem. The author also develops solution procedures using the augmented Lagrangian decomposition algorithm and scenario reduction method. A case study exploring the computational characteristics of the proposed methods is conducted and the benefit of using the stochastic programming approach is discussed. In the case study, the road network in Dallas District is used with data taken from the Texas Department of Transportation’s Pavement Management Information System. The case study results reveal that the stochastic programming solutions tend to allocate more resources to preventive maintenance than deterministic solutions that ignore the uncertainty information. The proposed methodology can help decision makers effectively obtain optimal maintenance plan under budget uncertainty. / text

This thesis presents machine and statistical learning approaches for sustainable planning in infrastructure and mobility systems. First, I have developed a convolutional neural network (CNN) to predict tree failure likelihood. Such assessments have traditionally been performed manually. I conduct a visual analysis of the predictions, indicating an approach for incorporating interpretability into model selection. Benchmarking the results against those produced by state-of-the-art CNNs, I show that a relatively simple model produces better results in a computational time that is three times faster. Via this novel framework, I demonstrate the potential of machine learning to automate and consequently reduce the costs of tree failure likelihood assessments in proximity to power lines, thereby promoting sustainable infrastructure. Secondly, I examine the effects of COVID-19 on mobility, segmented by transportation type, as well as social activity such as workplaces and residential, and their interdependencies. Using time series data across five continents, I estimate a Bayesian global vector autoregression model which explains patterns in activity and mobility trends and analyze their relationship with COVID-19 spread. I expect that the model framework and outcomes will guide policymakers to adopt appropriate measures to mitigate and safely recover from future disease outbreaks.

Sustainable pavement management implies maintaining acceptable condition of pavements while also considering the tradeoff between cost, environmental impacts and social impacts of pavement investments. Typical pavement management practices only consider economic considerations, and environmental mitigation techniques are employed after the selection of the maintenance action is complete. This dissertation presents a series of papers that demonstrate the impact of decision making on the environmental impact of the pavements both at the project and network levels of pavement management. An analysis was conducted of two models that relate pavement properties to vehicle rolling resistance and fuel consumption. These models were used, along with other tools to evaluate the impact of including the use phase of a pavement into pavement lifecycle assessments. A detailed project level lifecycle assessment was conducted, and it was found that the vehicles on the pavement during the use phase contribute the most to environmental pollutants by a significant margin over other phases of the lifecycle. Thus, relatively small improvements in the factors which contribute to rolling resistance may significantly influence the environmental impacts of the pavement. Building on this, a network level lifecycle assessment method was proposed to probabilistically quantify energy consumption for a given set of expected maintenance actions. It was shown that, although maintenance actions require a certain amount of energy consumption, this energy can be offset by improved road conditions leading to reduced rolling resistance. However, this tradeoff of reduced energy consumption also includes increased costs for a given network condition. In other words, the lowest energy consumption values did not tend to fall along the line defined by minimizing the cost divided by the pavement condition. In order to demonstrate how this tradeoff should be addressed, a novel decision analysis framework was developed, and implemented on a specific pavement network. Finally, a survey of transportation professionals was evaluated to determine their optimal points within the solution space defined by minimizing costs and energy consumption while maximizing pavement condition. It was found that the solution space could be greatly reduced by implementing their responses using the proposed decision analysis framework. / Ph. D.