| dc.description.abstract | The well-being and economic prosperity of urban areas are tied to the effectiveness and reliability of their infrastructure systems. These systems are interdependent, influencing each other across various dimensions. Moreover, the infrastructures are aging, and cities are confronted with growing challenges due to increasing populations and environmental concerns. Infrastructure
managers are facing increasing pressure to address these evolving challenges. Infrastructure asset management (IAM) approaches are the norm for managing infrastructure by their managers. However, infrastructure managers often overlook the potential benefits of coordinating their asset management works among various interdependent infrastructures. This
oversight is typically due to a lack of tools, interest, and other factors. The benefits of coordination can range from cost and carbon savings to reduced
community disruptions and increased performance. This thesis explores the potential of Integrated Multi-Infrastructure Asset Management (IMAM) to efficiently manage and coordinate various infrastructures that are in geographic proximity, like water, sewer, and road networks. The thesis first identifies the challenges hindering the application of IMAM and then addresses
selected challenges. The identified challenges are: dependencies and interdependencies, data quality, availability and interoperability, uncertainties
in modelling and decision-making, comparability, problems of scale, problems of fit, and problems of interplay.
To address the problems of spatial scale and fit, and quantify the spatial interdependencies, the thesis proposes two metrics—shared surface area and shared trench volume— and combines them to quantify the degree of co-location of various infrastructures. the degree of co-location also serves as a proxy for the potential cost savings through coordinated interventions. Case studies from Norwegian municipalities indicate that a cost-saving potential of up to 24% in urban and 11% in rural settings is possible through IMAM.
For the challenge of data unavailability for water and sewer infrastructure networks, the thesis evaluates the transferability of deterioration models across utilities. Utilizing datasets from multiple Norwegian utilities, global models (based on aggregated datasets) and local models (based on individual utility datasets) are developed. These models were then evaluated for their ability to predict water pipe failures/sewer pipe conditions in utilities that were not part of the training set. This study highlights how small utilities can leverage existing datasets and models from other utilities, thereby circumventing the challenges posed by data limitations.
To confront the problem of interplay, the thesis introduces a spatio-temporal model that integrates spatial and temporal analyses to identify critical geographic "hotspots" suitable for simultaneous interventions across multiple infrastructure systems. Employing a case study in a medium-sized Norwegian city, the research evaluates integrated interventions across water,
sewer, and road networks. The resulting "hotspot maps" furnish tactical insights into feasible locations for coordinated multi-infrastructure interventions. These maps enable utilities to engage in joint planning.
In summation, this research bridges gaps in literature and practice, providing actionable insights and tools for decision-makers in urban infrastructure management. It also provides an outlook for future research and suggestions for practitioners. | en_US |
