Economic Analysis and Information Modeling of Smart Multi-purpose Utility Tunnels

The traditional method of buried utilities (i.e. water, sewer and gas pipes, and electrical and telecommunication cables) has been used for many decades particularly in urban areas. Repeated excavations are needed to access these underground utilities for maintenance, repair, and renewal activities. Urban areas have been experiencing many street closures and traffic disruptions because of excavation for maintaining underground utilities. These construction works have imposed major costs on public and private utility companies as well as on citizens and local businesses (social cost). Multi-purpose Utility Tunnels (MUTs) have been built since the 19th century as a solution and alternative way that not only avoids these excavations but also facilitates inspection and protects utilities. However, MUTs are not widely used in most of the countries because of the high initial investment, safety and security issues, complicated design and construction, and complex coordination of utility companies. Despite the higher design and construction cost of MUTs, operational cost-savings can justify the investment from the project point of view. From the organization's point of view and based on cost-sharing, MUT should be more economical as well and the MUT benefits should be distributed fairly to convince utility companies to participate in the MUT project. Lifecycle Cost (LCC) analysis of the MUT and the buried utilities method is complicated because of various factors that influence the LCC. Also, there is a gap in defining the concept of fairness and applying mathematical methods for a fair cost-sharing. On the other hand, to facilitate the complicated design and construction, and complex coordination of utility companies in MUT projects, Building Information Modeling (BIM) tools are very helpful. However, BIM is mainly developed for buildings and there are efforts to extend it to civil structures (e.g. bridges, tunnels). Although using BIM for MUTs has progressed in recent years, there is still lack of a comprehensive framework covering MUT components and information requirements for all use cases, as well as its integration with Geographic Information System (GIS) and other technologies. This research aims to: (1) improve the decision-making related to MUT selection process by developing a comprehensive and systematic approach for MUT and buried utilities LCC analysis. In addition, this research investigates the influence of factors of utility specifications, location conditions, and construction methods. The output of this model determines the LCC of MUT and buried utilities, and the design and construction cost of MUT at the breakeven point to ensure the project decision-makers that MUT is the economic method; (2) improve the fairness of MUT cost-sharing by developing a fair model that considers fairness based on (a) balance of risk, (b) balance of benefit and cost, and (c) balance of contributed benefit and gained benefit. This model makes MUT the economical method for utility companies and distributes the benefits and costs of MUT fairly among the utility companies; and (3) improve the coordination among the MUT stakeholders by developing a framework integrating BIM and 3D GIS for Smart Multi-purpose Utility Tunnel Information Modeling (SMUTIM). The framework defines MUT information requirements, identifies SMUTIM use cases, and extends Industry Foundation Classes (IFC) to MUT. The contributions of this research are: (1) developing a comprehensive and systematic approach for MUT and buried utilities LCC analysis by considering the factors of utility specifications, location conditions, and construction/maintenance methods. The output of this model estimates the LCC of MUT and buried utilities. The proposed model can justify whether an MUT project is an economic alternative method for buried utilities; (2) developing an MUT cost-sharing method to ensure the decision-makers of utility companies that MUT is the economic method for their company and also the benefits and costs of MUT are distributed fairly among the utility companies. The fairness is defined based on three principals: balance of risk, balanced benefit-cost ratio, and balance in contributed benefit and gained benefit; (3) categorizing and integrating smart MUT physical and functional components and their relationships in a systematic way; (4) completing, integrating, and organizing the available knowledge about SMUTIM use cases within a framework. Then, using the case study to show the capabilities and gaps of current BIM applications, GIS, databases, and facility management tools for MUT lifecycle management; and (5) partially extending IFC to MUT by proposing Model View Definition (MVD), new entities and relationships, and taking advantage of reusable IFC entities, properties, and relationships. It is expected that the proposed model promotes using MUT by (1) facilitating economic analysis and cost-sharing for MUT projects from project and organization points of view; and (2) facilitating the design, construction, and operation of MUTs, and the coordination of utility companies

Integrated topological representation of multi-scale utility resource networks

PhD ThesisThe growth of urban areas and their resource consumption presents a significant global challenge. Existing utility resource supply systems are unresponsive, unreliable and costly. There is a need to improve the configuration and management of the infrastructure networks that carry these resources from source to consumer and this is best performed through analysis of multi-scale, integrated digital representations. However, the real-world networks are represented across different datasets that are underpinned by different data standards, practices and assumptions, and are thus challenging to integrate. Existing integration methods focus predominantly on achieving maximum information retention through complex schema mappings and the development of new data standards, and there is strong emphasis on reconciling differences in geometries. However, network topology is of greatest importance for the analysis of utility networks and simulation of utility resource flows because it is a representation of functional connectivity, and the derivation of this topology does not require the preservation of full information detail. The most pressing challenge is asserting the connectivity between the datasets that each represent subnetworks of the entire end-to-end network system. This project presents an approach to integration that makes use of abstracted digital representations of electricity and water networks to infer inter-dataset network connectivity, exploring what can be achieved by exploiting commonalities between existing datasets and data standards to overcome their otherwise inhibiting disparities. The developed methods rely on the use of graph representations, heuristics and spatial inference, and the results are assessed using surveying techniques and statistical analysis of uncertainties. An algorithm developed for water networks was able to correctly infer a building connection that was absent from source datasets. The thesis concludes that several of the key use cases for integrated topological representation of utility networks are partially satisfied through the methods presented, but that some differences in data standardisation and best practice in the GIS and BIM domains prevent full automation. The common and unique identification of real-world objects, agreement on a shared concept vocabulary for the built environment, more accurate positioning of distribution assets, consistent use of (and improved best practice for) georeferencing of BIM models and a standardised numerical expression of data uncertainties are identified as points of development.Engineering and Physical Sciences Research Council Ordnance Surve