Journal of Infrastructure Systems

This paper utilizes a unique data set comprising almost hundred years of Australian railway history and applies the translog and symmetric generalized McFadden functional forms to the data in order to estimate cost functions for Australia’s seven state-owned railway systems. It discusses the advantages and disadvantages of each functional form in light of the data, finding the translog to be superior, and the shortcomings of the data. It also explores economies of scale and density and suggests a simple method to calculate long-run marginal cost, which may be of use in applications such as economic regulation.

The exploration of life-cycle energy use and environmental effects from U.S. water infrastructure has been limited in spite of the strong connection between energy and water use. This research presents a methodology for quantifying the life-cycle energy consumption and associated air emissions from water supply, treatment, and distribution. A decision-support tool, the Water-Energy Sustainability Tool (WEST), has been developed to aid such analysis. WEST calculates the environmental effects of material production, including the supply chain, material delivery and transportation, construction and maintenance equipment use, energy production, and sludge disposal. Deterministic and probabilistic results for a California case study utility are provided to show the tool’s capabilities. Results indicate that producing a million liters of water consumes 5.4 GJ and produces 390 kg of ${\mathrm{CO}}_2$-equivalent greenhouse gases. Energy production is the most significant activity (50%), but material production, especially for treatment chemicals, is also important (37%). This case study is contrasted with two previously published case study utilities, and the reasons for the range of results are analyzed. The results demonstrate that estimating water supply’s energy needs and emissions without a life-cycle lens can underestimate the total effects significantly.

Planning and preparedness is essential for any resilient infrastructure system. Modeling and simulation give engineers and planners a better understanding of the system and help them make better decisions. The objective of this study is to demonstrate an improved model for the disaster restoration process by using a discrete event simulation approach. The study also aims to help improve the postearthquake restoration process by simulating restoration curves. In this paper, colored Petri nets are used to model the system and to simulate its behavior. The resource allocation after a rare event such as an earthquake differs from the resource allocation of other projects and processes in that the time to do the repair and recovery is not known before the event, and the priorities might change for different operational plans and strategies. The trunk network of the Tokyo water distribution system was used as an example to present the scenario and to model the restoration process. The timed simulation allowed visualizing the restoration progress, which is usually depicted as a restoration curve. The results for the restoration time for multiple simulations are presented.

The problem of allocating multiple emergency service resources to protect critical transportation infrastructures is studied in this paper. Different modeling approaches, including deterministic, stochastic programming, and robust optimization, are used to model various risk preferences in decision making under uncertain service availability and accessibility. Singapore is used as a case study for numerical experiments. The performances of different models are compared in terms of allocation strategies and the reliability and robustness of the system.

Managing sewer blockages represents a significant operational challenge for water utilities. In Australia, company-level blockage rates are used to compare the effectiveness of the management strategies of different utilities. Anecdotal evidence suggests that this basis may not be a fair one for comparison because blockages are influenced by a range of factors beyond management control and vary from company to company. This issue was investigated as part of a broader research effort on sewer-blockage management undertaken in conjunction with the Water Services Association of Australia (WSAA) and its members. A Web-based survey was used to collate expert opinion on factors that influence blockage rate. The identified factors were then investigated in an exploratory analysis of blockage-related data provided by two participating utilities, supported by literature reviews. The results indicate that blockage rate is influenced by a range of factors, including asset attributes, climatic conditions, water consumption, and soil type. Because these factors vary from utility to utility, this research supports the finding that company-level blockage rate in itself is not an appropriate metric for comparing management effectiveness.