Journal of Infrastructure Systems

Quality of design, material used and workmanship, affects the future operating, maintenance and rehabilitation costs of infrastructure; however, the extent to which quality affects these costs has never been explicitly quantified. The research described in this paper represents a major study in this area and significantly advances the understanding of the impact of quality upon building costs. Building design, construction, operating, maintenance and rehabilitation cost data for 215 buildings were collected from all available sources in the Canadian Department of National Defence. A metric was developed to measure quality in the design, construction, and operating and maintenance phases of a building’s service life. An analysis of variance of annual equivalent total costs, for the first $20\text{years}$ of building service life, clearly indicated that quality had a major impact on total costs when the influence of all other potential factors, particularly age, was minimized or removed. It was found that quality, in particular design quality, has the greatest demonstrable impact on building maintenance and rehabilitation costs.

Design and construction industries, along with owners, have an increasing interest in and responsibility for the environmental impacts of buildings. Since the environmental impacts of a building’s life cycle are considerable, quantification of all phases is important, especially the construction phase, which is often glossed over. This research focuses on the construction phase of a building project. Generally, the life-cycle inventory created in performing a life-cycle assessment (LCA) is developed using either a process or input–output approach; however, both techniques have distinct advantages and disadvantages. A hybrid approach combining both methods’ advantages has been proposed and will be demonstrated. Existing hybrid models are reviewed, along with a recommendation of a hybrid model for construction. A preliminary case study of a precast concrete parking garage’s construction using hybrid LCA methodology is presented. Preliminary investigations indicate transportation, equipment activity, and support functions have the largest effects on the environment.

In recent years, many state departments of transportation (DOTs) have developed performance measures to monitor their transportation systems and improve transportation planning. One of the main outstanding questions with regard to using performance measures is how to best characterize the connection between resources and outcomes, particularly at a system (state) level. In this paper, we examine the effectiveness of state DOT investment decisions on two performance areas: Safety and congestion. We collected expenditure and performance data from 1984–2000 and developed state-specific linear regression models for each performance area. The statistical significance and direction of influence of each expenditure category varied between models, so we used 29 transportation-system characteristics to interpret model results. The findings of this study provide a better understanding of the link between resources and outcome and will help state DOTs utilize their new funding opportunities, improve their planning procedures and address government accountability concerns.

This paper presents a scenario-based methodology for the ranking of the elements of a water-supply network according to their value to the network’s owner. The failures of the elements due to random causes and to malevolent acts are considered. The methodology is based on multiattribute utility theory and a graph theory-based network analysis algorithm. This methodology extends approaches proposed in the literature by taking into consideration the capacity of the infrastructure’s elements and their mean time to repair. The water-supply infrastructure of a midsize city serves as a case study. We model the infrastructure system as a network and create scenarios to evaluate the consequences of the failure of each of its elements. For each scenario, we evaluate the supply level to the various users considering the capacity of their connection to the available resources. We then evaluate the disutility of this supply level to the decision makers using multiattribute utility theory. The accident scenarios are ranked according to their expected disutility. The vulnerabilities to malevolent acts are ranked using a subjective combination of the disutilities and the scenario susceptibility to attack. The results are provided to the decision makers for evaluation and risk management. The limitations of the proposed methodology and its applicability to other infrastructures are discussed.

In this paper we discuss how to assess the vulnerability of electric power delivery systems with the help of standard power system performance indices. In two case studies, statistical analyses of disturbance data from Swedish power transmission and distribution are presented and discussed. The following indicators are used in the case studies: unserved energy, power loss, restoration time, and the number of disturbances with power loss. We demonstrate that disturbance size $Q$ for larger values of indices shows a power-law distribution, i.e., $P(Q>q)=1-F\left(q\right)\sim q^{-\beta }$ $(q\to \infty )$ , and that the times of disturbances are distributed as a Poisson process.

The requirements to protect public water systems from external contamination have expanded in the years following September 11, 2001. The areal extent and nonlinear nature of fluid demand and movement in the distribution system makes efficient location of sampling points difficult. This difficulty is compounded by the fact that contamination conceptually can occur at any time and at any point within the distribution system. This paper proposes a methodology to identify strategic locations within the system that can be established as critical detection points for such occurrences. This methodology is different from others in that it uses computer simulations to create a database of water system responses to contamination generated at every node in the system. A process is developed to mine this database systematically after considering concentration thresholds and “time since injection” parameters. The result is a network of monitoring locations that provide efficient coverage of the system under the conditions imposed.

This study investigates impacts of the 2001 World Trade Center attack on critical infrastructure systems in the New York City metropolitan area. Of particular interest are the physical or logical connections—also known as interdependencies—among these systems, and the impacts of the attack on them. This study extends knowledge about the behavior of complex and interdependent infrastructures systems following a significant disruption. The results depict impact to all infrastructure systems as a result of the attack, with disruptions reported throughout the $3\text{month}$ study period. Approximately 20% of these disruptions involved interdependencies, and a majority of infrastructure systems were involved in at least one interdependency. The results therefore suggest that interdependence is a pervasive condition of New York City’s critical infrastructures. Accordingly, approaches to planning for and managing infrastructure-related disruptions, particularly those involving interdependency, are discussed.