Journal of Infrastructure Systems

The reliability assessment of infrastructure systems providing power, natural gas, and potable water is an integral part of societal preparedness to unforeseen hazards. The topological properties of interface networks connecting electric substations to water pumping stations and natural gas compressors have received little attention, despite the key role these connections play in operation and failure propagation. This work introduces a performance assessment methodology for coupled infrastructures that links physical fragility modeling with the topology of realistic and ideal connecting interfaces. Distinct interfaces based on features such as betweenness, clustering, vertex degree, and Euclidean distance are assessed regarding their role in connecting utility systems and propagating failures from random and hurricane events in Harris County, Texas. The interface minimizing the Euclidean distance between electric substations and other utility nodes exhibits a slow performance decline as random failures increase, and retains the greatest functionality under hurricane events compared to alternative interfaces, although it suffers from limited efficiency and controllability during normal operation. A convenient hybrid interface using both betweenness and distance features shows adequate performance during normal operation while exhibiting tolerance to random failures and sufficient performance at increasing hurricane event levels. These findings provide utility owners and operators with new simple yet adequate strategies focused on the interface across complex systems to enhance routine operation and reduce the probability of widespread interdependent failures following disruptive events.

A supply driven dynamic input-output inoperability model (SDIIM), which extends the classical dynamic inoperability input-output model (DIIM), is described in this paper. The classical DIIM was developed to help understand the infrastructure interdependencies of deliberate external attacks or unfortunate natural disasters, such as terrorist attacks or earthquakes and flooding. However, classical DIIM is a demand-driven model. More supply driven sectors exist than demand-driven sectors in interdependent infrastructure systems, but value-added perturbation is the predominant feature in supply driven sectors for an interrupt event. Moreover, compared to classical DIIM, the value added by the proposed SDIIM can be controlled more easily than the final demand of a disruptive event because the final demand perturbation may be affected by the psychological effect on consumers. A supply driven input-output inoperability model (IIM) has also been proposed to complement the classical IIM. However, the supply driven IIM is a static model, and only equilibrium values can be determined. The SDIIM presented in this paper has been formulated to model the behavior of the value-added input perturbation up to equilibrium and to characterize the required sector adjustments for achieving new levels of output values. In addition, the interdependency resilience coefficient and the interdependency index are discussed by using the SDIIM. In this paper, the large-scale snow disaster that occurred in south China in 2008 is used as a case study, in which the SDIIM is used to analyze the inoperability and dynamic output values recovery of sectors caused by a value-added disturbance. The SDIIM is shown to effectively compute interdependent inoperability and economic losses, which can provide valuable insights into risk assessment and the management of interdependent infrastructure systems and sectors of the economy.

This paper presents a framework for characterizing, analyzing, and computing the performance of urban infrastructure systems. The framework is based on a systems approach and consists of performance indicators classified into three hierarchical levels: indicators, dimensions, and categories. A fuzzy synthetic evaluation technique has been developed to synthesize performance indicators into an index that ranges between 0 and 100. The performance of an individual infrastructure system, in the form of an index, is generated by aggregating the performance indicators in the first three hierarchical levels. The overall performance of the urban infrastructure systems is then obtained by combining the indexes of individual infrastructure systems. The relative importance of the performance indicators during the synthesis process is determined using the analytic hierarchy process technique. The framework demonstrates and measures the performance of the civil infrastructure systems in Kathmandu, Nepal. This framework can be applied to performance analysis of any infrastructure system in an urban area. It enables decision makers to identify the weak and strong components of urban infrastructure systems and to formulate appropriate strategies for infrastructure planning on the basis of performance and investment costs.

Rural infrastructure is of vital importance for agricultural growth, economic development, and poverty alleviation, particularly in developing countries such as China. In line with the implementation of a Coordinated Urban-Rural Development Strategy, infrastructure investment in China has consciously been tilted to rural areas. An urgent need exists to assess whether the investment has induced the benefits as expected. Existing research on rural infrastructure investment assessment focuses primarily on economic return while neglecting its social and ecological benefits. This paper identifies a set of critical assessment indicators (CAIs) that can be used to evaluate the multifaceted benefits of rural infrastructure investment in China. Research data were collected through a questionnaire survey given to three groups of experts, including government officers, professionals, and business practitioners who are working in China’s housing and urban-rural development sector. Monte Carlo simulation (MCS) is used to generate additional data to supplement the data set from the questionnaire survey. The fuzzy set theory, which appreciates the fuzziness of data from the questionnaire survey, is used in the selection of CAIs. The CAIs can help the local governments in China to make better decisions in investing in rural infrastructure. These critical indicators can also be generalized to provide valuable references for the investigations of rural infrastructure investment in other developing countries.

Responding to hurricanes is an exceedingly complex task, the effectiveness of which can significantly influence the final effects of a hurricane. Despite a lot of progress, recent events and unchecked population growth in hurricane-prone regions make it clear that many challenges remain. Hurricane Katrina has shown that having appropriate shelter options and an appropriate shelter evacuation plan are very important for hurricane evacuations. This paper proposes a scenario-based shelter location model for optimizing a set of shelter locations among potential alternatives that are robust across a range of hurricane events. This model considers the influence of changing the selection of shelter locations on driver route-choice behavior and the resulting traffic congestion. The state of North Carolina is used as a case study to show the applicability of the model.

As part of a streetlight-retrofitting project in Pittsburgh, this study performed a cradle-to-grave life-cycle assessment of four lighting technologies: the widespread high-pressure sodium and metal halide lights, and the newer and more efficient induction and light-emitting-diode technologies. The study used a hybrid life-cycle-assessment approach to build life-cycle models for the various technologies, including manufacturing and installation data for process models and energy supply and input-output data to complete life-cycle models. Three different electricity scenarios were used to examine the sensitivity of the impacts to changes in energy supply: the United States average mix, the regional mix for the ReliabilityFirst Corporation region, and a scenario with 100% wind power. The results show that for all technologies, the impacts of electricity in the use phase dominates the results. Because of their lower wattage, light-emitting diode (LED) and induction technology perform favorably and similarly. With anticipated improvements in technology, however, LEDs are expected to be more efficient than induction in the near future and have lower environmental impacts by the time that Pittsburgh and other cities buy and install lights as part of these streetlight projects, which have the potential to show large cost and emissions savings.

This study uses aggregate state-level data from 1999 to 2006 in the United States to examine the relationships among pavement performance (pavement roughness) and preservation expenditure, dominant surface geology, and climate. To account for possible random variations in parameters across geographic locations and time periods, a random-parameters logit (mixed logit) model was used. The analysis was carried out separately for roads in different functional classifications and considered the effect that a variety of variables had on the proportion of pavements in each state that are in one of the four International Roughness Index categories (excellent, good, fair, poor) defined by the Federal Highway Administration. The results of the analysis showed the extent to which increased pavement preservation spending yields increased pavement performance and the nature of this relationship for different base pavement-performance conditions and different regions of climate and surface geology.

A methodology is developed to evaluate the annual failure probabilities of a pressurized pipeline at an active metal-loss corrosion defect. The methodology takes into account three different failure modes at the defect (i.e., small leak, large leak, and rupture) and the time dependency of the pipe’s internal pressure by modeling the pressure as a simple stochastic process consisting of a sequence of independent and identically distributed random variables, each occupying a period of one year. The impact of periodic maintenance actions on the failure probabilities is incorporated in the methodology. Two numerical examples are used to illustrate the methodology. The sensitivity of the calculated failure probabilities with respect to the time dependency of the internal pressure is also investigated.