Journal of Infrastructure Systems

Infrastructure capital can be considered a necessary condition to extend the regional production potential but not automatically a sufficient requirement for enhanced regional competitiveness and income. The materialization of a region’s higher production potential rather relies on the region’s ability to utilize the existing and additional infrastructure capital in an efficient way. Against this background, the paper intends to identify Austrian and German regions’ environment with public transport infrastructure and their efficiency in using it. Therefore, the role of transport infrastructure is contrasted with the importance of other region-specific production factors namely educational attainments of the workforce and the availability of modern telecommunication networks. In order to increase the comparability of the regions, the latter are clustered according the land use pattern and industrial structure in a first step. In a second step a quantile regression analysis is performed for each cluster and factor. This, in turn, allows for a sequential bottleneck analysis.

There has been considerable work in recent years improving the methods for the appraisal of transport investments under conditions of imperfect competition which gives rise to possible wider economic benefits. This paper examines the further situation where the market for transport operates under a range of regulatory regimes. This develops the issues which may arise in the appraisal of investments by various forms of public-private partnerships where there may be different objectives for the private and public sectors. The paper discusses the issues involved in different forms of regulatory regime on the basis of experience with regulated transport markets in the U.K. and the European Union’s trans-European networks to assess the effects on investment decisions which fall into different regulatory regimes.

In the early estimation there is compromise between the amounts of information available and accuracy of estimation. We propose three levels of analysis such as regional, country and project level for road cost models in order to provide efficient data usage. The data for our research was obtained from the World Bank’s Road Costs Knowledge System database, which contains unit costs for road projects from over 80 developing countries. This paper investigates the impact of road upgrading and improvement works on overland trade in 18 out of 32 member countries of Asian Highway Network. The results indicated approximately $6.5 billion is required to upgrade roads and improve existing surface condition of the selected subnetwork with total length of 15,842 km. The gravity model approach was adopted to quantitatively evaluate overland trade expansion taking into account road quality improvements with two scenarios such as road quality increases up to 50% in the first scenario in the second one up to 75%. The results suggests that in the first scenario total intraregional trade will increase about 20% to $48.7 billion annually, while second scenario predicts that trade will increase by about 35% to $89.5 billion annually.

The purpose of this study is to propose a new road planning and financing scheme based on short-term social marginal cost pricing that facilitates the establishment of optimal road standards in the long-term. We conducted a simulation analysis based on the proposed planning scheme and observed that the simulation calculated the optimal road capacity in the future, and thus proved that the new planning scheme is feasible.

Throughout the past decade transport projects have played a pivotal role in support of economic development and poverty alleviation. This evaluation, using objectives-based methodology, assesses the World Bank’s activities in the transport sector during the past 10 years together with its preparedness to meet emerging challenges. It concludes that although past performance has been well managed and effective, especially for intercity highway construction and rehabilitation, transport must also give more focus on vital issues such as traffic congestion, air pollution, safety, and affordability which will have to be given greater priority. This will necessitate more innovative multisectoral approaches to resolve the complex global concerns confronting us in the future.

Exclusive bus lanes are intended to enhance the level of service of bus transport in terms of speed, reliability, safety, etc. This paper is concerned with application of a newly developed microsimulation technique to study the effect of provision of reserved bus lanes on the flow of nonlane-based heterogeneous traffic on urban roads in India. The aim of the study reported here is to modify and validate a newly developed simulation model of heterogeneous traffic flow using field observed data and to apply the validated model to study the effect of exclusive bus lanes on traffic flow. The effect is measured in terms of the reduction in the speeds of other categories of vehicles due to the possible reduction in the available road space for these vehicles. The results of the study indicate that it is possible to introduce exclusive bus lanes on carefully selected urban roads to enhance the level of service of bus, simultaneously ensuring a satisfactory level of service to the other vehicles on the road.

Infrastructure management is the process through which inspection, maintenance, and rehabilitation decisions are made to minimize total life-cycle cost. Condition measurement, spatial sampling, and forecasting introduce uncertainty into the process. The first and third uncertainties are captured in the infrastructure management literature. However, the second has not been recognized and quantified. This study focuses on motivating the incorporation of the spatial sampling uncertainty in decision-making, quantifying this uncertainty, and investigating its effect on the expected minimum life-cycle cost. Evaluation measures are defined to assess the contributions of the developed framework, namely incorporating uncertainty due to spatial sampling in the decision-making process and selecting the sample size optimally. A numerical analysis indicates that in general both contributions are important under a wide range of realistic scenarios and the implications of the combined effects on minimizing life-cycle cost and long-term budget planning are marked.

A decision-support-system has been developed for the rehabilitation planning of sewers based on inspection results. The heart of the system is the structural reliability module that receives input on damage from inspections and performs structural analyses to assess the current structural condition of the sewer. Similar analyses are performed at future times but with different parameters based on the evolution of (1) loads; (2) corrosion; and (3) soil-structure interaction. Some of the parameters are treated as random variables and the outcome is the probability of structural failure as a function of time which is needed in the rehabilitation module that selects the most appropriate rehabilitation method. Then the system prioritizes rehabilitation projects based on the structural condition of the sewer and the impact that sewer failure might have. Results show that high leakage promotes structural failure and that the influence of nonseismic effects in the presence of clay soil is larger than in sand. On the other hand, the influence of seismic effects is more pronounced in sand than in clay.

The sensor placement problem in contamination warning system design for municipal water distribution networks involves maximizing the protection level afforded by limited numbers of sensors, typically quantified as the expected impact of a contamination event; the issue of how to mitigate against high-consequence events is either handled implicitly or ignored entirely. Consequently, expected-case sensor placements run the risk of failing to protect against high-consequence 9/11-style attacks. In contrast, robust sensor placements address this concern by focusing strictly on high-consequence events and placing sensors to minimize the impact of these events. We introduce several robust variations of the sensor placement problem, distinguished by how they quantify the potential damage due to high-consequence events. We explore the nature of robust versus expected-case sensor placements on three real-world large-scale distribution networks. We find that robust sensor placements can yield large reductions in the number and magnitude of high-consequence events, with only modest increases in expected impact. The ability to trade-off between robust and expected-case impacts is a key unexplored dimension in contamination warning system design.

The global seaport sector made huge efforts in relation to port reform and technological development since the 1990s. This study attempts to systematically estimate the impacts of these efforts on world ports’ efficiency changes between 1991 and 2004. The Malmquist Total Factor Productivity Index can effectively measure efficiency changes and identify sources of efficiency gains and losses. Based on the decomposed Malmquist Productivity Index efficiency indices, this study creates a typology of ports regarding whether, and how, they have improved their efficiency over the last decade. The results suggest that: (1) while scale efficiency, mainly representing impacts of external economic environments on port performance, is still one of the important factors to shape port efficiency, it is neither determining nor predominant any longer; (2) the globalized competition in the container shipping and terminal markets enables potential strategies to be used that combine institutional restructuring and capital investment, as a partial solution to overcome the external limitations of ports, such as lack of hinterlands; and (3) an exclusive focus on aggressive investment in technological progress is a limited strategy, as other competitor ports can relatively easily replicate the process, and, consequently, it may negate any increase in long-term competitiveness.

This paper presents a rigorous approach to statistical modeling of postearthquake fire ignitions and to data collection for such modeling and applies it to late 20th century California. Generalized linear and generalized linear mixed models are used for this application for the first time. The approach recognizes that ignition counts are discrete, examines many possible covariates, and uses a small unit of study to ensure homogeneity in variable values for each area unit. Two data sets were developed to explore the effect of missing ignition data, each with a different assumption about the missing data. For one data set, the recommended model includes instrumental intensity; percentage of land area that is commercial, industrial, or transportation; total building area; percentage of building area that is unreinforced masonry; and people per square kilometer. The other includes the same, except area of high-intensity residential development replaces total building area, and median year built over all housing units is also included. The models should be useful in estimating the number and locations of postearthquake ignitions in future earthquakes.

The retirement of aging concrete infrastructure is resulting in significant material flows of concrete debris in the economy. A proposed outlet for this debris is new concrete: the debris can be crushed into small particles and used in place of virgin aggregate. This form of recycling lessens use of aggregate resources, but its consequences are less clear in terms of energy use and greenhouse gas emissions. To examine these impacts, we develop life-cycle inventory models of the manufacturing of recycled concrete aggregate from debris. Results from these models are then used in life-cycle models of nonstructural concretes containing varying proportions of recycled concrete aggregate. For scenarios in which virgin and recycled aggregates are locally available, only 20% recycled aggregate substitution is beneficial. This corresponds to a modest reduction in energy use and greenhouse gas emissions: up to $15\text{MJ}/{\text{m}}^3$ and 1.20 kg ${\text{CO}}_2\text{-eq}\text{.}/{\text{m}}^3$ of concrete, respectively. Only when virgin aggregate must be transported large distances are higher levels of substitution beneficial, in terms of the metrics studied.

Building infrastructure “performance” is a term which describes the in-service functioning of a building for a specified use. The concept refers to how effectively, safely, and efficiently a building supports its mission at any time during its life cycle. A building’s performance state, which changes during time in service, is reflected by two different indicators: the physical condition state and the functionality state. The physical condition state relates to a facility’s general “physical fitness,” independent of its mission, as it deteriorates due to routine aging, excessive or abusive use, or poor maintenance. The functionality state relates to the facility’s suitability to function as intended and required for the mission. The functionality state is distinct and independent from the physical condition state. Condition-based metrics are currently in use but a companion index of functionality was not developed at the same time. However, in order to fully describe a building’s fitness for changing missions over its entire life cycle, a quantitative and objective functionality index (FI) is needed. This paper describes the methodology of this FI measurement.

Warranties have been used by many highway agencies in response to increased demand for including quality concepts in all phases of the highway life cycle and to guard against premature infrastructure failures. Currently, warranty bid prices are often estimated subjectively due to the lack of a systematic methodology for quantifying warranty servicing costs for highway infrastructures. A risk-based model is presented here to fill this gap. The model is founded on Kaplan and Garrick’s theory of quantitative risk assessment and considers the warranted item’s probability of failure (as defined in the warranty clause) and the projected cost of repairing the failure. Probability of failure is determined using survival analysis of actual historical performance data. The model was demonstrated and tested using two hypothetical pavement construction projects in northern Illinois. The computed warranty cost is within the range of actual warranty bid prices for comparable projects, indicating the applicability of the proposed approach. Contractors and surety companies can use this model to make better informed decisions regarding the bidding and pricing of highway construction warranties.

In this paper, we address the problem of making inferences about a population of infrastructure facilities from a subset that is a biased sample. We consider the case in which the sample is biased toward facilities in worse condition or requiring more expensive repair. Two methods are developed that incorporate a model of the process through which the sample is selected. One of the methods is based on well-known truncated distributions, whereas the other assumes that the bias operates continuously. The methods are applied to a class of facilities under the Federal Aviation Administration’s jurisdiction known as “unstaffed facilities.” These consist of structures housing radars, navigation aids, radio beacons, and other ground-based equipment, and no previous system-wide evaluation has been attempted for these facilities. We present and discuss the estimates obtained from both the methods, and examine their goodness-of-fit with the sample. Given the premise that bias exists, the continuous bias model proved more suitable. However, the continuous bias model did not surpass the truncation models in terms of goodness-of-fit.

The development of preparedness strategies for natural and malevolent man-made hazards and approaches with which to compare such investments is fraught with uncertainty. The dynamic inoperability input-output model (DIIM) quantifies the inoperability that propagates through interdependent sectors following a disruptive event and then diminishes with time. This approach has been shown to quantify the efficacy of preparedness strategies for interconnected sectors of the economy. Work presented in this paper strengthens the DIIM with a multiobjective approach—the uncertainty DIIM—that evaluates the inherent uncertainty in the parameters of interdependency and its impact on projected economic loss calculated using the DIIM. Preparedness strategies can then be compared based on projected economic loss and on their sensitivity to changes in the interdependent nature of infrastructure sectors. Additionally, key sector analyses are discussed, where sectors are ranked according to their sensitivity to changes in interdependent relationships. Such enumeration of key sectors allows decision makers to focus on certain sensitive infrastructure sectors for the development of preparedness strategies. The models developed in this paper are illustrated with numerical examples.

One of the main topics in the Georgia Tech/NEES Grand Challenge project “Seismic Risk Mitigation for Port Systems” is the evaluation of seismic risk management approaches for ports. One subtopic of this main topic is the re-evaluation of pertinent financial risk and decision procedures for assessing seismic risk-reduction measures. In light of many criticisms of benefit-cost and least mean total cost methods, previous port seismic risk and decision procedures have benefited from the application of the mean-variance criterion. However, serious objections have been posed to the use of the mean-variance criterion so that exploration of stochastic dominance methods is encouraged. This paper outlines these methods in terms of simplifying nonparametric and upper-order statistics. Focusing on the tails of total cost distributions, this paper shows the value of these methods, but also the value of using almost stochastic dominance when strict stochastic methods fail.

Colonias are unincorporated settlements along the U.S.-Mexican border. The lack of access to infrastructure systems combined with poor housing conditions has resulted in excessively high cost of electricity and heating and cooking gas for colonia residents. The efficacy of a passive solar (PS) housing system in reducing home energy consumption and expenses in colonias has been evaluated using empirical data. The system is implemented in the Tierra Madre colonia in southern New Mexico and consists of PS housing design (orientation and windows), PS water heater, straw bale exterior walls, foundation insulation, and careful construction inspection for energy efficiency. Statistical and economic analyses of two years worth of monthly electricity and liquid propane gas bills (January 2005 to February 2007) from Tierra Madre and a directly adjacent conventional colonia (Sunland Park) showed that this system can be effective in reducing home energy consumption and cost. On average, a Tierra Madre house saves 5.868 million Btus every year compared to a Sunland Park house (representing 25% reduction in home energy consumption and a saving of $194.28 per house per year). The payback period for the Tierra Madre PS system (which is estimated to cost an extra $1,730 per house) is 10.5 years.