Journal of Infrastructure Systems

In recent decades, pavement management optimization has been designed with the objective of minimizing user and agency costs. However, recent analyses indicate that pavement management decisions also have significant impacts on life-cycle greenhouse gas (GHG) emissions. This study expands beyond minimization of life-cycle costs to also include GHG emissions. Previous work on the single-facility, continuous-state, continuous-time optimal pavement resurfacing problem is extended to solve the multicriteria optimization problem with the two objectives of minimizing costs and GHG emissions. Results indicate that there is a trade-off between costs and emissions when developing a pavement resurfacing policy, providing a range of GHG emissions reduction cost-effectiveness options. Case studies for an arterial and a major highway are presented to highlight the contrast between policy decisions for various pavement and vehicle technologies.

More than 20% of the bridges in the United States were built more than 50 years ago, at a time in which intense precipitation events were much less common. However, very little work has been done on the use of scour risk-assessment models to assess how climate change increases bridge failure probabilities. This paper develops a risk-assessment framework based on HYRISK, a model developed to assess the probability of a bridge failure due to scour, and illustrates one way in which current engineering risk-assessment models can be used to quantify the additional risks and expected economic losses associated with a changing climate. Application of this framework to all bridges in the United States that carry vehicular traffic over water finds that economic losses due to climate change factors will increase by at least 15% over current losses and that the expected number of annual bridge failures in the United States will increase by at least 10% over current failures. Climate-based risk measures, such as those developed as part of this study, could be included in asset management systems to help state DOTs prioritize maintenance, operation, and replacement schedules.

This paper describes current practice in road surface and subsurface drainage in Sweden and analyzes the necessity for adaptation of the planning, construction, operation, maintenance and monitoring of road drainage measures to climate change. Based on a survey of professionals working with various aspects of road drainage, the study sought to identify: (1) problems experienced concerning road drainage, focusing on the current Swedish climate; (2) future problems regarding climate change impacts such as flooding and high flows; and (3) suggestions for adaptation measures concerning road drainage systems, taking future climate change into account. Suggested improvements concerning management and planning included clarification of responsibility for drainage issues, better overview of the location and condition of drainage facilities, inclusion of drainage system maintenance in procurement of operation contracts, maintenance plans for drainage facilities, and monitoring and inspection of drainage measures. Suggestions concerning drainage system construction, operation and maintenance included increasing the capacity of drainage facilities, stabilizing ditch slopes and various measures to prevent clogging of culverts.

This paper applies graph theory metrics to network flow models, with the aim of assessing the possibility of using these metrics to identify vulnerable areas within infrastructure systems. To achieve this, a reduced complexity flow model that can be used to simulate flows in infrastructure networks is developed. The reason for developing this model is not to make the analysis easier, but to reduce the physical problem to its most basic level and therefore produce the most general flow model (i.e., applicable to the widest range of infrastructure networks). An initial assessment of the applicability of graph theory metrics to infrastructure networks is made by comparing the distribution of flows, calculated using this model, to the shortest average path length in three of the most recognized classes of network—scale-free networks, small-world networks, and random graph models—and it is demonstrated that for all three classes of network there is a strong correlation. This suggests that at least parts of graph theory may be used to inform one about the behavior of physical networks. The authors further demonstrate the utility of graph theory metrics by using them to improve their predictive skill in identifying vulnerable areas in a specific type of infrastructure system. This is done using a hydraulic model to calculate the flows in a sample water distribution network and then to show that using a combination of graph theory metrics and flow gives superior predictive skill over just one of these measures in isolation.

Maintaining an adequate safety level in concrete bridges under gradual degradation due to traffic and environmental actions is not only an expensive task, but also filled with some level of uncertainty. Degradation in itself is not easily quantifiable because numerous aspects reduce the load-bearing capacity of a concrete bridge. Furthermore, the effects of preventive maintenance and rehabilitation actions are difficult to predict. Chloride ion ingress is an important aspect of durability design and maintenance, especially in regions where winter salt is commonly applied for traffic safety. This paper introduces a feasible approach to analyze the effects of chloride-induced deterioration on the overall safety level, which is validated by the application to a real highway bridge, which was demolished after 38 years of service. Concrete samples were extracted from this bridge and chemical analyses were performed to determine the chloride concentration profile in the concrete. Once the present chloride levels were determined, an inverse analysis of chloride ion ingress based on the cellular automata technique provided information regarding the temporal and spatial development of the chloride concentration. These data serve as basis for a probabilistic prognosis of the corrosion processes during the planned service life of the structure, which accounts for uncertainties in the experimental investigations. The prediction of nonvisible degradation, e.g., reduced reinforcement area, allows the localization of critically corroded structural elements, and thus represents the main input for a long-term performance assessment. In particular, comprehensive probabilistic analyses reveal the time-dependent reliability levels with respect to code-based serviceability and ultimate limit states. The outcomes of the proposed methodology are a quantification of the current safety levels as well as a prediction of their future development with and without (preventive or corrective) intervention. Both are quintessential for cost efficiency and save maintenance management. Although the concept of sampling and chloride ingress prognosis will be covered, the focus of this contribution lies with the incorporation of time-varying chloride concentration information into the framework of nonlinear analysis and reliability assessment.

The central challenge in developing deterioration models for infrastructure facilities based on field data, is the right selection of base models along with the specific nature of the available condition data. A parametric model is extensively used in infrastructure deterioration modeling. However, the pre-assumed hazard shape of parametric models is questionable because of the lack of explanations of the underlying assumption. Cox proportional hazard models have the advantage that they make no advance assumption about the shape of the hazard function and support multivariate analysis; and are thus proposed to solve the problems stemming from the predefined distributions of the parametric models. However, the basic uncalibrated functions of Cox models can appear complex and inapplicable for maintenance management applications. Therefore, it is considered useful to incorporate both semi-parametric and parametric models in an integrated strategy for modeling survival data. The development of an integrated methodology to predict the distribution of durations between changes in condition states by incorporating both Cox regression analysis and parametric models for concrete bridge elements, is presented in this paper.

There is a growing demand to preserve transportation infrastructure utilizing limited funds, and the modeling of flexible pavement deterioration has become an integral component of any pavement preservation model. Markov chains have been used to model the performance of pavements in various pavement management systems (PMSs). The Markov property may be considered restrictive when modeling the deterioration of transportation assets, primarily because of the “memoryless” property and assumption of exponential distribution for sojourn times in the condition states. This paper outlines a semi-Markov model for modeling pavement deterioration in which the sojourn time in each condition state is assumed to follow a Weibull distribution and, thus, is more flexible than the traditional Markov chain model. The semi-Markov model does not possess the memoryless property if the sojourn time distribution is not exponential. Monte Carlo simulations are generated for the deterioration of flexible pavements over time based on both the traditional Markov chain model and the proposed semi-Markov model. The results of the work show that in some cases the semi-Markov model appears to be superior to the Markov chain model in modeling the actual deterioration patterns of the flexible pavements.

A fast and computationally efficient valuation tool assists governments involved in Public–Private Partnership (P3) projects to examine many contractual configurations and design a guarantee that minimizes cost and reasonably mitigates the risk. This paper presents a continuous stochastic process derived from the risk factor forecast, thereby providing a more realistic and flexible model. A new valuation approach is developed by using a finite-difference method based on this continuous stochastic process. In a numerical example with one risk factor, it is shown that this new valuation tool is 100 times faster than the existing simulation-based approach. Its superior speed presents the opportunity to examine different contractual configurations, and as a result, design a more cost effective guarantee contract. Exercise strategies are derived for a multiple-exercise (Australian) guarantees structure. This new approach can be used by a government to reserve budget for the guarantees. Finally, the continuous underlying random process and exercise strategy enable this method to value more complex guarantee structures.

A new approach is presented to evaluate corrosion of steel bars in concrete by 1.5- and 2.6-GHz ground-penetrating radar (GPR) and a modified half-cell potential method. Changes in time-lapsed travel times, amplitudes, and peak frequencies that are associated with short-time Fourier transform spectrograms of the bar reflections were continuously measured. The year-long corrosion process of the reinforcement bar rapidly accelerated within a few days by impressing direct current across a pair of embedded reinforcement bars, which served as the anode and cathode. When corrosion started, the travel times, amplitudes, and frequency spectra of the bar reflection changed. The results were analyzed by dividing the material’s response into three phases (NaCl contamination, depassivation, and corrosion). The writers attribute the phenomena of the first two phases to the ionic conduction and interfacial polarization effect, described in the low-frequency regime of complex dielectric permittivity outlined in the Maxwell-Wagner effect. The remaining phase corresponds with the appearance of large and multiple interfaces among steel, concrete, corrosion product, and cracks, in addition to the upward movement of the corrosion product to the concrete surface that intercepts wider radar footprints. The findings, based on time lapse measurements, provide a basis to further apply the GPR technique to spatial measurements in laboratory and field studies.

Pavement rutting is a critical measure of road condition. Severe rutting indicates road structure deformation and exposes drivers to hazards, especially when it holds rainwater. The Pavement Management Information System requires ruts to be measured regularly for pavement condition score calculation. In the past few decades, a number of automated rut-measurement devices have been developed and used for highway speed data collection. However, all these devices exhibit limitations on measuring ground truth in practice. This paper introduces a high-speed true three-dimensional (3D) pavement surface measurement tool that can produce accurate rut data at highway speeds. Network-level data collections were conducted and the results analyzed to evaluate and verify the system.

The funding needed to address aging water infrastructure ranges in the hundreds of billions of dollars over the next 25 years, and at current replacement rates, pipes are being expected to last for 200 years, although pipes are designed for 100 years or less. In addition to funding needs, utility congestion is making water main replacement more difficult, as is the lack of public tolerance for the disruption from construction. The increased availability of pipe-renewal technologies provides solutions that minimize these problems while providing cost-effective alternatives to traditional replacement. The primary contribution of this paper is the state-of-the-art review of current and emerging renewal technologies used for the repair, rehabilitation, and replacement of water mains. This paper also discusses the data and capability gaps in terms of needs that are unmet by the current renewal technologies. To overcome these gaps, recommendations include conducting renewal technology demonstrations in actual field conditions, identifying accelerated testing protocols to help predict long-term performance, and conducting retrospective analyses of rehabilitation materials to better understand service-life performance.