Journal of Infrastructure Systems

Water distribution systems (WDS) are among the most critical civil infrastructure systems. A reliable and safe water supply is essential for the prosperity and continued well-being of society. Hence, adequate maintenance, repair, and renewal of the vast physical assets in WDS are of paramount importance, especially in places with widespread deterioration of critical water infrastructure assets. However, due to limited resources, water utilities struggle for their asset management strategies to keep pace with the aging of components. Recently, utilities have made efforts to refine the traditional condition-based approach to pipeline asset management that focuses on maintaining the current condition of assets into a service-based approach in which system performance is explicitly considered. This paper reviews existing literature on the various aspects of asset management of WDS, focusing specifically on buried pipelines. Existing condition assessment (CA) techniques, failure prediction models, time-dependent vulnerability models, maintenance planning strategies, and renewal techniques are reviewed. Various techniques of modeling WDS performance, as well as its interdependence with other infrastructure systems, are also reviewed. As such, the paper presents a broad overview of the various aspects that constitute a service-based asset management strategy for WDS. The advantages and limitations of different methods and approaches to the various aspects are also compared to assist selection of an appropriate tool. An overview of future research needs related to asset management and interdependence is presented.

The infrastructure that serves us is aging, and yet it must remain functional to service daily needs, resilient to unforeseen events, and sustainable for future generations. This challenge emphasizes the need to accurately measure and assess the state of infrastructure to meet future demands while avoiding unwanted environmental consequences—what is truly meant by resilience or sustainability? Current assessment tools emphasize primarily the functional dimensions of environmental, social, and economic progress for infrastructure, and often as separate issues without comprehensively addressing the overall issues or changing demands. This paper presents a three-step framework focusing on the functionality-resiliency-sustainability aspects of infrastructure to assess its overall sustainability. A stormwater system in Toronto has been used to illustrate how the framework can be applied. This assessment framework is developed to integrate the three domains of functionality, resiliency, and sustainability based on three criteria: resource minimization, public health, and change management. Thirty-three indicators are identified—19 for functionality, 8 for resiliency, and 6 for sustainability—and guides have been developed for critical indicators to help decision makers step through the scoring process. A detailed multiobjective assessment is undertaken to score the overall functionality, resiliency, and sustainability of the infrastructure.

The process of developing a public–private partnership (PPP) is complex and dynamic throughout the project’s life cycle of project identification, preparation, procurement, implementation, transfer, and posttransfer phases. Although interests in reviewing general trends and diverse topics of the PPP literature have increased over the years, there is a lack of a systematic review of the PPP literature from the perspective of project life cycle. The purpose of this study is to analyze the research status and possible future studies from the viewpoint of project life cycle. The review is conducted by searching related papers from seven leading construction management journals, then classifying them into distinct phases to facilitate further discussion on significant research topics. The findings show that different PPP phases encounter different problems, attracting uneven attention from researchers. Specifically, the transfer phase, which is the end of PPP contract life cycle and the starting point of posttransfer operation, requires systematic research in the future. The outcomes of this study reveal the relationship between important project problems and corresponding PPP phases, which may serve as valuable reference for PPP participants to develop effective project management strategies, and for PPP researchers to better understand PPP research with specific focus on varied PPP phases.

Sustainable disaster recovery involves not merely the restoration of the physical built environment, but also meeting the needs of the impacted stakeholders and decreasing the vulnerability of the host community to future hazards. Nonetheless, the available disaster recovery frameworks deal with community restoration as isolated redevelopment projects and lack the integration of the host community’s overall welfare and vulnerability into the objective functions of the optimization models. This paper balances the short-term redevelopment objectives and the long-term goals of reducing the host community three-dimensional vulnerability (i.e., social, economic, and environmental). The authors develop an innovative decision-making framework that assimilates and meets the needs of the broad community stakeholders. Through a bottom-up multiagent-based model, the authors simulate the stakeholders’ decision-making processes and integrate well-established vulnerability indicators into the objective functions of the stakeholders to better guide the redevelopment strategies. Adopting the recovery processes in the aftermath of Hurricane Katrina catastrophe, the proposed model is implemented and tested on the residential housing and economic financial recovery as well as the infrastructure development in three devastated coastal counties in Mississippi. Each action plan provided by governmental agencies had its own advantages and negative impacts on the vulnerability and/or the recovery of the impacted communities. By holistically addressing the multidimensional recovery processes using simultaneous simulation and optimization techniques, the model develops a Pareto optimal set of strategies that increases the recovery rates and decreases the three-dimensional vulnerabilities. The proposed innovative approach gives decision makers a broader understanding of the disaster recovery outcomes rather than relying on strategies that aim to return the community to pre-event conditions. As such, the proposed holistic approach will enable decision makers to identify optimal disaster recovery strategies that achieve immediate redevelopment objectives and avoid sacrificing the right of future generations to sustainability and resilience.

Present modeling and risk management for resilience of interdependent and interconnected (I-I) physical and cyber-physical infrastructure systems of systems (SoS) often rely on the same risk functions, models, and algorithms used for single systems. This paper introduces an alternative methodology to model, manage, and prioritize safety critical infrastructure systems as complex systems of systems (complex SoS) for resilience planning and operation. The modeling methodology traces all critical I-I in terms of shared/common states (variables), decisions, decision makers, stakeholders, resources, time frame, and organizational setups. A prerequisite for modeling and managing complex SoS is an understanding of the mutual influence resulting from two or more subsystems that share states and other essential entities. Additionally, a novel implementation of fault trees is introduced to prioritize risk without the common need for or knowledge of the associated reliabilities.

A widespread practice used in concession-based public private–partnerships (PPPs) arrangements consists of granting the concessionaire the right, under certain circumstances, to extend the concession term under a build-operate-finance-transfer (BOFT) arrangement. The asset involved in the project becomes the property of the government on its transfer. Thus, extending the concession period means an opportunity cost for the host government. By using an option-pricing model, this paper proposes a methodology for valuing the impact on the public budget arising from this option. This method can be of use in different transportation infrastructure projects, such as motorways, tunnels, and bridges. A case study is provided to show how the proposed methodology can be applied. The results confirm that the opportunity cost for the government may be high, and the main drivers behind this cost are the extension period, the base interest rates, and the risk premium of the government.

This paper presents the specification and estimation of a model for hot-mix asphalt dynamic modulus $|E^{*}|$ using 6,821 observations of 265 specimens from three different data sets containing variables in common such as air voids, binder content, and gradation and variables about mix characteristics and testing conditions not available in some data sets, such as confinement level, number of freeze-thaw cycles, antistripping agents, and fibers. The model parameters were estimated using joint estimation and mixed effects. Joint estimation allowed the identification of parameters from information available only in some data sets and the determination of bias parameters. It also resulted in more efficient parameter estimates derived from all data sets. The mixed-effects approach was used to account for unobserved heterogeneities between samples. Together with proper consideration of heteroskedasticity, these approaches allowed the estimation of a comprehensive model closely satisfying all regression assumptions, providing accurate values of $|E^{*}|$ for any combination of temperature and frequency, and accounting for different testing conditions, component materials, and mixture volumetrics. All the previous factors were found to be statistically significant and to affect dynamic modulus according to a priori expectations. This paper discusses the characteristics of the data sets, the model specification, and general statistical results.

Leveraging thermography for managing built environments has become prevalent as a robust tool for detecting, analyzing, and reporting their performance in a nondestructive manner. Despite many documented benefits of thermographic inspection for better characterizing the conditions of built environments, current thermographic inspections still have several inefficiencies. Inspectors typically collect and store large numbers of thermal images or long-sequence thermal videos to support decision making on the maintenance and rehabilitation of built environments. However, more importantly, these large-scale visual data are typically unordered and not localized (a term used to define a process of finding locations or relative positions of a camera). This paper proposes and compares two approaches for simultaneous localization and thermal mapping. These methods estimate a camera’s pose and map the environment in three dimensions in real-time. Case studies using an off-the-shelf hardware configuration using solely thermal cameras and an author-customized configuration using both thermal and red, green, and blue (RGB) cameras are conducted and the results are compared with a well-established offline three-dimensional mapping tool. The results show that combining information from RGB and thermal cameras provides significant benefits to real-time localization compared with using solely thermal cameras and that the proposed real-time methods have localization performance comparable to the offline tool.

This study builds and applies a framework that addresses the twin uncertainties of traffic flow and interest rates in build-operate-transfer (BOT) projects. Existing valuation methods address traffic flow estimations using linear models, which yield point estimates of traffic predictions regardless of traffic flow volatility. Additionally, considering traffic projections alone ignores the financial risk of these projects, which is an important variable for public–private partnership (PPP) projects. The framework is demonstrated by simulating scenarios based on the model. The model accounts for possible traffic flow pathways and paths that interest rates can take, resulting in the net present value probability distribution for the project. The outcome is the risk profile of the project under consideration. The constructed profile can be employed for analysis by both government agencies and the concessionaire and can thus promote a more efficient environment for contracting purposes. Finally, various applications of the model, including determining the operation period to be allowed for the concessionaire, setting the toll rates, and determining the impact of other policies, are discussed.

An air-coupled (also known as noncontact or contactless) sensing technique in the impact-echo method has been developed and its practical application to the field has been significantly improved. However, unlike the flexural mode frequency, the thickness mode frequency is difficult to measure using the air-coupled sensing technique mainly due to direct acoustic noise from the impact source. The direct acoustic noise is transmitted through the air, while the thickness mode is a portion of leaky Lamb waves from a platelike concrete slab, known as the zero-group velocity (ZGV) or standing wave motion. The noise components and leaky Lamb waves can be separated in the frequency-wave number (f-k) domain because of their different characteristics in phase velocity. In this paper, the f-k domain analysis is validated through both numerical simulations and experiments on two different thicknesses including full depth of concrete slab and shallow delamination. For shallow delamination, a dry-coupled ultrasonic transducer is applied to generate high-frequency ultrasonic waves corresponding to the ZGV frequency of the thickness while a microelectromechanical system (MEMS) is used as an air-coupled sensor. The results demonstrate that the proposed f-k domain analysis scheme and the applied hybrid hardware are capable of clearly detecting the thickness mode frequency and minimize the direct acoustic noise, while the conventional impact-echo method has limits.

In the aftermath of an earthquake, the electric power supply system may have a reduced ability to maintain its intended function, leading to service disruptions of other interdependent facilities until the electricity sector gets restored. In order to analyze such extra functionality losses, the authors have developed an agent-based inoperability input-output model with a focus on damage propagation from a component level to a system level in the electricity sector. In addition, this research presents the probabilistic matrix for the quantification of correlation coefficients between two connected electricity sector components (e.g., power generator and deliverer) and uses these coefficients to identify critical components from a perspective of the network’s reliability. The developed model thus allows us to understand how a degradation of component affects the functionality of the whole electricity sector. To demonstrate the model’s analytic capability, this research conducted case simulations using the data from 2011 Tohoku earthquake. The simulation results show that the impact of seismic damage in a network is generally underestimated because there is unforeseen damage propagation from the component to the system level. Moreover, the results demonstrate that demand-side efforts to conserve electricity usage and restoration priority setting in accordance with component criticality are crucial to ensure community resilience in case of disaster.

Interest in the effective facility management (FM) of office buildings is rapidly increasing because of a significant demand for increased reliability and performance of facilities to enhance employee productivity. In this paper, a process model is proposed for the facility management of office buildings, which is the preferred type of commercial property due to the growth of the current financial market in South Korea. To construct an FM process model, critical success factors and major activities of the office building FM are investigated. The proposed model simulates a real operational setting with characteristics of an office building as a commercial property. The model involves six sequential processes: (1) identify facility; (2) identify characteristics of tenants; (3) develop a facility management plan; (4) implement operation and maintenance; (5) collect new information and respond; and (6) analyze performance and perform complementary actions. The model builds on the integration definition for the function modeling (${\mathrm{IDEF}}_0$) process in order to define the object requirement and relationships for sharing FM information. The aim of this process model is to align the FM objectives with the enhancement of profit. The applicability and effectiveness of the model are evaluated by five FM experts. This research will help us to understand the practical function of the FM of an office building, because this process model is developed based on thorough industry case studies, interviews, and an extensive survey.

A novel method is proposed to rank bridges for maintenance priorities based on the risk posed by structural deterioration. The proposed method integrates structural reliability analysis, public datasets, and traffic flow theory to provide more accurate estimates of (1) probabilities of bridge failure, and (2) failure consequences. For the former, failure probabilities of deteriorating bridges are determined based on the condition ratings of bridge superstructures and substructures as well as a Markov chain deterioration model; public datasets in the national bridge inventory of the United States are used to estimate Markovian transition probabilities. For the latter, social impacts of bridge failures are considered at the transportation network level to holistically evaluate the failure consequences. By virtue of traffic flow and random field theories, bridge failures and their impacts are analyzed beyond the project level, incorporating decision changes of traffic users in route choices and spatial correlation of bridge failures. Eventually, risk of each bridge in the network is quantified as the expected consequences of an undesirable outcome (i.e., bridge failure). Based on risks at network level, bridges are ranked for maintenance priorities. The proposed method is illustrated through numerical examples and is compared with bridge ranking results based on other indicators, including sufficiency ratings and risks at project level. Compared with other indicators, the proposed method provides a more rational criterion for maintenance planning and portfolio management.

Snow and ice on pavements would affect the mobility and safety of motorists unfavorably. As a cost-effective and pollution-free solution, this study proposes a heated pavement system using multifunctional conductive asphalt concrete containing graphite filler. The objective of this study is to find an efficient structural design for heated pavement and to evaluate its environmental, economic, and social impacts. The objectives were achieved through a three-stage methodology: a bench scale slab heating test and measurement of material properties, a set of parametric study using a nonsteady state heat transfer model, and lifecycle assessment. Based on the heat transfer analysis results, the location and thickness of the conductive layer that maximize the energy efficiency is proposed. The lifecycle assessment results champion the practical and sustainable applications of the heated pavement from the three-pillar perspective, conveying the fact that the initial high installment cost was eventually recouped by a substantial reduction in maintenance cost. The results and findings of this study will promote a wider adoption of the conductive asphalt concrete for sustainable infrastructure development and maintenance.

Residual value risk of an infrastructure asset under public–private partnerships (P3s) refers to the risk that on expiry or termination of the P3 contract, the asset does not have the value that the sponsoring public authority originally expected. A concern arises that significant residual value risk might present in long-term P3 projects. To address the concern, this paper presents a semiempirical method to quantify the residual value risk in P3 pavement assets relative to the public-sector comparators (PSCs). Based on a long-term pavement performance database maintained by a provincial ministry of transportation in Canada, the study shows that P3 pavement assets significantly outperform the PSCs in terms of service life, the probability and duration of deferred maintenance, and the residual life after the concession period. It was found that the average residual life of a P3 asset reaches 13.5 years, more than double the average residual life of 6.3 years of a PSC. Based on a modified depreciation method at zero discount rate, these residual lives were translated into mean residual values of 45.0 and 24.7% of capital expenditure for the P3 and PSC assets, respectively. The simulation study at different discount rates found that while the mean residual value risk is significantly greater than zero, suggesting obvious outperformance of P3s over traditional delivery methods, the probability that the residual value of a P3 asset is less than that of a PSC does not change with the discount rate and is stabilized at 20%. The outperformance of P3 assets over PSC assets was mainly attributed to the disciplined asset management and strict handback requirements under P3s. The study concludes that the P3 model, when the contract is strictly implemented, can effectively manage and mitigate the residual value risk in pavement assets.

This paper assesses the impact of power infrastructure investments in the developing economy of Ghana following sector restructure and reform and develops a forecasting model for predicting the future trend in electricity generation and electricity tariffs. Secondary data sourced via the World Bank Public-Private Infrastructure Advisory Facility (PPIAF)/Private Participation in Infrastructure (PPI) Project Database for the period 1994 to 2013 and Energy Commission for the period 2000 to 2014 were used to analyze Ghana’s power generation statistics using descriptive, exploratory data analysis and polynomial prediction models. Results reveal that reform has stimulated independent power producer (IPP) investment, particularly in thermal generation capacities to complement hydro alternatives. It is predicted that in the medium term the electricity tariff will continue to rise while electricity generation will decline if additional investments in power infrastructure are not made. This paper provides a case study that critically appraises Ghana’s power sector reform; exposes the gap between policy implementation and policy objectives attainment; and proposes a simple yet novel polynomial prediction model that can facilitate short-to-medium term planning of generation and tariff management.

Fresh water demand is rising due to factors such as population growth, economic development, and land use changes. At the same time, climate change is rendering the water supply even more uncertain for the future. Due to recurring water restrictions and increasing water-related fees triggered by droughts and water shortages, there is a widespread, growing discomfort with respect to future water availability. Among key stakeholders and local policy makers, this has led to an increased interest in modeling the availability of water resources, with the aim of developing and implementing the appropriate water resource infrastructure and management strategies. This paper examines the Washington metropolitan area (WMA) water supply system and uses a system dynamics approach as a planning tool to make an exploratory assessment of the adequacy of the study area’s water supply system to meet future water demand under the influence of substantial droughts and climate change. This assessment finds that the study area is self-sufficient under normal climate conditions during the entire planning horizon but that it will be strained under moderately severe droughts. On the basis of the temperature, streamflow and precipitation projections made by climate change models specific to the WMA region, climate change is expected to improve the water supply reliability. However, climate change has uncertainty associated with it. One of the four climate models for the Potomac River basin projects a decrease in the precipitation and streamflow, which may result in a reduction in the water supply and the system’s reliability. Regulating the price and the system losses are valuable tools that can be leveraged. But these policy interventions require stakeholder participation (price regulation) and capital investments (reduction of distribution losses). Finally, system reliability can also be improved by increasing water supplies.