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Select this Article		Using The “Economic and Financial Re‐Equilibrium” Model to Decrease Infrastructure Contract Incompleteness Carlos Oliveira Cruz and Rui Cunha Marques Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000110 Posted ahead of print 2 May 2012 Full Text: \| Download PDF
	+ -	Show Abstract Renegotiations are becoming an “undesirable protagonist” in infrastructure concessions, questioning the merit of this procurement model. Renegotiations emerge as a consequence of contract incompleteness. Unable to forecast in the long run, and anticipate all possible contingencies, contracts become obsolete and both parties need to negotiate new terms. The economic and financial re‐equilibrium (EFR) model, applied in most infrastructure concessions contracts in Portugal, provides a tool to manage the renegotiation process. Since it is not possible, or affordable, to write complete contracts due to high transaction costs, parties negotiate the rules under which the process of renegotiation might occur. By doing so, it is possible to reduce the incompleteness of contracts, but the model is not immune to opportunistic behaviors. This paper reflects on the effects of the EFR model by providing real data and a case study of a concession, as well as some alternatives able to improve the performance and management of infrastructure contracts regarding the renegotiation phenomenon.

Select this Article		Hurricane Risk Assessment of Power Distribution Poles Considering Impacts of a Changing Climate Sigridur Bjarnadottir, Yue Li, and Mark G. Stewart Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000108 Posted ahead of print 12 April 2012 Full Text: \| Download PDF
	+ -	Show Abstract Storm related power outages cause approximately $270 million per year in repair costs in the United States (U.S.). As a result of increasing sea surface temperatures due to the changing climate, hurricane patterns (i.e. intensity/frequency) may change; however, there is much uncertainty as to how climate change may affect hurricane patterns. Implications of the changing hazard patterns on hurricane risk warrants an investigation to evaluate the potential impact of climate change on power distribution pole failure. This paper proposes a probabilistic framework to evaluate the vulnerability of power distribution poles to hurricanes under the potential impact of a changing climate. Two methods for the design of distribution poles in the U.S., the National Electric Safety Code (NESC) method and the American Society of Civil Engineers (ASCE) method, are considered to investigate the difference of the vulnerability of a distribution pole subjected to hurricane hazard. The framework includes a reliability analysis of the designed power distribution poles using fragility analysis, the effects of degradation of timber poles, probabilistic wind models, and an assessment of the potential impacts of climate change on the annual failure probability of power distribution poles. This paper finds that climate change may have a significant effect on the structural failure probabilities of distribution poles. The age of the poles has a significant impact on the reliability of power distribution poles, which warrants the exploration of cost effective methods to determine when a distribution pole should be replaced to ensure adequate strength to withstand wind loads.

Select this Article		Collecting Horizontal Curve Data: Mobile Asset Vehicles and Other Techniques Daniel J. Findley, P.E., Joseph E. Hummer, P.E., F. ASCE, William Rasdorf, P.E., and Brian T. Laton Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000107 Posted ahead of print 11 April 2012 Full Text: \| Download PDF
	+ -	Show Abstract Mobile asset data collection vehicles can provide transportation agencies with inventories of various roadway and roadside elements containing location information as well as element type and condition data. Horizontal curves are of interest to agencies because they have been shown to be hazardous roadway components and have potential for mobile data collection concurrently with other roadway elements. The cost of manually acquiring horizontal curvature data to develop an inventory can be prohibitive for many agencies, so understanding the applicability of a mobile asset data collection effort for curves is important. The objective of this work was to study the ability of multiple commercial roadway inventory vehicles and to compare them to other methods for determining the geometric characteristics of horizontal curves. The comparison is based on data from three commercial vendors of roadway asset inventory data on a 38.8 km (24.1 mi) course in central North Carolina. Among the 16 curves studied, at least one vendor was within 10% of the radius value found with the manual chord method for six of the curves and within 25% for 13 of the curves. Only three curves had a larger radius variant. For the length measurements of the 16 curves, at least one vendor was within 10% of the length from the chord method for eleven of the curves and within 25% for fifteen of the curves. Only one curve had a larger length variant. The mobile vehicle vendors provided more accurate and consistent curve length measurements than radius measurements. Agencies that consider using mobile data collection vehicles for horizontal alignments should understand the limitations of each horizontal curve estimating technique and the changes that can occur in the radius within the curve. Collaborating with vendors to define the changes in roadway alignment that constitute a curve, the associated beginning and ending of the curve, and geometric characteristics can provide agencies the most appropriate data to meet their needs.

Select this Article		Optimization‐Based Regional Hurricane Mitigation Planning Meredith Legg, Rachel A. Davidson, M. ASCE, and Linda K. Nozick, M. ASCE Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000106 Posted ahead of print 11 April 2012 Full Text: \| Download PDF
	+ -	Show Abstract This paper introduces a constrained linear optimization model to help guide expenditure of government funds for regional hurricane risk management and to provide insight into some of the complexities involved in designing and prioritizing regional mitigation policies and programs. Specifically, it aims to help answer the questions: (1) How much should be spent on mitigation (specifically, retrofitting or acquiring/demolishing buildings)?; (2) What will the return on that investment be?; and (3) How should mitigation funds be spent (i.e., which buildings should be mitigated, how, and when)? A full‐scale case study for residential woodframe buildings in Eastern North Carolina is presented to show how a model application can consider the important features of hurricane loss and mitigation while remaining computationally tractable for real, regional applications, and to illustrate the type of results the model provides and how they can be interpreted. The case study considers damage from both high winds and storm surge flooding; includes a detailed assessment of the risk using a carefully selected set of hurricane scenarios to represent the regional hazard and a component‐based damage model; and considers physically realistic mitigation strategies.

Select this Article		Cost‐Benefit Analysis and the Optimal Timing of Road Infrastructures Pedro Godinho and Joana Dias Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000105 Posted ahead of print 11 April 2012 Full Text: \| Download PDF
	+ -	Show Abstract Standard cost‐benefit analysis is based on a static setting, allowing us to conclude whether or not we should build a new infrastructure, but not allowing us to conclude if it would be preferable to build it right now or in the future. In this paper, we address the optimal timing for building a road within a cost‐benefit framework. We propose a general approach for choosing the optimal timing, taking into account the characteristics of a road infrastructure. We define a model of the expected net present value, with two sources of uncertainty: gross domestic product growth and fuel prices. Both these variables are assumed to be stochastic, so we resort to Monte Carlo simulation for the implementation of the model. We also propose a methodology to estimate the thresholds that define the optimal starting time for the infrastructure. We apply the model to a real infrastructure currently under development, and analyze the rules that define the optimal timing for starting its construction.

Select this Article		High‐Speed Rail Opportunities around Metropolitan Regions: The Cases of Madrid and London Maddi Garmendia, Vicente Romero, José María de Ureña, José María Coronado, and Roger Vickerman Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000104 Posted ahead of print 19 March 2012 Full Text: \| Download PDF
	+ -	Show Abstract The original main aim of High‐Speed Rail (HSR) was to link big metropolitan areas 400–600 km apart. Recently, intermediate HSR stations have also been created in suburban areas or small cities within the limits of metropolitan areas (up to 100 km), opening up new metropolitan transportation opportunities, notably the strengthening of inwards and outwards commuting and through traffic across the metropolis. The argument advanced in this paper is under which conditions HSR could facilitate the development of small HSR suburban cities as special subcenters of the metropolitan area, with particularly good connections to the metropolitan center and to other distant metropolises. The paper focuses on a comparative study of this new type of metropolitan HSR by analyzing the Madrid (Toledo, Segovia and Guadalajara stations) and the London (Ashford, Ebbsfleet and Stratford stations) cases. Infrastructure lay‐out, station typologies and rail services are compared, together with each city's territorial contexts, activities and connections to other transport modes. This case‐study approach, taking account of specific circumstances and contexts, facilitates the understanding of the HSR impact on metropolitan development, offering new transport alternatives.

Select this Article		Empirical Data and Regression Analysis for Estimation of Infrastructure Resilience, with Application to Electric Power Outages Cameron A. MacKenzie and Kash Barker Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000103 Posted ahead of print 19 March 2012 Full Text: \| Download PDF
	+ -	Show Abstract Recent natural disasters have highlighted the need for increased planning for disruptive events. Forecasting damage and time that a system will be inoperable is important for disruption planning. The resilience of critical infrastructure systems, or their ability to recover quickly from a disruption, can mitigate adverse consequences of the disruption. This paper quantifies the resilience of a critical infrastructure sector through the Dynamic Inoperability Input‐Output Model (DIIM). The DIIM, which describes how inoperability propagates through a set of interdependent industry and infrastructure sectors following a disruptive event, includes a resilience parameter that has not yet been adequately assessed. This paper provides a data‐driven approach to derive the resilience parameter through regression models. Data may contain different disruption scenarios, and regression models can incorporate these scenarios through the use of categorical or dummy variables. A mixed effects model offers an alternate approach of accounting for these scenarios, and these models estimate parameters based on the combination of all scenarios (fixed effects) and an individual scenario (random effects). These regression models are illustrated with electric power outage data and a regional disruption that uses the DIIM to model production losses in Oklahoma following an electric power outage.

Select this Article		Spending Scarce Funds More Efficiently — including the Pattern of Interdependence into Cost‐Benefit Analysis Eckhard Szimba and Werner Rothengatter Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000102 Posted ahead of print 16 February 2012 Full Text: \| Download PDF
	+ -	Show Abstract The financial crisis has substantially aggravated shortages of public funds all over the world, particularly in many developed countries. After the expiration of investments made within the framework of public economic recovery plans, the availability of public funds for infrastructure investments will be subject to severe constraints. These conditions require that scarce available funds be spent in an efficient and effective manner. Evaluation methods to select and prioritize infrastructure projects of an investment package often presuppose that infrastructure projects are independent of one another. However, it is inherent in the nature of transport networks that links are interdependent and that changes in one link will affect other parts of the network. Some infrastructure projects might be characterized by substitutive interdependence, while others might interact in a synergistic context. Thus, the cost and benefits of a project are strongly dependent on the realization of other projects. This paper confronts this issue by comprehensively addressing the nature of the problem to derive an optimal set of investment projects. The approach utilizes a dynamic mixed integer algorithm, and the complexity of the combinatorial problem is reduced by elaborating on a heuristic method. Under application of these requisites, this paper develops a framework for integrating the interdependence between infrastructure projects in Cost‐Benefit Analysis. Results obtained from an example application related to investments made in the Trans‐European Network (TEN‐T) emphasize the importance and relevance of considering interdependence for evaluating the investment potential of infrastructure projects.

Select this Article		Urban Sprawl and Local Infrastructure in Japan and Germany Stefan Klug and Yoshitsugu Hayashi Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000101 Posted ahead of print 13 February 2012 Full Text: \| Download PDF
	+ -	Show Abstract Urban dispersion processes in metropolitan areas have led to patterns of suburbanisation and urban sprawl. These processes are inseparably connected with the shift of private mobility from green transport modes to cars. Urbanisation is always accompanied by the development of physical infrastructure, which requires huge investments and determines the structure of a city over long periods of time. Moreover, it cannot be readily adjusted to changing urbanisation patterns or demand of infrastructure service, e.g. triggered by population shrinking. Thus, the impacts of urban sprawl on the local urban infrastructure asset represent complex and important issues to be considered in this context. This comparative study, conducted for the metropolitan regions of Nagoya in Japan and Munich in Germany, correlated six land use pattern and two mobility parameters with the complexity of urban infrastructure by multiple regression modelling. The result confirms the impact of density on public infrastructure stock and additionally shows that there are other relevant parameters of urban sprawl beyond density, such as the concentration of urban development. The saving potential, which was calculated as the monetary cost difference between the most infrastructure efficient and most intensive municipalities, is 85% on average for Munich and 57% for the Nagoya region for sewage, primary schools and local roads.

Select this Article		Spatial Incidence of Economic Benefit of Road‐Network Investments: Case Studies under the Usual and Disaster Scenarios Atsushi Koike, Lori Tavasszy, Keisuke Sato, and Toshiyuki Monma Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000100 Posted ahead of print 13 February 2012 Full Text: \| Download PDF
	+ -	Show Abstract Road networks can be considered to be local public goods. Hence, if they are to be social efficient choices from an economic perspective, their spatial benefit incidence should be equal to their cost burden in each region. An analysis of benefit incidence should consider not only the usual scenario but also a disaster scenario, because the redundancy effect is expected to reduce the amount of economic damage incurred during a disaster. Our research group has developed a spatial computable general equilibrium model (RAEM‐Light) that can be applied to small spatial regions. We used RAEM‐Light to analyze the benefit incidence in the development and maintenance stages of proposed road networks under a usual and a disaster scenario. The spatial incidence of the economic effect of road investment differs between the usual and the disaster scenarios for both the development and maintenance stages. As Japan becomes more decentralized, it will become more important to decide on the optimum allocation of the road‐network cost burden among local governments, taking into account differences in the spatial benefit incidence at each stage and scenario. However, if we want to minimize the economic losses incurred by a disaster such as the Tohoku earthquake (March 11, 2011), more centralized decision‐making may be necessary although this is not social efficient choice from the economic perspective.

Select this Article		Time‐Varying Input‐Output Inoperability Model Roberto Setola, Gabriele Oliva, and Francesco Conte Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000099 Posted ahead of print 13 February 2012 Full Text: \| Download PDF
	+ -	Show Abstract Representing interdependent Critical Infrastructures is mandatory to implement protection policies and strategies. Among the several interdependency models that have been provided in these years, the Input‐output Inoperability Model (IIM) gained large attention due to its simplicity and compactness. Such a model is able to emphasize cascading effects induced in a complex scenario by dependencies and interdependencies; however the financial origin of data and the stationarity assumption greatly reduce the applicability of the framework. These aspects are very crude approximations, due to the intrinsic limits of the methodology. Indeed, while modeling realistic scenarios, the coupling of different infrastructures and sectors is expected to increase with the outage duration. In this paper a different formulation of IIM model is proposed where time varying interdependency coefficients are considered. Such coefficients are defined to explicitly take into account the severity and the duration of negative phenomena. Some interesting results are obtained from a complex case study including several infrastructures on the Italian territory, emphasizing the features of the proposed methodology. The proposed framework, based directly on operators’ experience, is able to capture the behaviours induced by the different backup strategies.

Select this Article		Performance of Ductile Iron Pipes: Sampling Scheme and Inferring Pipe Condition Yehuda Kleiner and Balvant Rajani Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000098 Posted ahead of print 6 February 2012 Full Text: \| Download PDF
	+ -	Show Abstract Ductile iron (DI) pipes have been used in North America since the late 1950s. This paper, the second of two companion papers, describes how understanding gained on the geometry of external corrosion pits is used to devise a sampling scheme and to infer the condition of a ductile iron buried water mains. A companion paper (Kleiner et al.,2011a) describes the exhumation of varying lengths of ductile iron pipes in four North American water utilities. The exhumed pipes were cut into sections, sandblasted and tagged. Soil samples extracted along the exhumed pipe were also provided. Pipe sections were scanned for external corrosion using a laser scanner to produce corrosion pit data sets. Statistical analyses were performed on geometric properties of corrosion pits such as pit‐depth, pit‐area and pit‐volume. These analyses were developed further to assess the impact of the different soil characteristics on these pit properties. This paper, describes the investigation of appropriate sampling schemes to represent the statistical properties of ductile iron pipe corrosion. With known statistical properties, an approach is developed to infer the condition of the pipe

Select this Article		Performance of Ductile Iron Pipes: Characterization of External Corrosion Patterns Yehuda Kleiner, Balvant Rajani, and Dennis Krys Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000097 Posted ahead of print 6 February 2012 Full Text: \| Download PDF
	+ -	Show Abstract Ductile iron pipes have been used in North America since the late 1950s. This paper, the first of two companion papers describes research that endeavored to gain a thorough understanding of the geometry of external corrosion pits and the factors (e.g., soil properties, appurtenances, service connections, etc.) that influence this geometry. This understanding is subsequently used in the second paper to devise a sampling scheme and to infer pipe condition of ductile iron buried water mains. Soil corrosivity is not a directly measurable parameter and pipe external corrosion is largely a random phenomenon. The literature is replete with methods and systems that attempt to use soil properties (e.g., resistivity, pH, redox potential and others) to quantify soil corrosivity and subsequently predict pipe corrosion. In this research, varying lengths of ductile iron pipes were exhumed by several North American water utilities. The exhumed pipes were cut into short sections, sandblasted and tagged. Soil samples were also obtained at discrete locations along the exhumed pipe. Pipe sections were scanned for external corrosion using a specially developed laser scanner. Scanned corrosion data were processed using specially developed software to obtain information on pit‐depth, pit‐area and pit‐volume. Statistical analyses were subsequently performed on these three geometrical attributes. Various soil characteristics were investigated to determine their impact on the geometric properties of the corrosion pits. Subsequently, a method is proposed to assess the condition of a ductile iron pipe, based on the geometry of corrosion pits of a few samples extracted along the pipe. This paper, the first of two companion papers, describes the pipe exhumation, data preparation and statistical analysis of corrosion pits. The second paper describes a sampling scheme to infer pipe condition of a ductile iron buried water mains.

Select this Article		A Random Parameters Seemingly Unrelated Equations Approach to the Post‐Rehabilitation Performance of Pavements Panagiotis Ch. Anastasopoulos, A. M. ASCE, Fred L. Mannering, M. ASCE, and John E. Haddock, M. ASCE Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000096 Posted ahead of print 14 January 2012 Full Text: \| Download PDF
	+ -	Show Abstract Pavement rehabilitation is one of the most critical and costly forms of infrastructure asset management. Yet determining the subsequent performance of rehabilitated pavements is complex task, particularly when multiple performance measures such as roughness, surface deformation, and structural integrity are considered. The complexity arises in part because of the interrelation among these performance measures, as well as the fact that data relating to factors known to affect these measures may not be available. This paper seeks to demonstrate an appropriate methodological approach for studying the post‐rehabilitation performance of pavements using data from rural interstate roads in Indiana. Specifically, a random parameters seemingly unrelated equations approach is applied to explicitly account for the cross‐equation correlation that exists among pavement‐performance measures as well as the underlying heterogeneity across observations caused by imperfect data. The results provide some new insights into the interrelationships among the pavement rehabilitation treatments considered, pavement performance, traffic loads and trucks, weather and soil conditions, and rehabilitation expenditures.

Select this Article		Government Supports in PPP Contracts: The Case of the Metro Line 4 of the São Paulo Subway System Luiz E. Brandão, Carlos Bastian‐Pinto, Leonardo Lima Gomes, and Marina Labes Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000095 Posted ahead of print 14 January 2012 Full Text: \| Download PDF
	+ -	Show Abstract In November 2005 the State Government of São Paulo, Brazil, announced the intention to bid a 30 year contract to build, operate and explore passenger services for the Metro Line 4 of the São Paulo Metropolitan Subway System. Given the high risk of the project, in order to attract private investors the bid documents stipulated that the government would offer risk mitigation mechanisms such as subsidy payments and a Minimum Demand Guarantee (MDG). Since a MDG has option like characteristics, we use the real options approach to analyze the effect of these incentives on the value and the risk of the Metro Line 4 concession project, as well as their cost and risk to the government. The results indicate that the incentives proposed are effective in reducing the risk and increase the net value of the project by 36% at a cost to the government of 5% of the total value of the project. Additionally, we show that for a given cost, the most effective risk reduction mechanisms are the ones that include a higher portion of minimum demand guarantees relative to the subsidy payment. The approach we develop can assist transportation authorities in designing optimal incentive mechanisms.

Select this Article		Network‐Level Pavement Asset Management System Integrated with Life Cycle Analysis and Life Cycle Optimization Han Zhang, Gregory A. Keoleian, and Michael D. Lepech Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000093 Posted ahead of print 14 January 2012 Full Text: \| Download PDF
	+ -	Show Abstract A new network‐level pavement asset management system (PAMS) utilizing life cycle analysis and life cycle optimization methods is developed. Integrated life cycle assessment and life cycle cost analysis expand the scope of the conventional network‐level PAMS from raw material extraction to end‐of‐life management. To aid the decision making process, a life cycle optimization model is applied to determine the near optimal preservation strategy for a pavement network. A geographic information system (GIS) model is utilized to enhance the network‐level PAMS by collecting, managing, and visualizing pavement information data. The network‐level pavement asset management system proposed in this paper allows decision makers to preserve a healthy pavement network and minimize life cycle energy consumption, greenhouse gas (GHG) emissions, or cost as a single objective, while also meeting budget constraints and other agency constraints within an analysis period. A case study of a pavement network in Michigan compares the near optimal preservation strategy to the Michigan Department of Transportation's current preservation practice. Compared to the current preservation plan, the optimal preservation strategy reduces life cycle energy consumption, GHG emissions, and cost by 20%, 24%, and 10%, respectively. The impact of annual preservation budget cuts on total life cycle cost is also analyzed. A $3 million annual preservation budget reduction (75% reduction of current annual budget) will significantly increase user cost (caused by congestion and pavement surface deterioration) by $450 million for a 40‐year analysis period.

Select this Article		Condition‐Dependent Maintenance Effectiveness in Dynamic Performance Models for Transportation Infrastructure James C. Chu Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000092 Posted ahead of print 5 January 2012 Full Text: \| Download PDF
	+ -	Show Abstract Dynamic performance models that combine performance prediction and maintenance effectiveness are required for state‐of‐the‐art optimization techniques such as optimal control. Because records of maintenance effectiveness depend on facility condition, nonlinear models are necessary to include interactions between variables to account for this dependence and estimate condition‐dependent maintenance effectiveness. Therefore, this paper proposes a procedure for estimating nonlinear dynamic performance models that capture interactions between variables using panel data. The relationships between maintenance effectiveness and current facility condition and between structural design and traffic impact were found to be polynomial in a numerical example of highway pavements. It was also demonstrated that imposing physical constraints on the maintenance effectiveness based on external data sources generated more reasonable models when self‐selected samples were used for estimation.

Select this Article		Developments in Performance Monitoring of Concrete Exposed to Extreme Environments W. J. McCarter, T. M. Chrisp, G. Starrs, A. Adamson, E. Owens, P. A. M. Basheer, S. V. Nanukuttan, S. Srinivasan, and N. Holmes Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000089 Posted ahead of print 19 December 2011 Full Text: \| Download PDF
	+ -	Show Abstract The performance of the surface zone of concrete is acknowledged as a major factor governing the rate of deterioration of reinforced concrete structures as it provides the only barrier to the ingress of water containing dissolved ionic species such as chlorides which, ultimately, initiate corrosion of the reinforcement. In‐situ monitoring of cover‐zone concrete is therefore critical in attempting to make realistic predictions as to the in‐service performance of the structure. To this end, this paper presents developments in a remote interrogation system to allow continuous, real‐time monitoring of the cover‐zone concrete from an office setting. Use is made of a multi‐electrode array embedded within cover‐zone concrete to acquire discretized electrical resistivity and temperature measurements, with both parameters monitored spatially and temporally. On‐site instrumentation, which allows remote interrogation of concrete samples placed at a marine exposure site, is detailed, together with data handling and processing procedures. Site‐measurements highlight the influence of temperature on electrical resistivity and an Arrhenius‐based temperature correction protocol is developed using on‐site measurements to standardize resistivity data to a reference temperature; this is an advancement over the use of laboratory‐based procedures. The testing methodology and interrogation system represents a robust, low‐cost and high‐value technique which could be deployed for intelligent monitoring of reinforced concrete structures.

Select this Article		Risk Allocation in Public—Private Partnership Infrastructure Projects in Developing Countries: A Case Study of the Tehran—Chalus Toll Road Gholamreza Heravi, A. M. ASCE and Zeinab Hajihosseini Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000090 Posted ahead of print 19 December 2011 Full Text: \| Download PDF
	+ -	Show Abstract All over the world, limited funding for the development and operation of infrastructure projects propels governments to attract private investment and enter public—private partnerships (PPPs). Different types of PPP have been practiced in infrastructure development in both developed and developing countries, with diverse results. While PPPs have many advantages, they involve some complexities in planning, execution, and monitoring and control that vary according to specific project and country conditions. This paper provides a case study of the Tehran—Chalus Toll Road project, one of the largest highway projects in Iran. The authors analyze the contract organization of the PPP project, identify the most important risks, compare the project's organization with successful and unsuccessful experiences in similar PPP projects, and suggest ways to improve risk allocation to achieve better project performance for this and other PPP projects in developing countries.

Select this Article		Texas Department of Transportation 3D Transverse Profiling System for High Speed Rut Measurement Yaxiong Huang, Phillip Hempel, and Todd Copenhaver Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000088 Posted ahead of print 19 December 2011 Full Text: \| Download PDF
	+ -	Show Abstract 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 3D pavement surface measurement tool which can produce accurate rut data at highway speeds. Network level data collections were conducted and the results analyzed to evaluate and verify the system.

Select this Article		Optimization of Short‐Term “On‐Street Park‐Pay” License Plate Surveying Deo Chimba, P.E., PTOE and Mbakisya Onyango Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000087 Posted ahead of print 19 December 2011 Full Text: \| Download PDF
	+ -	Show Abstract Many cities in urban and suburban areas are characterized by parking space problems, especially during peak hours and special events. To overcome these problems, some local governments initiate on‐street short term paying programs to limit length of stay and generate revenue. The problem becomes which data should be collected, for what frequency and for how long in order to produce significant results. This study applied “power analysis” in analyzing rate of turnover and utilization levels to develop optimum data collection using license plate surveying methodology. A case involving downtown areas, shopping center and beach parks is presented. Analysis evaluated the probability of detecting desired changes, minimum detectable changes (MDC) and coefficient of variation (CV) for different data monitoring frequencies over desired data collection periods. Three critical license plate monitoring intervals for downtown parking were identified to be between 5–20 minutes, 30–40 minutes and 40–60 minutes, with each group having different characteristics compared to others. There was a slight overlap on transitional monitoring time intervals. Analysis found that, to detect all possible optimal parking characteristics and cost efficient surveying, license plates should be monitored at intervals less than every 30 minutes for downtown and 60 minutes for beach parks.

Select this Article		Incorporating Delay Effects into Airport Runway Pavement Management Systems Bo Zou and Samer Madanat Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000086 Posted ahead of print 19 December 2011 Full Text: \| Download PDF
	+ -	Show Abstract This paper presents an approach to address pavement management decision problems at airports with multiple runways. It relaxes some of the underlying assumptions made in previous studies, and explicitly considers time requirement for runway reconstruction, deterioration dependence on traffic levels, and the growth of traffic demand over time. A finite‐horizon dynamic program is formulated to investigate the interplays among M&R action time, functional interdependence between runways, and traffic growth. Results from computational studies reveal these interplays, in particular the trade‐off between present M&R action and delay cost and long‐term benefits brought by significantly upgrading pavement condition through reconstructing runways. Sensitivity analyses suggest that baseline demand, demand growth rate, and the parameter differentiating traffic‐dependent transition probabilities significantly affect optimal M&R decisions and total expected cost‐to‐go.

Select this Article		Implementation of LRFD Design of Drilled Shafts in Louisiana Xinbao Yu, Murad Y. Abu‐Farsakh, Sungmin Yoon, Ching Tsai, and Zhongjie Zhang Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000084 Posted ahead of print 7 October 2011 Full Text: \| Download PDF
	+ -	Show Abstract This paper presents reliability based analyses for the calibration of resistance factor for axially‐loaded drilled shafts. A total of 16 cases of drilled shaft load tests were collected from Louisiana Department of Transportation and Development (LADOTD) archives. Only 11 out of the 16 cases met the Federal Highway Administration (FHWA) failure criterion. Due to the limited number of available drilled shaft cases in Louisiana, additional 15 drilled shaft cases were collected from a neighboring state, Mississippi, which has subsurface soil conditions similar to Louisiana soils. A database of 26 drilled shafts representing the typical design practice in Louisiana was created for a statistical reliability analysis. Predictions of load‐settlement behavior of drilled shafts from soil borings were determined using the FHWA design method (O'Neill and Reese method) via the SHAFT computer program. Measured drilled shaft axial nominal resistance was determined from either the Osterberg cell (O‐cell) test or the conventional top‐down static load test. Statistical analyses were performed to compare the predicted ultimate drilled shaft nominal axial resistance and the measured nominal resistance. Results show that the selected design method underestimates the measured drilled shaft resistance by an average of 17%. The Monte Carlo simulation method was selected to perform the Load and Resistance Factor Design (LRFD) calibration under strength I limit state. Total resistance factors for different reliability indexes (β) were determined and compared with those available in literature. LRFD calibration showed that the FHWA design method has a resistance factor (ϕ) of 0.60 at a target reliability index (βT) of 3.0.

Select this Article		Heuristic Analysis of the Effective Range of a Track Tamping Machine Rui Santos and Paulo Fonseca Teixeira Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000081 Posted ahead of print 3 October 2011 Full Text: \| Download PDF
	+ -	Show Abstract This paper develops a methodology to define the optimum length of railway track that would undergo maintenance work by one tamping machine. The acquisition and logistic costs associated with the use of this type of machine are very relevant in the context of track maintenance. However, no systematic approach was found in the literature that could help managers recognize the machines' real capacity, which seems to be more conditioned by the track's availability for maintenance than by machine's performance. The methodology presented here takes into account the execution capacity of the machine in a scenario where the intervention schedule is optimized from a long‐term perspective. It employs a metaheuristic process (simulated annealing) to deliver an optimized intervention schedule and the model is applied to several track length configurations. A trade‐off approach is therefore adopted, confronting the minimum logistic costs with the fixed costs of the machine. The implementation of the algorithm showed significant cost reduction. However, the results of the model showed a deviation of the minimum cost solution from the quality standards. Further research could provide more insight into quality standards through its integration into a multi‐objective analysis.

Select this Article		Emergency Evacuation Guidance Design for Complex Building Geometries James C. Chu and Chau‐Yuan Yeh Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000080 Posted ahead of print 3 October 2011 Full Text: \| Download PDF
	+ -	Show Abstract The planning for pedestrian evacuation in large public gathering buildings is important because they are vulnerable to various types of emergency events. One of the most critical measures of the preparedness of a building during these events is its evacuation guidance. The paper proposes a method for designing evacuation guidance systems in complex building spaces by solving a maximum coverage problem with side constraints of number of signs and evacuation routes. The solution of the problem is difficult to find in general so the problem is solved in two steps. The first step generates an ideal evacuation guidance system with unlimited number of signs. In the second step, the ideal system is reduced to the actual guidance system with a reasonable number of signs by constraining the number of signs and maximizing the sign coverage. There are two reasons for using the ideal system as a basis for generating the actual guidance system. First, the solution space of the maximum coverage problem is greatly restricted by limiting the sign installation choices to the candidate locations found in the ideal system. Second, calculating evacuation routes for the actual system is not necessary because the routes are readily available from the ideal guidance system. Finally, an example based on a transportation terminal is presented to validate the methodology. The results show that the proposed methodology is effective and can be used for supporting emergency evacuation planning for buildings.

Select this Article		Smart Garage Development Problem: A Model Formulation and a Solution Approach Seok Kim and Ivan Damnjanovic, M. ASCE Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000079 Posted ahead of print 28 September 2011 Full Text: \| Download PDF
	+ -	Show Abstract Plug‐in electric vehicles (PEVs) are becoming increasingly popular. In the next several years, all major vehicle manufacturers will introduce PEVs, either as battery electric vehicles (BEVs) such as the Nissan Leaf or plug‐in hybrid electric vehicles (PHEVs) with a dual powertrain such as the General Motors Volt and the Toyota Prius. This new generation of vehicles relies on electricity as a power source and a battery as an energy storage medium. Naturally, for PEVs, “refueling” occurs when the battery connects to an electrical outlet linked to a distribution network. The primary objective of this paper is to study optimal locations for building facilities (i.e., smart garages) that will maximize integrated benefits from the transportation system (i.e., parking fee) and the electric power system (i.e., revenue from vehicle‐to‐building [V2B] services). A deterministic smart garage development problem (SGDP) is formulated and modeled as a bi‐level program and solved using a genetic algorithm. The results of a simple numerical example show the sensitivity of the model results with respect to parameters including PEV penetration rate and battery capacity.

Select this Article		Prioritizing Infrastructure Investments in Afghanistan with Multi‐Agency Stakeholders and Deep Uncertainty of Emergent Conditions James H. Lambert, M. ASCE; P.E., D.WRE, Christopher W. Karvetski, David K. Spencer, Barbara J. Sotirin, Dawn M. Liberi, Hany H. Zaghloul, John B. Koogler, Samuel L. Hunter, William D. Goran, Renae D. Ditmer, and Igor Linkov Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000078 Posted ahead of print 10 September 2011 Full Text: \| Download PDF
	+ -	Show Abstract The Afghanistan National Development Strategy identified billions of dollars of needs for transportation, water, energy, telecommunications, and other necessary infrastructure development for the rebuilding of Afghanistan. With economic sustainability as a primary aim, the coordination and prioritization of investments has been a challenge in part due to Afghanistan's volatile security situation along with the intricacies of negotiating and coordinating efforts of numerous stakeholders. An understanding of the contributions of infrastructure systems and associated projects to the national development strategy is needed. This paper formulates a scenario‐informed multicriteria approach to prioritize major project investments for infrastructure development subject to deep, non‐probabilistic uncertainties. The methods are inclusive of stakeholder values and accounts for deep uncertainties in governance, security, economy, environment, workforce, and other topics. The methods are applied in Afghanistan's Nangarhar province to assist in the selection among twenty‐seven candidate infrastructure projects that are vulnerable to potential refugee immigration among other emergent conditions. The paper describes the relationships of selected projects to strategic goals while facilitating collaboration among government and non‐government investors, donors, technologists, and other stakeholders.

Select this Article		Pavement Network Maintenance Optimization Considering Multidimensional Condition Data Kenneth D. Kuhn Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000077 Posted ahead of print 10 September 2011 Full Text: \| Download PDF
	+ -	Show Abstract Pavement management systems inventory historical and current conditions of roadway networks, predict the future conditions of such networks and suggest schedules for maintenance, repair, and rehabilitation activities. Such systems typically rely on a composite condition index, a one‐dimensional and often discrete measure of the overall structural health and/or serviceability of pavement. The index is used during deterioration modeling, user and agency cost estimation, and selection and scheduling of maintenance activities. Pavement can suffer from a large number of related but distinct distresses. Difficulties associated with unobserved heterogeneity have hampered efforts to accurately model deterioration via composite condition indices. At the same time, optimization techniques used to generate recommended maintenance plans have been shown both to be sensitive to deterioration model specification and to become computationally intractable as condition data increase. This research describes how a large network of related sections of pavement, each one of which may be plagued by a number of different distresses, can be managed without reducing condition data to a composite index. The use of approximate dynamic programming mitigates the curse of dimensionality that has haunted distinct Markov decision problem formulations of the maintenance optimization problem and limited their complexity. A computational study illustrates how the proposed approach leads to more sophisticated maintenance decision rules, which can be used to ensure the suggestions of pavement management systems more closely match engineering best practices. The use of multidimensional condition data can also yield more accurate deterioration models and cost estimates. The techniques introduced here in the context of pavement management could easily be applied within any infrastructure management system.

Select this Article		Modeling Failure of Wastewater Collection Lines Using Various Section‐Level Regression Models Baris Salman and Ossama Salem, P.E., M. ASCE Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000075 Posted ahead of print 20 August 2011 Full Text: \| Download PDF
	+ -	Show Abstract Wastewater utilities are aiming to implement asset management strategies to minimize costly emergency repairs, to justify expenditures, and to optimize future renewal actions. Consequently, development of deterioration models that explain the behavior of wastewater lines and provide predictions regarding potential future condition levels is gaining importance. In this paper, deterioration models are generated to estimate the probability of failure values for sewer sections. A set of variables was obtained by examining the inventory and inspection databases of a sewer network. Three statistical methods (ordinal regression, multinomial logistic regression, and binary logistic regression) were employed in successive steps. Proportionality of odds assumption was tested for ordinal regression models, and suitability of this particular method was discussed. Estimated condition ratings were compared with observed data, and binary logistic regression model was found to be more suitable for predicting probability of failure than the multinomial logistic regression model. The models presented in this paper are expected to assist wastewater utilities in developing section‐level risk assessment models to identify pipe sections that require immediate attention and close monitoring.

Select this Article		Intelligent Transportation Systems (ITS) and NO₂ Emissions Dinesh Gupta, Ph.D., P.E., M. ASCE and Louis F. Cohn, Ph.D., P.E., F. ASCE Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000073 Posted ahead of print 11 August 2011 Full Text: \| Download PDF
	+ -	Show Abstract Environmental or air quality impacts of Intelligent Transportation Systems (ITS) are very difficult to measure. Some researchers have attempted to quantify the effects of individual ITS application on emissions; yet, the effects of ITS as a whole on ambient air quality have not been investigated. This paper shows how to model the relationship between ITS and ambient air quality. The multiple Artificial Neural Networks (ANN) training with the data yielded a model for predicting the NO₂ concentrations. In addition, the ANN made the measurement of the effect of ITS on NO₂ concentrations in ambient air possible. Data pertaining to fifty nine US cities (urbanized area) were used for this work. Input variables used were related to transportation and local characteristics, and ITS applications. Output variable was the annual average concentration of NO₂ in ambient air. The K‐fold cross validation technique was used to train the ANN. There was an unusual finding: in contrast to the common assumptions, NO₂ concentration increased with ITS intensity and that may be suggestive of causing conformity problems and may jeopardize the ITS project and the transportation program.

Select this Article		Measuring Energy Efficiency in Urban Water Systems Using a Mechanistic Approach Leon F. Gay and Sunil K. Sinha Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000072 Posted ahead of print 5 August 2011 Full Text: \| Download PDF
	+ -	Show Abstract This paper presents an energy efficiency metric for the raw water extraction process at urban water systems. Raw water pumping is the second largest energy consumer at water treatment plants after finished water pumping. U.S. water utilities are using more benchmarking metrics to assess performance and to compare their energy efficiency with other utilities. This trend became especially prevalent among water and wastewater utilities after the 2007 publication of a benchmarking method based on the EPA's energy star rating system for buildings. This paper proposes a thermodynamic score to provide complementary information of a utility's energy efficiency. The thermodynamic score arises from estimating the minimum energy required by the system, in contrast to the benchmarking method whose basis is an empirical approach. The thermodynamic score proved to be an effective additional tool for measuring energy efficiency in most cases, although may have significant limitations in others. However, the energy analysis developed for the thermodynamic score has further applications on proactive asset management of water utilities.

Select this Article		A Comprehensive Study on Using Externally Bonded FRP Composites for the Rehabilitation of Reinforced Concrete T‐Beam Bridges Julio F. Davalos, An Chen, Indrajit Ray, and Jeffrey R. Levan Journal of Infrastructure Systems doi:http://dx.doi.org/10.1061/(ASCE)IS.1943-555X.0000070 Posted ahead of print 20 July 2011 Full Text: \| Download PDF
	+ -	Show Abstract This paper describes a synthesis of findings pertaining to rehabilitation of concrete T‐beam bridges with externally bonded FRP composites from a Pennsylvania Department of Transportation District 3 (PennDOT D3) project, with the purpose of answering common questions of concern mainly by state Department of Transportation (DOT) engineers and officials. A method for selecting applicable candidate bridges for suitability of repair with externally bonded FRP composites is described. Three levels of repair are identified, Level 1 (contract), Level 2 (contract/Department force), and Level 3 (Department force). From this classification, a candidate bridge was selected for a contract repair project. Field and laboratory testing of existing bridge materials is described. Pre‐repair tests included ultrasonic pulse velocity and rebound hammer on beam concrete, compressive strength tests on deck concrete cores, carbonation tests for both beam and deck concrete, SEM‐EDX analyses for beam and deck concrete, and tension tests of the extracted reinforcing steel. Structural analysis was based on AASHTO specifications. Finite Element (FE) modeling was performed to determine existing capacity and the FE model was calibrated by testing of the bridge using applied truck loads. The FRP design was based on strengthening the bridge to sustain an HS‐20 AASHTO truck loading. The FRP repair system was designed based on current ACI 440.2R‐08 design guidelines. Repair work and post‐construction load testing were completed. Supporting full‐scale lab studies were conducted to evaluate the most effective concrete substrate repair method and FRP strengthening scheme for laboratory damaged concrete beams by accelerated corrosion, to assure better long‐term performance under static and fatigue loads. Results from the rehabilitated bridge and supporting testing were used to develop draft PennDOT design standards and construction specifications and to apply “lessons learned” to the design and constructability of nearly 1,000 concrete T‐Beam bridges in Pennsylvania, USA.