Journal of Infrastructure Systems

Artificial neural networks are efficient computing techniques that are widely used to solve complex problems in many fields. In this study, a counterpropagation neural network is used to locate structural damage for a beam, a frame, and support movements of a beam in its axial direction. The investigation considers a variety of diagnostic parameters, including static displacements, natural frequencies, mode shapes, and other parameters based on mode shapes. The method is first demonstrated on a plane frame, based on static displacements. It is then applied to continuous beams using dynamic properties of structures. The required data are obtained through computer simulation by finite-element analysis. The results demonstrate that these parameters can be used as diagnostic parameters for artificial neural networks in structural engineering. An anticipated application to bridge monitoring is discussed.

The public sector has increasingly been adopting private financing alternatives in providing new infrastructure investment to address an ever increasing imbalance between funding and needs for public works projects. These privately financed projects are alternatively called privatized projects or public/private partnership (P/P P) projects. This paper describes a tool that evaluates the viability of prospective P/P P transportation projects. Most of the available literature and discussions on the subject have taken a financial institution or public sector point of view. While these documents can provide a good introduction, they often fail to adequately represent the developer's perspective. Namely, why would an engineer/constructor be interested in undertaking a long-term and often very risky P/P P project? The tool described in this paper was developed after extensive interviews with owners, developers, and investment bankers who are familiar with P/P P projects. The tool is called the Project Scoring Table (PST), and it is designed to help potential P/P P developers identify high quality projects. The PST identifies nine high-level evaluation criteria for a P/P P project, ranging from the political circumstances of the project to its environmental cleanup needs. Using the PST helps both the public agency and its private partners evaluate potential projects in three ways. First, it helps establish the overall viability of the project. Second, it helps define the parity between the owner and the developer. Finally, it helps the P/P P partners determine where their interests are coincident and where they diverge.

Bridge material selection has traditionally been based on engineering and economic criteria. With the increasing interest of the public, industry, and government in sustainable development, environmental assessment in construction is becoming more important. However, we need metrics and data on design alternatives for effective decision making. In this paper, we present results of a life cycle inventory analysis of steel and steel-reinforced concrete bridge girders, based on publicly available data. We find that for the initial construction of equivalent designs for a particular location, a steel-reinforced concrete bridge generally has lower environmental effects than a steel bridge. The expected design life of the two types of bridges is influenced by wear and tear, but also by obsolescence. The uncertainty in bridge design life and related data uncertainties make comparisons based on annualized environmental effects difficult. The steel bridges' beneficial reuse and recycling rates may result in lower annualized environmental effects. In particular applications, however, one material might be preferred over the other due to engineering, aesthetic, or economic criteria, regardless of overall environmental effects.

This paper presents a method for assessing the seismic performance of a water delivery system with the aid of Geographic Information System (GIS) technology. In the proposed method, pipe damage from ground shaking and soil liquefaction are estimated separately. Two types of pipe damage, leak and break, are included in the analysis. Furthermore, the serviceability of a water delivery system is determined from the connectivity and flow analysis of a seismically damaged water network, which is established from the Monte Carlo simulation. As a case study, the seismic performance of the water delivery system in the Memphis area has been evaluated using the proposed method.

A building materials durability model has been developed using a framework that encompasses environmental stimuli, material degradation, structural performance criteria, and maintenance strategies. The model takes a global viewpoint, rather than a microscopic focus, to produce predictions of life-cycle costs of building materials for structural applications. The model is completely general and capable of either simple or complex simulations depending upon the sophistication of the damage models used, the repair strategies considered, and the economic conditions assumed. The current study applies the model to a simple beam to compare painted structural steel and reinforced concrete in different climates and economic environments. The life-cycle cost model allows the engineer to compare the economics of two candidate materials for a given application, assess the consequences of repair strategy, compare durability of a material in different environments, and choose the best durability strategy for short- and long-term applications.

In selecting the type of maintenance or rehabilitation (M&R) activity to apply to highway pavement sections, engineers rely on several items of information. Foremost among these is the effectiveness of the various M&R activities in slowing pavement deterioration and improving its condition. A number of researchers have sought to quantify the effectiveness of M&R activities by developing separate models of pavement deterioration for each type of M&R activity. Often, the results of such analyses have not been satisfactory. For example, some researchers have reported models with poor fits to data or counterintuitive signs of important variable coefficients. These results may be due to the fact that the sample used for model estimation was self-selected. The observations used to analyze the effectiveness of a certain M&R activity are not representative of the population of highway pavement sections, because these observations consist mainly of sections for which that particular activity was believed to be most effective. This paper presents a structured econometric approach for estimating the effectiveness of pavement M&R activities. This approach consists of a discrete model describing the choice of M&R activity by the highway agency, and a set of continuous models representing pavement response, with one equation for each activity. This model system accounts for the self-selected nature of the sample, and consequently obtains consistent model parameter estimates. A case study that demonstrates the applicability and value of the methodology is presented. The data set used for model estimation was provided by the Indiana Department of Transportation.