Journal of Infrastructure Systems

This paper develops an analytical framework with empirical applications to characterize infrastructure failure interdependencies (IFIs). It uses major electrical power outages as the context for understanding how extreme events (within or external to the power system) lead to failures of other infrastructure systems, given a major electrical power outage. The paper takes an empirical approach by examining the patterns of IFIs that occurred in three kinds of events: the August 2003 northeastern North American blackout, the 1998 Quebec ice storm, and a set of three 2004 Florida hurricanes. Data sources include media reports and official ex post assessments of the events. The results characterize IFIs in terms of the sectors affected, and the consequences for society. We developed scales to characterize the consequences of IFIs in terms of impact and extent indices. A comparison is provided of IFIs arising in all five events discussed in the paper, as a basis for considering priorities for risk mitigation. The most significant IFIs in all five events included effects on HVAC in buildings; effects on water systems; effects on health systems, including hospitals and public health efforts, and effects on road transportation systems.

Continuous functionality of critical infrastructure systems is essential to support the social and economic organization of productive sectors within a country. Electric power, potable water, natural gas, telecommunications, and transportation are examples of these critical systems, whose nature makes them suitable for network analysis. This study presents the topological characterization of two interdependent small-sized real networks. The same properties are calculated for ideal models of comparable size to the real networks. Selected topological properties are monitored for these interdependent systems when subjected to external or internal disruptions (e.g., deliberate attacks, malfunction due to aging, or lack of maintenance). This study introduces a simple rule to establish interdependencies among network elements based upon geographical proximity. The effect of the degree of coupling between networks is investigated with a tunable parameter that drives the networks from independence to complete interdependence. Network detrimental responses are observed to be larger when interdependencies are considered after disturbances. Effective mitigation actions could take advantage of the same network interconnectedness that facilitates cascading failures.

Bridge maintenance and replacement optimization methods use deterioration models to predict the future condition of bridge components. The purpose of this paper is to develop a framework for bridge maintenance optimization using a deterioration model that takes into account aspects of the history of the bridge condition and maintenance, while allowing the use of efficient optimization techniques. Markovian models are widely used to represent bridge component deterioration. In existing Markovian models, the state is the bridge component condition, and the history of the condition is not taken into account, which is seen as a limitation. This paper describes a method to formulate a realistic history-dependent model of bridge deck deterioration as a Markov chain, while retaining aspects of the history of deterioration and maintenance as part of the model. This model is then used to formulate and solve a reliability-based bridge maintenance optimization problem as a Markov decision process. A parametric study is conducted to compare the policies obtained in this research with policies derived using a simpler Markovian model.

Work zones often cause traffic congestion on high volume roads. As traffic volumes increase so does work zone-related traffic congestion and so does the public demand for road agencies to decrease both their number and duration. Negative impacts on road users can be minimized by bundling interventions on several interconnected road sections instead of treating each road section separately. Negative impacts on road users can be quantified in user costs. The optimum work zone is the one that results in the minimum overall agency and user costs. The minimization of these costs is often the goal of corridor planning. In order to achieve this goal the interventions on each asset type (pavement, bridges, tunnels, hardware, etc.) must be bundled into optimum packages. In this paper a method is presented that enables road agencies to determine optimum work zones and intervention packages. The method allows the consideration of both budget constraints and distance constraints, including maximum permissible work zone length or minimum distance between work zones. The mathematical formulation of this optimization problem is a binary program that can be solved by existing techniques (i.e., the branch-and-bound method). The feasibility of the approach is illustrated with a simple example.

Maintaining inductive loop detection (ILD) systems in good conditions is a requirement for systems to perform the functions for which they are designed. The objective of this study was to evaluate the typical maintenance policies for ILD so that guidance regarding appropriate maintenance policies could be developed. To address the interaction between the maintenance activities and deterioration of the system components, a microscopic simulation model was developed. Three maintenance policies and two ILD systems with different system compositions were evaluated based on system performance measures such as system availability, costs, working load between crews, and the ratio between cost and availability. The relationships of these system performance measures were compared with maintenance crew size. The results indicated that the characteristics of deterioration and the composition of system components play a major role in determining optimal maintenance policies. The simulation results implied that different maintenance policies should be adopted for the two ILD systems for which different system compositions were simulated in this study.

Northern countries are facing major challenges with regard to the deterioration of their built infrastructures, representing an investment of trillions of dollars. Every year in North America, billions of dollars are spent to repair bridge deck delaminations. The development of an efficient bridge deck rehabilitation system is vital for the efficient management of such infrastructures. This paper reports the results of a comprehensive study on the existing bridge deck rehabilitation practices in North America. A comprehensive information survey was conducted by sending a set of questionnaires to over one hundred individuals working for over 50 different bridge organizations/agencies. Feedback from engineers/managers across North America generated substantial information on various issues involved in a bridge deck rehabilitation project and is critically analyzed. The favored bridge deck rehabilitation techniques and practices adopted by various organizations across North America are summarized with a view to assist engineers/practioners to become familiar with rehabilitation techniques and strategies of concrete deck bridges.

Usually the rating values are determined by visual inspection in most of the bridge management systems (BMSs). A visual inspection is not very objective, and can sometimes result in a different assessment of element condition that may lead to improper prioritization for corrective action. Our novel evaluation results in a more objective condition rating based on visual inspection data. In order to provide an easier way to arrange and prioritize the maintenance schedule among the bridges, the health condition of a bridge needs to be diagnosed in a more practical and more accurate manner. This work utilized systematic classification and statistical analysis based on the thousands of sets of existing bridge inspection data collected in Taiwan over the past five years, with the following goals in mind: (1) develop a normal zone in the health condition shown on the diagnostic figure, and identify the health situation for the bridge using a specific inspection condition; (2) determine the time when the bridge will be in the worst situation, then determine the proper time for maintenance to be carried out; (3) introduce a new data process and innovative model into the BMS in Taiwan, as it will definitely be an asset to be able to estimate reliable maintenance costs in the future.

Microtunneling is a complex operation that requires the integration of several systems, a variety of supporting equipments and personnel, and is heavily influenced by subsurface condition. The objective of this research is to analyze and evaluate the factors that affect the productivity in microtunneling operations. Computer simulation can be used to study microtunneling operations before they are actually performed, thereby identifying operational inefficiency at different stages of the project and finding soil impact on the productivity. For this research, an actual microtunneling field study conducted at Louisiana Tech University was selected. Based on the data collected during this field study, a cyclic operations network model was developed with consideration on the impact of variations in soil compositions on the productivity of the operation. Simulations were repetitively conducted with different soil compositions. The simulation results were studied with regression analysis. A linear function of productivity and soil compositions was found. Various combinations of resources were also simulated. In this research study, the hypothesis that microtunneling boring machine is the bottleneck of the operation was proved to be true, whereas labor resources were found to be secondary limitations.