Journal of Bridge Engineering

The Florida Department of Transportation (FDOT) is in the process of implementing Pontis, a Bridge Management System, to provide decision support to engineers in the headquarters and district offices as they make routine policy, programming, and budgeting decisions regarding the preservation and improvement of the state’s bridges. As part of this effort, an ongoing research program is underway to adapt the system to FDOT needs as well as to advance the state of the art in several areas important to the Department. Most of the research results are organized around a new project-level decision support framework that complements and builds on Pontis’ existing network-level analysis. Specific new models include accident risk and user cost due to roadway width and alignment deficiencies; user cost of load capacity and vertical clearance restrictions, and moveable bridge openings; project-level prediction models for bridge element condition and costs; and prediction of economics of scale and scoping possibilities. The new models are built into a highly graphical spreadsheet model for decision support use.

In general, state-of-the-art bridge management systems have adopted Markov-chain models to predict the future condition of bridge elements and networks in different environments when various maintenance actions are implemented. However, the categories used to describe the various possible environments for a bridge element are neither accurately defined nor explicitly linked to the external factors affecting the element deterioration. In this paper, a new approach is proposed to provide transportation agencies with an effective decision support tool to identify the categories that best define the environmental and operational conditions specific to their bridge structures. This approach is based on genetic algorithms to determine the combinations of deterioration parameters that best fit each environmental category. The proposed approach is applied to develop Markovian deterioration models for concrete bridge decks using actual data obtained from the Ministére des Transports du Québec. This application illustrates the ability of the proposed approach to correlate the definition of environmental categories to parameters, such as highway class, region, average daily traffic, and percentage of truck traffic, in an accurate and efficient manner.

Advances in the production of optical fibers made possible the recent development of innovative sensing systems for the health monitoring of civil structures. The main reasons for this development are the reduced weight and dimensions of fiber optic sensors, the strong immunity to electromagnetic interference, the improved environmental resistance and the scale flexibility for small-gauge and long-gauge measurements. These systems can provide high-resolution and measurement capabilities that are not feasible with conventional technologies. In addition, they can be manufactured at a low cost and they offer a number of key advantages, including the ability to multiplex an appreciable number of sensors along a single fiber and interrogate such systems over large distances. For these reasons, it is evident that fiber optic sensors will change the instrumentation industry in the same way fiber optics has revolutionized communications. This paper provides an overview of the intensity modulated and spectrometric fiber optic sensors and techniques to assess the condition of existing structures in order to enhance the durability of the new bridges, increasing lifetime and reliability and decreasing maintenance activities. Application of these sensors to monitoring strain, temperature, inclination, acceleration, load measurements, ice detection, vehicles speeds and weights, and corrosion and cracking of reinforced and prestressed concrete structures will be described.

Bridge management systems have become increasingly sophisticated over the past decade and provide valuable information about the structural condition of all bridges in the national database. At the same time, reliability methods have gained increasing prominence and are used to forecast life-cycle performance over many decades of structural life. Such reliability analyses need to be updated based on the results of inspections. Specifically targeted nondestructive evaluations are the preferred solution, but are not always available for every bridge. This paper examines how the visual inspection data provided from bridge management systems already in place can be used to update the reliability of a bridge. The limitations and necessary modifications to current practice are discussed. The superstructure of a Colorado highway bridge deteriorating due to corrosion is used as an example.

Currently, the load rating is the method used by State DOTs for evaluating the safety and serviceability of existing bridges in the United States. In general, load rating of a bridge is evaluated when a maintenance, improvement work, change in strength of members, or addition of dead load alters the condition or capacity of the structure. The AASHTO LRFD specifications provide code provisions for prescribing an acceptable and uniform safety level for the design of bridge components. Once a bridge is designed and placed in service, the AASHTO Manual for Condition Evaluation of Bridges provides provisions for determination of the safety and serviceability of existing bridge components. Rating for the bridge system is taken as the minimum of the component ratings. If viewed from a broad perspective, methods used in the state-of-the-practice condition evaluation of bridges at discrete time intervals and in the state-of-the-art probability-based life prediction share common goals and principles. This paper briefly describes a study conducted on the rating and system reliability-based lifetime evaluation of a number of existing bridges within a bridge network, including prestressed concrete, reinforced concrete, steel rolled beam, and steel plate girder bridges. The approach is explained using a representative prestressed concrete girder bridge. Emphasis is placed on the interaction between rating and reliability results in order to relate the developed approach to current practice in bridge rating and evaluation. The results presented provide a sound basis for further improvement of bridge management systems based on system performance requirements.

Traditional methods of modeling and simulating lifecycle for infrastructure management, including bridge management systems, commonly do not account for risk associated with potential failure scenarios. These methods need to be reexamined to take advantage of risk technologies. In this paper, methods for performing reliability computations and managing information that are suitable for risk-informed expenditure allocation in lifecycle management are proposed. The methods include structural reliability assessment methods and the analytic hierarchy method for multicriteria ranking. The paper also presents the advantages of using web-based computing through an example of system reliability assessment software that can be used in an interactive web environment.

Accurate predictive analyses such as those associated with structural reliability and life-cycle costing are needed for the development of Bridge Management Systems. The present paper presents models for reliability and life-cycle cost analyses of reinforced concrete bridges damaged by corrosion. A stochastic deterioration process for corrosion initiation and propagation and then crack initiation and propagation are used to examine the effect of cracking, spalling, and loss of reinforcement area on structural strength and reliability. This will enable expected costs of failure for serviceability and ultimate strength limit states to be calculated and compared for different repair strategies and inspection intervals. It was found that, for a typical reinforced concrete slab bridge, the reduction of structural capacity at the time of severe cracking or spalling is relatively modest and causes probabilities of collapse conditional on spalling to increase by about an order of magnitude. Hence, expected costs of failure for serviceability were significantly higher than the expected costs of failure for ultimate strength limit states.