Bridge Maintenance Level Assessment

Abstract

Parameters in assessing the effectiveness of maintenance tasks on the overall cost of a bridge or system of bridges are identified and the linkage among maintenance, condition rating, and cost is made by subdividing the subjective process into smaller parts. Experience with New York City bridges is used to develop a life expectancy model once the maintenance and repair protocol is specified. Results for several sample maintenance allocations are given to show how a rapid spreadsheet calculation can provide a basis for comparing maintenance alternatives and to point in the direction of an optimized allocation of limited budgets. THE BRIDGE MANAGEMENT PROBLEMManagers of bridge systems are confronted by uncertain and often conflicting options usually centered on three basic, though not independent, questions: How do the various possible strategies for maintenance and repair affect the cost and performance of the system over some period of time? What is the potential effect of the range of possible values of uncertain and intangible factors? And, above all, what strategy should be implemented under specified constraints, such as a budget short of optimal for maintenance?A quantitative model is needed to form the basis for a formal optimization of the allocation of budget resources and, at the same time, give bridge managers a rapid way to explore alternatives among the myriad possible choices confronting them. In setting up such an analytical model, the decision-making process can be decomposed into smaller units that are more readily quantified for analysis, and thus less subjective in the aggregate. Moreover, it can include not only the readily quantifiable costs of maintenance, repair, and replacement, but also the much less tangible costs of disruptions during repairs or reconstruction.It is the objective of this work to present such a model, implemented and illustrated with a simplified computer spreadsheet that can be used to explore the consequences of managerial decisions and the effects of the range of possible values of uncertain data.The present development and application of the model draws on the New York City bridge system as an exemplar of the problems facing managers elsewhere. The New York City Department of Transportation is in charge of some 770 bridges with 4706 spans having a deck area of approximately 1 43 × 10 6 m 2 . Their average age in 1998 was 75 years. Typical recent annual expenditures for bridge rehabilitation, component rehabilitation, maintenance, repairs, and hazard mitigation surpass $0.5 billion. The average bridge condition over the last 10 years has remained near the rating of 4.5 on the New York State Department of Transportation scale, in which 7 signifies new and 1 denotes failure (State of New York, 1997). This

The Use of Knowledge Map Model in Construction Industry

“…However, the numbers of experts and senior engineers are insufficient in the area of maintenance of bridge; for that reason, how to translate tacit experience to explicit knowledge becomes a major problem in bridge maintenance (Gattulli and Chiaramonte 2005;Miyamoto et al 2000;Testa 2002;Wang and Elhag 2008).…”

Evidential reasoning approach for bridge condition assessment

“…There are many different ways such as pairwise comparison matrix method (or called AHP or Eigenvector method) (Saaty, 1998), Delphi method (Chang, Huang, & Lin, 2000;Curtis, 2004), and so on, which can all be used to determine the relative weights of the identified bridge factors. Table 2 shows the relative weights of the 13 identified bridge factors used in New York bridge management system (BMS) (Testa & Yanev, 2002;Yanev, 1998).…”

“…Each component is assigned a rating R i on the scale of 1-7 during inspection and contributes to overall bridge rating R through a weight w i , which varies from component to component and from one system to another. The overall bridge condition rating is given by (Testa & Yanev, 2002;Yanev, 1998) Melhem (1994) presented a fuzzy inference model for bridge condition rating, in which bridge condition ratings were given on a scale of 0-9 and were all considered as fuzzy numbers. The pairwise comparison matrix and eigenvector method were used to determine the priorities among bridge elements, and the fuzzy multiple attribute decision making technique was utilized to synthesize the ratings of bridge elements and to generate an overall assessment for each bridge component such as deck, superstructure and substructure.…”

Analysis of bridge condition on state road network in Slovenia

“…Appropriate maintenance and rehabilitation actions need to be planned and implemented throughout the lifecycle of the structure in order to maintain its adequate performance [4]. Rehabilitation actions should be initiated when performance of a structure falls below a pre-defined acceptable level [5]. The scope and type of these actions should be based on the current status of the structure, on the trends identified in recent past, as well as on predictions of the type and rate of future deterioration.…”