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INNOVATION IN COMPUTATIONAL STRUCTURES TECHNOLOGY
Edited by: B.H.V. Topping, G. Montero, R. Montenegro
Life-Cycle Maintenance of Structures by Condition, Reliability and Cost Oriented Probabilistic Optimization
D.M. Frangopol* and L.C. Neves+
*Department of Civil and Environmental Engineering, Lehigh University, Bethlehem PA, United States of America
D.M. Frangopol, L.C. Neves, "Life-Cycle Maintenance of Structures by Condition, Reliability and Cost Oriented Probabilistic Optimization", in B.H.V. Topping, G. Montero, R. Montenegro, (Editors), "Innovation in Computational Structures Technology", Saxe-Coburg Publications, Stirlingshire, UK, Chapter 5, pp 95-110, 2006. doi:10.4203/csets.14.5
Keywords: condition, lifetime cost, maintenance, life cycle performance, bridges, probability, reliability, optimization.
The reduction in the need for new structures, as well as an increase in the number of deteriorated structures created the urgent need for more accurate tools to analyse and predict future deterioration of existing structures, in particular bridges. Currently, maintenance actions, applied during the entire lifetime of a structure, are seen as the most economical strategy to keep structures safe and serviceable. Considering the huge amount of existing bridges, it is of paramount importance to provide highway agencies with tools that allow a better management of the existing civil infrastructure, using the limited information available on each structure.
In this chapter, simple models are introduced for predicting future performance of existing structures. Considering the large amount of parameters influencing the deterioration of structures and the very limited information available on these parameters and their influence on the evolution of safety and serviceability of structures, the models are integrated in a probabilistic framework.
Performance of a bridge is herein defined in terms of the condition index, safety index and cumulative maintenance cost. The time evolution of these indicators is analysed considering the effects of deterioration, repair and replacement of components.
The first model described considers the condition index and safety index under no maintenance as a bi-linear function [1,2,3]. The effects of maintenance actions on condition and safety are defined as one, several, or all of the following effects: (a) increase in the condition index and/or safety index immediately after application; (b) suppression of the deterioration in the condition index and/or safety index during a time interval after application; and (c) reduction of the deterioration rate of the condition index and/or safety index during a time interval after application [3,4,5]
In order to find the optimal maintenance strategy, a multi-objective optimization tool, based on genetic algorithms (GA), is used.
The proposed methodology is applied to two examples, showing the advantages, in terms of safety, serviceability and cost, of a consistent and rational decision making in the maintenance of existing structures.
The results obtained show the importance of preventive maintenance in reducing the life-cycle cost of structures, but also the importance of essential maintenance action in keeping structures safe and serviceable. The use of multi-objective optimization gives the decision maker a set of optimal solutions from which the best, for each specific case, can be selected.
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