Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/6211
Título: Probabilistic maintenance and optimization strategies for deteriorating civil infrastructures
Autor: Frangopol, D. M.
Neves, L. C.
Palavras-chave: Bridges
Existing structures
Genetic algorithms
Data: 1-Set-2004
Editora: Saxe-Coburg Publications
Relatório da Série N.º: Progress In Computational Structures Technology;
Resumo: In developed countries, civil infrastructures are one of the most significant investments of governments, corporations, and individuals. Among these, transportation infrastructures, including highways, bridges, airports, and ports, are of huge importance, both economical and social. Most developed countries have built a fairly complete network of highways to fit their needs. As a result, the required investment in building new highways has diminished during the last decade, and should be further reduced in the following years. On the other hand, significant structural deteriorations have been detected in transportation networks, and a huge investment is necessary to keep these infrastructures safe and serviceable. Due to the significant importance of bridges in the serviceability of highway networks, maintenance of these structures plays a major role. In this paper, recent progress in probabilistic maintenance and optimization strategies for deteriorating civil infrastructures with emphasis on bridges is summarized. A novel model including interaction between structural safety analysis,through the safety index, and visual inspections and non destructive tests, through the condition index, is presented. Single objective optimization techniques leading to maintenance strategies associated with minimum expected cumulative cost and acceptable levels of condition and safety are presented. Furthermore, multi-objective optimization is used to simultaneously consider several performance indicators such as safety, condition, and cumulative cost. Realistic examples of the application of some of these techniques and strategies are also presented.
URI: http://hdl.handle.net/10362/6211
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