Inverse analysis of masonry arch bridges for damaged condition investigation: Application on Kakodiki bridge. (15th November 2016)

• Record Type: Journal Article
• Authors: Conde, B.; Drosopoulos, G.A.; Stavroulakis, G.E.; Riveiro, B.; Stavroulaki, M.E.
• Is Part Of: Engineering structures. Volume 127(2016:Nov. 15)
• Page Start: 388
• Page End: 401
• Publication Date: 2016-11-15
• Subjects: Masonry arch bridges -- Inverse analysis -- Optimization -- Genetic algorithm -- Unilateral contact-friction; Structural engineering -- Periodicals; Structural analysis (Engineering) -- Periodicals; Construction, Technique de la -- Périodiques; Génie parasismique -- Périodiques; Pression du vent -- Périodiques; Earthquake engineering; Structural engineering; Wind-pressure; Periodicals; 624.105
• DOI: 10.1016/j.engstruct.2016.08.060
• Languages: English
• ISSNs: 0141-0296

Abstract

Highlights: An inverse analysis procedure for the investigation of pathological problems on masonry arch bridges. Damage identification is transformed into a parameter identification problem. A global optimization approach using a genetic algorithm is adopted within the inverse problem. The method is tested in a real case study located in Kakodiki village, on the island of Crete (Greece). Abstract: In this paper a novel approach for the investigation of pathological problems in masonry arch bridges using inverse analysis procedures is proposed. A real case study located in Kakodiki village on the island of Crete (Greece) is considered for the application of the proposed computational scheme. The method uses the damaged condition of the bridge as starting point and seeks the potential load cases that led to its development. The damage identification is transformed into a parameter identification problem which is studied by comparing numerical predictions and existing damage pattern. A global optimization approach by means of a genetic algorithm is adopted within the inverse problem, aiming at adjusting the parameters of the mechanical model of the structure so that an error function that measures the differences between the real and the numerically predicted damage pattern is minimized. The outcome of the methodology might provide a valuable information regarding to the planning of maintenance actions as well as to the design of retrofitting measures.