Condition Prediction of Existing Concrete Bridges as a Combination of Visual Inspection and Analytical Models of Deterioration

Abstract

In most state-of-the-art Bridge Management Systems, structural condition is predicted by a homogeneous Markov chain model that uses condition ratings assigned during visual inspections. Although generally accepted, such an approach exhibits certain shortcomings, one of which is not considering the nature of actual physical phenomena that cause deterioration. To overcome this shortcoming, this article presents a framework that combines both information on condition ratings through the semi-Markov process and knowledge of bridge properties using analytical deterioration models. In this manner, and contrary to current practice, not only are the results of visual inspection taken into account, but also information such as environmental loading, as well as material and structural properties. The presented framework was implemented in the case study bridge, in which the deterioration caused by carbonation-induced corrosion was studied. Along with the implementation in the case study, the article contained a detailed overview of the subject of carbonation-induced corrosion and emphasized issues that require additional research in order to develop the framework into a comprehensive and fully applicable tool for condition prediction. Accounting for its adaptability to other material types and deterioration processes and its consideration of the historic deterioration path, the framework presents a suitable alternative to frameworks presently implemented for condition prediction.

Value of Information (VoI) for the Chloride Content in Reinforced Concrete Bridges

“…Thus, the parameter identification and the process of obtaining prior probabilities of depassivation, P dep , were in this paper based on a general case. For quantification and a detailed description of parameters of the employed model, see [1][2][3]10,11,[39][40][41]. Furthermore, for a detailed insight into how the chosen parameters influence the outcome of the used model, see [42].…”

“…When observing developed countries, the main reasons for that can be traced to the boom in the building and reconstruction of infrastructure after the Second World War, as well as in the enhancement of concrete technology in the 20th century. Although, when compared with other building materials, concrete is deemed as a durable material, nonetheless, evidence of its ageing can be found in infrastructure all over the world [1,2].…”

Comparative analysis of some bridge management systems

“…Najšire su problemi u vezi s BMS-om razmatrani u Priručniku [2], i u poglavljima posvećenim deterioraciji, istraživanjima, nadgledanju i proceni. Od značaja je predviđanje stanja postojećih mostova, kao i formiranje modela deterioracije mosta, što je predmet radova [10], [24] i [25]; razvoj BMS-a, zasnovanog na modeliranju informacija o građevini, analiziran je u [26].…”

“…The problems related to BMS are most extensively considered in the Manual [2], with chapters devoted to deterioration, investigation, monitoring and assessment. In addition, the condition prediction of existing bridges is important, as well as forming the bridge deterioration model, which is the subject matter of 13], [24] and [25].…”

Data mining algorithms for bridge health monitoring: Kohonen clustering and LSTM prediction approaches

“…In order to ensure the safety and durability of bridges, the research and evaluation system for bridge health monitoring has been developed in the twentieth century and has made extensive achievements [6][7][8]. The UK first developed a long-term health monitoring devices and data acquisition processing system in the early 1980s [9].…”