Budapest University of Technology and EconomicsFaculty of Civil Engineering - Since 1782

Due to recent expansion of traffic infrastructure all around the world the bridge structures are increasing in number, size and life span as well. There is a conforming increasing preoccupation regarding the monitoring and maintenance of such structures. In this sense the demand for automated structural health monitoring (SHM) systems and damage identification techniques is high. The use of such systems efficiently improves the maintenance process, helps to predict necessary structural repair or strengthening, and to avoid a catastrophic collapse.  

The aim of the research is to study the up-to-date smart health monitoring and structural damage detection techniques, and based on these, to develop a method that can be used for the health monitoring and damage detection of reinforced concrete box girder bridge superstructures. Typical deteriorations of such bridges under normal environmental and traffic conditions may include excessive deformations and relocations of structural members, opening of cracks, corrosion of reinforcement and damage of bridge accessories like dilatation joints or bearings. Among these damages, the monitoring and detection of excessive deformations, cracks and reinforcement corrosion, as well as their effect on structural performance will be mainly addressed in the research.

The candidate must solve the following tasks:

Literature review: (i) typical deterioration of reinforced concrete box girder bridge structures; (ii) application of smart health monitoring method for bridges, including determination of sensor types and locations to be applied for typical box girder bridges; (iii) up-to-date methods for data processing and damage identification in case of reinforced concrete bridges, including the use of artificial intelligence and machine learning methods; (iv) applicability of the results of SHM and damage identification process for the design of strengthening strategies in case of reinforced concrete structures.

Theoretical adaptation and deployment of health monitoring and damage identification methods appropriate for given conditions, in case of an existing concrete box girder bridge: (i) development and verification of a numerical model for the selected bridge structure, using an appropriate FE software suitable for the consideration of internal steel reinforcement; (ii) numerical simulation of different environmental (temperature, humidity) and traffic conditions; (iii) selection of sensor types for the measurement of parameters, such as deformation, crack width and reinforcement corrosion; (iv) based on the peak values of internal forces and deformations obtained by static numerical analysis, critical zones inside the examined structure must be identified for the determination of the best possible sensor installment locations; (v) proposal of a suitable damage identification method for the examined structure that is using information from the recommended sensor system and static response of the structure obtained by the numerical simulation; (vi) numerical analysis of structural damages in accordance with randomly generated series of sensor data and the proposed damage identification method.

Evaluation of the results of numerical simulation, determination and sensitivity analysis of the main process parameters, definition of a suitable damage criteria for the examined structure. Determination of limit values for the data measured by different sensor types, which may be used by an appropriate warning system in the future.