Project Details
Projekt
Measurement-based condition assessment of prestressed concrete bridges with low shear reinforcement ratios under fatigue loading for service life prediction on a digital twin
Subject Area
Structural Engineering, Building Informatics and Construction Operation
Term
since 2022
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 501771082
Existing prestressed concrete bridges were often designed for a combination of shear, torsion, and flexural loading based on principal stress criteria and have high prestressing levels but only small amounts of reinforcement. If the assessment by recalculation or bridge inspection reveals deficiencies, preventive measures such as the reduction in bridge class, strengthening for temporary limited use, or taking the structure out of service are taken. From own preliminary work on shear behavior and shear fatigue, it is known that such structures usually have considerable reserves even after the appearance of fatigue-induced macro-cracking. Fiber optic strain measurement is a suitable tool for long-term monitoring. In addition, constitutive models to predict the fatigue life of concrete and reinforcement are available. However, today, neither the quantification nor exploitation of the identified reserves for extended service life is possible. Methods are lacking for systematically processing the measured data, their aggregation with preliminary information, central provision in a digital representation, and systematic linking with physical prediction models, which would allow us to assess the remaining service life duration.The objectives of this project are therefore (a) the identification and monitoring of the strain and degradation state due to micro- and macro-cracking in bridge structures made of reinforced and prestressed concrete under combined shear, torsion, and flexural loading, (b) the interpretation and linking of the time-variant state information with an extended BIM model to provide a digital twin of the structure, which finally (c) provides input for physical models that give a measurement-based prediction of the remaining service life. By means of developing innovative measurement, evaluation, and prognosis methods and allocating them to the digital twin, highly condensed information about the bridge condition is provided. This enables predictive, intelligent building management, which can be applied to significantly extend the usable service life of the structure. In order to achieve the research objectives, a coordinated work program of harmonized experimental and theoretical investigation methods is proposed: (WP 1) development of measurement concept, (WP 2) evaluation methodology on the digital twin, (WP 3) data aggregation and implementation in residual service life prediction model, (WP 4) experimental calibration and validation.The work of this proposal is assigned to the research area of "Digital Linkage". Generating a geometric building model is not part of this research. Based on the findings during the first funding period, the concept of service life prediction will be extended in the second period by advanced physical models. In addition, the developed methodology will be verified and validated by means of measurements on demonstrator structure.
DFG Programme
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