A local response function approach for the stress investigation of a centenarian steel railway bridge. (1st July 2023)

• Record Type: Journal Article
• Authors: Menghini, Alessandro; Leander, John; Castiglioni, Carlo Andrea
• Is Part Of: Engineering structures. Volume 286(2023)
• Publication Date: 2023-07-01
• Subjects: Surrogate model -- Monitoring -- Bridge assessment -- Time-dependent damage -- Stress histories; 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.2023.116116
• Languages: English
• ISSNs: 0141-0296

Abstract

Abstract: Local stress concentrations in some specific geometric details often play an essential role in time-dependent damage propagation. However, measured strain or stress data are generally available in locations that are not the most critical ones. Proper numerical models are thus required to aid the damage severity assessment. In this paper, a surrogate model procedure based on the local response function method is proposed to accurately predict stress time histories in particular regions of bridges through a multiscale numerical analysis. The methodology is calibrated on the basis of direct strain measurements on a railway bridge in Vänersborg, Sweden. The bridge is currently monitored with a set of strain gauges, accelerometers, and an inclinometer allowing the investigation of its in-service conditions during the train passages and the lifting of the bascule truss. The results show the reliability of the method for stress prediction in specific regions of the bridge without the availability of directly measured data together with more detailed knowledge about the stress histories that could lead to fatigue or corrosion damage. Highlights: A surrogate models procedure based on local response function method is presented. The proposed approach is based on advanced multiscale numerical analysis. Stress history estimations are used for fatigue cycle counting procedures. Reliable stress history predictions are obtained at some damaged locations.