John Leander

Reliability-Based Calibration of Fatigue Safety Factors for Existing Steel Bridges

Abstract This paper investigates the fatigue assessment of existing steel bridges. Measurements can be used to reduce uncertainties in the structural behavior and the effects of action. However, the treatment of the measured response is not clearly defined in today’s codes of practice. A reliability model is suggested that treats the uncertainties for bilinear fatigue endurance and the uncertainties in the measured response. A parametric study on the modeling of the load effect is performed and shows a significant influence on the reliability. The reliability model is used for calibration of the partial safety factors in a deterministic design equation. The suggested partial safety factors enable practical use of measured stresses in the fatigue assessment of existing steel bridges. A numerical example shows the merit of the proposed model and partial safety factors as an increase in fatigue life.

Quality Assurance of Measured Response Intended for Fatigue Life Prediction

By in situ measurements, the real distribution of stress ranges caused by service loads can be recorded. Inherent effects in the measured response as disturbance can, however, create puzzles in the interpretation of the result. In large monitoring campaigns, it is not possible to examine the result from every gauge over the whole measured period by visual control. An approach for a quality assurance of the measured response is presented here based on established statistical methods. The stress range spectra, the product of the monitoring program intended for fatigue assessment, are analyzed. The aim is to find deviant spectra and identify corrupt gauges. An additional aspect is the length of the monitoring period, which is the required duration for obtaining a stable result. A case study of a monitored Swedish steel railway bridge is incorporated to exemplify the approaches. Some statistical distributions for the monitored stress ranges are also presented and incorporated in a fatigue assessment.

Extending the fatigue service life of a railway bridge by local approaches

In this paper, fatigue assessment of a steel railway bridge is presented. The bridge is located in central Stockholm, Sweden, and is one of the most vital links for the railway network. The bridge ...

A New Approach to Damage Detection in Bridges Using Machine Learning

At the same time that civil engineering structures are increasing in number, size and longevity, there is a conforming increasing preoccupation regarding the monitoring and maintenance of such structures. In this sense the demand for new reliable Structural Health Monitoring systems and damage detection techniques is high. A model-free damage detection approach based on Machine Learning is presented in this paper. The method performs on the collected feature measurements on a railway bridge, which for this study were gathered in a numerical experiment using a three dimensional finite element model. The first step of the approach consists in collecting the dynamic response of the structure, simulated during the passage of a train over the bridge, in both the healthy and damage states of the structure. The next step consists in the design and unsupervised training of Artificial Neural Networks that use as input accelerations and axle loads and compute a novelty index, called prediction error, based on a novelty detection approach. The distribution of the obtained prediction errors is statistically evaluated by means of a Gaussian Process and, after this process, damage indexes can be defined. Finally, the efficiency of the method is assessed in terms of Type I (false positive) and Type II (false negative) errors using Receiver Operating Characteristic curves. The promising results obtained in the case study demonstrate the capability of the presented method.

Enhanced Assessment of the Remaining Service Life of a Steel Railway Bridge

During annual inspections of one of Sweden’s most important railway bridges, the Söderström Bridge in central Stockholm, cracks in the web of the main steel beams have been discovered. Extensive theoretical work has been undertaken to assess the remaining service life of the bridge. Furthermore, the bridge has recently been instrumented to enhance the theoretical predictions by monitoring the real railway traffic as well as the response of the bridge. This article describes the monitoring program and the analysis methods used. Some interesting results regarding the remaining fatigue life are presented.