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Mean Stress Effect in High-Frequency Mechanical Impact (HFMI)-Treated Steel Road Bridges

Author(s): ORCID
ORCID

Medium: journal article
Language(s): English
Published in: Buildings, , n. 5, v. 12
Page(s): 545
DOI: 10.3390/buildings12050545
Abstract:

High-frequency mechanical impact (HFMI) is a post-weld treatment method which substantially enhances the fatigue strength of steel weldments. As such, the method enables a more efficient design of bridges, where fatigue is often the governing limit state. Road bridges are typically trafficked by a large variety of lorries which generate load cycles with varying mean stresses and stress ranges. Unlike conventional welded details, the fatigue strength of HFMI-treated welds is known to be dependent on mean stress in addition to the stress range. The possibility of considering the mean stress effect via Eurocode’s fatigue load models (FLM3 and FLM4) was investigated in this paper. Moreover, a design method to take the mean stress effect into account was proposed by the authors in a previous work. However, the proposed design method was calibrated using limited traffic measurements in Sweden, and as such, may not be representative of the Swedish or European traffic. In this paper, larger data pools consisting of more than 873,000 and 446,000 lorries from Sweden and the Netherlands, respectively, were used to examine the validity of previous calibration in both countries. The comparison revealed no significant difference between the data pools with regards to the mean stress effect. Additionally, previous calibration provided the most conservative mean stress effect and was considered adequately representative for both countries. The proposed design method was further validated using four composite case study bridges. It was also found that the mean stress effect was mainly influenced by the self-weight, while variation in the mean stress due to traffic had a minor influence on the total mean stress effect. Furthermore, it was found that the mean stress effect could not be accurately or conservatively predicted using FLM3 or FLM4.

Copyright: © 2022 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10664344
  • Published on:
    09/05/2022
  • Last updated on:
    01/06/2022
 
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