Journal
JOURNAL OF BRIDGE ENGINEERING
Volume 17, Issue 1, Pages 58-70Publisher
ASCE-AMER SOC CIVIL ENGINEERS
DOI: 10.1061/(ASCE)BE.1943-5592.0000225
Keywords
Fatigue life; Cracking; Stress; Monitoring; Probability; Steel bridges; Fatigue life; Bilinear S-N; Crack growth; Equivalent stress range; Reliability assessment; Long-term monitoring; Probability
Categories
Funding
- National Science Foundation [CMS-0639428]
- Commonwealth of Pennsylvania, Department of Community and Economic Development through the Pennsylvania Infrastructure Technology Alliance (PITA)
- U.S. Federal Highway Administration [DTFH61-07-H-00040]
- U.S. Office of Naval Research [N-00014-08-0188]
Ask authors/readers for more resources
This paper focuses on estimating the fatigue life below the constant amplitude fatigue threshold (CAFT) of steel bridges by using a probabilistic approach on the basis of a bilinear stress life (i.e., the S-N approach). The current AASHTO S-N approach uses a single S-N line for predicting the fatigue life. However, because of the variation of actual applied live-load stress cycles, this approach very often results in a severe underestimation of the useful life of structures. It implies that fatigue damage in respective structural steel details may be overestimated. To improve fatigue life estimation, a bilinear S-N approach is integrated into a probabilistic framework that can model the uncertainties associated with the fatigue deterioration process. In this approach, the equivalent stress range is computed by using two S-N slopes and several probability density functions associated with stress ranges. These probabilistic functions are determined on the basis of stress-range bin histograms from long-term monitoring. An existing bridge that is expected to experience finite fatigue life is used to illustrate the application of the proposed approach. DOI: 10.1061/(ASCE)BE.1943-5592.0000225. (C) 2012 American Society of Civil Engineers.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available