Towards a general damage law for interior micro-defect induced fatigue cracking in martensitic steels

Author(s):  
Gang Zhu ◽  
Ya-Chun Wu ◽  
Ming-Liang Zhu ◽  
Fu-Zhen Xuan
1998 ◽  
Vol 08 (PR8) ◽  
pp. Pr8-159-Pr8-166 ◽  
Author(s):  
S. Fouvry ◽  
Ph. Kapsa ◽  
F. Sidoroff ◽  
L. Vincent

2015 ◽  
Vol 105 (23) ◽  
pp. 1-8 ◽  
Author(s):  
Chun-sheng Wang ◽  
Chang-yang Ou ◽  
Mu-sai Zhai ◽  
Lan Duan

1997 ◽  
Vol 1594 (1) ◽  
pp. 163-171 ◽  
Author(s):  
John A. Van Lund ◽  
Mark R. Kaczinski ◽  
Robert J. Dexter

The Lacey V. Murrow Bridge (LVM Bridge) is a 2013-m-long floating bridge on Interstate 90 across Lake Washington in Seattle, Washington. Single-support-bar, swivel-joist modular bridge expansion joint systems are located at each end of the bridge between the shore approach spans and the floating pontoons. These joints were designed for 960 mm of longitudinal movement as well as horizontal and vertical rotations caused by wind, wave, temperature, and changes in lake level elevation. A similar joint in an adjacent floating bridge had experienced premature fatigue cracking at welded attachment details because of low fatigue strength. For the LVM Bridge the joint components were fatigue tested and designed by using fatigue limit-states loads, resulting in welded attachment details with improved fatigue strength. In addition, a stiffer center beam and reduced center-beam span lengths produced lower fatigue stress ranges. Joint movements and rotations, fatigue design methodology, results of dynamic analyses, field measurements of the dynamic response, and construction details are described. The total cost of the LVM joints was 1 percent of the final bridge cost. The Washington State Department of Transportation required a 5-year guarantee for the LVM joints. These are the largest modular bridge expansion joints in the United States to be tested and designed for fatigue.


2017 ◽  
Vol 1 (20) ◽  
pp. 63-74 ◽  
Author(s):  
Arkadiusz Rychlik ◽  
Krzysztof Ligier

This paper discusses the method used to identify the process involving fatigue cracking of samples on the basis of selected vibration signal characteristics. Acceleration of vibrations has been chosen as a diagnostic signal in the analysis of sample cross section. Signal characteristics in form of change in vibration amplitudes and corresponding changes in FFT spectrum have been indicated for the acceleration. The tests were performed on a designed setup, where destruction process was caused by the force of inertia of the sample. Based on the conducted tests, it was found that the demonstrated sample structure change identification method may be applied to identify the technical condition of the structure in the aspect of loss of its continuity and its properties (e.g.: mechanical and fatigue cracks). The vibration analysis results have been verified by penetration and visual methods, using a scanning electron microscope.


Author(s):  
Guang Zou ◽  
Kian Banisoleiman ◽  
Arturo González

A challenge in marine and offshore engineering is structural integrity management (SIM) of assets such as ships, offshore structures, mooring systems, etc. Due to harsh marine environments, fatigue cracking and corrosion present persistent threats to structural integrity. SIM for such assets is complicated because of a very large number of rewelded plates and joints, for which condition inspections and maintenance are difficult and expensive tasks. Marine SIM needs to take into account uncertainty in material properties, loading characteristics, fatigue models, detection capacities of inspection methods, etc. Optimising inspection and maintenance strategies under uncertainty is therefore vital for effective SIM and cost reductions. This paper proposes a value of information (VoI) computation and Bayesian decision optimisation (BDO) approach to optimal maintenance planning of typical fatigue-prone structural systems under uncertainty. It is shown that the approach can yield optimal maintenance strategies reliably in various maintenance decision making problems or contexts, which are characterized by different cost ratios. It is also shown that there are decision making contexts where inspection information doesn’t add value, and condition based maintenance (CBM) is not cost-effective. The CBM strategy is optimal only in the decision making contexts where VoI > 0. The proposed approach overcomes the limitation of CBM strategy and highlights the importance of VoI computation (to confirm VoI > 0) before adopting inspections and CBM.


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