Finite element analysis of the wear fatigue resistance of gradient structure layers with different yield strength distributions
Source abstract
Abstract
Finite element analysis (FEA) was performed to study the wear fatigue resistance of gradient structures (GSs) with different types of yield strength distributions under rolling-sliding contact. We found that the GS layer can reduce the plastic strain and surface deformation of the rail, which transfers a portion of the stress from the base layer to the gradient layer and thus enhances the wear fatigue resistance of the rail. The GS layer with a convex-shaped yield strength curve can most effectively reduce wear fatigue, followed by the GS layer with a linear-shaped yield strength curve, the GS layer with an inverse logistic-shaped yield strength curve, and the GS layer with a concave-shaped yield strength curve. The phenomenon of shakedown is also visible under repeated loading, and the GS rails step into stabilized states more easily than the original rail. The results show that the wear resistance of GSs can be improved by adjusting the yield strength curve through material processing methods or surface treatment methods, which can be used as a guideline for the wear fatigue-resistant design of heavy haul rail surfaces and other material processing methods and surface treatment methods.
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Research context
OpenAlex topics: Metal Alloys Wear and Properties · Mechanical stress and fatigue analysis · Tribology and Wear Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Civil Engineering, Southwest Jiaotong University 1 , Chengdu 610031, China
MOE Key Laboratory of High-speed Railway Engineering, Southwest Jiaotong University 2 , Chengdu 610031, China
National Engineering Laboratory for Technology of Geological Disaster Prevention in Land Transportation, Southwest Jiaotong University 3 , Chengdu, Sichuan 610031, China
China University of Geoscience (Beijing), School of Water Resources and Environment 4 , Beijing 100083, China
Funding
National Natural Science Foundation of China
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