Investigation on Fatigue Crack Propagation Behaviour of U71Mn and U75V Rails Using Peridynamics

Xiaochuan Ma,Yajie Wang,Xianghe Wang,Weibin Yin,Linya Liu,Jingmang Xu

ENGINEERING FRACTURE MECHANICS（2023）

East China Jiaotong Univ | Southwest Jiaotong Univ

Cited 13|Views25

Abstract

Fatigue crack propagation in rails is an important factor that increases the cost of railway maintenance and threatens operating safety. Research into fatigue crack propagation rules for different rail materials helps to provide scientific guidance for rail selection and maintenance plans. Based on the results of fatigue crack propagation tests on U71Mn and U75V rails, the bond fatigue fracture criterion was established for the two materials, and their accuracy was verified. Using ordinary state-based peridynamic theory, a model was established to analyse the process of crack propagation in the two types of rails. The behaviour of U71Mn and U75V rails was then simulated with different wheel loads and wheel-rail friction coefficients, and the characteristics and rules for fatigue crack propagation in the two types of rails were analysed in a comparative manner. The results showed that the material type exerted little impact on the crack propagation path within the rails and that the U71Mn rail, which showed a lower crack propagation rate than the U75V rail, is more suitable for high-speed railways. The rate of crack propagation increased with both wheel load and wheel-rail friction coefficient. Certain measures, such as track regularity improvement, could be employed to reduce dynamic wheel-rail impact, while others, such as lubrication, could be adopted to decrease wheel-rail friction coefficients to prolong rail service life.

Translated text

Key words

Fatigue crack,Rail materials,Propagation rate,Propagation path,Peridynamics

求助PDF

上传PDF

Bibtex

AI Read Science

AI Summary

AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.

Example

Background

Key content

Introduction

Methods

Results

Related work

Fund

Key content

Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

Upload PDF to Generate Summary

Must-Reading Tree

Example

Generate MRT to find the research sequence of this paper