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严颖,赵春发,李勇俊,季顺迎.铁路道砟破碎特性的离散元分析[J].计算力学学报,2017,34(5):615~622
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铁路道砟破碎特性的离散元分析
Discrete element analysis of breakage characteristics of railway ballast
投稿时间:2016-07-25  修订日期:2016-09-17
DOI:10.7511/jslx201705013
中文关键词:  离散元方法  铁路道砟  破碎特性  统计分析
英文关键词:discrete element method  railway ballast  breakage characteristics  probability analysis
基金项目:国家自然科学基金(U1234209,11572067)资助项目.
作者单位E-mail
严颖 大连交通大学 土木与安全工程学院, 大连 116028  
赵春发 西南交通大学 牵引动力国家重点实验室, 成都 610031  
李勇俊 大连理工大学 工业装备结构分析国家重点实验室, 大连 116024  
季顺迎 大连理工大学 工业装备结构分析国家重点实验室, 大连 116024 jisy@dlut.edu.cn 
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中文摘要:
      为降低有砟铁路轨道维护成本并提高乘客舒适度,对铁路道砟材料破碎机理深入研究具有重要作用。本文设计并开展了测量铁路道砟材料特征强度的试验,对道砟受压破碎过程的力和位移等数据加以分析;同时,通过三维激光扫描系统获取道砟三角网格多面体边界,依此采用颗粒平行粘结方式构造具有不规则真实外观的铁路道砟,并采用离散单元方法(DEM)数值模拟道砟径向加载破碎过程,分析应力应变曲线和粘结断裂数等数据以分析颗粒破碎机制。通过对多个道砟颗粒加载试验及数值模拟计算发现,随着道砟尺寸的增加,其有效压缩强度逐渐减小。道砟颗粒的有效压缩强度符合威布尔概率分布函数,并确定了其残存概率的平均强度和威布尔参量,试验和数值模拟结果相吻合。
英文摘要:
      It is necessary to investigate the breakage characteristics of railway ballast to reduce the maintenance cost and to improve the travelling comfort of trains running on ballasted railway track.In this study,the mechanical test method was developed to measure the effective compressive strength of ballast particles.During the physical experiment,the force and the displacement of ballast samples were recorded.Meanwhile,the ballast particles were constructed with triangle-surface based on the layer scanning method in three dimensions.The irregular ballast particles were randomly filled with poly-dispersed spheres using parallel-bonding method.The breakage of ballast under compression was simulated with discrete element method (DEM) to determine the effective compressive strength.From the physical experiments and the DEM simulations,we found that the effective compressive strength decreases with the increase of effective diameter of ballast.The effective compressive strength of ballast satisfies the Weibull probability distribution.The parameters in the Weibull survival probability were determined.The simulated results with DEM were compared well with the experimental data.
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