Investigation of stress-induced progressive failure of mine pillars using a Voronoi grain-based breakable block model

沃罗诺图 块(置换群论) 压力(语言学) 材料科学 计算机科学 数学 几何学 哲学 语言学
作者
Shili Qiu,Shirui Zhang,Quan Jiang,Shaojun Li,Hao Zhang,Qiankuan Wang
出处
期刊:International journal of mining science and technology [Elsevier]
卷期号:34 (5): 713-729 被引量:3
标识
DOI:10.1016/j.ijmst.2024.05.001
摘要

The Voronoi grain-based breakable block model (VGBBM) based on the combined finite-discrete element method (FDEM) was proposed to explicitly characterize the failure mechanism and predict the deformation behavior of hard-rock mine pillars. The influence of the microscopic parameters on the macroscopic mechanical behavior was investigated using laboratory-scale models. The field-scale pillar models (width-to-height, W/H=1, 2 and 3) were calibrated based on the empirically predicted stress-strain curves of Creighton mine pillars. The results indicated that as the W/H ratios increased, the VGBBM effectively predicted the transition from strain-softening to pseudo-ductile behavior in pillars, and explicitly captured the separated rock slabs and the V-shaped damage zones on both sides of pillars and conjugate shear bands in core zones of pillars. The volumetric strain field revealed significant compressional deformation in core zones of pillars. While the peak strains of W/H=1 and 2 pillars were relatively consistent, there were significant differences in the strain energy storage and release mechanism. W/H was the primary factor influencing the deformation and strain energy in the pillar core. The friction coefficient of the structural plane was also an important factor affecting the pillar strength and the weakest discontinuity angle. The fracture surface was controlled by the discontinuity angle and the friction coefficient. This study demonstrated the capability of the VGBBM in predicting the strengths and deformation behavior of hard-rock pillars in deep mine design.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
科研通AI5应助三月肖采纳,获得10
刚刚
Eve丶Paopaoxuan应助钟志成采纳,获得10
刚刚
1秒前
GK完成签到,获得积分10
1秒前
所所应助谢朝邦采纳,获得10
3秒前
xx完成签到,获得积分10
3秒前
3秒前
洪焕良发布了新的文献求助10
3秒前
txq应助wangchong888采纳,获得10
3秒前
kaka发布了新的文献求助10
4秒前
REN关闭了REN文献求助
6秒前
6秒前
arui发布了新的文献求助10
7秒前
慕青应助糊涂的雁易采纳,获得10
8秒前
8秒前
眯眯眼的雪莲完成签到 ,获得积分10
9秒前
洪焕良完成签到,获得积分10
10秒前
sunsun完成签到,获得积分20
10秒前
11秒前
荣荣酱完成签到,获得积分10
12秒前
12秒前
正直夜梅完成签到,获得积分10
12秒前
务实的数据线完成签到,获得积分10
13秒前
lang完成签到,获得积分10
13秒前
清风朗月完成签到,获得积分20
13秒前
liumangtu发布了新的文献求助10
13秒前
14秒前
鱼儿想游完成签到,获得积分10
14秒前
14秒前
14秒前
科目三应助MR_Z采纳,获得10
15秒前
sun完成签到,获得积分10
15秒前
脑洞疼应助xiaowang采纳,获得30
16秒前
saidosiuceyiwo完成签到 ,获得积分10
16秒前
17秒前
17秒前
med_wudi发布了新的文献求助10
17秒前
pny发布了新的文献求助10
18秒前
荣荣酱发布了新的文献求助10
18秒前
清风朗月发布了新的文献求助30
19秒前
高分求助中
Continuum thermodynamics and material modelling 3000
Production Logging: Theoretical and Interpretive Elements 2500
Healthcare Finance: Modern Financial Analysis for Accelerating Biomedical Innovation 2000
Applications of Emerging Nanomaterials and Nanotechnology 1111
Les Mantodea de Guyane Insecta, Polyneoptera 1000
Theory of Block Polymer Self-Assembly 750
지식생태학: 생태학, 죽은 지식을 깨우다 700
热门求助领域 (近24小时)
化学 医学 材料科学 生物 工程类 有机化学 生物化学 纳米技术 内科学 物理 化学工程 计算机科学 复合材料 基因 遗传学 物理化学 催化作用 细胞生物学 免疫学 电极
热门帖子
关注 科研通微信公众号,转发送积分 3473558
求助须知:如何正确求助?哪些是违规求助? 3066150
关于积分的说明 9097005
捐赠科研通 2757214
什么是DOI,文献DOI怎么找? 1512789
邀请新用户注册赠送积分活动 699097
科研通“疑难数据库(出版商)”最低求助积分说明 698829