清晨好,您是今天最早来到科研通的研友!由于当前在线用户较少,发布求助请尽量完整的填写文献信息,科研通机器人24小时在线,伴您科研之路漫漫前行!

A model for the prediction of tunnel boring machine performance

岩体分类 隧道掘进机 推力 脆性 岩土工程 地质学 岩石力学 工程类 结构工程 机械工程 材料科学 复合材料
作者
Saffet Yağız
链接
摘要

A key factor in the successful application of a Tunnel Boring Machine (TBM) in tunnelling is the ability to develop accurate penetration rate estimates for determining project schedule and costs. Rate of penetration (ROP), defined as the distance the machine advances in a given time in rock, is a complex process that not only depends upon intact and rock mass properties (strength, fractures, and texture of rock) but also machine specifications including thrust and torque requirement. The Earth Mechanics Institute (EMI) of the Colorado School of Mines (CSM) has developed a model to predict the performance of TBM in hard rock conditions. The model is primarily based on intact rock properties and machine specification. Although the model has proven reliable in massive rock conditions, its accuracy has been limited in brittle rocks exhibiting a high degree of fracturing. Therefore, this research was conducted to investigate the effect of rock mass fracture and brittleness on TBM performance. In order to accomplish the goal, extensive mapping of the tunnel was conducted to make a record of the joints and fractures along the 16-kilometer long Queens Water Tunnel in New York City. A large number of cores were taken from inside the tunnel where rock exhibited varying degrees of fracturing to conduct geomechanical tests including uniaxial compressive strength, tensile strength, and punch penetration tests. Additionally, the field TBM data from the tunnel was analysed in detail. Consequently, the data collected for the machine, rock properties and geology were then subjected to a multiple regression analysis together with the basic penetration rate derived from the existing model. As a result of this research, a new model was proposed for TBM performance prediction.

科研通智能强力驱动
Strongly Powered by AbleSci AI

祝大家在新的一年里科研腾飞
更新
大幅提高文件上传限制,最高150M (2024-4-1)

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
kkpinkman完成签到,获得积分20
18秒前
kkpinkman发布了新的文献求助20
23秒前
王波完成签到 ,获得积分10
1分钟前
xun完成签到,获得积分20
1分钟前
Omni发布了新的文献求助10
2分钟前
眠眠清完成签到 ,获得积分10
2分钟前
ljx完成签到 ,获得积分10
2分钟前
科研通AI2S应助科研通管家采纳,获得10
3分钟前
柏小霜完成签到 ,获得积分10
3分钟前
4分钟前
月亮完成签到,获得积分10
4分钟前
凯文完成签到 ,获得积分10
5分钟前
cc发布了新的文献求助100
5分钟前
田田完成签到 ,获得积分10
5分钟前
肆肆完成签到,获得积分10
6分钟前
feng完成签到 ,获得积分10
6分钟前
Dandraine发布了新的文献求助10
6分钟前
6分钟前
6分钟前
7分钟前
7分钟前
8分钟前
angen完成签到 ,获得积分10
8分钟前
TTK完成签到,获得积分10
8分钟前
TTK发布了新的文献求助20
8分钟前
小羊发布了新的文献求助10
8分钟前
LSH完成签到 ,获得积分10
8分钟前
Dandraine发布了新的文献求助10
9分钟前
9分钟前
可爱的函函应助小羊采纳,获得10
9分钟前
SciGPT应助Dandraine采纳,获得30
9分钟前
严冰蝶完成签到 ,获得积分10
9分钟前
9分钟前
守墓人完成签到 ,获得积分10
10分钟前
高高代珊完成签到 ,获得积分10
10分钟前
10分钟前
toyal发布了新的文献求助100
10分钟前
11分钟前
Dandraine发布了新的文献求助30
11分钟前
胡可完成签到 ,获得积分10
11分钟前
高分求助中
Востребованный временем 2500
诺贝尔奖与生命科学 1000
Aspects of Babylonian celestial divination: the lunar eclipse tablets of Enūma Anu Enlil 1000
Kidney Transplantation: Principles and Practice 1000
Separation and Purification of Oligochitosan Based on Precipitation with Bis(2-ethylhexyl) Phosphate Anion, Re-Dissolution, and Re-Precipitation as the Hydrochloride Salt 500
effects of intravenous lidocaine on postoperative pain and gastrointestinal function recovery following gastrointestinal surgery: a meta-analysis 400
The Collected Works of Jeremy Bentham: Rights, Representation, and Reform: Nonsense upon Stilts and Other Writings on the French Revolution 320
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 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 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3379190
求助须知:如何正确求助?哪些是违规求助? 2994678
关于积分的说明 8759980
捐赠科研通 2679262
什么是DOI,文献DOI怎么找? 1467584
科研通“疑难数据库(出版商)”最低求助积分说明 678733
邀请新用户注册赠送积分活动 670433