期刊
ROCK MECHANICS AND ROCK ENGINEERING
卷 49, 期 4, 页码 1517-1532出版社
SPRINGER WIEN
DOI: 10.1007/s00603-015-0834-7
关键词
Punch penetration test; Tunnel boring machine (TBM); Performance prediction; Cutter force; Load indices
资金
- Ministry of Land, Transport and Maritime Affairs, Korea [10CCTI-E09]
Rock indentation tests are often called punch penetration tests and are known to be related to penetration rates of drilling equipment and hard rock tunnel boring machines (TBMs). Various indices determined from analysis of the force-penetration plot generated from indentation tests have been used to represent the drillability, boreability, and brittleness of rocks. However, no standard for the punch penetration test procedure or method for calculating the related indices has been suggested or adopted in the rock mechanics community. This paper introduces new indices based on the punch test to predict the performance of hard rock TBMs. A series of punch tests was performed on rock specimens representing six rock formations in Korea with different dimensions, i.e., the core specimens had different lengths and diameters. Of the indices obtained from the punch tests, the peak load index and mean load index showed good correlations with the cutting forces measured in full-scale linear cutting machine tests on the same rock types. The indices also showed good linear correlations with the ratio of uniaxial strength to Brazilian tensile strength, which indicates the brittleness of rock. The scale effect of using core specimens was investigated, and a preferred dimension for the punch test specimens is proposed. This paper also discusses the results of the punch test and full-scale rock cutting tests using LCM. The results of this study confirm that the proposed indices from the punch tests can be used to provide a reliable prediction of the cutting forces that act on a disc cutter. The estimated cutting forces can then be used for optimization of cutter-head design and performance prediction of hard rock TBMs.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据