Laboratory-Scale Limestone Rock Linear Cutting Tests with a Conical Pick: Predicting Optimal Cutting Conditions from Tool Forces
Han-eol Kim, Sung-Pil Hwang, Wan-Kyu Yoo, Wooseok Kim, Chang-Yong Kim, Hankyu Yoo
Korea Institute of Civil Engineering and Building Technology Hanyang University
阅读操作
确认中在文库中上传 PDF 后可生成中文音频讲解。
摘要与影响
This study introduces a simplified method for predicting the optimal cutting conditions to maximize excavation efficiency based on tool forces. A laboratory-scale linear rock-cutting test was conducted using a conical pick on Finike limestone. The tool forces and their ratios were analyzed in relation to cutting parameters such as penetration depth and spacing. While the cutting force (FC) and normal force (FN) increased with the penetration depth and spacing, this relationship could not predict the optimal cutting conditions. The ratio of the mean normal force to the mean cutting force (FNm/FCm) increased with the penetration depth and the ratio of spacing to penetration depth (s/d). However, even while including this relationship, predicting optimal cutting conditions remained challenging. The ratio of the peak cutting force to the mean cutting force (FCp/FCm) reached a maximum value at a specific s/d, which is similar to the relationship between the specific energy (SE) and s/d. The optimal s/d obtained through the SE methodology was found to be between 3 and 5, and FCp/FCm reached a maximum at s/d. The error between the optimal s/d and the s/d in which FCp/FCm was maximized was less than 5%. Therefore, it was confirmed that the optimal cutting conditions could be predicted through the relationship between FCp/FCm and s/d. Additionally, by using the results from previous studies, the optimal cutting conditions obtained from the SE methodology and the proposed methodology were found to agree within a margin of error of 20%. The proposed methodology can be beneficial for the design of cutter heads and the operation of excavation machines.
逐年被引趋势
关键指标
同类平均 = 1
同领域 · 同年份 · 同类型
Google Scholar 与 OpenAlex 的被引统计范围不同,数值存在差异属正常。
AI 辅助阅读
依据:摘要
可就本文提问;依据不足时会说明。
学术脉络
学科主题
工程Tunneling and Rock Mechanics
Soil Mechanics and Vehicle Dynamics · Rock Mechanics and Modeling
参考文献 44
此处列出前 3 条
引用本文 2
按被引量排序,此处列出前 3 条