• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.5
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• pp.395-409
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• 2022

To overcome the limitation of conventional rock excavation methods, the excavation with abrasive waterjet has been actively developed. The abrasive waterjet excavation method has the effect of reducing blasting vibration and enhancing the excavation efficiency by forming a continuous free surface on the rock. However, the waterjet cutting performance varies with rock fracturing characteristics. Thus, it is necessary to analyze the cutting performance for various rocks in order to effectively utilize the waterjet excavation. In this study, cutting experiments with the high pressure waterjet system were performed for basalt and granite specimens. Water pressure, standoff distance, and traverse speed were determined as effective parameters for the abrasive waterjet cutting. The cutting depth and width of basalt specimens were analyzed to compare with granite results. The averaged cutting depth of basalt was shown in 41% deeper than granite; in addition, the averaged cutting width of basalt was formed by 18.5% narrower than granite. The results of this study are expected to be useful basic data for applying rock excavation site with low strength and high porosity such as basalt.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.5
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• pp.357-371
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• 2023

In cable tunnel construction using TBM, the vertical shaft is an essential structure for entrance and exit of TBM equipment and power lines. Since a shaft penetrates the ground vertically, it often encounters rock mass. Blasting or rock splitting methods, which are mainly used to the rock excavation, cause public complaints due to the noise, vibration and road occupation. Therefore, mechanical excavation using vertical shaft excavation machine are considered as an alternative to the conventional methods. However, at the current level of technology, the vertical excavation machine has limitation in its performance when applied for high strength rock with a compressive strength of more than 120 MPa. In this study, the potential utilization of waterjet technology as an excavation assistance method was investigated to improve mechanical excavation performance in the hard rock formations. Rock cutting experiments were conducted to verify the cutting performance of the abrasive waterjet. Based on the experimental result, it was found that ensuring excavation performance with respect to changing in ground conditions can be achieved by adjusting waterjet parameters such as standoff distance, traverse speed and water pressure. In addition, based on the relationship between excavation performance, uniaxial compressive strength and RQD, it was suggested that excavation performance could be improved by artificially creating joints using the abrasive waterjet. It is expected that these research results can be utilized as fundamental data for the introduction of vertical shaft excavation machines in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.562-569
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• 2019

Raman spectroscopy has been receiving increased attention as a standoff explosive detection technique. In addition, there is a growing need for a fast search method that can identify raman spectrum for measured chemical substances compared to known raman spectra in large database. By far the most simple and widely used method is to calculate and compare the Euclidean distance between the given spectrum and the spectra in a database. But it is non-trivial problem because of the inherent high dimensionality of the data. One of the most serious problems is the high computational complexity of searching for the closet spectra. To overcome this problem, we presented the MPS Sort with Sorted Variance+PDS method for the fast algorithm to search for the closet spectra in the last paper. the proposed algorithm uses two significant features of a vector, mean values and variance, to reject many unlikely spectra and save a great deal of computation time. In this paper, we present two new methods for the fast algorithm to search for the closet spectra. the PCA+PDS algorithm reduces the amount of computation by reducing the dimension of the data through PCA transformation with the same result as the distance calculation using the whole data. the Hierarchical Cluster Tree algorithm makes a binary hierarchical tree using PCA transformed spectra data. then it start searching from the clusters closest to the input spectrum and do not calculate many spectra that can not be candidates, which save a great deal of computation time. As the Experiment results, PCA+PDS shows about 60.06% performance improvement for the MPS Sort with Sorted Variance+PDS. also, Hierarchical Tree shows about 17.74% performance improvement for the PCA+PDS. The results obtained confirm the effectiveness of the proposed algorithm.