Tunnel and Underground SpaceISSN:1225-1275(Print) 2287-1748(Online)한국암반공학회

Ongoing interest in deep geological repositories for high-level radioactive waste has led to the widespread implementation of in-situ tracer tests across various underground research facilities worldwide, targeting spatial scales ranging from centimeters to hundreds of meters. These tests have played a crucial role in identifying key parameters that influence the transport and retardation of radioactive nuclides in fractured rocks. Serving as essential empirical data, in-situ tracer tests contribute to the quantitative understanding of solute transport mechanisms in rock media and support the long-term safety assessment of disposal systems. The primary observable output of these tests is the concentration breakthrough curve, which provides insights into the transport and retention behavior of radionuclides. However, isolating and distinguishing the characteristic time-scales of transport and retardation solely from breakthrough curves remains a significant challenge due to the inherent complexity and uncertainty of numerical inversion. In particular, there remains an ongoing debate regarding the practical validity of in-situ tracer tests for evaluating large-scale and long-term radionuclide migration in fractured rock environments, and the methodological frameworks required for their interpretation. In this study, we present a comprehensive review of in-situ tracer test design and implementation cases, primarily conducted in domestic and international underground research laboratories, in the context of developing deep geological disposal concepts for high-level radioactive waste. Key information from in-situ tracer tests conducted in different countries was systematically reviewed, including site characteristics, test objectives, borehole configurations, types and injection amounts of tracers, and injection and pumping rates. This review aimed to identify the critical factors governing the design, execution, and interpretation of field tracer tests. The results are expected to contribute to improving the understanding and technical preparedness required for planning and conducting tracer tests during the detailed site investigation stage of future repository site selection in Korea.

This study was conducted to evaluate changes in rock cutting characteristics of a pick cutter under dry and saturated conditions. Linear cutting tests were performed on Macheon granite in Korea. The tests were conducted under dry and saturated conditions by varying the depth of cut and the spacing-to-depth of cut ratio (s/d), and the cutting force, specific energy, and fragment size distribution were analyzed. The results showed a general trend of increasing cutting and normal forces with depth of cut and s/d for all conditions. The acting forces and specific energy measured under saturated conditions were consistently lower than those under dry conditions. These findings indicated that even for low-porosity granite, rock cutting characteristics can change significantly with limited water infiltration. The fragment size distribution also exhibited clear differences between dry and saturated conditions, indicating a relative shift toward coarser fragments under saturated conditions.

In constant stress-rate testing, the statistical variability of the subcritical crack growth index (n) is governed by four parameters: the expected index n, the number of specimens per stress rate (N), the stress-rate layout coefficient (C_R), and the Weibull modulus (m). While previous studies have relied on Monte Carlo simulations to characterize this variability, a practical analytical solution for pre-test design has been lacking. This study employs the propagation-of-error method to derive an analytical expression for the coefficient of variation, CV(n), which is subsequently inverted to propose a minimum-specimen-number estimation formula. The proposed analytical model was validated against bootstrap resampling (1,000 iterations) using experimental data from Coconino sandstone grooved-disc specimens (N = 40 per stress rate, m = 9.07, n = 37.0). While the estimation formula slightly underestimates the bootstrap results at N = 10, it yields conservative and safe-side estimates for N ≥ 13. According to the derived estimation formula, achieving a target CV(n) ≤ 30% under the standard ASTM C1368 three-decade stress-rate range requires at least 13 specimens per stress rate for Coconino sandstone, compared to the 10-specimen minimum established for ceramics with higher Weibull moduli. Bootstrap analysis further indicates that the distribution of n is strongly right-skewed at small sample sizes but approaches normality as N increases. Furthermore, a subset analysis of the four experimental stress rates (0.01, 0.1, 1, and 10 MPa/s) demonstrates that when the full four-rate protocol is impractical, utilizing only the extremum rates (0.01 and 10 MPa/s) retains 90% of the layout coefficient. This alternative yields a minimal n-estimate bias of +1.5% and attains a comparable level of precision by using 15 specimens per stress rate to meet the CV ≤ 30% criterion. Conversely, relying solely on adjacent stress rates introduces severe estimation biases (up to 108% in the present dataset) and must be avoided. While theoretically applicable to any brittle material conforming to a Weibull distribution, the empirical validation of the proposed estimation formula is currently limited to Coconino sandstone.

The stability of underground structures is highly dependent on the uncertainty of in-situ rock mass properties, making reliable back analysis based on monitored responses essential. However, conventional back-analysis methods often encounter difficulties in high-dimensional problems involving the simultaneous estimation of multiple parameters, including excessive computational cost and premature convergence to local optima. To address these limitations, this study proposes a multi-parameter back-analysis method using Sparse Axis-Aligned Bayesian Optimization (SAASBO). The proposed approach estimates multiple rock mass properties simultaneously by minimizing the discrepancy between monitored responses and numerical analysis results. In the case of inverse analysis with nine parameters, SAASBO showed the fastest convergence and the lowest estimation error among the compared optimization methods, and it provided the best reproduction of the target responses. The results demonstrate that SAASBO can efficiently identify influential variables in a high-dimensional parameter space and achieve stable and accurate parameter estimation with a limited number of numerical evaluations. Therefore, the proposed method can be considered an effective and practical framework for multi-parameter back analysis in deep rock engineering applications.

Recent demand for deep underground space development has increased the importance of understanding mechanical excavation mechanisms that reflect the confining stress conditions of deep rock masses. Although the roadheader is a representative excavation machine capable of free-face excavation, studies on the cutting characteristics of its primary cutting tool, the pick cutter, under confining stress conditions remain limited. In particular, previous studies have mainly focused on TBM disc cutters, making direct application to pick cutters difficult because of differences in cutting principles and rock fragmentation mechanisms. In this study, linear cutting tests were conducted using a roadheader pick cutter under confining stress conditions to investigate cutting characteristics according to confining pressure (0, 5, and 15 MPa) and penetration depth (3, 5, and 7 mm). Average and peak normal and cutting forces, force ratios, and specific energy were analyzed. In addition, sieve analysis of the generated chips was performed to obtain cumulative passing curves and to determine the uniformity coefficient (Cu) and coefficient of curvature (Cc), thereby evaluating particle size distribution characteristics. The results experimentally present the cutting and fragmentation characteristics of roadheader pick cutters under confining stress conditions and provide fundamental data for the design and operational optimization of mechanical excavation methods and for improving performance prediction models for roadheaders in deep underground construction.