Rock Mass Quality Research Articles

Stability Analysis of Tunnel Rock Mechanical Parameters Based on Multi-Source Sensor Data Fusion

In this paper, the sensor is applied to the collection of rock parameter data. Aiming at the classification and evaluation of stability (i.e. rock quality), an attribute recognition model for the classification and evaluation of surrounding rock quality of underground engineering is established. Using multi-source data fusion and orthogonal numerical simulation test methods, the effects of rock mechanics parameters on the horizontal convergence of the tunnel, the settlement of the vault and the plastic zone coefficient are studied. Six factors (elastic modulus, Poisson’s ratio, internal friction angle, tensile strength, cohesion and density) and three levels of orthogonal experimental solutions were selected. The method of defining similar weight by using similar number to determine the weight of evaluation index, so as to calculate the comprehensive attribute measure, and apply confidence criteria to identify the stability of rock samples. Through the analysis and evaluation of rock mass quality classification of underground engineering, the application of the model and the evaluation method of rock mass quality classification are explained. The test results match the orthogonal test results; Considering the stability of tunnel envelope, the horizontal convergence, vault settlement and plastic zone coefficient after excavation should be comprehensively considered.

A New CRITIC-GRA Model for Stope Dimension Optimization Considering Open Stoping Stability, Mining Capacity and Costs

In the long-hole stage open stoping with subsequent backfill mining of underground metal mines, the selection or optimization of stope dimension parameters is significant for safe and economic mining operations. To analyze the optimal stope sizes, the Mathews empirical graph method and FLAC3D numerical method can be used, but the analyzed safety results of the two methods are generally independent from each other. More importantly, economic indicators including production capacity and mining costs should be considered simultaneously to optimize the stope dimension which was mostly ignored in previous reports. In this paper, a new CRITIC-GRA model was proposed for the first time to build up a multi-factor quantitative optimization for stope dimension, which allows for a comprehensive analysis with preset influential safety and economic indicators. The indicators considered include the safety indicators such as stability probability for the side walls and roof of the open stope via the updated Mathews graph method, maximum displacement, plastic zones volume and maximum principal stress via FLAC3D simulations, as well as economic indicators such as mining costs and stope production capacity in mine operations. The model was then illustrated in an underground iron mine. With the given rockmass quality in the mine, the overall stability of the open stope can be improved instead of reduced to enlarge the single stage stope height (60 m) to a double stage height (120 m) by reducing the stope width from 20 m to 15 m, thereby significantly increasing the mineable ore amount and improving the stope safety. An integrated evaluation of open stope stability, mining capacity and costs objectively determined that scheme No. 10, with a slope length of 50 m, a width of 15 m and a height of 120 m, was the optimum out of the 20 preset schemes. The new CRITIC-GRA model offers a dependable reference tool for determining the optimal stope dimensions in similar underground mines.

The Influence of Geotechnical, Geological and Mining Factors on the Formation of Sinkholes at Lubambe Mine, Zambia

Mining-induced sinkholes are a common feature in underground mines. Sinkholes usually disrupt mining operations and associated infrastructure when they occur. This paper presents a case study of the Lubambe copper mine, where nine (9) sinkholes have been reported on the eastern and southern limbs. The development of sinkholes has resulted in increased mining costs due to the closure of the 182 mL decline on the eastern limb and the 175 mL truck route on the southern limb. This study establishes the influence that poor ground formation, rock stability, geological structures, and inappropriate mining practices have on the formation of surface sinkholes. Assessment of ground condition was done by core logging, and borehole analysis was conducted using GEM4D-BasRock software to classify the rock mass quality based on RQD, RMR, Q-System and GIS. Assessment of the mining operational environment was focused on the effects of varying stope designs and sequencing on ground stability. Results of the study indicate that the formation of surface-induced sinkholes is attributed to historical mining in weak rock formation and weathered rock coupled with subsequent failure of unsupported stopes with stope height between 8 and 25 metres and less stand-up time of 7 days.

Stability Challenges and Remedial Practices in Himalayan Hydro-power Tunnels – A Review

The instability in tunnels is mainly affected by geological anomalies, rock mass quality, complex geological structures, active tectonics, and stress anisotropy. This review article presents challenges associated with stability and applied remedial measures prevailing in hydropower tunnels in the Himalayas. The review covers nine hydropower tunnels located in different parts of the Himalayas. The review found that rock bursting/spalling frequently occurs when the tunnel passes through a high overburden with good rock mass quality. On the other hand, plastic deformation (squeezing) occurs when a tunnel passes through the weak and schistose rock mass. It has been found through the review that the tunnel crew was able to successfully solve instability challenges. Effective planning, design, and selection of appropriate construction techniques help to complete tunneling projects in the Himalayas.

Rapid profiling rock mass quality underneath tunnel face for Sichuan-Xizang Railway

The Sichuan-Xizang Railway is a global challenge, surpassing other known railway projects in terms of geological and topographical complexity. This paper presents an approach for rapidly profiling rock mass quality underneath tunnel face for the ongoing construction of the Sichuan-Xizang Railway. It adopts the time-series method and carries out the quantitative analysis of the rock mass quality using the depth-series measurement-while-drilling (MWD) data associated with drilling of blastholes. A tunnel face with 15 blastholes is examined for illustration. The results include identification of the boundary of homogeneous geomaterial by plotting the blasthole depth against the net drilling time, as well as quantification of rock mass quality through the recalculation of the new specific energy. The new specific energy profile is compared and highly consistent with laboratory test, manual logging and tunnel seismic prediction results. This consistency can enhance the blasthole pattern design and facilitate the dynamic determination of charge placement and amount. This paper highlights the importance of digital monitoring during blasthole drilling for rapidly profiling rock mass quality underneath and ahead of tunnel face. It upgrades the MWD technique for rapid profiling rock mass quality in drilling and blasting tunnels.

Determining the Relevance of Commonly Used Hydraulic Parameters for Representing the Water Erosive Force in Rock Mass Erosion within Dam Spillways

Spillways are essential control structures in hydroelectric dams for evacuating excess water during periods of high-water flow. These structures are generally excavated within a rock mass, without lining, and they take the form of a flow channel or a plunge pool. Rock mass erosion is an important issue facing engineers when designing unlined spillways. Methods commonly used to analyze this phenomenon are based on the threshold line concept, i.e., the correlation between rock mass resistance and its destruction against the erosive force of water. Multiple indices have been proposed for both rock mass quality and water energy (or erosive force) to assess rock mass erosion. The selection of appropriate indices is critical when evaluating hydraulic erosion. The erosive force of water is often represented by energy dissipation; however, other parameters, including average flow velocity and shear stress at the bottom of the flow channel, may also be relevant. Thus, a critical question is framed: which index best represents the erosive force of water? Here, we develop an approach to assess the applicability of the various indices used to represent the erosive force of water by relying on erosional events at more than 100 study sites. We determine that the most relevant parameters are linked to water pressure, as pressure head and flow velocity better explain the erosive force of the water than shear stress and water dissipation energy.

New Method to Estimate Rock Mass Deformation Modulus Based on BQ System

The rock mass deformation modulus is one of the most important design parameters in a range of rock engineering applications. Its value is usually obtained directly through in situ testing or estimated indirectly on the basis of a rock mass quality classification system. Because in situ testing is generally costly, time-consuming, and presents operational difficulties, it cannot be carried out extensively, and many researchers have concentrated on developing indirect procedures to obtain information on the modulus of deformation, such as the RMR method, Q method, and GSI method. The purpose of this paper is to present a new system for estimating the rock mass deformation modulus called the BQ method, which is based on the BQ (basic quality) system. In this paper, the BQ system is first briefly reviewed, and then more than 60 in situ measurements from three large hydropower stations in China are used to develop a new relationship between BQ and the deformation modulus, based on a power function relationship. The paper also derives correlations based on the existing estimation formula and the relationship between BQ and other classification schemes, resulting in several recommended formulas for estimating the deformation modulus of a rock mass using the BQ method.

ANALYSIS OF ROCK QUALITY AND LANDSLIDE POTENTIAL IN NORTH JERING HILLS, SLEMAN, YOGYAKARTA

The study was to identify the direction and type of potential landslides, as well as assess the rock quality on the slopes of North Jering Hills. The scanline method, consisting of stretching the meter, was employed to collect data on the plane of failure. The information gathered encompassed the direction, slope level, and condition of the unsuccessful plane, aligned with the parameters in the RMR table of Bieniawski from 1989. Following the collation of data, kinematic and rock mass quality analysis was undertaken using stereographic projection and RMR parameter weighting respectively. The kinematic analysis revealed a planar avalanche type on the slope. The RMR value of the research location's slope was 80, classifying it as good rock.

Data driven assessment of rock mass quality in red-bed hilly area: a case study of Guang’an city, SW China

The evaluation of geological suitability for urban underground space (UUS) development is an indispensable prerequisite for its optimal utilization. As the actual carrier of underground facilities, the evaluation of rock mass quality plays a crucial role in assessing geological suitability. However, it is notable that the evaluation of rock mass quality has regrettably remained somewhat marginalized within the broader framework of the geological suitability assessment in recent years. The selection of pertinent indicators for the evaluation of rock mass quality inherently presents an appreciable degree of subjectivity. Predominantly subjective evaluation methods continue to dominate the field, while the application of objective algorithms, such as unsupervised clustering, remains in its nascent stage. Furthermore, there is a lack of comprehensive investigations into distinct combinations of attributes. This limitation confines the broader applicability of the evaluation outcomes in the context of urban underground space. Within this study, we meticulously amassed rock core test data from over 40 boreholes of engineering geological significance within the urban planning ambit of Guang'An City. Utilizing the K-means unsupervised clustering algorithm and the Principal Component Analysis (PCA) algorithm. We successfully conducted an unsupervised clustering procedure with nine distinct physical and mechanical attributes. This yielded an aggregation into five discernible clusters. Building upon the derived clustering outcomes, a stratification of rock mass quality was effectuated into three distinct tiers: Level 1 (characterized by pure sandstone), Level 2 (primarily dominated by sandstone), and Level 3 (denoting fair conditions predominantly influenced by mudstone). This structured stratification facilitates a relatively objective and comprehensive evaluation of rock mass quality within the context of the red-bed hilly terrain. In the course of this analytical trajectory, we conducted a dissection of the clustering efficacy. For strongly correlated attributes, we propose a preliminary dimensionality reduction procedure prior to the clustering endeavor. Moreover, we recommend intervals of 10 m for the stratified evaluation in red bed hilly urban terrains.

Intelligent Algorithm for Rock Core RQD Based on Object Detection and Image Segmentation to Suppress Noise and Vibration

In the construction of the civil engineering infrastructure, the noise and vibration are affected by the geological conditions, adopting specific construction techniques based on the geological conditions is of great significance in suppressing the noise and vibration caused by the construction. To classify and evaluate the rock mass quality, the rock quality designation (RQD) is adopted widely in the geological and mining engineering. Traditionally, to obtain RQD, lengths of drilling core pieces are measured and RQD is calculated manually, which is labor-expensive and time-consuming. With the development of the computational power, the image treatment driven by the computer vision creates a potential approach to obtain RQD automatically. In the present work, the image treatment process with the aid of the object detection and the image segmentation is adopted to obtain RQD automatically, based on the similarity of features such as color and texture, the segment anything model is adopted to detect the rock cores in the image, then, the YOLOv8 algorithm is adopted to train the model, and the gap features of the rock chip segments are extracted for segmentation of different rock core segments. To test the performance of the proposed approach, 10 boreholes from Shapingba Railway Comprehensive Reconstruction Project are adopted to conduct the case study. Compared to the traditional manual approach, RQD obtained by the proposed approach is relatively accurate and obviously efficient, namely, the average error is less than 5% and the time consumed is less than 70%.

Enhancement Seismic Response of a Bored Tunnel Using Isolation for the Challenge of a Faulted Rock Crossing

The tunnel boring method (TBM) is a widely used and effective tunneling technology in various rock mass quality circumstances. A “faulted rock mass” can range from a highly fractured rock mass to a sheared weak rock mass, making the ground conditions challenging for tunneling, especially for TBMs. “Faulted rock” significantly affects hard rock TBMs, primarily due to the TBM’s high geological risk and poor flexibility. TBMs require careful planning and preparation, starting with preliminary assessments. This study investigates the impact of establishing an isolation material between a circular tunnel and the adjacent faulting rock on seismic response. The two parts of the parametric analysis for the isolation material utilized in the model look at how changes in the mechanical characteristics of the material, such as the shear modulus of the rock and the fault, affect the stresses created in the tunnel. The second section examines how changes in the isolation width concerning the fault width affect the stresses and displacements produced in the tunnel. Additionally, the effectiveness of isolating the tunnel during sudden changes in the characteristics of the rock was investigated under seismic loading perpendicular to the tunnel and parallel to the tunnel. The finite element approach was utilized to model the TBM tunnel and the neighboring rock with a fault or sudden change in the rock using Midas/GTS-NX, simulating the interactions between the rock and the tunnel. Time-history analysis using the El Centro earthquake was conducted to calculate the stresses in the tunnels during seismic events. Peak ground accelerations between 0.10 g and 0.30 g were utilized for excitation. A time step of 0.02 s and a length of 10 s for the seismic event were used in the analysis, with traditional grout pea gravel vs. the isolation layer. Comparisons were made between the absolute stresses (the greatest possible values) in the normal tunnel section (Sxx) and those induced in the tunnel with traditional grout and with isolation. Furthermore, the study of vertical displacement was taken into consideration. The seismic isolation method is highly effective in improving the seismic safety of bored tunnels. The results show that the significant values of the ratio between the shear modulus of isolation and the surrounding soil should be between 0.2% and 0.4%. Where parts of the tunnel run through a fault, the effective length of isolation should be between one and two times the fault width. The dynamic behavior of the tunnel with isolation is better than that with traditional grout. Generally, when isolation is used for any length, it reduces the stresses at the area of sudden change. Consequently, engineering assessments from both structural and geotechnical engineering viewpoints are now required for these unique constructions. An underground structure’s safety should be evaluated by the designer to ensure that it can sustain various applied loads, taking into account seismic loads in addition to construction and permanent static loads. Tunnels may be especially vulnerable in areas where the composition of the soil or rock varies.

Rock mass quality prediction on tunnel faces with incomplete multi-source dataset via tree-augmented naive Bayesian network

Rock mass quality serves as a vital index for predicting the stability and safety status of rock tunnel faces. In tunneling practice, the rock mass quality is often assessed via a combination of qualitative and quantitative parameters. However, due to the harsh on-site construction conditions, it is rather difficult to obtain some of the evaluation parameters which are essential for the rock mass quality prediction. In this study, a novel improved Swin Transformer is proposed to detect, segment, and quantify rock mass characteristic parameters such as water leakage, fractures, weak interlayers. The site experiment results demonstrate that the improved Swin Transformer achieves optimal segmentation results and achieving accuracies of 92%, 81%, and 86% for water leakage, fractures, and weak interlayers, respectively. A multi-source rock tunnel face characteristic (RTFC) dataset includes 11 parameters for predicting rock mass quality is established. Considering the limitations in predictive performance of incomplete evaluation parameters exist in this dataset, a novel tree-augmented naive Bayesian network (BN) is proposed to address the challenge of the incomplete dataset and achieved a prediction accuracy of 88%. In comparison with other commonly used Machine Learning models the proposed BN-based approach proved an improved performance on predicting the rock mass quality with the incomplete dataset. By utilizing the established BN, a further sensitivity analysis is conducted to quantitatively evaluate the importance of the various parameters, results indicate that the rock strength and fractures parameter exert the most significant influence on rock mass quality.

Developing two robust hybrid models for predicting tunnel deformation in squeezing prone grounds

The ground deformation under squeezing conditions has a considerable impact on the tunnel excavation process. In this study, we utilize a combination of particle swarm optimization (PSO) and the Entropy Weight Method (EWM) optimization algorithms to optimize the hyperparameters of Extreme Gradient Boosting (XGBoost) and Random Forest (RF) algorithms. This optimization process aims to accurately predict tunnel deformation in squeezing prone grounds, utilizing a dataset derived from 263 tunnel case histories. In the initial step, the database underwent processing utilizing the DBSCAN method to eliminate outlier data. Subsequently, XGBoost and RF algorithms were applied within the Python environment. The optimal hyperparameters for each model were then determined through two methods: PSO and EWM. The overburden depth (H), tunnel diameter (D), support stiffness (K), and rock mass quality index (Q) serve as inputs for the tunnel deformation estimation models. The performance evaluation of the developed models, based on 10-fold cross-validation, using three statistical indices (Normalized Root Mean Square Error/NRMSE, Coefficient of Determination/R2, and Variance Accounted For/VAF), shows that the proposed XGBoost-PSO model accurately predicts tunnel deformation with acceptable performance (R2 = 0.922, NRMSE = 0.344, and VAF = 91.675). Moreover, the results regarding the importance of the input parameters suggest that the rock mass quality index (Q) holds the most significant influence, while the tunnel diameter (D) exhibits the least impact on tunnel deformation in squeezing prone grounds. This study can be a reference for predicting tunnel deformation in the squeezing prone grounds, as well as estimating the severity of the squeezing phenomenon based on deformation. It aids in estimating project costs, selecting an appropriate support system, and determining the necessary methods to mitigate the risk of squeezing.

ASSESSMENT OF ROCK MASS QUALITY AND ROCKFALL POTENTIAL EVALUATION FOR RECLAMATION OF A QUARRY

In order to make an informed decision about implementing sustainable and efficient development during land reclamation in an area deemed geohazard-prone, thorough geological input is necessary. Quarry areas are vulnerable to slope failure and rockfalls, making it imperative to evaluate rock slopes for quarry reclamation. For this reason, researchers in Kinta Valley, Malaysia, set out to evaluate the slopes GG1, GG2, and GG3 at a defunct quarry. To evaluate the rock mass classification, the Rock Mass Rating (RMR) and Slope Mass Rating (SMR) systems were utilized, and the analyzing rock block's trajectory was using a rockfall analysis. The kinematic stability analysis was also performed to identify possible failure mechanisms. In order to assess the site's suitability for urban development, the rockfall scenarios were conducted. The SMR scaled from moderate to very good, while the RMR ranked the rock mass quality as good to very good. For all three of the slopes analyzed, the kinematic stability analysis pointed to the possibility of various failures (toppling, planar and wedge). According to the rockfall trajectory analysis, the rock block could roll as far as 5 metres from the base of the slope. For this reason, the study advised creating a buffer zone of 20 metres or more away from the rock slope as a means of protection against the geohazard of rockfall.

ANALYSIS OF LIMESTONE QUARRY SLOPE STABILITY, NIMBOKRANG DISTRICT, JAYAPURA REGENCY, PAPUA, INDONESIA

Slope stability analysis generally uses the concept of factor of safety (FoS) value using several whole rock parameters. The slope stability analysis method that will be used in this research is the slope stability analysis method in open pit mines based on rock mass classification with the Rock Mass Rating (RMR) system and the Geological Strength Index (GSI) system and analyses the potential for landslides that can occur on slopes at that location with kinematics and limit equilibrium methods so that the type of landslide can be determined based on the intensity of the geological structure on the slope of the CV. Inti Jaya open pit limestone mine, in Wahab Village, Nimbokrang District, Jayapura Regency. This research aims to provide information on the current condition of the slope whether it is by safety standards, make slope engineering improvements and redesign safe slopes if unstable slope conditions are found. Research on the stability of limestone slopes begins with the collection of field data and rock samples. Furthermore, sample testing was carried out to obtain physical and mechanical properties and weighting of rock masses, which were then analysed to obtain the characteristics and quality of rock masses that would be applied using the finite element method with Slide 6 from Rocscience to determine the Factor of Safety (FK) and the design of safe slope geometry. The RMR value for slope 1 is 62, slope 2 is 61, and slope 3 is 62. So it can be concluded that the rock is included in rock mass class 2 with good quality. Based on the analysis of potential avalanche types, the three slopes have non-arc avalanche types. From the analysis carried out using Rocscience Slide 6.0 software, the FoS value for slopes in original, dry, and saturated conditions is obtained, where on slope 1: FoS in original conditions is 0.935, FoS in dry conditions is 1.619, and FoS in saturated conditions is 0.671. Then slope 2: FoS in original condition is 0.896, FoS in dry condition is 1.457, and FoS in saturated condition is 0.806. Slope 3: FoS in original condition is 3.490, FoS in dry condition is 4.199, and FoS in saturated condition is 3.368. So it can be concluded that slopes 1 and 2 are unsafe or unstable in original and saturated conditions so that landslides can occur. In the analysis of the FoS value of the actual condition of the slopes in the field using the Hoek & Brown method, the FoS value of slope 1 is 0.387, the FoS value of slope 2 is 0.579, and the FoS value of slope 3 is 1.272, it can be seen that the actual condition of the slopes in the field is slopes 1 and 2 in an unsafe or unstable state. Improvements must be made to the slope geometry to maintain the stability of the slope to remain safe or stable. The recommended improvement is to create a new working level for slopes 1 and 2, with steep height and large rock porphyry.

Application of supervised random forest paradigms based on optimization and post-hoc explanation in underground stope stability prediction

This study applies a supervised random forest (SRF) paradigm to predict the underground stope stability. To improve the model prediction accuracy, 400 actual stopes with three main features (the optimized stability number (N), the hydraulic radius (HR), and a rock mass quality factor (Q)) are used to train the model, and nine meta-heuristic (MH) optimization algorithms are utilized to select the optimal hyperparameters of the SRF model. The prediction results show that the tiki taka algorithm-based SRF (TTA-SRF) model obtains the most satisfactory classification performance, with the smallest variance in the overfitting evaluation (Precision of 0.0201, Recall of 0.0257, Specificity of 0.0061, Accuracy of 0.0125, and F1-measure of 0.0246). Furthermore, four post-hoc explainable techniques (i.e., model-independent) including the feature importance (FI), the Shapley additive explanations (SHAP), the partial dependence plot (PDP), and the individual conditional expectation (ICE) are adopted to explain the best prediction model. The results of the model interpretation show that all features are essential for predicting the stope stability and they have an opposite tendency on the stability prediction of stable and caved stopes. In particular, the limits at which HR, Q, and N do not contribute to the stope stability prediction are 18 m, 40, and 100, respectively. The results of optimization designs for a specific case stope based on the visualization program showed that the suggestions given by the prediction model are desirable. In conclusion, a high-performance and strongly explanatory prediction model is proposed in this study to facilitate the refinement of stope stability assessment in underground space.

Rock mass permeability evolution during triaxial shearing based on three-dimensional distinct element model (3DEC) simulation

The evolution and change in jointed rock mass hydraulic conductivity (krm) during triaxial compression was investigated using the discrete element method code 3DEC bonded block model approach. The code’s fluid flow logic was used to simulate flow tests at various stages, from the initial confined state through to the post-peak (i.e., failed) state. A target percent of joint contacts were randomly “broken” to produce different initial fracture intensities. The rock mass fluid flow behaviour was compared with laboratory flow tests of thermally brecciated granular marble. A new joint constitutive model was developed to account for nonlinear, hysteretic load–displacement behaviour to accurately reproduce changes in joint aperture due to complex inter-block stress changes. The simulations provided quantifiable measurements of krm evolution with axial strain throughout the test for several rock mass quality conditions. The evolution of krm with loading was found to be nonlinear, with significant increases associated with yielding-induced dilation, followed by relatively minor changes in the post-peak loading range. These trends are similar to the laboratory tests conducted on intact rock and on rock joints. The findings will be useful for improving groundwater flow models for stability assessment of rock slopes, particularly where significant shearing is expected.

Geological Mapping and Stand-up Time Estimation based on Core Drilling Evaluation using Rock Mass Rating Method on The Main Spillway and Diversion Tunnel at Manikin Dam, Kupang Regency, Nusa Tenggara Timur

The Main Spillway and Diversion Tunnel at Manikin Dam is one of the dams under construction in the Kupang City area, where several soil or rock investigations have been carried out around it. However, the field investigations are not accompanied by a surface geological investigation or evaluation of subsurface geological conditions based on core drill results. Therefore, the purpose of this paper is to evaluate the engineering geological condition in tunnel construction by displaying surface and subsurface geological mapping with a scale of 1:10,000 and evaluate samples of core drilling using the Rock Mass Rating method in order to have more accurate stand-up time assumptions. The result of engineering geological mapping shows that the research area has three lithologies, namely a basalt unit, a carbonaceous sandstone unit, and a scaly claystone with a chaotic rock unit. The core-drill evaluation indicates that the research area is classified into three quality rock masses, namely Good Rock with an RMR Rating of 64, Fair Rock with an RMR Rating of 46, and Poor Rock with an RMR Rating of 36. The stand-up time value for each rock mass quality category is obtained from the quality rock mass results. The stand-up time value for the Good Rock category is 2200 hours, the Fair Rock category is 30 hours and the Poor Rock category is 1.2 - 1.7 hours. Based on the low stand-up time values in the Fair Rock and Poor Rock categories, it is expected that a support system will be installed immediately after tunnel excavation.

Geotechnical and slope stability analysis in the landslide-prone area: A case study in Sawla – Laska road sector, Southern Ethiopia

Examining the factors underlying landslides and assessing the stability of slopes is crucial for reducing the negative impact of landslides on the environment and the lifespan of infrastructure. This study assessed certain slope portions along the Sawla to Laska Road to determine the factors contributing to landslides and identify the mechanisms and conditions that lead to slope failure. Slope stability analysis was conducted using the limit equilibrium method, and a range of laboratory tests were conducted following ASTM standards. The analysis has shown that the three slope portions, specifically sections 1, 2, and 3, had distinct shear strength characteristics, as shown by variations in their cohesion and internal friction angle values. The average values for cohesion were 19.24, 10.41, and 12.9, respectively, while the internal friction angle values ranged from 11.32 to 17.8 for slope section three, 18.96 to 21.12 for slope section two, and 30.08 to 37.26 for slope section one. The limit equilibrium method was utilized to compute the safety factor of slopes. Five methods were employed to evaluate the safety factor: the ordinary method, Bishop method, Janbu method, Spencer method, and Morgenstern-Price method while considering three groundwater conditions (GWT at great depth, GWT at half of the slope, and GWT on the surface). Only slope section one exhibited a slightly stable safety factor that exceeded one under dry conditions. The slope-mass rating analysis showed that rock slopes one and two were deemed stable under class II, rock slopes three and four were partially stable under class III, and rock slope five was unstable under class IV. A slope mass range of 78 to 79 indicates excellent to very good rock mass quality and high stability potential for RSs1. In contrast, RSs5 shows a wide SMR range from 7 to 57, indicating a spectrum of very poor to fair to good quality rock mass and an associated range of stability from extremely low to moderate. RSs2 and RSs3 fall within the SMR range of 71.1–72 and 49.9–55.9, respectively, indicating good to fair rock mass quality with varying degrees of stability potential. Last, RSs4, with an SMR range of 39.6–45.1, shows poor rock mass quality and substantial stability concerns. RSs1 has a UCS of 28.68 MPa, indicating a "Medium strong" classification, and it belongs to the lithology type of "Trachyte." RSs2 showcases a higher UCS value of 32.25 MPa, similarly classified as "Medium strong," and is also identified as "Trachyte." RSs3, with a UCS of 28.83 MPa, falls under the "Medium strong" classification and is categorized as "Basalt." In contrast, RSs4 demonstrates a lower UCS of 18.41 MPa, leading to a "Weak" classification associated with the lithology type "Basalt." Lastly, RSs5 presents a UCS of 25.77 MPa, classified as "Medium strong," and shares the lithology type of "Basalt." The study identified that the landslide types in the study area were rockfall, earth flow, and soil/rock slides. The factors contributing to landslides in the study area were slope steepness, weathering, groundwater, and rainfall.

Recommendation of excavation method and support system based on engineering geology at Riam Kiwa Dam diversion tunnel, South Kalimantan, Indonesia

River flow diversion is one of the most critical factors that must be considered for the success of dam construction. Soil and rock can support and load; therefore, understanding their strength and properties before tunnel construction is essential. Tunnel excavation and support depend totally on rock mass quality. Surface geological mapping, drill core analysis, and laboratory testing characterized the engineering geology conditions. Rock Mass Rating (RMR) and Japan Society of Civil Engineers (JSCE) methods were compared to determine rock mass quality and recommend excavation and support systems. Results showed that slightly weathered andesite lava and tuff lapilli lithologies dominate the tunnel alignment. Based on RMR, the rock masses quality along the tunnel alignment consists of poor and fair, and based on JSCE, the tunnel alignment consists of D I and C II rock categories with L and M massive rock types. Top heading and bench are recommended for tunnel excavation based on RMR, and the double bench and full-face method with an auxiliary bench cut are recommended for tunnel excavation based on JSCE. Although the characteristics of other support systems vary marginally, support systems based on RMR and JSCE recommend rock bolts and shotcrete as the primary tunnel support systems.