Rock Mass Rating Research Articles

Analysis of Slope Failure Using Finite Element Method: A Case Study of the Dehradun Region, India

ABSTRACT Slope destabilization in urbanizing areas, particularly along road-cut hill slopes, poses significant risks to infrastructure and human safety. This study focuses on assessing the stability of slopes in the Siwalik range, a region prone to landslides due to its geological characteristics. Utilizing numerical modeling techniques, specifically the Finite Element Method (FEM) and the Shear Strength Reduction (SSR) technique, we evaluated the stability of various locations along a dilapidated road in Dehradun District, India. The analysis incorporates local geological conditions, including joint abundance and rock mass properties, to determine factors such as total displacement, shear strain, and strength reduction factors (SRF) of the slopes. Our findings reveal a distinct, albeit subtle relationship between SRF and the slope mass rating (SMR). Locations with SRF < 2.35 and ‘Partially stable’ classification were identified as having higher risks of failure compared to those location with SRF > 2.35 and ‘Stable’ classification. Nearly half of the studied slopes are partially stable. Among them, those with relatively low SRF of ≤ 1.52 (four in number or ~25% of all studied slopes) may be poised for failure in the long run. One of the slopes that failed subsequent to the completion of our site study was classified as ‘Partially Stable’ with ‘Fair’ rock (rock mass rating [RMR] classification) and had a SRF of 1.13 (i.e., < 2.35), thus validating our predictions. Moreover, locations classified as ‘Stable’ have substantially higher joint normal stiffness compared to those classified as ‘Partially Stable’. The study underscores the importance of continuous monitoring and proper slope management to mitigate the risk of landslides in this region.

Geomechanical classification of the downstream section of the Ighrem Aousser Deposit with determination of optimal spacing for mine workings

Purpose. The paper seeks to classify the downstream rock mass of the Ighrem Aousser (I/A) mine and examines its fractu-ring in order to determine the optimal distance between mine workings. Methods. The study starts with a geo-mechanical classification of the rock mass using widely recognized methods: Rock Quality Designation (RQD), Rock Mass Rating (RMR), Q-Barton, Geological Strength Index (GSI), and Rock Mass Index (RMI). Fracturing surveys were then carried out to identify the primary fracture families using DIPS software. Finally, PHASE 2 software was employed to determine the optimal distance between galleries. Findings. This study presents a comprehensive geological and geomechanical analysis of the Ighrem Aousser (I/A) mine, including field observations, core drilling, and structural analysis using DIPS software. The rock mass was found to be highly fractured and altered, particularly within the mineralized zones. Laboratory tests show a UCS of 58.79 MPa for flysh, and RQD values are 66.2 for flysh and 48.5 for mineralized zones. The RMR ranges from 28 to 45, and Barton’s Q-values vary from 0.8 to 3.7, indicating poor to fair rock quality. Numerical modeling suggests an optimal distance of 16 to 17 meters between vein drifts and main mine workings for improved stability and safety as the mine deepens. Originality. This study offers a comprehensive classification and structural analysis of the downstream I/A rock mass to propose the optimal distance between the vein drifts (GF) and the main mine workings (VM). This integrated approach not only enhances the understanding of rock mass behavior but also ensures improved safety, stability, and productivity in mining operations, establishing a new benchmark for sustainable mining development. Practical implications. In the mining industry, classifying rock masses, designing excavation supports, and determining the optimal distance between galleries improve safety, boost site productivity by reducing contamination, and lower mining costs.

Relationship between petrography and geomechanical properties of the sandstone: A case study from Wadi Halfa, North Sudan

Abstract The investigation of the effect of petrography and diagenetic features on the geomechanical properties of the sandstone and their relationship to rock failure are of vital importance for different construction projects. The present study involves analyzing multi-vertical lithofacies profiles around the region of Wadi Halfa, North Sudan. The sandstone is dominantly composed of monocrystalline quartz grains (60%) accompanied by some polycrystalline quartz, feldspars, lithic fragments, micas, and heavy minerals. Iron oxides are the main type of cementing materials (14%), with some (2%) of carbonates and clay minerals. The average porosity of all studied samples is 12%. The compressive strength ranges widely, influenced by weathering, grain size, cementing materials, and bedding planes. The uniaxial compressive strength is more influenced by wetting when the load is parallel to bedding planes. Sandstone anisotropy is suggested by a U-shaped curve, with lower values at 45° and higher values at 90° and 0°. The geomechanical behavior of rocks masses in Wadi Halfa was evaluated through a combination of field and laboratory analyses which revealed a variable Rock Mass Rating (RMR) ranging from 58 to 92 and a Geological Strength Index (GSI) ranging from 33 to 61.

Geological Strength Index quantitative estimation of flysch rock masses from on-field geomechanical data based on AI tools

This work proposes a quantitative estimation of the Geological Strength Index (GSI) in flysch rock masses based on data gathered from geomechanical stations, i.e. Rock Quality Designation (RQD), and spacing, persistence, aperture and roughness of the discontinuities. Artificial Intelligence (AI) techniques are explored as a tool to set such estimation. Particularly, Artificial Neural Networks (ANN) and Support Vector Machine (SVM) techniques are used, and a total of 40200 AI models are developed, investigating the optimum value of different hyperparameters. Data for training and testing such models comes from an intensive geological-geotechnical investigation conducted on 33 flysch outcrops of Late Cretaceous of age in a 100 km2 area belonging to the Basque Arc in northern Spain. This formation consists of a thick package of more than 700 m of interbedded marls and marly limestones, changing to quartz-rich clastic turbidites towards the top of the succession. The results show that the AI techniques can satisfactorily estimate the GSI of flysch rock masses from the characterization of their discontinuities. ANN show to yield better performance than SVM, and the best ANN models provide a superior performance to estimate the GSI than existing expressions based on the Rock Mass Rating (RMR). These ANN models reach very high values of R2 (very close to 1), and low values of the RMSE, being therefore suitable for their use by practitioners.

Excavation methods and support system stability analysis for the Pasir Kopo Dam Diversion Tunnel in Banten, Indonesia

Abstract As part of the Pasir Kopo Dam construction, a twin-tunnel diversion system with an outer diameter of 6.4 meters was designed to facilitate water drainage. The tunnel excavation, utilizing top heading and benching methods, was planned in 2018 by BBWS C3 in collaboration with PT Mettana. The support system, comprising steel ribs, rock bolts, and shotcrete, was selected based on the Rock Mass Rating (RMR) classification. The stability of the tunnel was evaluated using the Finite Element Method (FEM) with Rockscience software, incorporating the Geological Strength Index (GSI) along the tunnel’s trajectory. This analysis aimed to determine the safety factor and deformation of the support system, following the guidelines established by the Japan Society of Civil Engineers (JSCE). Two excavation methods were implemented: the full-face method for sections STA 0–132.9 and STA 312.9–412.9 and the top-and-bench method for STA 132.9–312.9. The support system included 4-meter-long rock bolts installed at 1.2–2 meters intervals, 10–15 cm thick shotcrete, and H-150 steel ribs specifically used in the STA 219.9–312.9 section. The stability analysis of the tunnel support system, conducted post-dewatering, revealed a safety factor (SF) ranging from 6.43 to 11.81 (>1.5) under static conditions and from 5.32 to 10.95 (>1.1) under dynamic conditions, confirming the design’s adequacy.

Rock Mass Classification in TBM Tunneling using Artificial Neural Network Techniques: A Case Study from Siwalik Region of Nepal

The Himalayan region exhibits a highly complex geological setting influenced by tectonic activities, resulting in faulted, folded, sheared, and deeply weathered rock mass. Accurate rock mass characterization is crucial for Tunnel Boring Machine (TBM) tunneling projects, particularly in the challenging geological conditions of the Nepal Himalayas. Empirical rock mass classification systems, such as the Rock Mass Rating (RMR) and Q-system, often fall short in TBM operations due to limited access to the tunnel face and the dynamic nature of TBM excavation. To address these challenges, this research employs machine learning (ML) technique to classify rock mass conditions using operational and geological data collected from the Sunkoshi Marin Diversion Multipurpose (SMDM) project in Nepal where a double-shield TBM was used to excavate the headrace tunnel. A comprehensive dataset comprising 3,173 TBM cycles, including parameters such as cutter head speed, torque, thrust, and penetration rates, were utilized for model development. An Artificial Neural Network (ANN) model was developed, trained, and optimized using grid search to identify the best hyperparameters. The Synthetic Minority Oversampling Technique (SMOTE) was applied to address the class imbalance, which significantly improved the model’s recall for Class V (poor rock mass class). Performance metrics such as accuracy, precision, recall, and F1-score were used to evaluate the model. Additionally, SHAP (Shapley Additive Explanations) analysis was conducted to interpret feature contributions for rock mass Class V, which revealed that torque and thrust had the highest influence on predicting poor rock mass conditions. This study highlights the effectiveness of ML models in improving rock mass classification, especially for underrepresented classes, and provides valuable insights for optimizing TBM operations in complex geological settings.

Stability Analysis of a TBM Excavated tunnel at a Critical Section between Main Boundary Thrust and Mahabharat Thrust using RS2 and RS3

This article demonstrates a detailed stability analysis of a tunnel excavated by a Tunnel Boring Machine (TBM) at a critical section between the Main Boundary Thrust (MBT) and Mahabharat Thrust (MT), a case study of Sunkoshi Marine Diversion Multipurpose Project (SMDMP) where double shield TBM was deployed to excavate the tunnel. The geological complexity in this area, including weak rock masses, poses severe challenges to TBM operations. We use the RS2 (2D) and RS3 (3D) numerical modeling software to assess the deformation, squeezing potential, and stress distribution at critical chainage, 4+669m. Rock mass classification based on the Rock Mass Rating (RMR) system was used to determine the quality of the surrounding rock and different empirical methods were applied to estimate rock mass strength and deformability. The results indicate significant deformation at chainage 4+669m, leading to TBM jamming as the installed thrust capacity of the machine was insufficient to overcome the shield friction.

Advancing overbreak prediction in drilling and blasting tunnel using MVO, SSA and HHO-based SVM models with interpretability analysis

Overbreak prediction in drilling and blasting tunnel construction remains a significant challenge due to the complexity and variability of influencing factors. Existing models, including empirical, statistical, and machine learning approaches, often fall short in terms of generalizability and accuracy. Empirical methods lack universal applicability due to their reliance on specific project conditions, while statistical models struggle with inconsistent patterns across different datasets. Furthermore, traditional AI models, including single machine learning algorithms, often overlook the multifaceted nature of overbreak, and hybrid models lack comprehensive evaluation standards. To address these limitations, this research proposes three innovative hybrid models that integrate metaheuristic optimization algorithms with support vector machine (SVM): multi-verse optimizer-SVM (MVO-SVM), salp swarm algorithm-SVM (SSA-SVM), and Harris’s Hawk optimization-SVM (HHO-SVM). These models optimize SVM hyperparameters, enhancing its ability to handle high-dimensional, non-linear data with robustness to outliers and improving the prediction of overbreak. The study’s motivation stems from the need for more accurate and universally applicable overbreak prediction models that can also explain the relationship between input parameters and overbreak outcomes. By incorporating SHapley Additive explanations (SHAP) and local interpretable model-agnostic explanations (LIME), the research introduces interpretability to enhance model transparency. The results show that rock mass rating and hole depth are the most crucial factors influencing overbreak predictions. Compared to previous models, the proposed hybrid models demonstrate significant improvements, with the HHO-SVM model showing superior predictive performance across various metrics. This study lays the groundwork for more reliable overbreak predictions and offers a powerful tool for geotechnical engineers.

Evaluating the RMR correlation with the rock mass wave velocity using the meta-heuristics algorithms

Determining the rock mass rating (RMR) plays a key role in designing rock engineering projects. Direct determination of the RMR involves the measurement of six parameters which is a destructive, expensive and time-consuming task. Hence, non-destructive determination of the RMR based on the easy and inexpensive measurable parameters can be an attractive and economic process. In this study, relationships of the RMR with shear wave velocity (Vs) and compression wave velocity (Vp) of the rock mass are evaluated using genetic algorithm (GA), trust region reflective (TRR), and hybrid TRR-GA model. This study involves the analysis of 150 in-situ datasets related to the rock mass with diverse rock types. Random forest (RF) analysis confirmed that the simultaneous combination of both Vp and Vs parameters is more reliable for RMR determination than when each of Vp and Vs is considered individually. Deep estimation capability analyses of the proposed GA, TRR and GA-TRR models were performed using the performance evaluation metrics, scatter plots, error histogram, Taylor diagram and regression error characteristic curve. Results indicated that all suggested models provide high accuracy in predicting RMR. However, the hybrid TRR-GA model emerging as the best model in predicting RMR based on the Vp and Vs. The diversity of examined rock types, utilizing the cost-effective and easily measurable input variables, and the application of non-destructive robust meta-heuristic algorithms for RMR determination are the main innovations of this study. However, further studies involving more datasets and diverse rock types are required for more validation and practical application of these findings.

Anisotropic Deformation Mechanism in the Twin-Tube Tunnel Sections: Empirical Insight from Multi-Point Displacement Monitoring

This study evaluates the stability of a twin-tube tunnel through a combined approach of rock mass classification, numerical modeling, and real-time deformation monitoring. The rock mass along the tunnel alignment was characterized using the Rock Mass Rating (RMR) system, incorporating physical, geological, and geotechnical data from the project site. Support systems were designed for each geotechnical unit based on RMR and the Q-system support chart. Field monitoring was conducted over one year using a Leica TS09 tachometer and 3D displacement monitoring targets installed at the top heading and invert/bench, with data processed via Amberg Tunnel 2.0 software. Complementing the field measurements, 2D numerical analyses were performed to assess the left portal slope stability (Slide 6.0 software) and provisional support behavior (Phase2 2D program). The numerical results were validated against in-situ monitoring data, demonstrating strong agreement. The study confirms effective rock mass deformation control and satisfactory confinement stability, highlighting the reliability of the integrated methodology for tunnel stability assessment.

Tunnel Face Mapping for Evaluate Support System Design of the Inlet Area at the Budong-Budong Dam Diversion Tunnel, West Sulawesi, Indonesia

Abstract A comprehensive advanced engineering geology investigation is essential for the construction of a tunnel. During the construction stage, tunnel face mapping is strongly suggested to observe and identify geological conditions that have not been recorded directly by the borehole data. Tunnel face mapping is conducted to identify changes or variations in geological engineering conditions prior to excavation. The Budong-Budong Dam diversion tunnel was excavated using an excavation method and a selection support system based on the Rock Mass Rating (RMR) classification determined in the design stage. However, the geology of tunnel construction poses unique challenges, primarily as it is located in volcanic rock and steep slope topography with a high potential for landslides and rock failures. This research aims to provide an evaluation of the tunnel excavation method and support system based on tunnel face mapping in the inlet side of tunnel. The two empirical methods used are Rock Mass Rating (RMR) and Q-System classifications. The results show that the inlet tunnel consists of tuffaceous sandstone and tuffaceous siltstone. According to RMR, the rock mass quality along the inlet tunnel side consists of a fair rock mass class with RMR values ranging from 42 to 53. According to Q-System, the inlet side of the tunnel is dominated by poor rock mass quality. The tunnel excavation method using top heading and bench excavation with 1.5 - 3 meters advance in heading is recommended based on RMR. The tunnel requires a combination of rock bolts and shotcrete represents the optimal support system for the inlet tunneling area. In order to mitigate risk and ensure the safety of the tunnel, it is recommended a numerical analysis to verify the empirical design.

Engineering Geology Characterization for Alternative-2 Feasibility Plan of Bodri Dam Diversion Tunnel in Kendal, Central Java

Abstract Understanding site characteristics is essential to prevent failures especially in tunnel construction planning. Bodri Dam with the diversion tunnel has feasibly planned by River Basin Organization for Pemali Juana of Ministry of Public Works and Housing in 2018 and produced two alternatives of site plan. However, the detailed analysis for rock mass quality around the diversion tunnel site plan has never carried out. This paper aims to identify the characteristics of the tunnel site plan area through engineering geology, including morphological and lithological unit, geological structure, and geomechanics, which are rock mass characterization using Rock Mass Rating (RMR) and Geological Strength Index (GSI). The results from geological mapping indicated that the Bodri Dam diversion tunnel site plan alternative-2 has two primary lithologies, namely andesite breccia unit and tuffaceous sandstone unit. This tunnel plan is projected in rock mass with rating Very poor (RMR=20), poor (29≤GSI≤36), fair (42≤GSI≤43), based on Rock Mass Rating method (Bieniawski, 1989). The rock mass is classified very poor (GSI=10.5), poor (30≤GSI≤35.5), fair (46.61≤GSI≤54.05), and good (GSI=58.9) based on Geological Strength Index method (Hoek et al., 2013). The rock mass quality characterization will determine the excavation method and support system for the Bodri Dam diversion tunnel.

Engineering Geological Study to Determine Excavation Methods and Support Systems in Alternative Planning Construction of The Bodri Diversion Tunnel, Kendal District, Central Java Province

Abstract Based on The feasibility study report 2018 from Organization River Basin of Pemali Juana did not explain the excavation method and support system to be used in the Bodri diversion tunnel. Based on this, this research examines the appropriate excavation methods and support systems to use based on the engineering geological characteristics that exist in the area around the Bodri diversion tunnel alignment. The results of this research can provide input excavation methods and tunnel support systems for planning the construction of the Bodri bypass tunnel on alternative route 1. The research method used in this research is to carry out technical geological mapping in the area around the alternative Bodri diversion tunnel alignment for primary data collection. Secondary data collection was carried out on drilling results from planning consultants at Organization River Basin of Pemali Juana. Determining the excavation method based on the excavability graph (Pettifer and Fokes, 1994) shows that the dominant excavation methods are easy digging and hard digging. Determining another excavation method to be used is based on the Rock Mass Rating (Bienawski, 1989), which shows that the appropriate excavation method results are by making a top heading and bench and installing supports along with excavation 10 m from the face of the excavation. Determination of the buffer system is divided into 3 areas, namely inlet, middle and outlet. The tunnel inlet outlet and middle require supports, namely shortcrete, rock bolts, wire mesh, steel sets, and fiber reinforced sprayed concrete.

Assessment of geotechnical considerations for ground control and stability in the synclinorium area at Nkana mine of Zambia

Abstract Nkana Synclinorium is in the southern part of the Nkana mining license area. The orebody structure of the mine is characterized by complex folding, with anticlines and synclines. Due to increase in mine depth, mining operations have been encountering geotechnical challenges related to ground control and ground stability. The mine has witnessed an increase in fall of ground accidents in the last 5 to 9 years. This study assesses the ground control mechanisms, support standards and evaluates the design, installation and quality control of rock support in order to establish adherence to ground control and stability requirement at the mine. A number of factors were examined: historical and current geotechnical data; geological structures; pillar support and reinforcement requirements and excavation design practices. The study applied borehole logging to obtain geotechnical data, scanline mapping for geological structures, numerical modeling and empirical methods in the assessment of pillar design. Results of the study indicate that geological structures are major contributors to rock instability around underground excavations at the Synclinorium mine. Using the rock mass rating system, it is indicated that rock types of sedimentary nature, like Shale are associated with most of the ground instability at the Synclinorium mine.

Investigating the role of geological strength index and susceptible zones in landslide triggering mechanisms from Chukyatan-Kumrat road, Dir Upper, Pakistan

This study presents a comprehensive investigation of landslide susceptibility along the 83.5-km Chukyatan-Kumrat road, Upper Dir, North Pakistan. Despite its critical role in transportation and tourism, the region faces recurrent landslides due to hydrometeorological hazards, posing significant threats to stability. Employing a multidisciplinary approach, this study integrates the geological strength index (GSI) calculated from joint analysis of bedrock and landslide susceptibility index (LSI) analysis to understand the complex interactions underlying landslide occurrences. The study area contains a variety of rock formations, including metavolcanic, andesite, metarhyolite, igneous rocks, volcanic limestones, granodiorites, and spotted slates, which are overlain by remnant soils. Utilizing the landslide susceptibility index (LSI) map developed via the frequency ratio technique, regions proximal to road cuts, fault lines, and mineralogically altered and sheared lithology are identified as highly susceptible to future sliding events. GSI and rock mass rating (RMR) analyses categorized jointed bed rocks into relatively stable (zones 1 and 2; GSI 66–59, RMR classes II and III) and sheared and altered (zones 3 and 4; GSI 37–15, RMR class IV) segments, highlighting their differing susceptibilities. These zones have a moderately to highly weathered, slicken-sided jointed structure that allows rainwater and snow to infiltrate. The alteration mechanism of minerals such as chlorite, biotite, amphibole and alkali feldspar, as well as the influence of freeze–thaw cycles and precipitation on the pores and joints of bedrock, further weaken the rock, and there is a serious risk of landslide. This research contributes to the development of effective natural disaster mitigation and preparedness measures in the Chukyatan-Kumrat region. This study provides valuable insights for mapping landslide vulnerability in similar geological settings.

A Novel Approach to Selecting Rational Supports for Underground Mining Workings

The goal of this study is to examine the stress-strain state and stability of rock massifs to select a rational type of support for underground workings in challenging mining and geological conditions. The primary aims include increasing the speed of mine workings, reducing capital expenditure, and enhancing safety. Established and novel theoretical methods for mining, geomechanics, and rock massif management were employed. These methods involve analyzing factors affecting the mine working speed, studying the physical and mechanical properties of rocks, developing stratigraphic profiles, and assessing the stress-strain state and stability using Bieniawski’s Rock Mass Rating (RMR), Barton’s Q-rating, and construction norms and rules. Numerical modeling with the Rocscience RS2/RS3 software was utilized to identify failure-prone areas and determine rational support types and parameters. This study provides comprehensive insights into the stress-strain state of the massif, identifying high-risk zones, and recommending suitable support types. The findings contribute to accelerating the progress of underground work, enhancing safety, and reducing construction costs. The developed support systems for challenging mining and geological conditions were designed to increase the speed, safety, and profitability of underground workings. Additionally, this research emphasizes the significance of selecting appropriate support systems to ensure the longevity and stability of underground structures, thereby optimizing operational efficiency and cost-effectiveness. Doi: 10.28991/CEJ-2025-011-03-022 Full Text: PDF

Numerical Analysis of Inlet Slope Diversion Tunnel at Cijurey Dam, Bogor Regency, West Java, Indonesia

Abstract Diversion tunnel is an important supporting structure in dam construction. During construction phase, diversion tunnel is essential to divert river flow from the upstream to the downstream sides. Therefore, this study aimed to analyze stability of inlet slope diversion tunnel against slope failure using numerical analysis with the software Rockscience (RS2). The data required were engineering geological mapping and core analysis, including determining the lithology type and rock mass quality based on Rock Mass Rating (RMR), Geological Strength Index (GSI), laboratory testing, and earthquake coefficient, which were used as input parameters in the rock science software. The result showed that slope condition during post-construction, as well as the normal, flood, and minimum water levels, reached unstable conditions with static and dynamic load. Consequently, reinforcement for slope was found to be essential in strengthening stability. This could be achieved using soil nailing/tie back with a diameter of 48 mm, a length of 18 m at a spacing of 1 m, and shortcrete with a thickness of 10 cm to increase Strength Reduction Factor (SRF).

Comparative evaluation of different rock mass and slope mass rating systems for road cut slopes along National Highway 7, from Rudraprayag to Joshimath in Uttarakhand, India

Comparative evaluation of different rock mass and slope mass rating systems for road cut slopes along National Highway 7, from Rudraprayag to Joshimath in Uttarakhand, India

Application of machine learning tools in predicting basic rock mass rating of mountainous road cut slopes

Application of machine learning tools in predicting basic rock mass rating of mountainous road cut slopes

Empirical and numerical hill slope health evaluation at Malling Nala, NH-505, Himachal Pradesh, India

Slope failures and rock mass movements are continuous geomorphic processes, particularly in a dynamically charged terrane like the Himalaya. Thus, failures emanating from weak geology, hydrogeology and anthropogenic disturbances are aplenty. Present research evaluates slope stability in the vicinity of Malling Nala, along NH-505 in Himachal Pradesh, India. For the two most vulnerable sections in the study area, geo-mechanical and structural attributes have initially been ascertained. Field surveys and laboratory tests identified weak and weathered mica schist and gneissic rocks in the study area. Kinematic analysis, Rock Mass Rating (RMR), Geological Strength Index (GSI), Slope Mass Rating (SMR), modified Global Slope Performance Index (mGSPI) led to determination of possible failure mechanism and rock mass behaviour. Finite element analysis provided a comprehensive understanding of slope behaviour under various conditions, highlighting significant shear strain and displacement in both sections. As noticed from the field and classification schemes, planar and localized bench failures were established. Slope section L-1 was found to collapse under saturated water condition, manifesting the influence of snow melt. The findings indicate that both natural and human factors are causing instability. Effective risk management and mitigation strategies are essential to maintain the stability and reliability of this critical frontier region.