Rock Mechanics Bulletin最新文献

Impact mechanism of fabric changes in different classes of redbeds under static water on their degradation of physical properties 静水作用下不同类型红床织物变化对其物理性能退化的影响机理

Rock Mechanics Bulletin Pub Date : 2025-07-01 DOI: 10.1016/j.rockmb.2025.100194

Zhen Liu, Guangjun Cui, Cuiying Zhou, Chunhui Lan

{"title":"Impact mechanism of fabric changes in different classes of redbeds under static water on their degradation of physical properties","authors":"Zhen Liu, Guangjun Cui, Cuiying Zhou, Chunhui Lan","doi":"10.1016/j.rockmb.2025.100194","DOIUrl":"10.1016/j.rockmb.2025.100194","url":null,"abstract":"<div><div>Deterioration of the physical properties of redbeds is one of the leading causes of geological disasters, engineering problems, and ecological damage. Fabric changes are internal factors leading to the deterioration of physical properties. Existing research on fabric changes in redbeds is qualitative and fuzzy, and their impact on the decline of physical properties needs to be revealed urgently, making the efficient control of redbeds disasters challenging. Therefore, this study focuses on 22 types of redbeds samples and divides them into five classes based on their fabric (composition and structure). Physical property degradation experiments were conducted on different classifications of redbeds during water–rock interaction, and the impact of fabric changes on the degradation of physical properties was analyzed. The results indicate that a linear correlation exists between the internal changes in composition, structure, and physical properties under the action of static water. Moreover, the trend of changes between composition and structure, composition–physical properties, and structure–physical properties shows an exponential regression relationship. Based on this, an action mechanism between compositions such as redbeds, catastrophic minerals, elements, and oxides, as well as the void structure, was proposed, revealing the multifield degradation mechanism of the chemical reactions of the compositions, physical response of the structure, and mechanical reaction of the rock block under the influence of the fabric. The research results can provide a foundation for theoretical research and engineering practice of disaster modes, disaster mechanisms, and prevention and control principles of redbeds disasters.</div></div>","PeriodicalId":101137,"journal":{"name":"Rock Mechanics Bulletin","volume":"4 3","pages":"Article 100194"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144633178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis of spectrum characteristics for multi-attribute seismic data from shaking table test of tunnel underpass hauling sliding surface 隧道地下通道牵引滑面振动台试验多属性地震数据频谱特征分析

Rock Mechanics Bulletin Pub Date : 2025-07-01 DOI: 10.1016/j.rockmb.2025.100196

Lifang Pai , Honggang Wu , Zhongqiang Yi

{"title":"Analysis of spectrum characteristics for multi-attribute seismic data from shaking table test of tunnel underpass hauling sliding surface","authors":"Lifang Pai , Honggang Wu , Zhongqiang Yi","doi":"10.1016/j.rockmb.2025.100196","DOIUrl":"10.1016/j.rockmb.2025.100196","url":null,"abstract":"<div><div>The objective of this research is to analyze the deformation characteristics in space and the dynamic reaction of tunnel underpass hauling sliding surfaces when subjected to potential seismic activities. The response characteristics and failure mode of tunnel linings are uncovered through an analysis of their time-frequency dynamic behavior. It is thoroughly discussed that there are correlation characteristics of plectrum amplitude in multivariate data under different excitation intensities and the spectrum difference characteristics during different shaking stages. The findings indicate that the slope's structural characteristics and failure modes correspond to the shallow slip type and the deformation trend of the deep weak basement slip type. The influence of topographic bias can be disregarded in tunnel underpass hauling sliding surfaces. The axial force (<em>f</em><sub><em>a</em></sub>) in the tunnel lining section primarily exhibits pressure, while the bending moment (<em>M</em><sub><em>b</em></sub>) is symmetrically distributed along the lining section. Tunnels are susceptible to collapse and invert uplift damage. The dominant frequency bands of dynamic strain, dynamic soil pressure, and acceleration are mainly concentrated within the 1–15 Hz range. Dynamic soil pressure and acceleration have a significant correlation, whereas the dynamic strain exhibits a weak correlation with both. The dynamic strain and acceleration exhibit sensitivity in their spectrum response before and during the main shock, whereas the dynamic soil pressure shows sensitivity in its spectrum response after the main shock. Based on the spectral response differences of multi-attribute data during various shaking stages, which can present a novel approach for dynamic monitoring and early warning of seismic actions.</div></div>","PeriodicalId":101137,"journal":{"name":"Rock Mechanics Bulletin","volume":"4 3","pages":"Article 100196"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144535859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exploring machine learning techniques for open stope stability prediction: A comparative study and feature importance analysis 机器学习技术在空场稳定性预测中的应用：比较研究与特征重要性分析

Rock Mechanics Bulletin Pub Date : 2025-07-01 DOI: 10.1016/j.rockmb.2024.100146

Alicja Szmigiel , Derek B. Apel , Yashar Pourrahimian , Hassan Dehghanpour , Yuanyuan Pu

{"title":"Exploring machine learning techniques for open stope stability prediction: A comparative study and feature importance analysis","authors":"Alicja Szmigiel , Derek B. Apel , Yashar Pourrahimian , Hassan Dehghanpour , Yuanyuan Pu","doi":"10.1016/j.rockmb.2024.100146","DOIUrl":"10.1016/j.rockmb.2024.100146","url":null,"abstract":"<div><div>The stability of underground excavations is essential for ensuring the safety of mining operations. Classical stability assessment methods, established in empirical formulas and rock mass classification systems, have long been employed for evaluating stope stability in underground mining. Stability graphs, a popular empirical approach, utilize factors like rock stress, joint orientation, and surface orientation to calculate stability numbers critical for stope design. However, modern advancements in machine learning present new opportunities for enhancing predictive capabilities and understanding complex relationships influencing stope stability. Building upon research demonstrating the feasibility of using machine learning for stability prediction, our study investigates and compares several machine learning algorithms. By analyzing a dataset comprising stope dimensions and geomechanical properties, we explore the potential of machine learning models such as Random Forest, Support Vector Machine, AdaBoost, XGBoost, LightGBM, and Artificial Neural Network in predicting stope stability. Evaluation metrics including accuracy, precision, recall, and F1 score are employed to assess model performance, with the Artificial Neural Network emerging as the most effective. Furthermore, SHapley Additive exPlanations (SHAP) analysis enhances interpretability by explaining the contribution of individual features to model predictions.</div></div>","PeriodicalId":101137,"journal":{"name":"Rock Mechanics Bulletin","volume":"4 3","pages":"Article 100146"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144569845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Elastoplastic analysis of deep circular tunnels affected by blasting damage and hydraulic flow 爆破损伤和水力流对深埋圆形隧道弹塑性影响分析

Rock Mechanics Bulletin Pub Date : 2025-07-01 DOI: 10.1016/j.rockmb.2025.100195

Saeed Karamipoor, Ali Reza Kargar, Abbas Majdi, Fariborz Matinpoor

{"title":"Elastoplastic analysis of deep circular tunnels affected by blasting damage and hydraulic flow","authors":"Saeed Karamipoor, Ali Reza Kargar, Abbas Majdi, Fariborz Matinpoor","doi":"10.1016/j.rockmb.2025.100195","DOIUrl":"10.1016/j.rockmb.2025.100195","url":null,"abstract":"<div><div>In drill and blast method, due to uncontrolled blasting operations, the blast-induced damaged zone (BIDZ) is formed, whose mechanical and hydraulic properties are altered. This zone affects the behavior of the rock mass such that it reduces the strength of surrounding mass, and stability of the excavation. On the other hand, the groundwater is also effected by damaged zone induced stress and displacement, leading to a change in hydraulic flow around the tunnel which subsequently could produce new stress and displacement fields. In this research, an analytical solution for evaluating the stress and displacement of deep circular tunnels in elastoplastic rock mass is proposed, assuming the presence of BIDZ and hydraulic flow around the tunnel. The tunnel is subjected to in situ hydrostatic stresses, under radial hydraulic flow, and the damaged zone is supposed cylindrical shaped surrounding the cavity. Four different scenarios are predicted for stress evolution around the cavity considering the seepage zone, damage zone and plastic zone spread for elastic brittle-plastic behavior of surrounding mass. The analytical solution is validated using FLAC software, which shows excellent agreement. Examples are given to investigate the effect of BIDZ on the stress and displacement fields around the tunnel in both drained and undrained condition. The results show a significant impact on tunnel wall displacement especially for small magnitude of the ratio of seepage zone to damage zone radii, indicating its great significance in tunnel practice in terms of support and ground control.</div></div>","PeriodicalId":101137,"journal":{"name":"Rock Mechanics Bulletin","volume":"4 3","pages":"Article 100195"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144695124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data-driven machine learning approaches for predicting the shear strength of rock joints 预测岩石节理抗剪强度的数据驱动机器学习方法

Rock Mechanics Bulletin Pub Date : 2025-07-01 DOI: 10.1016/j.rockmb.2025.100209

Zhang Jinge , Jiang Yujing , Zhang Sunhao , Shang Dongqi , Sun Zhenjiao , Chen Hongbin

{"title":"Data-driven machine learning approaches for predicting the shear strength of rock joints","authors":"Zhang Jinge , Jiang Yujing , Zhang Sunhao , Shang Dongqi , Sun Zhenjiao , Chen Hongbin","doi":"10.1016/j.rockmb.2025.100209","DOIUrl":"10.1016/j.rockmb.2025.100209","url":null,"abstract":"<div><div>Accurate prediction of the shear strength of rock joints is crucial for assessing the stability of civil and mining engineering projects. Traditional methods for determining the shear strength of rock joints are time-consuming, costly, and computationally complex. Machine learning methods, which are driven by data, provide a cost-effective and rapid approach to predicting rock joint shear strength, overcoming the limitations of traditional techniques. This study employs nine machine learning models: eXtreme gradient boosting (XGBoost), random forest (RF), Support vector regression (SVR), decision tree (DT), Gaussian process regression (GPR), K-nearest neighbors (KNN), categorical boosting (CatBoost), extreme learning machine (ELM), and adaptive boosting (AdaBoost). A dataset of 288 data points was compiled from an extensive set of literature. Five input features, namely, normal stress, uniaxial compressive strength, Young’s modulus, joint roughness coefficient (JRC), and specimen length, were selected, with shear strength of the rock joints as the output variable. The performance of the nine ML models was assessed using the root mean square error (RMSE), coefficient of determination (<em>R</em><sup>2</sup>), and mean absolute error (MAE). Due to its unique ordered boosting mechanism and symmetric tree structure, CatBoost outperformed the other models, achieving RMSE, <em>R</em><sup>2</sup>, and MAE values of 0.4663, 0.9765, and 0.3508, respectively. Compared with the experimental results, the model yielded a mean square error (MSE) of 0.0360. The proposed ML method offers a cost-effective and efficient solution for predicting rock joint shear strength.</div></div>","PeriodicalId":101137,"journal":{"name":"Rock Mechanics Bulletin","volume":"4 3","pages":"Article 100209"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144654051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Definition and classification of rockburst 岩爆的定义和分类

Rock Mechanics Bulletin Pub Date : 2025-07-01 DOI: 10.1016/j.rockmb.2025.100206

Manchao He , Ismet Canbulat , Fidelis T. Suorineni , Murat Karakus , Wen Nie , Dongqiao Liu , Chengguo Zhang , Alexey Nagibin , Bauyrzhan Rustembek

{"title":"Definition and classification of rockburst","authors":"Manchao He , Ismet Canbulat , Fidelis T. Suorineni , Murat Karakus , Wen Nie , Dongqiao Liu , Chengguo Zhang , Alexey Nagibin , Bauyrzhan Rustembek","doi":"10.1016/j.rockmb.2025.100206","DOIUrl":"10.1016/j.rockmb.2025.100206","url":null,"abstract":"<div><div>The rockburst is a violent failure in rock during mining and tunneling operations. Since tunnel constructions for hydropower and transportation purposes and mining operations in deep rock masses have been increasing recently, more frequent rockburst cases have been reported. This paper proposes a new definition for rockburst, considering the main components of the rockburst along with triggering mechanisms and reasons. For this purpose, the historical definitions of rockburst and its related classifications have been reviewed. In terms of triggering mechanisms, a rockburst must be induced by excavation resulting from three effects arising from the transition of stress state from 3- to 1-dimension, such as the transient radial stress loss, the time-dependent tangential stress increase, and the peak strength drop, which are explained by examining the stress transition in the <em>shear stress vs normal stress</em> space and energy transition in the <em>stress-strain</em> space. Based on the understanding of the three effects of excavation, a new definition of rockburst is proposed: “A r<em>ockburst is a sudden failure of rock mass surrounding the excavations caused by the rapid release of stored energy when induced stresses exceed the rock strength</em>”. Additionally, rockbursts are classified according to transitions in the static and dynamic stress fields, with further subclassifications into instantaneous and delayed bursts based on the timing of occurrences relative to radial stress drop and tangential stress increase. Rockburst management strategies are also proposed to address stress and energy transitions in excavations.</div></div>","PeriodicalId":101137,"journal":{"name":"Rock Mechanics Bulletin","volume":"4 3","pages":"Article 100206"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144580500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The phlogiston theory of rock mass Classification: Philosophical and mathematical critique of ordinal data usage 岩体分类的燃素理论：序数数据使用的哲学和数学批判

Rock Mechanics Bulletin Pub Date : 2025-07-01 DOI: 10.1016/j.rockmb.2025.100205

Junzhe Liu , Yu Feng , Yuyong Jiao

{"title":"The phlogiston theory of rock mass Classification: Philosophical and mathematical critique of ordinal data usage","authors":"Junzhe Liu , Yu Feng , Yuyong Jiao","doi":"10.1016/j.rockmb.2025.100205","DOIUrl":"10.1016/j.rockmb.2025.100205","url":null,"abstract":"<div><div>The widespread use of rock mass classification systems in engineering practice relies on mathematical operations and assumptions that violate fundamental principles of measurement theory. This paper presents a critical analysis of current classification methodologies, focusing on the Rock Mass Rating (RMR), Q-system, and Geological Strength Index (GSI), drawing parallels with historical scientific misconceptions such as the phlogiston theory. Through detailed examination of measurement theory principles and their application to geological characterization, we demonstrate that these classification systems contain inherent flaws in their treatment of ordinal data and parameter independence. The paper identifies four critical issues: the invalid summation of ordinal ratings in the RMR system, the inappropriate multiplication and division operations in the Q-system, the unjustified visual interpolation in the GSI system, and the universal problem of assumed parameter independence. Through examination of measurement theory principles and their application to geological characterization, we demonstrate that current classification systems violate basic mathematical rules in their treatment of ordinal data and parameter independence. The implications of these violations extend beyond theoretical concerns, affecting practical engineering decisions and risk assessment. We also illustrate how these theoretical flaws manifest in practice and propose directions for developing more theoretically sound approaches to rock mass characterization. This critical analysis aims to initiate a necessary dialogue about the future of rock mass classification in engineering practice.</div></div>","PeriodicalId":101137,"journal":{"name":"Rock Mechanics Bulletin","volume":"4 3","pages":"Article 100205"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144572728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prediction of blast-induced ground vibration in dolomitic marble quarry using Z-number information and fuzzy cognitive map based neural network models 基于z数信息和模糊认知图的神经网络模型预测白云岩采石场爆破诱发地面振动

IF 7

Rock Mechanics Bulletin Pub Date : 2025-06-18 DOI: 10.1016/j.rockmb.2025.100217

Shahab Hosseini , Abiodun Ismail Lawal , Francois Mulenga

{"title":"Prediction of blast-induced ground vibration in dolomitic marble quarry using Z-number information and fuzzy cognitive map based neural network models","authors":"Shahab Hosseini , Abiodun Ismail Lawal , Francois Mulenga","doi":"10.1016/j.rockmb.2025.100217","DOIUrl":"10.1016/j.rockmb.2025.100217","url":null,"abstract":"<div><div>Blast-induced ground vibration (BIGV) is one of the detrimental environmental consequences of blasting operations in mining and civil engineering. Hence, accurate prediction of BIGV is highly imperative. Therefore, different novel artificial intelligence (AI) methods such as Bayesian regularized neural network (BRNN), Bayesian regularized causality-weighted neural network (BRCWNN) and Z-number-based Bayesian regularized causality-weighted neural network (Z-BRCWNN) are proposed in this study for the reliable prediction of BIGV in a dolomitic marble quarry using the obtained field data. The outcome of the proposed models is subjected to rigorous statistical analyses. The outcome of analyses revealed that the Z-BRCWNN model outperformed the other models with 70%, 82% and 82% threshold statistic values evaluated at the 5%, 10% and 15% confidence levels for the testing phase and 63%, 91% and 91% threshold values for the validation phase evaluated at the same levels as above. The sensitivity analysis conducted revealed that the distance from the measuring point to the blasting point (DI) has the highest influence on BIGV.</div></div>","PeriodicalId":101137,"journal":{"name":"Rock Mechanics Bulletin","volume":"4 4","pages":"Article 100217"},"PeriodicalIF":7.0,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144766474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A green coal mining method for protecting roadways and overlying strata 一种保护巷道及上覆岩层的绿色采煤方法

Rock Mechanics Bulletin Pub Date : 2025-03-21 DOI: 10.1016/j.rockmb.2025.100192

Shilin Hou , Manchao He , Jun Yang , Jun Zhang , Yajun Wang , Xuhui Kang , Zijie Han , Fukang Du

{"title":"A green coal mining method for protecting roadways and overlying strata","authors":"Shilin Hou , Manchao He , Jun Yang , Jun Zhang , Yajun Wang , Xuhui Kang , Zijie Han , Fukang Du","doi":"10.1016/j.rockmb.2025.100192","DOIUrl":"10.1016/j.rockmb.2025.100192","url":null,"abstract":"<div><div>The non-pillar mining method with automatically formed roadway (NPM-AFR) is an innovative mining method. This paper provides a detailed description of how this method achieves the cancellation of pillar retention and the advance excavation of roadways through optimized mining processes. Based on mining mechanics modeling, the paper explains how the NPM-AFR compensates for mining-induced damage by utilizing the bulking of the goaf gangue and uses directional roof cutting technology interrupt the stress transmission path from the goaf to the roadway, thereby enhancing the protection of both the overlying strata and the roadway. Geological and mechanical model tests were conducted based on the Ningtiaota coal mine to compare the NPM-AFR and traditional mining method. The results show that under the NPM-AFR, the development height of overlying strata damage is reduced by 36.14 % compared to traditional mining method, and overlying strata stress is reduced by 25 %. The overlying strata is effectively protected in the NPAFR mining area. In both mining methods, the roadways remain in a low-stress zone, but the peak stress on the coal pillar side in the NPM-AFR is reduced by 40.6 % compared to the traditional method, significantly reducing the safety risks of the roadway. Field verification tests further demonstrate that the NPM-AFR, along with its supporting processes, successfully achieves the goals of pillar-free mining, surface protection, and safe roadway preservation. This technology represents a sustainable, green mining approach that protects both the overburden and the roadway, providing new solutions for safe and efficient coal mining.</div></div>","PeriodicalId":101137,"journal":{"name":"Rock Mechanics Bulletin","volume":"4 3","pages":"Article 100192"},"PeriodicalIF":0.0,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144489449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The effect of geometrical parameters on wedge failure of rock slopes using physical and numerical modelling 采用物理和数值模拟方法研究几何参数对岩质边坡楔形破坏的影响

Rock Mechanics Bulletin Pub Date : 2025-03-20 DOI: 10.1016/j.rockmb.2025.100193

Mohammadmatin Mahdizadeh , Erfan Amini , Mohammad Hossein Khosravi

{"title":"The effect of geometrical parameters on wedge failure of rock slopes using physical and numerical modelling","authors":"Mohammadmatin Mahdizadeh , Erfan Amini , Mohammad Hossein Khosravi","doi":"10.1016/j.rockmb.2025.100193","DOIUrl":"10.1016/j.rockmb.2025.100193","url":null,"abstract":"<div><div>This study investigated the role of the geometrical parameters of a wedge block on its stability using physical and numerical modeling. For the purpose of physical modeling, a new experimental setup was developed, and the stability of rock slopes was modeled. Sensitivity analysis was performed on four geometrical parameters: tilt angle of the wedge (<em>β</em>), included angle of the wedge (<em>ξ</em>), the apparent dip of the slope in the sliding direction (<em>Ψ</em><sub><em>fi</em></sub>), and the difference in dip direction of the slope face and discontinuities intersection line (Δ<em>α</em>). A total number of 89 rock slope models were tested, and the wedge factor (<em>K</em>) was calculated for each model. Subsequently, 3D numerical models, corresponding to each physical model were conducted. Rock slope face inclination was applied by defining gravity vectors in different directions, which led to the development of models with a much simpler geometry. Ultimately, numerical modeling results almost align with the outcomes of physical modeling. Good agreement was observed between physical and numerical models and the existing analysis. According to the results, the behavior of the wedge-shaped block and its safety factor depends on the geometric conditions of the wedge and its slope, regardless of the rock material properties, as models were tested with two different materials. Additionally, sensitivity analysis demonstrates that by increasing Δ<em>α</em>, the slope safety factor was increased, as expected. Finally, practical graphs were developed by which the safety factor against the wedge failure can be estimated using the geometrical parameters of the wedge and the rock slope.</div></div>","PeriodicalId":101137,"journal":{"name":"Rock Mechanics Bulletin","volume":"4 3","pages":"Article 100193"},"PeriodicalIF":0.0,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144489448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0