Engineering Geology最新文献

{"title":"Statistical analysis of factors influencing overall rockfall activity and the spatially-normalized rockfall power law activity constant, Ast","authors":"Cameron Phillips,&nbsp;Gabriel Walton","doi":"10.1016/j.enggeo.2025.108297","DOIUrl":"10.1016/j.enggeo.2025.108297","url":null,"abstract":"<div><div>Natural and human-constructed rock slopes pose a hazard to humans and infrastructure in mountainous areas around the world. Rockfall inventories provide a basis for slope-scale or regional rockfall hazard assessment, improving the ability for management agencies to make informed mitigation decisions. A power law relating rockfall volume to frequency is commonly used to represent the volume distribution of a rockfall inventory to quantify hazard and forecast the recurrence interval of future events. This power law can be spatially normalized by the relevant rockfall source zone area to allow for direct comparison of rockfall activity at different slopes.</div><div>This work focuses on statistical analysis of geological, climatic, and database (non-physical) variables potentially affecting the vertical scaling of the rockfall power law. 44 rockfall inventories from the literature were used to assess whether relationships exist between independent variables and power law metrics for overall rockfall activity with a focus on the spatially-normalized activity constant, <em>A</em>_<em>st</em>.</div><div>Monitoring frequency and monitoring method were found to have a large, statistically significant effect on apparent rockfall activity due to the intrinsic limitations of observational rockfall inventories. Isolation of terrestrial remote sensing inventories showed that the most important variables influencing overall rockfall activity (to varying degrees) are lithology, rockmass condition, number of annual freezing degree-days, and whether the slope is natural or cut. Focusing future research on the effects that these variables have on rockfall activity has the potential to improve inventory-derived and field-based rockfall hazard assessment.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"357 ","pages":"Article 108297"},"PeriodicalIF":8.4,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144900822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The first application of AMR approach to non-mining induced seismicity: A case study from water injection boreholes and water reservoirs","authors":"Przemysław Romański,&nbsp;Maciej J. Mendecki,&nbsp;Iwona Stan-Kłeczek","doi":"10.1016/j.enggeo.2025.108301","DOIUrl":"10.1016/j.enggeo.2025.108301","url":null,"abstract":"<div><div>Critical-point-like models can be used for the examination of seismic activity and attempts to forecast seismic events. One such model is the Accelerated Moment Release (AMR), based on cumulative seismic moment. While this method is commonly used in studying natural seismicity, it has yet to be thoroughly tested for areas with induced seismicity, where it may yield better results. This paper aimed to examine the potential application of AMR for three datasets related to hydraulic injections (Soultz data collected in: 2000, 2003, 2004) and three artificial water reservoirs (Czorsztyn, Monteynard, Val D'Agri). We determined the types of seismic energy release for each area. Furthermore, we compared them with injection rates and wellhead pressures in the research boreholes for the Soultz episodes and water level fluctuations in the reservoirs. The final results demonstrated increased seismic activity related to water and brine injection into the rock mass, manifested in accelerated-like AMR curves. However, no correlation was observed between water levels in artificial reservoirs and the rate of seismic energy release. Additionally, we analysed the distribution of seismic events focusing on participating in the main earthquake nucleation process, and the observations were related to geological-tectonic conditions. Finally, we created a model of the relationship between the rate of <em>M</em>_<em>0</em> release and wellhead pressure over a one-day interval<em>.</em> Comparing it with the AMR models enabled a better understanding of how the rock mass releases seismic energy. The final conclusion of the research confirms the usefulness of using AMR for seismicity caused by injections.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"356 ","pages":"Article 108301"},"PeriodicalIF":8.4,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144892182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A generalized phenomenological approach for real-time automatic time of failure forecasting of landslides","authors":"Junrong Zhang ,&nbsp;Huiming Tang ,&nbsp;Xingping Zhang ,&nbsp;Qiong Wu ,&nbsp;Wen Zhang ,&nbsp;Xuexue Su ,&nbsp;Kun Fang","doi":"10.1016/j.enggeo.2025.108303","DOIUrl":"10.1016/j.enggeo.2025.108303","url":null,"abstract":"<div><div>Human activities, tectonic shifts, and global climatic changes have heightened both the frequency and severity of landslides, creating a growing need for reliable failure time prediction. However, the complexity and variability of monitored displacement data present formidable obstacles to the automated assessment of landslides' time of failure (TOF). As such, a generalized real-time TOF forecasting model is developed in this study to minimize dependency on subjective judgments. Initially, the mutation and trend characteristics of displacement data before and after the onset of acceleration (OOA) from landslides with the exponential deformation pattern were analyzed. Subsequently, a multi-loop time forecast (MLTF) model incorporating exponential moving average (EMA), dynamic typical displacement trend (DTDT) test, automatic OOA identification based on major mutation detection and deformation speed ratio (DSR), and the inverse velocity method (INV) is proposed and validated for reliability with 25 historic landslides' datasets. The results indicate that the MLTF model can automatically identify the OOA of landslides with a low error rate. It significantly narrows the alarm time window and predicted TOF window, which helps reduce false alarms. Additionally, compared to manual INV, the predicted TOF is more accurate and shows better consistency with the actual TOF. Generalizability assessments demonstrate that it can be widely applied in automatic OOA identification and TOF prediction across various deformation patterns of landslides with high reliability.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"356 ","pages":"Article 108303"},"PeriodicalIF":8.4,"publicationDate":"2025-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144892148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A proposed concept for classifying uniaxial compressive strength (UCS) from SWIR hyperspectral data","authors":"Edward C. Wellman,&nbsp;Dean Riley,&nbsp;Amanda Hughes,&nbsp;Nathalie Risso,&nbsp;Moe Momayez,&nbsp;John Kemeny","doi":"10.1016/j.enggeo.2025.108300","DOIUrl":"10.1016/j.enggeo.2025.108300","url":null,"abstract":"<div><div>With the development of lower-cost and portable spectral imagers and spectral radiometers, the question arises: Can hyperspectral image data be used to estimate the Unconfined Compressive Strength (UCS) of rock? Reflectance, emissivity, absorption, and transmission are fundamental properties of rock and minerals. This study focuses on correlating data from non-destructive hyperspectral images and destructive test methods.</div><div>Hyperspectral images of 32 altered granite samples were acquired in the Shortwave Infrared (SWIR). The reflectance from the 1000 to 2500 nm range of core samples was analyzed. The primary objective of this study is to identify key spectral features that correlate with rock strength and classify samples into ISRM strength categories for weak, moderately strong, and strong rock. The methodology encompasses data preprocessing, feature extraction based on deviations from the mean spectral response, and statistical analysis to identify significant spectral components. The k-Nearest Neighbor (kNN) classifier demonstrated reliable performance for moderately strong and strong rock categories, achieving an overall accuracy of 90 %. This paper outlines the experimental procedure, machine learning analysis methods, and a recommended path forward for further developing this technique. The ultimate goal is to develop additional methods for quantifying UCS from hyperspectral images of both surface and drill core data, utilizing International Society of Rock Mechanics (ISRM) classification guidelines.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"356 ","pages":"Article 108300"},"PeriodicalIF":8.4,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144887380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hydrogeochemical weathering of reservoir-bank heritage sites: Water-rock interaction mechanism at Bingling Temple Grottoes, NW China","authors":"Wenwu Chen ,&nbsp;Peiran Liu ,&nbsp;Shaoran Zhang ,&nbsp;Yuan Li ,&nbsp;Zongchang Liu ,&nbsp;Li Wang","doi":"10.1016/j.enggeo.2025.108298","DOIUrl":"10.1016/j.enggeo.2025.108298","url":null,"abstract":"<div><div>The Bingling Temple Grottoes, a UNESCO World Heritage site, are undergoing accelerated weathering due to changes in hydrogeochemical conditions following the construction of a nearby reservoir. This study examines the chemical composition and evolutionary trends of three water types—reservoir water, spring water, and fissure water—all of which impact the grottoes. For the first time, we integrate 55 sets of historical data and on-site field data collected from the Bingling Temple Grottoes. We also propose a research framework that combines hydrochemical indicators with software-based calculations. The results reveal the following: (1) A distinct hydrochemical differentiation: reservoir water is primarily of the HCO₃-Ca type, while spring and fissure waters have evolved from SO₄-HCO₃-Ca to mixed HCO₃-SO₄-Na types due to prolonged feldspar dissolution. (2) Fissure water exhibits the highest concentrations of Na⁺, Ca²⁺, and SO₄²⁻, driven by sustained water-rock interactions, whereas reservoir water remains low in mineral saturation. (3) HCO₃⁻ plays a critical role in gypsum dissolution and enhances rock weathering under alkaline environments. (4) Seasonal water level fluctuations intensify ion exchange and salt precipitation, posing a direct threat to the preservation of murals and sculptures. This study provides the first comprehensive assessment of reservoir-regulated hydrogeochemical processes affecting grotto heritage sites. It highlights how changes in water chemistry, particularly bicarbonate dynamics, can exacerbate the deterioration of sandstone relics. Our findings offer a scientific foundation for developing strategies to mitigate hydrological risks to cultural heritage sites located near reservoir banks.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"356 ","pages":"Article 108298"},"PeriodicalIF":8.4,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144892147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fracture evolution and damage model of composite coal-rock under bending: An integrated physical-numerical-analytical approach for rock homogeneity effects","authors":"Weitao Yue ,&nbsp;Xiaojun Feng ,&nbsp;Enyuan Wang ,&nbsp;Qiming Zhang ,&nbsp;Zeng Ding ,&nbsp;Dong Chen ,&nbsp;Xiangguo Kong","doi":"10.1016/j.enggeo.2025.108299","DOIUrl":"10.1016/j.enggeo.2025.108299","url":null,"abstract":"<div><div>To elucidate the underlying bending and fracture mechanisms inherent in composite coal-rock (CCR) roof structures within deep mining environments, this study introduces a groundbreaking analytical framework. The proposed framework integrates three methodological components: physical modeling through three-point bending tests (TPBT), numerical simulation using the particle flow code (PFC^2D), and analytical damage modeling. This integrated approach is specifically tailored for CCR fracture analysis with detailed characterization of rock layer heterogeneity. Focusing on the strata of the Fuxin Hengda coal mine, we employed a multifaceted monitoring approach, incorporating acoustic emission (AE), digital image correlation (DIC), scanning electron microscopy (SEM), and the 3D profilometry. This comprehensive strategy systematically unveiled the regulatory mechanisms governing how rock heterogeneity influences damage evolution. Our findings reveal that CCR undergoes a distinct four-stage evolutionary pattern under TPBT conditions: “weak contact-strong contact-peak load-post-peak.” This damage progression is intricately linked with DIC strain fields and AE energy release patterns. Notably, sandstone composite coal-rock (CCR<img>S), characterized by its high homogeneity, exhibits localized strain distribution and concentrated energy release, culminating in abrupt brittle fracture. In contrast, sandy conglomerate composite coal-rock (CCR-SC) with its coarse particle structure, fosters multi-level microcrack branching, leading to progressive failure. Furthermore, the developed Weibull damage model quantitatively delineates the interplay between the homogeneity coefficient (<em>φ</em>), coal-rock energy weight factor (<em>w</em>), and fracture rate. Our analysis underscores that damage rates escalate markedly in high-homogeneity rock layers compared to their low-homogeneity counterparts. This observation substantiates the mechanism whereby high-homogeneity rock layers expedite energy release through strain localization. Collectively, these insights offer a robust theoretical foundation for deep coal-rock dynamic disaster prediction and roof stability control.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"356 ","pages":"Article 108299"},"PeriodicalIF":8.4,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144879405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient simulation of conditional random fields and its geotechnical applications","authors":"Chengxin Feng ,&nbsp;Zhibao Zheng ,&nbsp;Michael Beer","doi":"10.1016/j.enggeo.2025.108284","DOIUrl":"10.1016/j.enggeo.2025.108284","url":null,"abstract":"<div><div>Random fields are a powerful tool for modeling spatial variability of geotechnical properties, but they may overestimate variability if field investigation data, such as borehole measurements, are not incorporated. With advancements in testing techniques and the growing availability of high-quality data, reliable spatial variability modeling has become increasingly feasible in geotechnical engineering. This article proposes an efficient and versatile method for simulating conditional random fields (CRFs), aiming to overcome the computational inefficiency of traditional approaches when dealing with large datasets. The proposed method involves three key steps. First, the mean values of CRFs is estimated from observed data by the Kriging interpolation. Then, a conditional covariance matrix of the CRF is constructed by combining the covariance matrix of the unconditional random field with the Kriging interpolation or the Nyström approximation. Finally, the CRF is simulated using the Karhunen–Loève (KL) expansion, which combines the derived eigenvalues and eigenfunctions with random variables. Therefore, this process simulates CRFs effectively by integrating the Kriging interpolation, the conditional covariance modeling and the stochastic expansion. The effectiveness of the proposed method is verified using one-, two-, and three-dimensional geotechnical applications. Numerical results confirm that the proposed method can accurately preserve spatial correlations while significantly reducing the computational effort. Furthermore, it also enables efficient modeling of large-scale geotechnical problems. In these senses, the proposed framework provides a robust tool for spatial variability modeling in geotechnical engineering.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"356 ","pages":"Article 108284"},"PeriodicalIF":8.4,"publicationDate":"2025-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144863289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of underground explosions on soil and structures based on PD–SPH modeling","authors":"Xieping Huang ,&nbsp;Yansong Yue ,&nbsp;Bin Zhu ,&nbsp;Yunmin Chen ,&nbsp;Qiang Lu ,&nbsp;Dezhi Zhang ,&nbsp;Xiangzhen Kong ,&nbsp;Qin Fang","doi":"10.1016/j.enggeo.2025.108296","DOIUrl":"10.1016/j.enggeo.2025.108296","url":null,"abstract":"<div><div>In recent decades, researchers have struggled to develop computational models capable of simultaneously simulating the effects of underground explosions on both soil and structures. Traditional mesh-based methods, such as the finite element method (FEM), fail to achieve this due to challenges related to large deformations and discontinuities in soil and structures. To address this limitation, we develop a coupled peridynamics–smoothed particle hydrodynamics (PD–SPH) model, both based on meshfree particle methods. By introducing a robust data exchange algorithm between PD and SPH domains, incorporating a dynamic contact model for different materials in PD domains, and integrating a modified Drucker–Prager plasticity model for soil along with a rate-dependent damage model for concrete, the PD–SPH model effectively captures explosive gas–soil interactions, soil–structure interactions, large soil deformations, and rate-dependent damage and fracture processes in concrete structures.</div><div>The effects of underground explosions on soil are then first modeled, demonstrating that the model successfully captures the severe soil ejections and excavation crater formations caused by shallow-buried explosions, as well as subsidence crater formations due to deep-buried explosions. Comprehensive qualitative and quantitative comparisons between PD–SPH simulations and centrifuge tests are provided, with errors below 15 %. In the meantime, the PD–SPH model can also accurately reproduce the damage effects of blast waves in soil on nearby concrete slabs and silo structures. The damage and fracture processes of these structures are analyzed and validated against experimental results. Furthermore, this study also explores the influence of nearby structures on soil ejection and cratering processes. The successful applications of the model to various explosion scenarios demonstrate that the developed PD–SPH model is capable of consistently and accurately capturing the effects of underground explosions on both soil and structures.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"356 ","pages":"Article 108296"},"PeriodicalIF":8.4,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144863290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In-situ block intelligent identification: Large-scale artificial intelligence (AI) models enable efficient geological surveys via image segmentation","authors":"Jiawei Wang ,&nbsp;Jun Zheng ,&nbsp;Jie Hu ,&nbsp;Rafael Jimenez ,&nbsp;Anlong Zhu ,&nbsp;Qing Lü ,&nbsp;Jiongchao Wang","doi":"10.1016/j.enggeo.2025.108286","DOIUrl":"10.1016/j.enggeo.2025.108286","url":null,"abstract":"<div><div>In-situ block identification is important for characterizing the degree of rock mass jointing and for predicting rockfall volumes on engineering sites. Presently, research primarily focuses on using remote sensing techniques, such as drone-based photogrammetry, generating large-scale point cloud data of rock exposures as a substitute for dangerous and labor-intensive field surveys, while overlooking the huge difficulty of extracting block information from this data. Specifically, the difficulty lies in the nonintuitive characteristics of point cloud data and the lack of an efficient extraction technology. Large-scale models (LSMs) provide powerful visual perception capabilities across complex environments in computer vision, opening a relevant question for geological surveys: Can LSMs enable efficient identification of in-situ blocks? This study explores such possibility and proposes a novel approach, called Segment Anything for Three-Dimensional Blocks (SA4B-3D), that (i) converts (complex) 3D block identification challenges into (simpler) two-dimensional (2D) image segmentation problems, and (ii) leverages the Segment Anything Model (SAM) to intelligently identify individual blocks within point clouds of rock exposures. This paper evaluates the effectiveness of the method using a cardboard experiment, explores a real rock mass exposure and discusses the applicability of the proposed method, with results showing that the proposed method can obtain 7303 block observations with a total volume of 3462.7739 m³, tasks that were previously unachievable. Moreover, this LSM-based method paves the way for hour-level accurate geological surveys and advances engineering geology practice by reducing on-site labor and enhancing safety in high-risk projects.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"356 ","pages":"Article 108286"},"PeriodicalIF":8.4,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144879357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mechanical response and fracture behaviors of pre-cracked granite under time-delayed triaxial compression: Experimental and 3D DEM insights","authors":"Yunhe Ao ,&nbsp;Baoxin Jia ,&nbsp;Chuang Sun ,&nbsp;Yunbo Pu ,&nbsp;Baicong Yao","doi":"10.1016/j.enggeo.2025.108294","DOIUrl":"10.1016/j.enggeo.2025.108294","url":null,"abstract":"<div><div>The time-delayed failure of rocks is a potential geological hazard, and it poses severe challenges to the stabilization and safety in deep rock engineering. To explore the triaxial time-delayed failure process under high-stress conditions, this paper conducts time-delayed triaxial compression (TDTC) experiments on multiple granite samples. A three-dimensional grain-based model (3D-GBM) for pre-cracked granite is constructed. Combined with the parallel-bonded stress corrosion (PSC) model, TDTC numerical simulations are carried out to investigate the triaxial time-delayed damage and fracture characteristics of pre-cracked granite under high-stress levels. The results show that when the stress level <em>k</em> is 85 %, the fracture characteristic of each type of sample is the most obvious. The fractal dimension and damage variable of the type B-30 sample are the largest. The pre-cracked granite 3D-GBM based on the real mineral composition achieves a high consistency between the numerical simulations and the experimental results in conventional triaxial compression tests. For all types of samples, the axial strain confining pressure compliance during the time-delayed deformation stage shows a gradual upward trend as <em>k</em> increases. The fracture degree is most significant when <em>k</em> = 85 % for the same type of samples. The x-direction particle displacement of the type B-30 sample is the largest. The number of intragranular cracks in all samples is generally larger than that of intergranular cracks for <em>k</em> = 85 %.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"356 ","pages":"Article 108294"},"PeriodicalIF":8.4,"publicationDate":"2025-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144829463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}