Bulletin of Engineering Geology and the Environment最新文献

{"title":"Re-design of a railway tunnel intersected by surface rupture of the Erkenek fault segment during the 6 February 2023 Pazarcik (Mw 7.7) Earthquake (Türkiye)","authors":"Servet Karahan,&nbsp;Evren Posluk,&nbsp;F. Burak Büyükdemirci,&nbsp;Candan Gokceoglu","doi":"10.1007/s10064-025-04217-y","DOIUrl":"10.1007/s10064-025-04217-y","url":null,"abstract":"<div><p>The T3 Tunnel on the Malatya-Narlı Conventional Railway Route was intersected by the surface rupture during the February 6, 2023 Pazarcık Earthquake (Mw 7.7), and a part of the tunnel was damaged completely. In this study, the investigation results, and re-design of the tunnel, are presented. The T3 Tunnel, which was built in 1933 with interlocking stone masonry lining, was cut by the Erkenek fault, one of the segments of the East Anatolian Fault Zone (EAFZ), and a landslide was triggered around the tunnel portal. Under the influence of these two factors, collapse, and various deformations occurred in the tunnel. To understand the character of the failure, detailed geological, geophysical, and geotechnical studies were carried out in addition to in-situ observations. Subsequently, the tunnel was re-designed and repaired to open the railway to service. For this purpose, a re-design project was developed that included 2-stage engineering solutions including on-tunnel and in-tunnel construction efforts. In the first stage, the portal landslide was rehabilitated using support systems, and in the second stage, tunnel consolidation injection, redesign of the portal structure, and reconstruction of the tunnel support system were carried out. The obtained data and scientific evaluations are presented together with analyses. It is of vital importance that transportation structures continue to function during and after earthquakes. Therefore, the case presented in the study is one of the rare and interesting cases in terms of tunneling literature. The construction efforts in the T3 Tunnel were completed without any problems 6 months after the earthquakes, while more than 30,000 aftershocks continued.</p></div>","PeriodicalId":500,"journal":{"name":"Bulletin of Engineering Geology and the Environment","volume":"84 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10064-025-04217-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143645599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An empirical-driven machine learning (EDML) approach to predict PPV caused by quarry blasting","authors":"Panagiotis G. Asteris,&nbsp;Danial Jahed Armaghani","doi":"10.1007/s10064-025-04216-z","DOIUrl":"10.1007/s10064-025-04216-z","url":null,"abstract":"<div><p>Blasting in mining and quarrying serves multiple purposes but poses environmental challenges, notably generating shockwaves and vibrations through peak particle velocity (PPV) from explosions. Previous efforts to predict PPV values have relied on empirical equations using parameters such as maximum charge per delay (MC) and distance from the blast face (D). Numerous attempts have employed machine learning (ML) to estimate PPV with the same input parameters. This study introduces a novel approach called empirical-driven ML (EDML), which integrates empirical equations and their outcomes as inputs for PPV prediction. EDML leverages existing knowledge to enhance model performance, interpretability, and generalization. For the EDML approach, four empirical equations, namely USBM, CMRI, General Predictor, and Ambraseys-Hendron have been chosen based on prior research. These four empirical equations were selected based on their good performance as reported in the literature. Using these equations’ PPV values as inputs, three advanced tree-based techniques (random forest, deep forest, and extreme gradient boosting) have been employed for model training. Comparison with the conventional ML approach (using only maximum charge per delay and distance from the blast face) reveals EDML’s superior predictive capacity for PPV estimation. Note that the inputs of these databases were directly and indirectly extracted from MC and D with the same PPV values. The proposed EDML approach effectively integrates data-driven insights with domain expertise, improving accuracy and interpretability through the inclusion of PPV and blasting observations.</p></div>","PeriodicalId":500,"journal":{"name":"Bulletin of Engineering Geology and the Environment","volume":"84 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10064-025-04216-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143645515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification, distribution, and mechanisms of large landslides in the upper reaches of Jinsha River","authors":"Weihua Zhao,&nbsp;Fengjiao Wang,&nbsp;Qiang Xu,&nbsp;Jianjun Zhao,&nbsp;Fuling Zhang,&nbsp;Weile Li,&nbsp;Xiujun Dong,&nbsp;Jian Yang,&nbsp;Decun Guo,&nbsp;Wantong He","doi":"10.1007/s10064-025-04211-4","DOIUrl":"10.1007/s10064-025-04211-4","url":null,"abstract":"<div><p>The upper reaches of Jinsha River are rich in water resources, so it is planned to develop cascade hydropower stations here. Affected by the subduction between plates and the continuous uplift of the Qinghai-Tibet Plateau, adverse geological phenomena are developed here, especially landslides. Previous studies have mainly focused on single landslides, small-scale areas, lacking of systematic investigations of landslides in the upper reaches of the Jinsha River. Therefore, we used optical remote sensing, InSAR technology, airborne lidar, UAV photography and field geological survey to sort out the large-scale landslide data, and focused on the typical landslides in the basin. There are 252 active landslides and 171 large landslides in the study area, which are characterized by cluster distribution under the influence of Jinsha River suture zone. Landslide has the characteristics of large scale and cluster distribution. The mechanism of typical landslide cases is analyzed in detail. Taking Woda landslide, Baige landslide and Mengu landslide as examples, the main types of landslides in the upper reaches of the Jinsha River are revealed, including the ancient landslide resurrection affected by rainfall and water level change, the deformation of residual rock landslide after sliding, and the local damage of the toppling deformation slope. Considering that ancient landslide is the most typical hidden danger of landslide in the region, the paper further discusses the relationship between the dating time of ancient landslide and the evolution of historical structure and climate, and supposes that the upper reaches of Jinsha River should have experienced strong tectonic activities in the history. The possible influence of hydropower development on landslide disaster in the upper reaches of Jinsha River basin and the regulation effect of cascade power station construction on disaster are further discussed.</p></div>","PeriodicalId":500,"journal":{"name":"Bulletin of Engineering Geology and the Environment","volume":"84 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143645575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Influence mechanisms and control effects of overburden on rock slope stability: case study in Yanqianshan iron mine, China","authors":"Lingfei Zhang,&nbsp;Zhongxin Wang,&nbsp;Jian Cao,&nbsp;Xiangyu Zeng,&nbsp;Fengliang Tian,&nbsp;Fengyang Xin,&nbsp;Junting Huang","doi":"10.1007/s10064-025-04179-1","DOIUrl":"10.1007/s10064-025-04179-1","url":null,"abstract":"<div><p>With the continuous development of mineral resources, many open-pit mines are transitioning to underground mining projects as they reach greater depths. Long-term open-pit mining has resulted in the formation of high, steep slopes, the stability of which is significantly affected by the material overlaying the ore (the “overburden”). Landslide damage characteristics and deformation ranges of the Yanqianshan iron mine are analyzed in this study using unmanned aerial vehicle (UAV) photogrammetry and Small Baseline Subset InSAR (SBAS-InSAR) technology. Based on the limit equilibrium theory, this analysis reveals the control mechanism of the overburden on slope instability; a theoretical approach for calculating overburden thickness is also established using Janssen’s pressure theory. The effects of various treatment schemes are evaluated through a discrete–continuous coupling method and verified by field measurements. The results indicate that the overburden significantly influences slope stability. When the overburden influence coefficient <i>u</i> ≥ 1, it exerts a positive stabilizing effect. The optimal overburden thickness for the Yanqianshan iron mine is determined to be 65.38 m.</p></div>","PeriodicalId":500,"journal":{"name":"Bulletin of Engineering Geology and the Environment","volume":"84 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143645573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of extreme gradient boosting for predicting standard penetration test N-values from cone penetration test data","authors":"Xiao Han,&nbsp;Jiangtao Yi,&nbsp;Xiaobin Li,&nbsp;Siyu Li,&nbsp;Hongyu Tang,&nbsp;Zhen Wang,&nbsp;Jingnian Ran","doi":"10.1007/s10064-025-04219-w","DOIUrl":"10.1007/s10064-025-04219-w","url":null,"abstract":"<div><p>The standard penetration test (SPT) and cone penetration test (CPT) are widely used for subsurface stratigraphic characterization and the determination of geotechnical properties. While the CPT is increasingly adopted in site investigations, the SPT <i>N</i>-value continues to be a key parameter for developing empirical design formulas. As a result, establishing an accurate correlation between CPT data and SPT <i>N</i>-values remains a critical challenge in geotechnical engineering. In this study, a new side-by-side SPT-CPT database is constructed to evaluate existing conventional models, revealing their shortcomings and highlighting the need for a more reliable model. An innovative approach using an Extreme Gradient Boosting (XGBoost) model to predict SPT <i>N</i>-values from CPT data. This model overcomes the limitations of conventional transformation models by leveraging machine learning algorithm that can capture complex relationships within the data. The new XGBoost model incorporates a broader range of input variables compared to conventional models, including cone resistance, sleeve friction, soil behavior type index, fines content, depth of CPT data, and effective overburden stress. Through comparative analyses with other prevalent machine learning models, including random forests, back-propagation artificial neural networks, and support vector machines, we demonstrate that the XGBoost model significantly outperforms both conventional and machine learning-based models in terms of accuracy and robustness.</p></div>","PeriodicalId":500,"journal":{"name":"Bulletin of Engineering Geology and the Environment","volume":"84 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143638206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of leakage seismic attribute characteristics considering the discrete random properties of earth-rock dam media","authors":"Hao Xu,&nbsp;Jiangping Liu,&nbsp;Xuan Xiong,&nbsp;Yuquan Zong,&nbsp;Yuxi Ma","doi":"10.1007/s10064-025-04199-x","DOIUrl":"10.1007/s10064-025-04199-x","url":null,"abstract":"<p>Leakage is a prevalent latent hazard in earth-rock dams. Accurate detection of the location and severity of leakage areas can provide the basis for treating leakage and reducing the damage to the dam. The key to detecting leakage using seismic wave methods is mastering the response characteristics of leakage reflection wavefields and accurately identifying them from the acquired seismic data. In this study, the dam models with different water content leakage areas are established using discrete random modeling method, based on the soil-rock mixture characteristics of the actual dam media. The effects of water content changes on the leakage reflected wavefields are elaborated, and the seismic attributes that can effectively identify leakage wavefields are summarized. Scattering caused by the heterogeneity of the earth-rock dam reduces the energy of leakage reflected waves and complicates the identification of the leakage wavefields. The characteristics of leakage converted waves, primarily low-frequency signals, are more advantageous for identifying leakage wavefields. With the decrease of water content in the leakage area, the energy of converted waves gradually weakens, and the continuity of the phase axis deteriorates. Wavelet transform can enhance the continuity of the leakage reflected phase axis and effectively suppress random noise interference. The combined use of instantaneous frequency and wavelet transform frequency slice allows for more accurate identification of leakage-reflected wavefields.</p>","PeriodicalId":500,"journal":{"name":"Bulletin of Engineering Geology and the Environment","volume":"84 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143632589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning for time series prediction of valley deformation induced by impoundment for high arch dams","authors":"Hang-Hang Zang,&nbsp;Dian-Qing Li,&nbsp;Xiao-Song Tang,&nbsp;Guan Rong","doi":"10.1007/s10064-025-04214-1","DOIUrl":"10.1007/s10064-025-04214-1","url":null,"abstract":"<div><p>This study develops a data-driven hybrid model using machine learning methods to predict the valley deformation induced by impoundment for high arch dams. The elastic net and random forest are employed to identify and rank the key influencing factors of valley deformation as the best input features in the model. The variational mode decomposition (VMD) is introduced to decompose the original nonstationary valley deformation time series. The least square support vector machine (LSSVM) model is constructed to generate the predictions of valley deformation. The sparrow search algorithm (SSA) is utilized to find the optimal model parameters of LSSVM. A practical example involving the time series prediction of valley deformation for the Baihetan high arch dam in China is presented to validate the developed model. The developed model can generate long-term predictions of valley deformation efficiently and accurately based on the present monitoring valley deformation time series. Both the daily reservoir water level and 8-week accumulated rainfall show a significant influence on the valley deformation for the Baihetan high arch dam. The utilization of the VMD and SSA improves the accuracy of the developed model substantially. Thus, the developed VMD-SSA-LSSVM model produces better predictions of the fluctuation trend and turning points of the monitoring time series of valley deformation than the LSSVM model without the VMD and SSA. In addition, the role of VMD is more significant than that of SSA in improving the accuracy of the LSSVM model.</p></div>","PeriodicalId":500,"journal":{"name":"Bulletin of Engineering Geology and the Environment","volume":"84 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143632566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"New insights into the progressive failure process and mechanisms of the 2017 Xinmo Slope in Mao County, China","authors":"Ling Zhu,&nbsp;Xiangjun Pei,&nbsp;Shenghua Cui,&nbsp;Luguang Luo,&nbsp;Hui Wang","doi":"10.1007/s10064-025-04205-2","DOIUrl":"10.1007/s10064-025-04205-2","url":null,"abstract":"<div><p>The Xinmo landslide, one of the most catastrophic landslides in Sichuan Province following the 2008 Wenchuan earthquake, resulted in 10 deaths and 73 missing persons. This event garnered significant attention both in China and worldwide. In this study, we focused on the contributions of historical earthquakes, rainfall, and gravity to the progressive failure of the slope. Through a series of field investigations, rock creep tests, and numerical simulations, we found that the damage in the phyllite layer is significantly greater than that in the surrounding metamorphic sandstone layers, attributed to the incompatible deformation caused by earthquakes. Rainwater infiltrates along the densely developed seismic fractures, leading to the softening of phyllite and a reduction in long-term strength, which is related to the clay mineral expansion, non-uniform deformation, and the dissolution of intergranular cement. We proposed that the Xinmo landslide underwent several processes prior to its initiation, including the triggering, propagation, and coalescence of seismic fractures, the softening of phyllite due to rainwater, and time-dependent deformation.</p></div>","PeriodicalId":500,"journal":{"name":"Bulletin of Engineering Geology and the Environment","volume":"84 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143638370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of the causes of excessive leakage in the fractured rock masses of the Ludila hydropower station dam foundation","authors":"Lifeng Wen,&nbsp;Yanlong Li","doi":"10.1007/s10064-025-04212-3","DOIUrl":"10.1007/s10064-025-04212-3","url":null,"abstract":"<div><p>Seepage complications in fractured rock masses represent a significant concern in hydraulic engineering. This paper aims to investigate non-steady seepage behavior and determine the causes of excessive seepage rates in fractured rock masses containing complex seepage control systems in the Ludila hydropower station dam foundation. To achieve this goal, a novel analysis framework for seepage field in fractured rock masses with sophisticated seepage control systems was proposed. The seepage analysis framework was established by incorporating methods for determining permeability tensor, employing parabolic variational inequality approach which transforms the seepage problem within wet region into a boundary value problem for a fixed area, and utilizing drainage substructure technique. The numerical results closely agreed with empirical observations, which demonstrated effectiveness and suitability for seepage analysis in fractured rock masses with complex seepage control systems of the proposed framework. On this basis, transient seepage behavior and the factors contributing to the excessive seepage rates in the Ludila hydropower station dam foundation were investigated by combination of parametric numerical analysis and measured results. The results indicate that the grouting curtain is the main measure to control the seepage rate. A defective upstream curtain below a 60 m depth emerges as the primary cause for excessive seepage rates on the left bank of the Ludila hydropower station dam foundation. It is crucial to ensure construction quality and integrity of the grouting curtain, especially the bottom grouting curtain, in actual engineering.</p></div>","PeriodicalId":500,"journal":{"name":"Bulletin of Engineering Geology and the Environment","volume":"84 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 dynamic behavior of marine soft soil under cyclic wave loading","authors":"Chun Li,&nbsp;Ping Yang,&nbsp;Zhaoxue Wu,&nbsp;Wei Chen,&nbsp;Yi Cai","doi":"10.1007/s10064-025-04206-1","DOIUrl":"10.1007/s10064-025-04206-1","url":null,"abstract":"<div><p>Many engineering activities are conducted on marine soft soil foundations, with various types of soft soil influencing these projects differently. Studying the engineering characteristics and deformation mechanism of marine soft soil is crucial for the design and construction of marine structures. To reveal the dynamic mechanical characteristics of marine soft soil under wave loading, a set of soil samples under different confining pressure conditions were tested via a dynamic triaxial apparatus. Furthermore, a constitutive model was developed to predict the dynamic strength of marine soft soil subjected to wave loading. The experimental results demonstrate that the dynamic stress‒strain behaviour of marine soft soil progresses through three stages: compaction, deformation, and failure. The dynamic strain‒time history curve of the soil exhibited a cyclic trend characterized by a superposition of monotonic changes, which was attributed to the simultaneous occurrence of plastic deformation and cyclic deformation. The strain rebound gradually disappears with increasing number of loading cycles; the strain accumulation mainly occurs as compressive strain during the postvibration period. Within each stage, the dynamic shear modulus decreases with increasing shear strain, showing consistent curve characteristics across different dynamic stress amplitudes. During long-term cyclic loading, the damping ratio initially decreases and then stabilizes, with a negligible influence from the confining pressure. The Martin‒Davidenkov constitutive model effectively characterizes the correlation between the dynamic shear modulus and shear strain, with fitting curves closely matching the measured data.</p></div>","PeriodicalId":500,"journal":{"name":"Bulletin of Engineering Geology and the Environment","volume":"84 4","pages":""},"PeriodicalIF":3.7,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}