Engineering Geology最新文献

{"title":"Interfacial shearing characteristics between siliceous sand and the various scales of bioinspired scaled suction caisson during penetration","authors":"Jipeng Zhao ,&nbsp;Dayong Li ,&nbsp;Yukun Zhang","doi":"10.1016/j.enggeo.2025.108040","DOIUrl":"10.1016/j.enggeo.2025.108040","url":null,"abstract":"<div><div>Siliceous sand is widely encountered in the Yellow Sea, China, in which offshore wind and photovoltaic farms have been gradually constructed. The suction caisson has been proven to be suitable to support the upper structures due to its easy installation and retrieval. However, the high strength and compactness of the siliceous sand may increase the difficulty in the suction caisson installation. Also, the soil parameters are the key factors in designing the suction caisson. Therefore, this study proposes an innovative scaled suction caisson (SSC), which features easy penetration, high bearing capacity, and elimination of grouting in the gap between the soil plug and the cap. Compared with the traditional suction caisson, a bio-inspired design concept on its outer sidewall mimics the characteristics of snake belly scales to reduce resistance during installation and to increase resistance when being subjected to uplift. Smooth penetration to the design depth is crucial under reasonable arrangement of the scales. Therefore, the arrangement of scales on the outer sidewall in the design of the SSC is examined through a series of direct shear tests. The interface shear behaviors of sand-sand and sand-scaled steel are investigated with various scale types, scale heights, scale aspect ratios, sand grain gradations, and normal stresses. Results show that the sand-sand interface exhibits strain softening. The amount of sand roundness exceeding 0.7 for sizes 0.5–1.0 mm and 1.0–2.0 mm is 67.92 % and 41.55 %, respectively. Under identical sand particle size and normal stress conditions, the interface shear stress at the sand-scaled steel increases first and then decreases with increasing scale height for similar types of scales. Under normal stresses of 200 kPa and 400 kPa, the number of sand particles in 0.5–1.0 mm increases by 7.96 % and 8.29 %, respectively, after shearing for sand size 1.0–2.0 mm with scaled steel plates. In addition, as the scale height increases during shearing, two shear zones are observed: the sand-scaled steel shear zone and the sand-sand shear zone. Meanwhile, the theoretical formulas for calculating the critical shear stress are obtained. Finally, the peak shear stress, stress ratios and sand vertical movement at the sand-scaled steel interface are analyzed, determining the optimal geometric characteristics and arrangement of scales. This study can provide guidance for the construction of foundation structure in marine geological engineering of siliceous sand.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"351 ","pages":"Article 108040"},"PeriodicalIF":6.9,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143678176","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":"Numerical estimation of river blockage and the whole lifecycle of landslide-generated impulse waves in mountain reservoirs using a hybrid DEM-SPH and SWEs method","authors":"Hangsheng Ma ,&nbsp;Huanling Wang ,&nbsp;Weiya Xu ,&nbsp;Hongjuan Shi ,&nbsp;Jing Hou","doi":"10.1016/j.enggeo.2025.108022","DOIUrl":"10.1016/j.enggeo.2025.108022","url":null,"abstract":"<div><div>Landslides occurring in mountain reservoirs could induce severe geological hazards, posing substantial risks on both the infrastructure and life. Considering the hazards always encompass different spatial and temporal scales, this paper proposes a novel hybrid Discrete Element Method (DEM) - Smoothed Particle Hydrodynamics (SPH) and Shallow Water Equations (SWEs) method to study the landslide motion and the whole lifecycle of LGIWs in a mountain reservoir. In the proposed method, the connecting between the DEM-SPH model and SWEs model is realized by transferring the hydrodynamic condition from the DEM-SPH model to SWEs model after the landslide halts, and the topography of the river channel is reconstructed based on the deposit morphology. After the validation, this method is applied to predict the hazard chains induced by ZJ landslide. The processes of landslide sliding, accumulation, impulse wave generation, propagation, running up on the dam, and dissipation are studied. The deposit morphology of the landslide and the distribution of the maximum water level are obtained. In addition, some special phenomena, such as the drainage of water from the deposit, dam-break-liked impulse waves, multiple reflections of impulse waves between the deposit and dam, and the rise of water level, are discovered under the influence of both river topography and landslide deposit. This study presents the first application of the 3D coupled DEM-SPH model in the nested near-field and far-field method, provides a useful method to comprehensively study the whole landslide-induced hazard chains in mountain reservoirs, and offers valuable references for disaster prevention and reduction.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"351 ","pages":"Article 108022"},"PeriodicalIF":6.9,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143675565","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":"Analysis of fracture spatial distributions and fast reconstruction of discrete fracture networks model based on non-parametric kernel density estimation method","authors":"Xianzhen Mi ,&nbsp;Liyuan Yu ,&nbsp;Jing Zhang ,&nbsp;Richeng Liu ,&nbsp;Bowen Hu ,&nbsp;Shikai Qiu","doi":"10.1016/j.enggeo.2025.108034","DOIUrl":"10.1016/j.enggeo.2025.108034","url":null,"abstract":"<div><div>Fracture spatial distributions significantly impact the mechanical properties of rocks and play a vital role in subsurface flow and transmission. However, many studies generate random geometrical distributions for fractures, leading to unrealistic subsurface models. This paper describes a new method for analyzing and modeling fracture spatial distributions based on borehole and outcrop observations. The center of gravity of the fracture is used to define the fracture position, and the non-parametric kernel density estimation is used to analyze the cluster distribution of the fractures in space. Then, the Fast Fourier Transform (FFT) is utilized to rapidly determine the fracture position. Finally, the length and occurrence of fractures are generated by the Monte Carlo method, and the discrete fracture network (DFN) is reconstructed in Matlab. This approach is applied to three field examples. Numerical simulations demonstrate that the generated fracture morphology exhibits flow behavior similar to the original fracture network. Furthermore, it is found that the fractal dimension of the fracture center point (<em>C</em>) can characterize the spatial distribution of fractures and shows a logarithmic normal relationship with fracture permeability. This modeling method accelerates the speed of complex DFN reconstruction and improves the ability to quantify the permeability of fractured rock mass.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"351 ","pages":"Article 108034"},"PeriodicalIF":6.9,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143675561","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":"Improving soil liquefaction prediction: A sophisticated ensemble classifier utilizing enhanced correlation features and a metaheuristic ant colony optimization approach","authors":"Nerusupalli Dinesh Kumar Reddy,&nbsp;Diksha,&nbsp;Ashok Kumar Gupta,&nbsp;Anil Kumar Sahu","doi":"10.1016/j.enggeo.2025.108036","DOIUrl":"10.1016/j.enggeo.2025.108036","url":null,"abstract":"<div><div>Soil liquefaction is a major contributor to earthquake damage. Evaluating the potential for liquefaction by conventional experimental or empirical methods is both time-intensive and laborious. Utilizing a machine learning model capable of precisely forecasting liquefaction potential might diminish the time, effort, and expenses involved. This research introduces an innovative predictive model created in three phases. Initially, correlation analysis determines essential elements affecting liquefaction. Secondly, predictions are produced using Convolutional Neural Networks (CNN) and Deep Belief Networks (DBN), verified by K-fold cross-validation to guarantee resilience. Third, Ant Colony Optimization (ACO) improves outcomes by increasing convergence efficiency and circumventing local minima. The suggested EC + ACO model substantially surpassed leading approaches, such as SVM-GWO, RF-GWO, and Ensemble Classifier-GA, attaining a very low False Negative Rate (FNR) of 2.00 % when trained on 90 % of the data. A thorough performance evaluation shown that the model achieved a cost value of 1.133 % by the 40th iteration, exceeding the performance of other models such SVM-GWO (1.412 %), RF-GWO (1.305 %), and Biogeography Optimized-Based ANFIS (1.7439 %). The model exhibited significant improvements in convergence behavior, with a steady decline in cost values, especially between the 20th and 50th iterations. Additional validation using empirical data from the Tohoku-oki, Great East Japan earthquake substantiated the EC + ACO model's enhanced accuracy and dependability in mirroring observed results. These findings underscore the model's resilience and efficacy, providing a dependable method for forecasting soil liquefaction and mitigating its seismic effects.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"351 ","pages":"Article 108036"},"PeriodicalIF":6.9,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143675563","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":"Data-driven framework for predicting rate of penetration in deepwater granitic formations: A marine engineering geology perspective with comprehensive model interpretability","authors":"Yichi Zhang ,&nbsp;Liang Yu ,&nbsp;Lele Yang ,&nbsp;Zhiqiang Hu ,&nbsp;Yaxin Liu","doi":"10.1016/j.enggeo.2025.108039","DOIUrl":"10.1016/j.enggeo.2025.108039","url":null,"abstract":"<div><div>Deepwater oil and gas resources are vital for meeting global energy demand, supporting economic growth, and ensuring energy security. The marine engineering geology of deepwater environment presents significant challenges for drilling operations, with rock behavior of deep granitic formations increasing the risk of well control incidents. Rate of Penetration (ROP) is a crucial parameter for evaluating efficiency, ensuring operational safety and controlling economic costs of deep-water drilling. In recent years, data-driven methods have provided new ways for predicting ROP in deepwater drilling. In this work, the database is derived from actual deepwater drilling operations at depths ranging from 2203 to 2938 m in China and three different data-driven methods are used to predict ROP based on field measured deepwater drilling data. After preliminary screening, the results show that the method of LightGBM has the best prediction performance. Subsequently, hyperparameter optimization has been conducted based on Bayesian principle. A comprehensive model interpretability approach based upon SHAP and PDP is adopted to conduct explanatory analysis on the improved LightGBM from global and local perspectives. The contribution degree of different feature variables to ROP is obtained as follows: TORQUE, BitTime, Pump Time, WHO (weight on hook), SPP (standpipe pressure), WOB (weight on bit), FLWPump (flow pump), and RPM (revolution per minute). Furthermore, the impact of important feature variables on ROP is analyzed with consideration of actual operating conditions and drilling hydraulics.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"351 ","pages":"Article 108039"},"PeriodicalIF":6.9,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143675562","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":"Study on the propagation law of blast-induced vibration waves in landfill","authors":"Dian Chen ,&nbsp;Yong-gui Chen ,&nbsp;Wei-min Ye ,&nbsp;Hong-yang Zheng ,&nbsp;Guang-hui Lei ,&nbsp;Qing-zhong Lai","doi":"10.1016/j.enggeo.2025.108038","DOIUrl":"10.1016/j.enggeo.2025.108038","url":null,"abstract":"<div><div>When a tunnel is constructed using drilling and blasting techniques beneath a landfill, investigating the propagation laws of blast-induced vibration waves within the landfill is crucial for ensuring the successful construction of the tunnel and maintaining the stability of the landfill. This study, based on on-site monitoring data, employed the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise-Hilbert transform (CEEMDAN-HT) method to conduct a detailed analysis of typical blasting signals. The results indicate that the blast-induced vibration waves attenuated with distance from the blast source. The liner at the bottom of the landfill and landfill body accelerated the attenuation. These led to a reduction in peak particle velocity (PPV), a decrease in total energy and an increased proportion of energy in the low-frequency band. Maximum single-stage charge and elevation led to an increase in PPV, an augmentation of total energy, and an elevated proportion of energy in the low-frequency band of the vibration wave, which were highly unfavorable for the stability of the landfill. Zero-crossing frequency was more appropriate as the main frequency of blasting vibration waves in the landfill. The applicability of classical formulas for predicting main frequency and PPV in landfills was validated using measured data. Additionally, site-specific prediction formulas for main frequency and PPV were proposed through dimensional analysis, which aligned well with on-site monitoring data. The results of this study can offer reference for the design of blasting parameters and construction control in similar engineering projects.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"351 ","pages":"Article 108038"},"PeriodicalIF":6.9,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143675566","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":"Liquefaction susceptibility mapping using artificial neural network for offshore wind farms in Taiwan","authors":"Chih-Yu Liu,&nbsp;Cheng-Yu Ku,&nbsp;Ting-Yuan Wu,&nbsp;Yu-Jia Chiu,&nbsp;Cheng-Wei Chang","doi":"10.1016/j.enggeo.2025.108013","DOIUrl":"10.1016/j.enggeo.2025.108013","url":null,"abstract":"<div><div>In seismically active Taiwan, soil liquefaction poses a significant challenge to offshore wind farm development. This study introduces an advanced artificial neural network (ANN) model to assess liquefaction susceptibility, trained on a synthetic database using parameters from the NCEER method. Among six machine learning techniques evaluated, the proposed ANN model demonstrated outstanding predictive accuracy, achieving 100 % accuracy in distinguishing between liquefaction and non-liquefaction across 112 actual cases. A key innovation of this model is its ability to maintain high accuracy over 91 % using fewer input parameters than traditional methods. This study expands the use of geographic information system integrated with the ANN model to predict soil liquefaction potential at offshore wind farm sites, utilizing 120 offshore borehole logs from previously unassessed marine areas in western Taiwan. Results indicate that six out of the twelve offshore wind farm areas have the highest liquefaction potential across all three depths. The study also highlights the critical role of the SPT-N value in offshore liquefaction assessments.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"351 ","pages":"Article 108013"},"PeriodicalIF":6.9,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143675545","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":"Volume change and mechanical behavior of weakly expansive soils under wetting–drying cycles with different hydraulic coupling paths","authors":"Senwei Wang ,&nbsp;Weimin Yang ,&nbsp;Chuan Wang ,&nbsp;Meixia Wang ,&nbsp;Chuanyi Ma ,&nbsp;Zhiyuan Zhang ,&nbsp;Enming Zhang ,&nbsp;Linkun Jin","doi":"10.1016/j.enggeo.2025.108030","DOIUrl":"10.1016/j.enggeo.2025.108030","url":null,"abstract":"<div><div>Improper anti-drainage treatment of weakly expansive soil subgrades can lead to significant post-construction deformation and uneven settlement, which severely affect the operational safety and service life of engineering projects. To comprehensively analyze the evolution of soil volume and strength under different hydraulic coupling paths during wetting-drying (W-D) cycles, a loaded W-D cycle testing device was developed. Soil volume was measured during the W-D cycles, and the shear strength and soil-water characteristic curves were analyzed after different cycles. The results indicate that during the W-D cycles, changes in soil volume and strength exhibited distinct stages with similar evolution characteristics. Under the investigated loading conditions, the soil demonstrated significant collapsibility during the wetting process, which gradually diminished as the number of cycles increased. Eventually, the W-D cycles caused the soil to reach an equilibrium state, where its swelling and shrinkage behavior became nearly elastic. At equilibrium state, there is a corresponding void ratio for any moisture content, which is the elastic void ratio (<span><math><msub><mi>e</mi><mrow><mn>0</mn><mi>el</mi></mrow></msub></math></span>). The <span><math><msub><mi>e</mi><mrow><mn>0</mn><mi>el</mi></mrow></msub></math></span> is irrespective of the number of cycles and initial dry density. Conversely, higher load and larger amplitude in W-D cycles tend to decrease the <span><math><msub><mi>e</mi><mrow><mn>0</mn><mi>el</mi></mrow></msub></math></span>. Furthermore, by correlating the unsaturated soil matric suction, secant modulus, and stress path, the volume evolution mechanism of the soil was analyzed based on the soil effective stress theory and pore evolution. The results of this study can serve as a crucial reference point for revealing the deformation mechanism of weakly expansive soil subgrades and selecting appropriate road settlement control methods.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"351 ","pages":"Article 108030"},"PeriodicalIF":6.9,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644683","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":"Estimating VS30 structure from topographic and geological data in the southeast of Spain","authors":"Manuel Navarro ,&nbsp;Fernando López ,&nbsp;Pedro Martínez-Pagán ,&nbsp;Antonio García-Jerez ,&nbsp;Marcos A. Martínez-Segura ,&nbsp;Yoshiya Oda ,&nbsp;Takahisa Enomoto","doi":"10.1016/j.enggeo.2025.108037","DOIUrl":"10.1016/j.enggeo.2025.108037","url":null,"abstract":"<div><div>The V_S30 was introduced as a representative parameter of the site's seismic amplification and is currently considered to prescribe site-dependent design response spectra. Although the determination of V_S30 by geophysical methods can be time-consuming, using empirical relationships between this quantity and the slope of the terrain is a rapid and very low-cost procedure that may be sufficient for some applications. A specific correlation at regional scale is performed using 3216 measurements of V_S30 obtained from SPAC, MASW and Mini-array seismic methods, located within 8 municipalities belonging to the Spanish provinces of Almería, Granada and Murcia. The measurement points have been grouped into 10 classes with different seismic behavior according to the geological units represented on the Geological Map of Spain (MAGNA_50). Two relationships have been fitted: a) Model 1 consisting of a linear dependence between the logarithm of Vs30 and the ground slope; b) a linear relationship between log(V_S30) and the slope including the dependence on the geological units through additive constants (model M2). The best-fitted regional V_s30 model is built from a DEM with a resolution of 100 m, in which the incorporation of geological units has demonstrated its convenience in reducing residual errors by up to 28 %. The mean absolute residual obtained at the V_S30 sampling sites was 80 m/s for model M1 and 64 m/s for model M2. The mean estimated V_S30 values obtained from model M2 range between 360 ± 130 m/s in the marshes and wetlands formation and 750 ± 69 m/s in the geological unit composed of quartzites, schists and phyllites.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"351 ","pages":"Article 108037"},"PeriodicalIF":6.9,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644684","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 coupled probabilistic site characterization method for estimating soil stratification and spatial variability using multiple-source site investigation data","authors":"Xueyou Li ,&nbsp;Yongxin Zhang ,&nbsp;Zhiwen Li ,&nbsp;Zhiyong Yang ,&nbsp;Xiaohui Qi","doi":"10.1016/j.enggeo.2025.108024","DOIUrl":"10.1016/j.enggeo.2025.108024","url":null,"abstract":"<div><div>Probabilistic site characterizations, which primarily involve delineating soil stratification and assessing the spatial variability of soil properties, is crucial for geotechnical reliability analysis and risk assessment. Geotechnical site investigation typically produces sparse, multiple-source and multiple-type data. However, most current site characterization methods can only handle a single type of data such as cone penetration test (CPT) data and address the stratification uncertainty and the spatial variability of soil properties separately. To overcome these limitations, this study proposes a coupled probabilistic site characterization method that integrates the Markov random field and Gibbs sampler methods to simultaneously quantify both types of uncertainties. The Markov random field (MRF) is used to estimate the distribution of the soil stratification while the Gibbs sampler is used to construct the probability density function (PDF) of soil properties for each soil stratum. The Bayesian method is employed to account for the interaction between soil stratification and the spatial variability of soil properties. The proposed method is demonstrated through application to a virtual site and a real project site in Hong Kong. Results show that the proposed method effectively leverages limited multi-source site investigation data, considering the interactions between stratigraphic uncertainty and the spatial variability of soil properties. It delivers higher prediction accuracy of soil stratification compared to the Markov random field alone and models the spatial variability of soil properties more effectively.</div></div>","PeriodicalId":11567,"journal":{"name":"Engineering Geology","volume":"351 ","pages":"Article 108024"},"PeriodicalIF":6.9,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143678177","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}