Soils and Foundations最新文献

{"title":"Efficient reliability analysis of unsaturated slope stability under rapid drawdown using XGBoost-based surrogate model","authors":"Wengang Zhang ,&nbsp;Bo Ran ,&nbsp;Xin Gu ,&nbsp;Yanmei Zhang ,&nbsp;Yulin Zou ,&nbsp;Peiqing Wang","doi":"10.1016/j.sandf.2024.101539","DOIUrl":"10.1016/j.sandf.2024.101539","url":null,"abstract":"<div><div>Reservoir slope stability during water level drawdown has drawn increasing concern in geotechnical engineering in recent years. In this study, an efficient reliability analysis framework based on the extreme gradient boosting (XGBoost) surrogate model is employed to evaluate the failure probability of unsaturated slopes subjected to the rapid drawdown considering the depth-dependent properties of spatially varying soils. A <em>c</em>-<em>φ</em> slope is selected as an illustrative example to investigate the coupled influence of the non-stationary characteristic of shear strength parameters and saturated hydraulic conductivity, as well as water level drawdown velocity, maximum drop height and scale of fluctuation on the slope failure probability. Results show that the adopted framework can estimate the low-level probability of slope failure with high accuracy and efficiency. It is found that the velocity and maximum height of water level drawdown have a significant effect on the unsaturated slope stability. Furthermore, it is recommended that the depth-dependent non-stationary soil properties be considered in most cases to ensure a more accurate result.</div></div>","PeriodicalId":21857,"journal":{"name":"Soils and Foundations","volume":"64 6","pages":"Article 101539"},"PeriodicalIF":3.3,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663552","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":"Advancement ratio effect on screw pile performance in the bearing layer","authors":"Adnan Anwar Malik ,&nbsp;Shekh Istiaq Ahmed ,&nbsp;Umair Ali ,&nbsp;Syed Kamran Hussain Shah ,&nbsp;Jiro Kuwano","doi":"10.1016/j.sandf.2024.101537","DOIUrl":"10.1016/j.sandf.2024.101537","url":null,"abstract":"<div><div>The advantages of using screw piles are quite evident nowadays, which enhances its importance in the field of deep foundations. Moreover, the current environmental challenges direct the construction industry towards sustainability, creating more opportunities for such type of piling techniques to be used in the future. Therefore, more investigation is required to optimise screw pile performance in terms of ultimate bearing capacity associated with installation efforts. To explore further, the current study focused on the effect of the advancement ratio on ultimate bearing capacity and work done due to installation load and torque. The model scale of testing is adopted, and two kinds of ground (using Toyoura sand), i.e., scenario I: loose sand over dense sand and scenario II: loose sand, are prepared to install the single helix screw pile. In the case of scenario I, the screw is installed up to 1 times the helix diameter into the dense bearing layer. Based on the experimental results, it was observed that as the advancement ratio (from 0.25 to 1.25) increased, the installation load also increased. On the other hand, the installation torque decreased with the increase in advancement ratio. This was due to the increase in the number of rotations per pitch penetration and the resultant movement of sand particles. The change in the state of the ground around the screw pile is strongly related to the advancement ratio and initial density. The ideal advancement ratio (1.0) is difficult to attain in the field due to high pressing load demand; empirical equations are developed, which can be used to estimate the increase/decrease of ultimate bearing capacity and associated installation requirements in terms of work done for the initial design stage.</div></div>","PeriodicalId":21857,"journal":{"name":"Soils and Foundations","volume":"64 6","pages":"Article 101537"},"PeriodicalIF":3.3,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663550","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":"Spatial earth pressure analysis of clayey fill behind retaining wall in V-shaped gully terrain","authors":"Yun Que ,&nbsp;Jisong Zhang ,&nbsp;Yu Tian ,&nbsp;Xiaosong Li","doi":"10.1016/j.sandf.2024.101538","DOIUrl":"10.1016/j.sandf.2024.101538","url":null,"abstract":"<div><div>Mountain road construction often involves crossing numerous ravine terrains. To ensure road safety, numerous shoulder retaining walls are built to stabilize the roadbed. However, the limitations imposed by gullies result in significant spatial effects on the soil pressure distribution behind the walls, rendering traditional two-dimensional soil pressure theories inadequate. To investigate the spatial distribution of active earth pressure on clayey fill behind the walls, this paper presents a three-dimensional theoretical solution for earth pressure on V-type retaining walls in gully terrains, using theoretical analysis and numerical simulation. The results indicate that the clayey fill causes a slip crack behind the wall, forming a tension crack region with zero earth pressure, the depth of which increases with the fill’s cohesive force. Additionally, the earth pressure distribution behind the V-type retaining wall exhibits a significant spatial effect, being “larger in the middle and smaller at the ends” along the wall’s width. Compared to traditional two-dimensional theories, the earth pressure predicted by this spatial theory is lower, and the resultant force location is higher, and the overturning resistance in region III is largest. Therefore, this part should be enhanced in construction design.</div></div>","PeriodicalId":21857,"journal":{"name":"Soils and Foundations","volume":"64 6","pages":"Article 101538"},"PeriodicalIF":3.3,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663551","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":"Instability of sand under a lateral extrusion stress path with different drainage conditions","authors":"Antonio Souza ,&nbsp;Ana Claudia Telles ,&nbsp;David Reid ,&nbsp;Andy Fourie ,&nbsp;Marcio Almeida","doi":"10.1016/j.sandf.2024.101529","DOIUrl":"10.1016/j.sandf.2024.101529","url":null,"abstract":"<div><div>A series of lateral extrusion (LE) tests were carried out on silica fine sand using the triaxial device to study the initiation of instability under various drainage conditions on this stress path. All specimens were reconstituted using the moist tamping technique, having achieved state parameter (ψ₀) values between −0.020 and +0.086 after anisotropic consolidation. The LE stress path consists in a decrease of mean effective stress and increase of the deviator stress at a constant rate, maintaining the vertical stress constant. The LE tests were performed either with the drainage valves open or with undrained increments followed by drainage. Different magnitudes of undrained increments were tested. For the same initial state parameter, the results indicated that the instability stress ratio (<span><math><mrow><mi>η</mi></mrow></math></span><em>_IL</em>) decreases as drainage conditions changes from drained to undrained/drained increments. As the magnitude of the undrained increment increases, <span><math><mrow><mi>η</mi></mrow></math></span><em>_IL</em> decreases. Further, consistent with previous studies, the test data shows that the static liquefaction can be triggered in tests where the drainage valves are open, generating high values of excess of pore pressure only after the onset of instability. The results were also compared to results from CSD and CAU tests.</div></div>","PeriodicalId":21857,"journal":{"name":"Soils and Foundations","volume":"64 6","pages":"Article 101529"},"PeriodicalIF":3.3,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663593","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":"Inverse analysis for estimating geotechnical parameters using physics-informed neural networks","authors":"Shinichi Ito ,&nbsp;Ryusei Fukunaga ,&nbsp;Kazunari Sako","doi":"10.1016/j.sandf.2024.101533","DOIUrl":"10.1016/j.sandf.2024.101533","url":null,"abstract":"<div><div>Physics-informed neural networks (PINNs) have been proposed for incorporating physical laws into deep learning. PINNs can output solutions that satisfy physical laws by introducing information, such as partial differential equations (PDEs), boundary conditions, and initial conditions, into the loss functions used during the construction of the neural network model. This study presents two cases in which geotechnical parameters were estimated through an inverse analysis of PINNs. PINNs were applied to simulate consolidation and unsaturated seepage processes. The inverse analysis of the PINNs helped estimate the coefficient of consolidation and the parameters related to the unsaturated soil hydraulic properties with sufficient accuracy. The inverse analysis of PINNs for geotechnical parameter estimation was found to be an effective approach that utilizes measurement data.</div></div>","PeriodicalId":21857,"journal":{"name":"Soils and Foundations","volume":"64 6","pages":"Article 101533"},"PeriodicalIF":3.3,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663592","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":"Electrodeposition-based self-healing technique for structures with loosely compacted sand","authors":"Ibuki Nishimura,&nbsp;Hitoshi Matsubara","doi":"10.1016/j.sandf.2024.101535","DOIUrl":"10.1016/j.sandf.2024.101535","url":null,"abstract":"<div><div>The natural erosion of sand along coastlines and in landfills is a complex phenomenon influenced by interactions among currents, waves, tides, and wind. Countermeasures against internal erosion in landfills often involve installing geotextile sheets and/or filters between seawalls and landfills. However, the mere installation of such structures proves insufficient for comprehensively monitoring and mitigating soil erosion, and ensuring adequate ground stability and safety is challenging. This study focuses on the application of electrodeposition for mitigating soil erosion and potentially repairing these structures. By applying a weak electric current to severely deteriorated objects, carbonate minerals, called electrodeposits, are deposited on the cathode side and can repair vulnerable areas through self-organized solidification. Experiments were conducted using various silica sand specimens to assess the applicability of electrodeposition to discrete sand. The results revealed that, in specimens with relatively large sand particles, such as those in silica sand No. 3, the sand adhered to the cathode, forming a solidified area approximately 15–17 mm high. A microstructural analysis indicated the presence of crystallized minerals resembling calcium carbonate bonding within the interstitial spaces between the sand particles. These experimental findings suggest that electrodeposition can be applied to enhance the stability and safety of sandy soil-based structures.</div></div>","PeriodicalId":21857,"journal":{"name":"Soils and Foundations","volume":"64 6","pages":"Article 101535"},"PeriodicalIF":3.3,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663553","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":"Modeling effect of rock shape characteristics on run-out distribution of rockfalls","authors":"T. Yoshida ,&nbsp;R. Nomura ,&nbsp;Y. Tuda ,&nbsp;I. Yoshida ,&nbsp;K. Terada ,&nbsp;S. Moriguchi","doi":"10.1016/j.sandf.2024.101531","DOIUrl":"10.1016/j.sandf.2024.101531","url":null,"abstract":"<div><div>The aim of this study was to analyze and model the effect of rock shapes on the run-out distribution characteristics of rockfalls. To this end, we conducted a parametric study of rockfall simulations using the discrete element method, which is a numerical simulation method capable of directly representing rock shapes. The results indicated a strong correlation between the sphericity of rocks and the run-out distribution characteristics, expressed by two types of sphericity. Furthermore, we developed a regression model that can predict the run-out distribution using these two sphericities and the parameters of the calculation conditions as the explanatory variables. Although there is some room for improvement in terms of the developed regression model, it was confirmed that the relationship between the sphericity of rocks and the run-out distribution characteristics suggests the potential to enhance efficient rockfall risk assessments through numerical analysis.</div></div>","PeriodicalId":21857,"journal":{"name":"Soils and Foundations","volume":"64 6","pages":"Article 101531"},"PeriodicalIF":3.3,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663554","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":"Crack evolution mechanism of stratified rock mass under different strength ratios and soft layer thickness: Insights from DEM modeling","authors":"Qinji Jia,&nbsp;Xiaoming Liu,&nbsp;Xin Tan","doi":"10.1016/j.sandf.2024.101534","DOIUrl":"10.1016/j.sandf.2024.101534","url":null,"abstract":"<div><div>Research on stratified rock masses, which are common geological formations, has primarily focused on their mechanical properties, while studies on crack evolution and microscopic damage mechanisms remain limited. This study addresses this gap by investigating the combined effects of strength ratios and soft layer thicknesses on the microcrack evolution mechanism of stratified rocks using the discrete element method (DEM). Through FISH language programming in the particle flow code (PFC), this study reveals the acoustic emission (AE) characteristics, crack initiation and propagation, damage degree, and final failure characteristics. The key findings are: (1) Higher strength ratios between the hard and soft components of stratified rocks make specimens more sensitive to increases in soft layer thickness. (2) Three types of AE events were identified: continuous active, intermittent active, and silent. (3) Cracks initiate at the interface between components and propagate along the interface into the rock matrix. The strength ratios determine the crack propagation path and the damage extent of the components. (4) The failure of stratified rocks is primarily controlled by the soft component. Crack connections typically form vertical and sub-vertical tensile failure planes in the hard component, and a shear failure surface with a “V”-shaped intersection in the soft component.</div></div>","PeriodicalId":21857,"journal":{"name":"Soils and Foundations","volume":"64 6","pages":"Article 101534"},"PeriodicalIF":3.3,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663555","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":"Natural soils’ shear strength prediction: A morphological data-centric approach","authors":"Maher Omar ,&nbsp;Mohamed G. Arab ,&nbsp;Emran Alotaibi ,&nbsp;Khalid A. Alshibli ,&nbsp;Abdallah Shanableh ,&nbsp;Hussein Elmehdi ,&nbsp;Dima A. Hussien Malkawi ,&nbsp;Ali Tahmaz","doi":"10.1016/j.sandf.2024.101527","DOIUrl":"10.1016/j.sandf.2024.101527","url":null,"abstract":"<div><div>The deformation characteristics and constitutive behavior of granular materials under normal forces acting on particles are dependent on the geometry of the grain structure, fabrics and the inter-particle friction. In this study, the influence of particle morphology on the friction and dilatancy of five natural sands was investigated using deep learning (DL) techniques. A Three-dimensional (3D) imaging technique using computed tomography was utilized to compute the morphology (roundness and sphericity) of collected natural sands. Triaxial tests were conducted on the five different natural sands at different densities and confinement stresses (<em>σ₃</em>). From the triaxial results, peak friction angle (<span><math><mrow><msub><mi>φ</mi><mi>p</mi></msub><mrow><mo>)</mo></mrow></mrow></math></span>, critical state friction angle (<span><math><mrow><msub><mi>φ</mi><mrow><mi>c</mi><mi>s</mi></mrow></msub></mrow></math></span>), and dilatancy angle (ψ) were obtained and modeled using conventional multiple linear regression (MLR) models and DL techniques. A total of 100 deep artificial neural networks (DANN) models were trained at different sizes of first and second hidden layers. The use of MLR resulted in R² of 0.709, 0.565, and 0.795 for <span><math><mrow><msub><mi>φ</mi><mi>p</mi></msub></mrow></math></span>, <span><math><mrow><msub><mi>φ</mi><mrow><mi>c</mi><mi>s</mi></mrow></msub></mrow></math></span> and <em>ψ</em>, respectively, while the best performed DANN (30 and 50 neurons for the 1st and 2nd hidden layers, respectively) had R² of 0.956 for all outputs (<span><math><mrow><msub><mi>φ</mi><mi>p</mi></msub></mrow></math></span>, <span><math><mrow><msub><mi>φ</mi><mrow><mi>c</mi><mi>s</mi></mrow></msub></mrow></math></span> and <em>ψ</em>) combined. Using the best-performed DANN model, the weight partitioning technique was used to compute an importance score for each parameter in predicting <span><math><mrow><msub><mi>φ</mi><mi>p</mi></msub></mrow></math></span>, <span><math><mrow><msub><mi>φ</mi><mrow><mi>c</mi><mi>s</mi></mrow></msub></mrow></math></span> and <em>ψ</em>. The <em>σ₃</em> had the highest importance followed by relative density, roundness, and sphericity with a relative importance of more than 10%. In addition, sensitivity analysis was conducted to investigate the effect of each parameter on the shear parameters and ensure the robustness of the developed model.</div></div>","PeriodicalId":21857,"journal":{"name":"Soils and Foundations","volume":"64 6","pages":"Article 101527"},"PeriodicalIF":3.3,"publicationDate":"2024-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142586799","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":"Estimating S-wave velocity profiles from horizontal-to-vertical spectral ratios based on deep learning","authors":"Koichi Hayashi ,&nbsp;Toru Suzuki ,&nbsp;Tomio Inazaki ,&nbsp;Chisato Konishi ,&nbsp;Haruhiko Suzuki ,&nbsp;Hisanori Matsuyama","doi":"10.1016/j.sandf.2024.101525","DOIUrl":"10.1016/j.sandf.2024.101525","url":null,"abstract":"<div><div>S-wave velocity (Vs) profile or time averaged Vs to 30 m depth (V_S30) is indispensable information to estimate the local site amplification of ground motion from earthquakes. We use a horizontal-to-vertical spectral ratio (H/V) of seismic ambient noise to estimate the Vs profiles or V_S30. The measurement of H/V is easier, compared to active surface wave methods (MASW) or microtremor array measurements (MAM). The inversion of H/V is non-unique and it is impossible to obtain unique Vs profiles. We apply deep learning to estimate the Vs profile from H/V together with other information including site coordinates, deep bedrock depths, and geomorphological classification. The pairs of H/V spectra (input layer) and Vs profiles (output layer) are used as training data. An input layer consists of an observed H/V spectrum, site coordinates, deep bedrock depths, and geomorphological classification, and an output layer is a velocity profile. We applied the method to the South Kanto Plain, Japan. We measured MASW, MAM and H/V at approximately 2300 sites. The pairs of H/V spectrum together with their coordinates, geomorphological classification etc. and Vs profile obtained from the inversion of dispersion curve and H/V, compose the training data. A trained neural network predicts Vs profiles from the observed H/V spectra with other information. Predicted Vs profiles and their V_S30 are reasonably consistent with true Vs profiles and their V_S30. The results implied that the deep learning could estimate Vs profile from H/V together with other information.</div></div>","PeriodicalId":21857,"journal":{"name":"Soils and Foundations","volume":"64 6","pages":"Article 101525"},"PeriodicalIF":3.3,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142552414","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}