Computers and Geotechnics最新文献

{"title":"Artificial intelligence transformations in geotechnics: progress, challenges and future enablers","authors":"Brian Sheil ,&nbsp;Christos Anagnostopoulos ,&nbsp;Róisín Buckley ,&nbsp;Matteo Oryem Ciantia ,&nbsp;Eky Febrianto ,&nbsp;Jinlong Fu ,&nbsp;Zhiwei Gao ,&nbsp;Xueyu Geng ,&nbsp;Bin Gong ,&nbsp;Kevin Hanley ,&nbsp;Pengpeng He ,&nbsp;Kostas Kolomvatsos ,&nbsp;Bruna de C.F.L. Lopes ,&nbsp;Jelena Ninic ,&nbsp;Marco Previtali ,&nbsp;Mohammad Rezania ,&nbsp;Agustin Ruiz-Lopez ,&nbsp;Jin Sun ,&nbsp;Stephen Suryasentana ,&nbsp;David Taborda ,&nbsp;Pin Zhang","doi":"10.1016/j.compgeo.2025.107604","DOIUrl":"10.1016/j.compgeo.2025.107604","url":null,"abstract":"<div><div>Our reliance on the underground space to deliver critical civil engineering infrastructure is growing: to accommodate utility and transport infrastructure in urban environments, to provide innovative housing and commercial solutions, and to support proliferating renewable energy infrastructure, particularly offshore. Artificial intelligence (AI) is arguably the most promising enabler to transform geotechnical engineering by extracting knowledge from data to achieve step-change increases in efficiency, sustainability, reliability and safety. This paper seeks to develop a shared understanding of the state of the art of AI in geotechnics and to explore future developments. By way of example, specific popular use cases in geotechnics are considered to highlight current progress in AI applications including intelligent site investigation, predictive modelling for soil behaviour, and optimisation of design and construction processes. The paper then addresses key research challenges, such as data scarcity and interpretability, and discusses the opportunities that lie ahead in the integration of AI with geotechnical engineering. Finally, priority technological enablers are identified for future transformations.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"189 ","pages":"Article 107604"},"PeriodicalIF":6.2,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145010812","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":"Probabilistic analysis of top deflection of laterally loaded piles considering spatially variable soil stiffness","authors":"Yongbo Gan ,&nbsp;Yajun Li ,&nbsp;Honghu Zhu ,&nbsp;Bin Zhang","doi":"10.1016/j.compgeo.2025.107592","DOIUrl":"10.1016/j.compgeo.2025.107592","url":null,"abstract":"<div><div>Pile foundations represent one of the most prevalent foundation types utilized in offshore geotechnical engineering for deep foundations. For the laterally loaded piles which primarily experience bending deformation, engineers are mainly concerned about the characteristics of the pile top deflection under the action of lateral load during the service period. Due to the spatial variability of soil properties, the pile top deflection may still exceed the design maximum allowable deflection under the requirements of Serviceability Limit State (SLS), and the probabilistic approach can address this issue. This paper investigates the failure probability of a single pile’s top deflection in consideration of the spatial variability of soil lateral stiffness. Using the random finite element method (RFEM), the statistical characteristics of the pile top deflection under different degrees of soil stiffness variability are analyzed. Based on the local average theory, an approximate analytical method is proposed. This method is verified by the Monte Carlo simulation (MCS) results of random finite element analysis. The results demonstrate that the analytical method can accurately predict the statistical characteristics and failure probability of the pile top deflection. It offers an alternative to the complicated Monte Carlo simulations, and provides a convenient tool for estimating the failure probability of pile top deflection for laterally loaded piles.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"189 ","pages":"Article 107592"},"PeriodicalIF":6.2,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019311","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 composite constitutive model for municipal solid waste considering multiple influencing factors","authors":"Dian Chen ,&nbsp;Yong-gui Chen ,&nbsp;Zhao Sun ,&nbsp;Yong-feng Deng ,&nbsp;Wei-min Ye ,&nbsp;Qiong Wang","doi":"10.1016/j.compgeo.2025.107615","DOIUrl":"10.1016/j.compgeo.2025.107615","url":null,"abstract":"<div><div>The stability of landfills poses a significant challenge to both environmental protection and safety, and the constitutive model of municipal solid waste (MSW) plays a crucial role in the nonlinear numerical analysis of landfill stability. This study proposes a composite constitutive model for MSW, which comprehensively considers the effects of fiber reinforcement, particle compression, mechanical creep, biodegradation, and dynamic loading. Based on a two-phase assumption, the model conceptualizes MSW as consisting of two phases: the basic phase and the fiber phase. The basic phase incorporates bounding-surface plasticity theory, considering the influences of particle compression, mechanical creep, biodegradation, and dynamic loading during specific volume evolution, boundary surface hardening, and the calculation of stress and strain. The fiber phase is modeled using an ideal elastic model to represent the fiber reinforcement effect. By constructing coupled equations, the two phases are successfully integrated into a unified constitutive model. Validation against triaxial test data from the literature demonstrates that the model’s predictions align well with experimental results. The model accurately simulates the upward curvature of the stress–strain curve and the continuous increase in volumetric strain under drainage conditions. Additionally, it effectively describes the increase in shear strength and pore water pressure, and the decrease in volumetric strain, under higher confining pressures. With increasing MSW age, the model predicts a significant increase in shear strength accompanied by a slight increase in volumetric strain. Furthermore, the model well captures the dynamic shear behavior of MSW under varying strain amplitudes and confining pressures. Finally, parameter analysis further explores the characteristics of the model.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"189 ","pages":"Article 107615"},"PeriodicalIF":6.2,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145010811","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":"Simulating the grouting process with flowing water based on two-phase flow model using extended numerical manifold method","authors":"Zhijun Wu ,&nbsp;Yunqi Xue ,&nbsp;Xiangyu Xu ,&nbsp;Lei Weng ,&nbsp;Xiuliang Yin ,&nbsp;Longji Wu ,&nbsp;Liuyang Sun","doi":"10.1016/j.compgeo.2025.107627","DOIUrl":"10.1016/j.compgeo.2025.107627","url":null,"abstract":"<div><div>In this study, an extended cohesive element-based numerical manifold method (Co-NMM) combined with the two-phase flow model is proposed for simulating the migration of the two-phase fluid during the grouting process with flowing water. To achieve this, the two-phase flow model coupled with the Bingham fluid constitutive model is adopted to characterize the displacement process of the multiphase fluid flow. To solve the challenge of simulating the fluid mixing process in the intersecting fracture, the mixed fluid flow algorithm is incorporated into the model to more effectively and accurately capture the flowing and mixing of multiphase fluids. After these improvements, the two-phase flow model coupled with the Bingham fluid constitutive model is verified by reproducing the slurry displacing air and the slurry displacing water in the single fracture against analytical results. The mixed fluid flow algorithm is then validated by reproducing the grouting process in the intersecting fracture under different types of fluid intersection conditions, and comparisons between the results predicted by this proposed method and other numerical methods regarding the diffusion process of slurry and the fluid pressures at the junction are presented. Finally, with the extended Co-NMM, the grouting processes in the fracture network with flowing water are conducted to study the effects of the injection rate (slurry velocity) and the water velocity on the variation of the fluid distribution and slurry diffusion. The results reveal that the injection rate, the water velocity, and the direction of water flow affect the diffusion pattern and diffusion range.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"189 ","pages":"Article 107627"},"PeriodicalIF":6.2,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019310","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 novel method for simulating large-scale 3D non-Gaussian random fields in geotechnical engineering","authors":"Yunzhu Lu ,&nbsp;Rui Pang ,&nbsp;Yang Zhou ,&nbsp;Shuihua Jiang ,&nbsp;Bin Xu","doi":"10.1016/j.compgeo.2025.107621","DOIUrl":"10.1016/j.compgeo.2025.107621","url":null,"abstract":"<div><div>The spatial variability of the soil properties usually represented by random fields, is crucial for structural failure modes determination and reliability assessments. In this paper, a novel and efficient method was proposed for simulating non-Gaussian three-dimensional (3D) random fields. This method fully leverages the characteristics of circulant embedding matrix and uses an L-moment-based quartic Hermite polynomial for non-Gaussian transformation. It has three main advantages. <strong>Firstly</strong>, this method significantly reduces computational memory consumption and saves computation time, enabling efficient simulation of large-scale 3D random fields. Compared to the traditional Cholesky decomposition method (CDM), it improves the resolution of discretized random fields by more than 50 times and reduces computational time by up to five orders of magnitude. Moreover, it offers notable advantages over widely used approaches such as the Karhunen–Loève expansion method (KLM). <strong>Secondly</strong>, this method shows notable advantages in adapting to various stationary auto-correlation functions (ACFs) and scale of fluctuations (SOFs) through theoretical analysis and statistical validation. It also effectively captures the statistical characteristics of the marginal distribution with strong variability. <strong>Thirdly</strong>, this method is adaptable to various model geometries without requiring any modifications to the core algorithm. Two numerical cases, slope stability and foundation bearing capacity analyses validate its performance. <strong>In short</strong>, principal research achievements addresses key challenges in large-scale, high-dimensional, and non-Gaussian processing to some extent. The method proposed in this paper facilitates spatial variability modeling for general 3D geotechnical reliability analysis.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"189 ","pages":"Article 107621"},"PeriodicalIF":6.2,"publicationDate":"2025-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145010810","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":"Transfer learning enhanced physics-informed neural network for buried pipeline deformation analysis under permanent ground deformation","authors":"Junduo Wang ,&nbsp;Linchong Huang ,&nbsp;Yu Liang ,&nbsp;Jie Dong ,&nbsp;Wei Sun","doi":"10.1016/j.compgeo.2025.107630","DOIUrl":"10.1016/j.compgeo.2025.107630","url":null,"abstract":"<div><div>Pipelines are essential infrastructure networks, critical for transporting materials over long distances. However, buried pipelines are susceptible to permanent ground deformation (PGD) which can introduce substantial strain, potentially leading to structural issues such as bending, wrinkling, or cracking. This paper proposes a deep learning framework based on physics-informed neural networks (PINNs), enhanced with transfer learning (TL), to analyze buried pipeline deformation under PGD. By incorporating the residuals of governing physical equations into the loss function, the PINN model integrates the underlying physical laws directly into the deep neural network. The PINN model demonstrates superior generalization and parameter inversion capabilities by integrating physical mechanisms, reducing the dependence on large datasets, compared to traditional deep neural networks (DNNs). Using TL, the model is efficiently extended to new scenarios by partially re-training the network, enhancing computational efficiency. The effectiveness of the proposed model is demonstrated through three scenarios, using only a small amount of training data. A parametric study further shows that the TL-enhanced PINN model offers an efficient surrogate model to reproduce the influence of key parameters on pipeline deformation under PGD. The TL-enhanced PINN framework provides a robust and efficient tool for accurate pipeline deformation prediction, even with limited data, making it suitable for practical engineering applications.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"189 ","pages":"Article 107630"},"PeriodicalIF":6.2,"publicationDate":"2025-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145005414","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":"An MPM-FDM coupled method for landslide analysis considering surface–subsurface conjugated water flow","authors":"Z.Q. Zhan ,&nbsp;C. Zhou ,&nbsp;C.Q. Liu","doi":"10.1016/j.compgeo.2025.107618","DOIUrl":"10.1016/j.compgeo.2025.107618","url":null,"abstract":"<div><div>The material point method (MPM) can effectively simulate large deformation problems involving hydro-mechanical coupling, such as rainfall-induced landslides. Current MPM formulations simulate rainfall boundaries by applying either pore water pressure or velocity boundaries directly. This method does not incorporate the effects of surface water ponding and runoff during heavy rainfall. To address this problem, this study proposes a coupled method that integrates the MPM with the finite difference method (FDM) for hydro-mechanical analysis. Underground water flow is modelled using a two-phase, two-point MPM with the Richards equation, while surface water flow is computed by FDM based on shallow water equations. The two models are coupled: the FDM provides the surface water flow velocity and pore water pressure for subsurface flow simulation in the MPM, while the MPM supplies the surface infiltration rate for surface water flow simulation in the FDM. The new method was validated against existing numerical simulations and centrifuge tests. It was found that the new method can effectively capture the interactions between surface and subsurface flows, as well as the shallow landslide involving surface erosion or washout, which existing MPM codes cannot simulate. Parametric studies further reveal that neglecting the coupling effects of surface–subsurface flow predicts deeper sliding surfaces and longer rainfall durations to failure due to the ignorance of surface ponding and positive pore water pressure at the ground surface. Considering surface water flow tends to shift the failure mode from “slide-to-flow” to “flow-like”, especially when slope angle is larger and soil permeability is lower.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"189 ","pages":"Article 107618"},"PeriodicalIF":6.2,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145005412","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":"Pore-scale simulation of soil water retention curves using DEM-derived pore networks","authors":"Nazanin Mahboobi Motlagh,&nbsp;Arman Khoshghalb,&nbsp;Nasser Khalili","doi":"10.1016/j.compgeo.2025.107625","DOIUrl":"10.1016/j.compgeo.2025.107625","url":null,"abstract":"<div><div>This study presents a pore-scale modelling approach for simulating the soil–water retention curves (SWRCs) of silty sands and sands using a pore network model (PNM) applied to artificially generated non-uniform sphere packs. The adopted approach enables detailed analysis of pore size distribution (PSD) and its dependency on key soil properties, including void ratio, grain size distribution (GSD), and soil fabric, thereby offering mechanistic insights into the observed SWRC behaviour. Compared to experimental techniques, this method offers a superior ability to isolate the effects of individual parameters. Furthermore, coupling the PNM with a constructed sphere pack provides a framework for future investigations into the influence of soil moisture on micro-mechanical interactions among particles.</div><div>In the proposed method, soil samples are represented as sphere packings generated using a discrete element method (DEM) platform, with their pore spaces idealised as networks of pore bodies connected by pore throats. SWRCs are then derived by applying varying capillary pressures to the pore network. The approach is thoroughly validated against experimental data from the literature before being employed to investigate the effects of void ratio, GSD, and soil fabric on soil water retention behaviour.</div><div>It is shown that the model successfully reproduces the hysteresis effect in SWRCs, highlighting the impact of capillary forces and pore connectivity on wetting and drying cycles. The effects of particle size and GSD on the retention behaviour is also examined. Finally, the influence of soil fabric is briefly explored by comparing samples prepared to the same void ratio but subject to different loading paths, namely, one-dimensional and isotropic compressions.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"189 ","pages":"Article 107625"},"PeriodicalIF":6.2,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145005411","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":"Smoothed particle hydrodynamics (SPH) modelling for rainfall-induced unsaturated slope failure considering void ratio dependence and variability","authors":"Guodong Ma ,&nbsp;Annan Zhou ,&nbsp;Ha H. Bui","doi":"10.1016/j.compgeo.2025.107629","DOIUrl":"10.1016/j.compgeo.2025.107629","url":null,"abstract":"<div><div>Rainfall-induced unsaturated slope failures are among the most frequent and destructive forms of landslides worldwide, often resulting in significant casualties and economic losses. Accurately predicting such failures requires not only a robust numerical approach that captures the coupled hydraulic and mechanical behaviours of unsaturated soils, but also a thorough understanding of how spatial variability of soil properties influences slope stability. In this study, smoothed particle hydrodynamics (SPH) is employed in conjunction with an advanced unsaturated constitutive model to investigate, for the first time, the effects of void ratio dependence and variability on rainfall-induced unsaturated slope failure. The model captures the coupled hydro-mechanical behaviour of unsaturated soils, accounting for the influence of void ratio on water retention, infiltration and strength characteristics. A single-layer multiphase SPH approach is employed, where each particle simultaneously represents the water, air, and solid phases, enabling the efficient and robust simulation of large-deformation problems. The SPH model is applied to a synthetic slope with spatial variable soil properties to explore how heterogeneity in void ratio alters failure mechanisms and onset conditions. The results provide new insights into the role of void ratio heterogeneity in rainfall-triggered landslides and demonstrate the potential of advanced SPH modelling for practical probabilistic analysis in geotechnical applications.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"189 ","pages":"Article 107629"},"PeriodicalIF":6.2,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145005413","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":"Three-dimensional elastoplastic constitutive modeling of green sandstone within ductile domain","authors":"Jiacun Liu ,&nbsp;Lei Zhu ,&nbsp;Han Gao ,&nbsp;Jie Feng ,&nbsp;Xing Li ,&nbsp;Kaiwen Xia","doi":"10.1016/j.compgeo.2025.107610","DOIUrl":"10.1016/j.compgeo.2025.107610","url":null,"abstract":"<div><div>During deep underground engineering construction, rocks transition into ductile domain under the influence of high three-dimensional geostress. Therefore, this study proposed a three-dimensional elastoplastic constitutive model incorporating Lode angle dependence within ductile domain. Besides, this study conducts a series of experiments on green sandstone within ductile domain, including hydrostatic compression test and true-triaxial test adopting constant Lode angle loading path. Based on the strength and plastic deformation characteristics of rock within ductile domain, both yield function and potential function are expressed as the product of elliptical equation and deviatoric plane. Both yield function and potential function incorporate parameters that evolve with the plastic internal variable. This enables the yield surface and plastic potential surface to evolve in the deviatoric and meridian planes, providing a more accurate depiction of the stress state and plastic flow direction during hardening. The comparison between proposed model and experimental data of green sandstone validates its applicability and accuracy. A comparison between the associated (yield surface) and non-associated (plastic potential surface) flow rules indicates that the plastic shear strain predicted by the associated flow rule is smaller than that predicted by the non-associated flow rule. To demonstrate the significance of Lode angle dependence in the potential function, a comparison is made between potential functions with and without Lode angle dependence. The comparison results indicate that the potential function without Lode angle dependence overestimates the intermediate principal strain under true-triaxial stress state. The parameter sensitivity analysis reveals that the intermediate principal strain is mainly controlled by deviatoric parameter within potential function. This study provides a theoretical foundation for upcoming numerical simulations of underground engineering within the ductile domain.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"188 ","pages":"Article 107610"},"PeriodicalIF":6.2,"publicationDate":"2025-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144988163","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}