Article
Engineering, Industrial
Jiayi Ding, Jianfang Zhou, Wei Cai
Summary: This paper proposes an efficient variable selection-based Kriging model method to approximate the finite element analysis model in reliability analysis of slopes. The variable selection technique successfully solves the curse of dimensionality problem within Kriging model induced by numerous random variables. The implementation procedure of this method for the reliability analysis of slopes is introduced in detail, and the validity is demonstrated through examples.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Computer Science, Interdisciplinary Applications
Lin Wang, Chongzhi Wu, Zhiyong Yang, Luqi Wang
Summary: The Three Gorges Reservoir Area (TGRA) is an important landslide-prone region in China, and evaluating the stability of reservoir slopes is crucial for prevention of landslide disasters. This study proposes a deep learning-based approach for time-dependent reliability analysis. The results show that this approach can accurately depict the variation tendency of the failure probability of reservoir slopes, providing a promising method for rational evaluation considering the spatial variability of soil properties.
COMPUTERS AND GEOTECHNICS
(2023)
Article
Computer Science, Interdisciplinary Applications
Jing-Ze Li, Shao-He Zhang, Lei-Lei Liu, Lei Huang, Yung-Ming Cheng, Daniel Dias
Summary: This study systematically investigates the influence of soil spatially variable anisotropy on the stability of pile-reinforced slopes. An integrated probabilistic analysis framework is used to obtain the optimal reinforcement scheme, and subset simulation is employed to enhance the computational efficiency. The results show that rotated anisotropy significantly affects the performance and failure probability of pile-reinforced slopes.
COMPUTERS AND GEOTECHNICS
(2022)
Article
Engineering, Geological
Carlotta Guardiani, Enrico Soranzo, Wei Wu
Summary: This paper evaluates and analyzes the stability of reservoir slopes, develops an intelligent surrogate model, and uses two machine learning algorithms to predict the relationship between geomechanical parameters and the factor of safety. The probability of failure is estimated through Monte Carlo simulations. Sensitivity analysis shows that the coefficient of variation in the effective friction angle and the correlation between effective cohesion and friction angle have the highest impact on the probability of failure.
Article
Engineering, Geological
Mao-Xin Wang, Qiang Wu, Dian-Qing Li, Wenqi Du
Summary: This paper presents a numerical-based seismic displacement analysis for slopes considering the spatial variability of soils. It develops two generic slope models based on a finite-difference approach, and models soil parameters as random fields. Dynamic analyses estimate slope displacements for both deterministic and random slope cases. The results show that neglecting soil spatial variability significantly underestimates slope displacement hazard, and two proposed strategies differ in treatment of aleatory variability.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2023)
Article
Engineering, Geological
Mohammad Aminpour, Reza Alaie, Navid Kardani, Sara Moridpour, Majidreza Nazem
Summary: This paper presents a highly efficient machine learning-aided reliability technique for stochastic reliability analysis in geotechnical engineering. The proposed technique accurately predicts the probability of failure with significantly reduced computational time compared to traditional methods.
Review
Computer Science, Interdisciplinary Applications
Shui-Hua Jiang, Jinsong Huang, D. Griffiths, Zhi-Ping Deng
Summary: The spatial variability of soil properties has been largely overlooked in traditional slope stability analyses. However, in the past two decades, an increasing number of research papers have focused on explicitly modeling this variability. The first phase of research primarily emphasized the importance of including spatial variability in probabilistic slope stability analysis, while the second phase witnessed rapid developments in quantitative risk assessment, computational efficiency improvement, and the utilization of site investigation and field monitoring data. This review aims to summarize these advances to guide future research directions.
COMPUTERS AND GEOTECHNICS
(2022)
Article
Engineering, Geological
Jian Ji, Wenwang Liao, Yining Hu, Qing Lue
Summary: This paper proposes an efficient geotechnical reliability analysis framework that integrates the advantages of FORM and KL to evaluate the reliability of spatially variable soil slopes. The improved iHLRF algorithm is used to implement the FORM procedure, and KL is used to reduce the dimension of random variables. The proposed framework is particularly useful for fast and accurate slope reliability analysis using the finite element method.
GEORISK-ASSESSMENT AND MANAGEMENT OF RISK FOR ENGINEERED SYSTEMS AND GEOHAZARDS
(2023)
Article
Engineering, Geological
Ze Zhou Wang, Changlin Xiao, Siang Huat Goh, Min-Xuan Deng
Summary: The paper proposes a novel and computationally efficient metamodeling technique using convolutional neural networks for random field finite-element analyses, showing promising potential for reliability analysis in spatially variable soils. The CNN outputs demonstrated good agreement with FEM predictions, indicating the effectiveness of using CNNs as metamodels to replace expensive simulations.
JOURNAL OF GEOTECHNICAL AND GEOENVIRONMENTAL ENGINEERING
(2021)
Article
Engineering, Industrial
Yogesh Chandrakant Mathpati, Kalpesh Sanjay More, Tapas Tripura, Rajdip Nayek, Souvik Chakraborty
Summary: We propose a novel model-agnostic data-driven reliability analysis framework, named MAntRA, for time-dependent reliability analysis. The framework combines Bayesian inference and stochastic differential equations to evaluate the reliability of stochastically-driven dynamical systems with unknown governing physics. The proposed approach adopts a two-stage method: an efficient variational Bayesian equation discovery algorithm is used to determine the governing physics from output-only data, and then the discovered equation is solved and the probability of failure is computed using a stochastic integration scheme. The efficacy of the approach is demonstrated through four numerical examples, indicating its potential application for reliability analysis of in-situ and heritage structures from on-site measurements.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Mathematics, Applied
Kiera van der Sande, Natasha Flyer, Bengt Fornberg
Summary: The use of ML for solving PDEs is a growing research area. In this work, ML is applied to accelerate the RBF-TD method, a numerical discretization scheme for PDEs. The costly L1 minimization step in the original RBF-TD method is replaced with an ERT model, resulting in significant speed up while maintaining high order accuracy.
JOURNAL OF SCIENTIFIC COMPUTING
(2023)
Article
Engineering, Geological
Barbara Maria Switala, Carlotta Guardiani, Enrico Soranzo, Wei Wu
Summary: This study applies a coupled hydro-mechanical model to analyze the effect of plant roots on soil shear strength. By considering the variability of soil and root properties, the probability of failure for rain-induced root-reinforced slopes is estimated using machine learning algorithms.
CANADIAN GEOTECHNICAL JOURNAL
(2023)
Article
Engineering, Civil
Hung Dang, Ramona Trestian, Thanh Bui-Tien, Huan X. Nguyen
Summary: This study proposes a novel framework using a Bayesian neural network data-driven model to compute the dynamic reliability and uncertainty quantification of structures under time-varying excitation, significantly reducing time complexity. The effectiveness and correctness of the proposed method are validated through three case studies, recommending an 11-year maintenance routine for prestressed bridge structures in marine and chemically aggressive environments.
Article
Computer Science, Interdisciplinary Applications
Gan Wang, Rui Pang, Xiang Yu, Bin Xu
Summary: Studying the influence of mainshock-aftershock sequences on the reliability of soil slopes is of great significance for disaster prevention. This paper proposes a new analysis method for random dynamic response analysis and permanent displacements reliability evaluation of soil slopes considering the uncertainty of the mainshock-aftershock sequences. The method includes a simulation method of random seismic sequence based on Copula function, calculation of permanent displacement under different seismic sequences, analysis of aftershock influence, and probability evaluation using the probability density evolution method. The results show that the randomly generated mainshock-aftershock sequence can meet the needs of random dynamic analysis and probability analysis of soil slope, and the slope has larger permanent displacement under mainshock-aftershock sequences compared to single mainshocks. The influence of aftershocks on the slope reliability is explained for the first time, highlighting the necessity of studying this influence from a probability perspective.
COMPUTERS AND GEOTECHNICS
(2023)
Article
Engineering, Geological
Ze-Zhou Wang, Siang Huat Goh
Summary: The study introduces a metamodel-based method using Convolutional Neural Networks (CNNs) for efficient slope reliability analysis in spatially variable soils. By training CNNs with random field samples, the method can replace computationally demanding RF-FEM analyses for accurate predictions at a fraction of the cost. Results demonstrate the effectiveness of the proposed CNN approach in terms of computational efficiency and accuracy compared to other metamodel-based methods.
ENGINEERING GEOLOGY
(2021)
Article
Engineering, Geological
Xuzhen He, Fang Wang, Wengui Li, Daichao Sheng
Summary: The study introduces the use of deep learning to train models for improving computational efficiency in stochastic analysis. Training models with a large dataset allows for accurate results for new data without the need for re-training. The research shows that deep learning models have a competitive edge in complex problems and can extend their capabilities by generating more data and re-training.
Article
Construction & Building Technology
Wenkui Dong, Wengui Li, Zhihui Sun, Idris Ibrahim, Daichao Sheng
Summary: This study applied different surface coatings to graphene/cement-based sensors to achieve superhydrophobicity and enhance piezoresistive stability. The results showed improved water resistance and sensitivity in the sensors, making them suitable for structural health monitoring of smart concrete infrastructure.
AUTOMATION IN CONSTRUCTION
(2022)
Article
Construction & Building Technology
Wenkui Dong, Wengui Li, Yipu Guo, Fulin Qu, Kejin Wang, Daichao Sheng
Summary: The study utilized SHP and CWA to enhance the impermeability of CB/cement-based sensors. Results showed that SHP improved water impermeability, while CWA enhanced chloride resistance. Performance testing in different environments demonstrated that SHP had a more stable impact on electrical resistivity and piezoresistivity.
CEMENT & CONCRETE COMPOSITES
(2022)
Article
Construction & Building Technology
Zhiyu Luo, Wengui Li, Kejin Wang, Surendra P. Shah, Daichao Sheng
Summary: The study analyzed the heterogeneity and properties of ITZs in geopolymer concrete, revealing that the gel-related phases at the top and bottom boundaries have higher mechanical properties. A strategy involving polished aggregates, rapid scratch, and statistical analysis was proposed for investigating complex ITZs within a reasonable testing duration.
CEMENT AND CONCRETE RESEARCH
(2022)
Article
Computer Science, Interdisciplinary Applications
Marti Lloret-Cabot, Daichao Sheng
Summary: This paper evaluates the computational performance of a first order accurate fully implicit integration scheme and four different order explicit substepping integration schemes, in order to provide practical guidance for solving numerical problems in geotechnical engineering involving critical state models.
COMPUTERS AND GEOTECHNICS
(2022)
Article
Engineering, Geological
Feng Gao, Sheng Zhang, Xuzhen He, Daichao Sheng
Summary: This paper presents experimental investigation into the effects of particle size distribution of subgrade soil on mud pumping. The results show that subgrade soils with higher fine contents do not necessarily lead to more serious mud pumping. The findings can help selecting proper rail embankment fills to reduce mud pumping.
JOURNAL OF GEOTECHNICAL AND GEOENVIRONMENTAL ENGINEERING
(2022)
Article
Engineering, Geological
Xuzhen He, Haoding Xu, Daichao Sheng
Summary: Data-driven intelligent surrogate models have gained popularity, and in this paper, a framework is proposed that builds surrogate models to handle spatially variable inputs and outputs, and explores the use of U-Nets as surrogate models for geotechnical problems.
Article
Chemistry, Multidisciplinary
Xuzhen He
Summary: This paper investigates the relationship between the jamming limits from isotropic compression tests and the critical state through discrete element method (DEM) simulations. The results show that the loosest jammed state line obtained from the isotropic compression method is the same as the critical state pressure-volume fraction line, and the stress state of the critical state can also be well described by a Coulomb-type equation in the octahedral profile.
APPLIED SCIENCES-BASEL
(2023)
Article
Multidisciplinary Sciences
Xuzhen He
Summary: The recent progress in machine learning is attributed to the availability of high-performance computers and development tools. The accelerated linear algebra (XLA) compiler is a tool that optimizes array operations and compiles them into high-performance programs specific to target platforms. This study examines the efficiency of XLA for numerical models and compares its performance with optimal implementations.
Article
Engineering, Geological
Zhonghui Bi, Liaojun Zhang, Xuzhen He, Yafei Zhai
Summary: This paper developed a model for the tank-soil-fluid system to study the effects of different incidence angles and earthquake types on the dynamic characteristics of liquid tanks. The results show that the response of the tank-soil-fluid system is highly sensitive to incidence angles, earthquake type, and earthquake record frequency contents. Therefore, both the tank characteristics and seismic characteristics should be considered in the design of tanks.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2023)
Article
Green & Sustainable Science & Technology
Chia Yu Huat, Danial Jahed Armaghani, Sai Hin Lai, Haleh Rasekh, Xuzhen He
Summary: Mechanised tunnelling is widely used for twin tunnel construction in urban areas, but surface settlement caused by the tunnelling activities is a common challenge. Existing methods for determining surface settlement are often constrained by soil types and are time-consuming, and they often omit crucial parameters such as tunnel operational factors. Therefore, this paper employs 3D numerical analysis to simulate tunnelling-induced surface settlement, taking into account various factors and incorporating data from in-situ and laboratory tests. The obtained results closely match field measurements, and the approach allows for customizable mitigation strategies. Overall, this paper is highly important in improving the planning and construction of sustainable tunnels. Evaluation: 9/10.
Article
Mathematics
Haoding Xu, Xuzhen He, Feng Shan, Gang Niu, Daichao Sheng
Summary: This research proposes dimensionless equations to estimate the run-out distance of landslides or debris flows, supported by experimental data and numerical simulations. The study uses the coupled Eulerian-Lagrangian method to handle large deformations, models soil using the Mohr-Coulomb model, and focuses on the failure of cohesionless soil slopes. New scaling relationships for the normalized run-out distance are suggested and validated, showing the dependence on initial geometry, plane angle, material properties, and slope angle.
Article
Computer Science, Interdisciplinary Applications
Yinghao Deng, Yang Xia, Di Wang, Yan Jin
Summary: This study investigates the mechanism of hydraulic fracture propagation in laminated shale, develops a numerical solver, and validates the effectiveness of the method through simulation experiments. The study also examines the influence of the interaction between hydraulic fractures and weak interfaces on the mechanical properties of shale.
COMPUTERS AND GEOTECHNICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Zhichao Zhang, Mingfei Feng, Guangshuo Zhou, Zhenglong Xu
Summary: A thermodynamic constitutive model for structured and destructured clays is proposed in this paper. The model includes state-dependent relations of hyperelasticity and plasticity without the concept of yielding surface. The proposed model captures the couplings between elasticity and plasticity and the effects of bonding structure.
COMPUTERS AND GEOTECHNICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Deze Yang, Xihua Chu
Summary: Creep and stress relaxation behaviors in granular materials are influenced by the time-dependent changes in their microstructure, with particle shape playing a significant role. However, the effects of particle shape on these behaviors are still not well understood. In this study, 3D DEM models incorporating the rate process theory and superellipsoids are used to simulate creep and stress relaxation in granular samples with different aspect ratios and blockiness. The results show that both aspect ratio and blockiness have a significant influence on creep and stress relaxation, with aspect ratio affecting creep through contact force ratio and blockiness affecting stress relaxation through variation in normal contact force anisotropy. These findings provide insights into the effects of particle shape on creep and stress relaxation in granular assemblies.
COMPUTERS AND GEOTECHNICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Shahab Amanat, Kourosh Gholami, Reza Rafiee-Dehkharghani, Dipanshu Bansal
Summary: This paper investigates the optimal design of wave barriers using the modified non-dominated sorting genetic algorithm-II (NSGA-II) and the Bloch-Floquet theory. The aim is to find the optimal design of plane wave barriers with a wide bandgap at a low-frequency range and low construction cost. The study develops a modified NSGA-II algorithm to determine the optimal arrangement of concrete in wave barrier unit cells. The performance of the optimal barriers is examined through finite element simulation and their efficacy in attenuating plane S-waves is verified.
COMPUTERS AND GEOTECHNICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Yanlin Su, Guoqing Cai, Fengjie Yin, Yepeng Shan, Annan Zhou
Summary: This paper presents a novel elastic-viscoplastic constitutive model that takes into account particle breakage to reproduce the time-dependent behavior of coarse-grained soil. The model integrates the Unified Hardening (UH) model, the elastic-viscoplastic (EVP) model, and the overstress theory. The relationship between particle breakage and loading rate is established, and state variables associated with the critical state of coarse-grained soil are derived to consider both time and particle breakage. A three-dimensional elastic-viscoplastic constitutive model is constructed by combining a one-dimensional viscoplastic hardening parameter with a secondary consolidation coefficient considering particle breakage. The proposed model requires 19 parameters and effectively describes the influence of time-dependency and particle breakage on the shear, dilatancy, and compression behaviors of coarse-grained soil with different confining pressures or initial void ratios. Experimental data comparisons validate the model's ability to replicate the time-dependent behavior of coarse-grained soil.
COMPUTERS AND GEOTECHNICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Shichao Zhang, Yaqiong Wang, Qidong Gao, Xiaobo Ma, Haixiao Zhou, Zhifeng Wang
Summary: Accurately evaluating and predicting ground settlement during tunnel excavation is essential for ensuring tunnel stability. This study conducted a probabilistic analysis of ground settlement under uncertain soil properties. The results demonstrate that spatially variable soils significantly influence the ground settlement in the vertical direction.
COMPUTERS AND GEOTECHNICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Xu Zhang, Bin Luo, Youjun Xu, Zhiwen Yang
Summary: This paper presents an analytical solution for horizontal displacements induced by small radius curve shield tunneling. The formula is derived based on the image method and Mindlin solution, considering additional thrust, frictional resistance, ground loss, and grouting pressure. The solution is validated with on-site data, demonstrating its reliability and providing a new approach for predicting and controlling stratum horizontal displacements in curve shield tunneling. The study finds that ground loss has the most significant influence on displacements, and soil closer to the tunnel exhibits larger horizontal displacements.
COMPUTERS AND GEOTECHNICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Jian-Hong Wan, Ali Zaoui
Summary: Ground vibrations during earthquakes can cause soil strength loss and structural damage. Rubber-soil mixtures (RSM) have shown promise in reducing residual ground deformation. This study used molecular dynamics simulations to investigate the friction behavior of the rubber-clay interface in RSM systems. The results revealed a direct correlation between normal stress and friction force, with denser soil systems exhibiting higher friction forces.
COMPUTERS AND GEOTECHNICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Hongying Wang, Qiang Zhang, Peinan Wu, Yanjing Li, Lijun Han, Guilei Han
Summary: In addition to the Mohr-Coulomb and Hoek-Brown criteria, other nonlinear functions are used to describe the plastic response of rock mass. This paper derived the equivalent cohesive strength, frictional angle, and dilatancy angle for nonlinear yield and plastic flow rock masses. The solution for a circular tunnel in any nonlinear yield and plastic flow rock masses was derived and verified using a numerical procedure. The analysis of strain-softening rock masses under two assumed nonlinear yield criteria was also studied.
COMPUTERS AND GEOTECHNICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Zhijun Wu, You Wu, Lei Weng, Mengyi Li, Zhiyang Wang, Zhaofei Chu
Summary: This study proposed a machine learning approach to predict the uniaxial compression strength (UCS) and elastic modulus (E) of rocks. By measuring meso-mechanical parameters and developing grain-based models, a database with 225 groups of data was established for prediction models. The optimized kernel ridge regression (KRR) and gaussian process regression (GPR) models achieved excellent performance in predicting UCS and E.
COMPUTERS AND GEOTECHNICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Mingjun Zhou, Zhenming Shi, Chong Peng, Ming Peng, Kahlil Fredrick E. Cui, Bo Li, Limin Zhang, Gordon G. D. Zhou
Summary: In this paper, the erosion and deposition processes during overtopping dam breaching are simulated using a novel method (ED-SPH). The proposed model is able to capture the complex behaviors of dam soil erosion, entrainment, and depositions. Soil deposition hinders particle movement and reduces water velocity at the water-soil interface.
COMPUTERS AND GEOTECHNICS
(2024)
Article
Computer Science, Interdisciplinary Applications
C. Chavez-Negrete, F. J. Dominguez-Mota, R. Roman-Gutierrez
Summary: To accurately simulate groundwater flow in porous layered media, it is important to consider all environmental factors and use a generalized finite differences scheme as a meshless method for spatial discretization. This approach ensures robustness and accuracy of the numerical solution.
COMPUTERS AND GEOTECHNICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Shuairun Zhu, Lulu Zhang, Lizhou Wu, Lin Tan, Haolong Chen
Summary: This paper investigates the effectiveness of the cascadic multigrid method applied to the improved Picard iteration method for solving nonlinear problems in deforming variably saturated porous media. Two improved Picard iteration methods are proposed, and their effectiveness is verified through numerical examples. The results show that the improved methods have faster convergence and higher computational efficiency compared to the classical method.
COMPUTERS AND GEOTECHNICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Yuan Cao, Yan-Guo Zhou, Kyohei Ueda, Yun-Min Chen
Summary: Investigated shear stress responses of enclosed soil in deep soil mixing (DSM) grid-improved ground, and revealed the characteristics of the waist effect and mathematical model for shear stress reduction ratio.
COMPUTERS AND GEOTECHNICS
(2024)
Article
Computer Science, Interdisciplinary Applications
Jinfan Chen, Zhihong Zhao, Jintong Zhang
Summary: This study develops data-driven criteria to estimate the peak shear strength (PSS) of rock fractures, considering the effects of surface roughness features. A high-quality dataset is created using particle-based discrete element method and diamond-square algorithm. Tree-based models and convolutional neural network are trained to predict the PSS of rock fractures, and their reliability is verified using experimental data.
COMPUTERS AND GEOTECHNICS
(2024)