Lorenzo Milan, Monica Barbero, Mauro Borri‐Brunetto
Spalling and rockburst are severe criticalities that can emerge while excavating deep tunnels in rock masses under heavy natural stress states. Here, rock brittle failure can induce massive releases of the energy stored during the excavation and dangerous projections of rock blocks into the opening. The prediction of rock brittle failure is therefore crucial and, for this purpose, different empirical brittleness indexes have been proposed in the past. However, many of them provide predictions that is often not consistent and/or truthful, as they do not consider the stress and energy variations induced in the rock mass by the excavation. This paper presents an innovative method to distinguish between ductile and brittle failure of rock around deep tunnels. The method is based on two mechanical models of rock damage that were formulated to describe brittle and ductile failure mechanisms within the rock mass, as induced by the stress release during the excavation. These models are integrated into the definition of a new brittleness index, named tunnel brittleness index (TBI). TBI quantifies the outcome of the competition between the two failure mechanisms, estimating the susceptibility of the rock mass to brittle failure. The effectiveness and the application of TBI are shown with reference to a real case study. Specifically, TBI appears as a promising and useful tool for engineers dealing with deep tunnel projects that may be employed for predicting brittle collapses in the early stages of the design, which would be crucial in the preliminary choice of excavation techniques and machinery, and the support systems.
{"title":"A New Method to Assess the Possibility of Brittle Failure of Rock Induced by Deep Excavations","authors":"Lorenzo Milan, Monica Barbero, Mauro Borri‐Brunetto","doi":"10.1002/nag.3953","DOIUrl":"https://doi.org/10.1002/nag.3953","url":null,"abstract":"Spalling and rockburst are severe criticalities that can emerge while excavating deep tunnels in rock masses under heavy natural stress states. Here, rock brittle failure can induce massive releases of the energy stored during the excavation and dangerous projections of rock blocks into the opening. The prediction of rock brittle failure is therefore crucial and, for this purpose, different empirical brittleness indexes have been proposed in the past. However, many of them provide predictions that is often not consistent and/or truthful, as they do not consider the stress and energy variations induced in the rock mass by the excavation. This paper presents an innovative method to distinguish between ductile and brittle failure of rock around deep tunnels. The method is based on two mechanical models of rock damage that were formulated to describe brittle and ductile failure mechanisms within the rock mass, as induced by the stress release during the excavation. These models are integrated into the definition of a new brittleness index, named tunnel brittleness index (TBI). TBI quantifies the outcome of the competition between the two failure mechanisms, estimating the susceptibility of the rock mass to brittle failure. The effectiveness and the application of TBI are shown with reference to a real case study. Specifically, TBI appears as a promising and useful tool for engineers dealing with deep tunnel projects that may be employed for predicting brittle collapses in the early stages of the design, which would be crucial in the preliminary choice of excavation techniques and machinery, and the support systems.","PeriodicalId":13786,"journal":{"name":"International Journal for Numerical and Analytical Methods in Geomechanics","volume":"12 1","pages":""},"PeriodicalIF":4.0,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143192314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ziyu Jin, Jiaying Liu, Gang Ma, Chengbao Hu, Qihang Yang, Xiusong Shi, Xinquan Wang
The cover image is based on the article How Does the Largest Cluster in the Strong Network Rule Granular Soil Mechanics? A DEM Study by Jiaying Liu et al., https://doi.org/10.1002/nag.3903.
{"title":"Cover Image, Volume 49, Issue 3","authors":"Ziyu Jin, Jiaying Liu, Gang Ma, Chengbao Hu, Qihang Yang, Xiusong Shi, Xinquan Wang","doi":"10.1002/nag.3955","DOIUrl":"https://doi.org/10.1002/nag.3955","url":null,"abstract":"<p>The cover image is based on the article <i>How Does the Largest Cluster in the Strong Network Rule Granular Soil Mechanics? A DEM Study</i> by Jiaying Liu et al., https://doi.org/10.1002/nag.3903.\u0000\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure>\u0000 </p>","PeriodicalId":13786,"journal":{"name":"International Journal for Numerical and Analytical Methods in Geomechanics","volume":"49 3","pages":"i"},"PeriodicalIF":3.4,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/nag.3955","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143111904","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}
Kai Li, Tianming Lu, Minyi Zhu, Shaorui Sun, Jihong Wei, Yu Huang, Hu Zheng
Bimrocks, a complex rock mass commonly found in geotechnical engineering, are often analyzed through the discrete element method (DEM) to understand their mechanical behavior from both macro and micro perspectives. However, there is limited research addressing the post‐peak behavior of bimrocks, particularly in terms of the uniaxial compression stress–strain curve and failure characteristics, with many studies overlooking the complex nature of their post‐peak behavior. This study proposes a comprehensive method for constructing three‐dimensional (3D) numerical samples of bimrocks and selecting appropriate parameters, focusing on accurately capturing both the post‐peak curve shape and failure characteristics. By combining laboratory tests with CT scanning techniques, numerical samples with structures matching those of the physical samples are created, addressing the issue of block stone breakage in traditional discrete element simulations. The study introduces the selection criteria for matrix and block stone parameters and analyzes the microscopic factors influencing the post‐peak curve and failure characteristics. Results indicate that the damping coefficient and loading rate are crucial in shaping the post‐peak curve, with complex curves requiring multiple damping coefficients. Additionally, the radius multiplier influences crack propagation direction, while the strength ratio affects crack penetration and secondary cracking, with these factors being dependent on the matrix strength.
{"title":"An Integrated 3D DEM Modeling Process for Bimrocks Considering Post‐Peak Behavior and Block Breakage","authors":"Kai Li, Tianming Lu, Minyi Zhu, Shaorui Sun, Jihong Wei, Yu Huang, Hu Zheng","doi":"10.1002/nag.3954","DOIUrl":"https://doi.org/10.1002/nag.3954","url":null,"abstract":"Bimrocks, a complex rock mass commonly found in geotechnical engineering, are often analyzed through the discrete element method (DEM) to understand their mechanical behavior from both macro and micro perspectives. However, there is limited research addressing the post‐peak behavior of bimrocks, particularly in terms of the uniaxial compression stress–strain curve and failure characteristics, with many studies overlooking the complex nature of their post‐peak behavior. This study proposes a comprehensive method for constructing three‐dimensional (3D) numerical samples of bimrocks and selecting appropriate parameters, focusing on accurately capturing both the post‐peak curve shape and failure characteristics. By combining laboratory tests with CT scanning techniques, numerical samples with structures matching those of the physical samples are created, addressing the issue of block stone breakage in traditional discrete element simulations. The study introduces the selection criteria for matrix and block stone parameters and analyzes the microscopic factors influencing the post‐peak curve and failure characteristics. Results indicate that the damping coefficient and loading rate are crucial in shaping the post‐peak curve, with complex curves requiring multiple damping coefficients. Additionally, the radius multiplier influences crack propagation direction, while the strength ratio affects crack penetration and secondary cracking, with these factors being dependent on the matrix strength.","PeriodicalId":13786,"journal":{"name":"International Journal for Numerical and Analytical Methods in Geomechanics","volume":"76 1","pages":""},"PeriodicalIF":4.0,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143083534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this study, a modified reconstruction method for rock that considers the irregularity of minerals and microcracks was proposed. First, the quartet structure generation set (QSGS) method was modified by establishing two different growth modes of initial growth cores to generate the minerals and microcracks. Then, three‐dimensional (3D) digital rock modeling software was developed based on the modified method, achieving efficient and parametric rock modeling using real rock characteristic parameters. Next, taking granite as an example, a series of digital rock models were reconstructed based on the real characteristic parameters obtained by x‐ray diffraction (XRD) and computed tomography (CT) tests. Finally, the accuracy of the modified method was verified by comparing the fractal dimensions of minerals and microcracks of digital rock models and granite sample. The results show that 3D digital rock modeling software can generate digital rock models with different mineral contents and porosities and that the generation time of the model decreases exponentially as the grid size increases. Meanwhile, the fractal dimensions of minerals and microcracks in the digital rock models are similar to those in the granite sample with acceptable errors of ± 5.0%. In summary, the modified method can reconstruct rock accurately and effectively by considering the irregularity of minerals and microcracks.
{"title":"Reconstruction of Rock Composed of Multiple Irregular Minerals and Microcracks Using the Modified Quartet Structure Generation Set Method","authors":"Peng Guo, Hanyu Chen, Guangyao Li, Lifeng Fan","doi":"10.1002/nag.3951","DOIUrl":"https://doi.org/10.1002/nag.3951","url":null,"abstract":"In this study, a modified reconstruction method for rock that considers the irregularity of minerals and microcracks was proposed. First, the quartet structure generation set (QSGS) method was modified by establishing two different growth modes of initial growth cores to generate the minerals and microcracks. Then, three‐dimensional (3D) digital rock modeling software was developed based on the modified method, achieving efficient and parametric rock modeling using real rock characteristic parameters. Next, taking granite as an example, a series of digital rock models were reconstructed based on the real characteristic parameters obtained by x‐ray diffraction (XRD) and computed tomography (CT) tests. Finally, the accuracy of the modified method was verified by comparing the fractal dimensions of minerals and microcracks of digital rock models and granite sample. The results show that 3D digital rock modeling software can generate digital rock models with different mineral contents and porosities and that the generation time of the model decreases exponentially as the grid size increases. Meanwhile, the fractal dimensions of minerals and microcracks in the digital rock models are similar to those in the granite sample with acceptable errors of ± 5.0%. In summary, the modified method can reconstruct rock accurately and effectively by considering the irregularity of minerals and microcracks.","PeriodicalId":13786,"journal":{"name":"International Journal for Numerical and Analytical Methods in Geomechanics","volume":"63 1","pages":""},"PeriodicalIF":4.0,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143083535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The excavation‐induced fractured zone (EFZ) and the anisotropic evolution in time of drifts’ convergence, as observed in the Mesue/Haute‐Marne Underground Researche Laboratory (MHM URL), reveal the complex behavior of Callovo‐Oxfordian (COx) claystone, the host formation for geological radioactive waste disposal project (Cigéo) in France. Especially, the dispersion of the in situ convergence monitoring exhibits the non‐negligible uncertainty of the host rock properties that must be quantified and considered in the stability analysis of the repositories’ support systems. In this work, the well‐known Bayesian inference with the transitional Markov chain Monte Carlo sampling technique is chosen to quantify the uncertainty of the short‐ and long‐term behavior of COx claystone and EFZ using the convergence data of a drift excavated in the major horizontal stress direction. An engineering approach is adopted to simulate the anisotropy of drift convergence. To reduce the computational cost of the numerical model prediction during the probabilistic inversion, the artificial neural network–based surrogate is chosen. The uncertainty of the visco‐elastoplastic behavior of COx claystone, as well as the uncertainty of the EFZ shape, is then considered in the reliability analysis of the concrete liner of an intermediate‐level long‐lived radioactive (IL‐LLW) repository. The numerical applications allow verifying the robustness of the current design for the repository support system.
{"title":"Uncertainty Quantification of the Short‐ and Long‐Term Behavior of COx Claystone and Reliability Analysis of the IL‐LLW Repository's Concrete Liner Based on In Situ Convergence Data","authors":"Duc Phi Do, Minh Ngoc Vu, Truong Toan Nguyen, Dashnor Hoxha, Gilles Armand","doi":"10.1002/nag.3949","DOIUrl":"https://doi.org/10.1002/nag.3949","url":null,"abstract":"The excavation‐induced fractured zone (EFZ) and the anisotropic evolution in time of drifts’ convergence, as observed in the Mesue/Haute‐Marne Underground Researche Laboratory (MHM URL), reveal the complex behavior of Callovo‐Oxfordian (COx) claystone, the host formation for geological radioactive waste disposal project (Cigéo) in France. Especially, the dispersion of the in situ convergence monitoring exhibits the non‐negligible uncertainty of the host rock properties that must be quantified and considered in the stability analysis of the repositories’ support systems. In this work, the well‐known Bayesian inference with the transitional Markov chain Monte Carlo sampling technique is chosen to quantify the uncertainty of the short‐ and long‐term behavior of COx claystone and EFZ using the convergence data of a drift excavated in the major horizontal stress direction. An engineering approach is adopted to simulate the anisotropy of drift convergence. To reduce the computational cost of the numerical model prediction during the probabilistic inversion, the artificial neural network–based surrogate is chosen. The uncertainty of the visco‐elastoplastic behavior of COx claystone, as well as the uncertainty of the EFZ shape, is then considered in the reliability analysis of the concrete liner of an intermediate‐level long‐lived radioactive (IL‐LLW) repository. The numerical applications allow verifying the robustness of the current design for the repository support system.","PeriodicalId":13786,"journal":{"name":"International Journal for Numerical and Analytical Methods in Geomechanics","volume":"1 1","pages":""},"PeriodicalIF":4.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143026659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The cover image is based on the article Characterization of Long-Term Municipal Solid Waste Constitutive Behavior With Coupled Biodegradation and Fibrous Reinforcing Effects by Yuchen Zhang et al., https://doi.org/10.1002/nag.3894.
{"title":"Cover Image, Volume 49, Issue 2","authors":"Xiulei Li, Chunwei Yang, Yuchen Zhang, Yuping Li, Jianyong Shi, Yanan Sun","doi":"10.1002/nag.3950","DOIUrl":"10.1002/nag.3950","url":null,"abstract":"<p>The cover image is based on the article <i>Characterization of Long-Term Municipal Solid Waste Constitutive Behavior With Coupled Biodegradation and Fibrous Reinforcing Effects</i> by Yuchen Zhang et al., https://doi.org/10.1002/nag.3894.\u0000\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure>\u0000 </p>","PeriodicalId":13786,"journal":{"name":"International Journal for Numerical and Analytical Methods in Geomechanics","volume":"49 2","pages":"i"},"PeriodicalIF":3.4,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/nag.3950","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143026660","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}
Granular flow is ubiquitous in various engineering scenarios, such as landslides, avalanches, and industrial processes. Reliable modeling of granular flow is crucial for mitigating potential hazards and optimizing process efficiency. However, the complex behavior of granular media, which transitions between solid‐like and fluid‐like states, poses a significant challenge in their modeling, particularly when involving rapid mobilization. To address this challenge, we propose an innovative constitutive model capable of capturing the highly nonlinear behavior of granular flow by integrating frictional and collisional mechanisms under varying states. The proposed model incorporates two distinct stress components: frictional stress and collisional stress. The frictional stress is governed by a critical‐state‐based elastoplasticity model, which accurately describes the solid‐like behavior of granular media. On the other hand, the collisional stress is formulated using a well‐established kinetic theory, which effectively captures the fluid‐like behavior of granular media. To seamlessly transition between these two states, we introduce a novel state variable, the granular temperature, which serves as a measure of the kinetic energy of the granular system. This innovative transition model is further incorporated into a GPU‐based material point method (MPM) and used to model two types of granular flows, including column collapse and flume test on an inclined surface. The numerical results show good agreement with available experimental data, highlighting the efficacy of our proposed phase transition model with the MPM modeling approach in effectively capturing the transition of granular materials from solid‐like to fluid‐like states throughout the mobilization process, from initiation to final deposition.
{"title":"Material Point Method Modeling of Granular Flow Considering Phase Transition From Solid‐Like to Fluid‐Like States","authors":"Hang Feng, Weijian Liang, Zhen‐Yu Yin, Liming Hu","doi":"10.1002/nag.3947","DOIUrl":"https://doi.org/10.1002/nag.3947","url":null,"abstract":"Granular flow is ubiquitous in various engineering scenarios, such as landslides, avalanches, and industrial processes. Reliable modeling of granular flow is crucial for mitigating potential hazards and optimizing process efficiency. However, the complex behavior of granular media, which transitions between solid‐like and fluid‐like states, poses a significant challenge in their modeling, particularly when involving rapid mobilization. To address this challenge, we propose an innovative constitutive model capable of capturing the highly nonlinear behavior of granular flow by integrating frictional and collisional mechanisms under varying states. The proposed model incorporates two distinct stress components: frictional stress and collisional stress. The frictional stress is governed by a critical‐state‐based elastoplasticity model, which accurately describes the solid‐like behavior of granular media. On the other hand, the collisional stress is formulated using a well‐established kinetic theory, which effectively captures the fluid‐like behavior of granular media. To seamlessly transition between these two states, we introduce a novel state variable, the granular temperature, which serves as a measure of the kinetic energy of the granular system. This innovative transition model is further incorporated into a GPU‐based material point method (MPM) and used to model two types of granular flows, including column collapse and flume test on an inclined surface. The numerical results show good agreement with available experimental data, highlighting the efficacy of our proposed phase transition model with the MPM modeling approach in effectively capturing the transition of granular materials from solid‐like to fluid‐like states throughout the mobilization process, from initiation to final deposition.","PeriodicalId":13786,"journal":{"name":"International Journal for Numerical and Analytical Methods in Geomechanics","volume":"30 1","pages":""},"PeriodicalIF":4.0,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142988274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Most of the robust artificial intelligence (AI)‐based constitutive models are developed with synthetic datasets generated from traditional constitutive models. Therefore, they fundamentally rely on the traditional constitutive models rather than laboratory test results. Also, their potential use within geotechnical engineering communities is limited due to the unavailability of datasets along with the model code files. In this study, the data‐driven constitutive models are developed using only laboratory test databases and deep learning (DL) techniques. The laboratory database was prepared by conducting cyclic direct simple shear (CDSS) tests on reconstituted sand, that is, PDX sand. The stacked long short‐term memory (LSTM) network and its variants are considered for developing the predictive models of the shear strain (γ [%]) and excess pore pressure ratio (ru) time histories. The suitable input parameters (IPs) are selected based on the physics behind the generation of ru and γ (%) of the liquefiable sands. The predicted responses of γ (%) and ru agree well in most cases and are used to predict the dynamic soil properties of the PDX sand. The same modeling framework is extended for other sand and compared with existing AI‐based constitutive models to verify its practical applicability. In summary, it is observed that though the trained models predicted the time histories of ru and γ reasonably well; however, they struggled to predict the hysteresis loops at higher cycles. Therefore, more research is needed to verify and enhance the predictability of existing AI‐based models in the future before using them in practice for simulating cyclic response.
{"title":"Evaluation and Future Prospects of Data‐Driven Intelligence‐Based Framework for Predicting Cyclic Behavior of Reconstituted Sand","authors":"Kaushik Jas, Amalesh Jana, G. R. Dodagoudar","doi":"10.1002/nag.3939","DOIUrl":"https://doi.org/10.1002/nag.3939","url":null,"abstract":"Most of the robust artificial intelligence (AI)‐based constitutive models are developed with synthetic datasets generated from traditional constitutive models. Therefore, they fundamentally rely on the traditional constitutive models rather than laboratory test results. Also, their potential use within geotechnical engineering communities is limited due to the unavailability of datasets along with the model code files. In this study, the data‐driven constitutive models are developed using only laboratory test databases and deep learning (DL) techniques. The laboratory database was prepared by conducting cyclic direct simple shear (CDSS) tests on reconstituted sand, that is, PDX sand. The stacked long short‐term memory (LSTM) network and its variants are considered for developing the predictive models of the shear strain (<jats:italic>γ</jats:italic> [%]) and excess pore pressure ratio (<jats:italic>r<jats:sub>u</jats:sub></jats:italic>) time histories. The suitable input parameters (IPs) are selected based on the physics behind the generation of <jats:italic>r<jats:sub>u</jats:sub></jats:italic> and <jats:italic>γ</jats:italic> (%) of the liquefiable sands. The predicted responses of <jats:italic>γ</jats:italic> (%) and <jats:italic>r<jats:sub>u</jats:sub></jats:italic> agree well in most cases and are used to predict the dynamic soil properties of the PDX sand. The same modeling framework is extended for other sand and compared with existing AI‐based constitutive models to verify its practical applicability. In summary, it is observed that though the trained models predicted the time histories of <jats:italic>r<jats:sub>u</jats:sub></jats:italic> and <jats:italic>γ</jats:italic> reasonably well; however, they struggled to predict the hysteresis loops at higher cycles. Therefore, more research is needed to verify and enhance the predictability of existing AI‐based models in the future before using them in practice for simulating cyclic response.","PeriodicalId":13786,"journal":{"name":"International Journal for Numerical and Analytical Methods in Geomechanics","volume":"4 1","pages":""},"PeriodicalIF":4.0,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142986237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A critical state plasticity model is proposed to describe the anisotropic sand behaviour under both proportional and non‐proportional loading conditions. An evolving fabric tensor is introduced into the model to reflect the influence of fabric anisotropy on the stress‐strain relation of sand. By employing a fabric‐dependent plastic flow direction, the non‐coaxial response can be simulated in a simple way. A non‐proportional loading mechanism is incorporated to consider the plastic deformation induced by the stress increment tangential to the yield surface. The influence of accumulative plastic strain on the dilatancy function and plastic modulus is properly considered, enabling the model to reasonably capture the evolutions of volumetric and deviatoric strains under both drained and undrained principal stress axes rotation. The model was validated based on the simulations of experimental results for monotonic loading and pure principal stress axes rotation tests covering a wide range of conditions.
{"title":"A Constitutive Model for Anisotropic Sand Considering Fabric Evolution Under Proportional and Non‐Proportional Loadings","authors":"Dong Liao, Chao Zhou, Zhongxuan Yang","doi":"10.1002/nag.3937","DOIUrl":"https://doi.org/10.1002/nag.3937","url":null,"abstract":"A critical state plasticity model is proposed to describe the anisotropic sand behaviour under both proportional and non‐proportional loading conditions. An evolving fabric tensor is introduced into the model to reflect the influence of fabric anisotropy on the stress‐strain relation of sand. By employing a fabric‐dependent plastic flow direction, the non‐coaxial response can be simulated in a simple way. A non‐proportional loading mechanism is incorporated to consider the plastic deformation induced by the stress increment tangential to the yield surface. The influence of accumulative plastic strain on the dilatancy function and plastic modulus is properly considered, enabling the model to reasonably capture the evolutions of volumetric and deviatoric strains under both drained and undrained principal stress axes rotation. The model was validated based on the simulations of experimental results for monotonic loading and pure principal stress axes rotation tests covering a wide range of conditions.","PeriodicalId":13786,"journal":{"name":"International Journal for Numerical and Analytical Methods in Geomechanics","volume":"93 1","pages":""},"PeriodicalIF":4.0,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142986236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Soil arching is one of the main mechanisms for load transfer in pile‐supported embankments, and the soil arching evolution patterns varied significantly depending on fill heights, pile spacings, pile stiffness, and soil stiffness. However, research on the effect of pile settlement on soil arching is relatively scarce, and most studies still use the traditional trapdoor test with a fixed arch foot to examine the soil arching. Therefore, this study establishes numerical models of a damping spring‐based trapdoor that considers pile settlement, and through 52 sets of spring‐based trapdoor tests and 1 set of reference tests, it systematically investigates the effects of various factors such as pile–soil stiffness ratio, fill height, and pile spacing on the soil arching under pile settlement conditions. The research results show that reducing the pile–soil stiffness ratio will reduce differential settlement between piles and soil, but it will exacerbate overall settlement. The stiffness ratio has a significant impact on soil arching: appropriately reducing the pile–soil stiffness ratio will help to recover fill deformation and suppress the formation of passive soil arch; increasing the stiffness ratio will enhance the stability of the soil arching. In addition, when the soft soil stiffness ks is low, pile settlement helps to enhance the soil arching, and the enhancement effect becomes more significant with an increase in fill height H and pile spacing S/a. When ks is high, pile settlement weakens the soil arching, which intensifies with an increase in fill height but weakens with an increase in S/a.
{"title":"Numerical Study on Soil‐Arching Behavior in Pile‐Supported Embankments With Pile Settlement by Developed Damping Spring‐Based Trapdoor Model","authors":"Jie Zhou, Ling Zhang, Wenzhe Peng, Zeyu Xu, Shuai Zhou, Gaoqiao Wu","doi":"10.1002/nag.3940","DOIUrl":"https://doi.org/10.1002/nag.3940","url":null,"abstract":"Soil arching is one of the main mechanisms for load transfer in pile‐supported embankments, and the soil arching evolution patterns varied significantly depending on fill heights, pile spacings, pile stiffness, and soil stiffness. However, research on the effect of pile settlement on soil arching is relatively scarce, and most studies still use the traditional trapdoor test with a fixed arch foot to examine the soil arching. Therefore, this study establishes numerical models of a damping spring‐based trapdoor that considers pile settlement, and through 52 sets of spring‐based trapdoor tests and 1 set of reference tests, it systematically investigates the effects of various factors such as pile–soil stiffness ratio, fill height, and pile spacing on the soil arching under pile settlement conditions. The research results show that reducing the pile–soil stiffness ratio will reduce differential settlement between piles and soil, but it will exacerbate overall settlement. The stiffness ratio has a significant impact on soil arching: appropriately reducing the pile–soil stiffness ratio will help to recover fill deformation and suppress the formation of passive soil arch; increasing the stiffness ratio will enhance the stability of the soil arching. In addition, when the soft soil stiffness <jats:italic>k</jats:italic><jats:sub>s</jats:sub> is low, pile settlement helps to enhance the soil arching, and the enhancement effect becomes more significant with an increase in fill height <jats:italic>H</jats:italic> and pile spacing <jats:italic>S</jats:italic>/<jats:italic>a</jats:italic>. When <jats:italic>k</jats:italic><jats:sub>s</jats:sub> is high, pile settlement weakens the soil arching, which intensifies with an increase in fill height but weakens with an increase in <jats:italic>S</jats:italic>/<jats:italic>a</jats:italic>.","PeriodicalId":13786,"journal":{"name":"International Journal for Numerical and Analytical Methods in Geomechanics","volume":"1 1","pages":""},"PeriodicalIF":4.0,"publicationDate":"2025-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142986235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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