Pub Date : 2026-01-16DOI: 10.1016/j.compgeo.2026.107914
Gerardo Grelle
The Geomechanical Core (GMC) is a novel, scalable, and modular computational framework designed as the central engine component of hybrid AI systems for predicting and mapping seismic-induced landslides. GMC is founded on three pillars: a generalized failure model, a dimensionless constitutive model, and a serial modular architecture. The generalized failure model is a physically consistent adaptive function that distributes the initial shear strength over a normalized logarithmic shear-surface template, accounting for potential strength reductions caused by pre-seismic straining. At the heart of the engine, the constitutive model reproduces nonlinear elastoplastic stress–strain behavior through the relationship between normalized seismic load and straining (ductility ratio). This dimensionless formulation integrates the Hardening Soil (HS) approach for slope deformation and the Limit Equilibrium (LE) method for triggering and sliding, enabling the computation of both reversible and irreversible excess pore-water pressures under seismic excitation. The GMC chain of modules can be configured to represent different sectors of a landslide mass, where interacting boxes exchange static stress for initialization and dynamically update deformation states during shaking. GMC demonstrates high computational efficiency and aims to bridge the gap between large-scale predictive modeling and advanced constitutive-based numerical simulations.
{"title":"A Dimensionless Geomechanical Core to Inform ML-AI Prediction of Seismic-Induced Landslides","authors":"Gerardo Grelle","doi":"10.1016/j.compgeo.2026.107914","DOIUrl":"10.1016/j.compgeo.2026.107914","url":null,"abstract":"<div><div>The Geomechanical Core (GMC) is a novel, scalable, and modular computational framework designed as the central engine component of hybrid AI systems for predicting and mapping seismic-induced landslides. GMC is founded on three pillars: a generalized failure model, a dimensionless constitutive model, and a serial modular architecture. The generalized failure model is a physically consistent adaptive function that distributes the initial shear strength over a normalized logarithmic shear-surface template, accounting for potential strength reductions caused by pre-seismic straining. At the heart of the engine, the constitutive model reproduces nonlinear elastoplastic stress–strain behavior through the relationship between normalized seismic load and straining (ductility ratio). This dimensionless formulation integrates the Hardening Soil (HS) approach for slope deformation and the Limit Equilibrium (LE) method for triggering and sliding, enabling the computation of both reversible and irreversible excess pore-water pressures under seismic excitation. The GMC chain of modules can be configured to represent different sectors of a landslide mass, where interacting boxes exchange static stress for initialization and dynamically update deformation states during shaking. GMC demonstrates high computational efficiency and aims to bridge the gap between large-scale predictive modeling and advanced constitutive-based numerical simulations.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"192 ","pages":"Article 107914"},"PeriodicalIF":6.2,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976133","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}
Pub Date : 2026-01-16DOI: 10.1016/j.compgeo.2026.107922
Xinyang Lv , Youjun Ning
Rock bolting serves as a crucial reinforcement measure by mobilizing and enhancing the strength and self-stability of rock masses. In this work, a rock bolt model that incorporates the axial-bending coupling deformation and the bolt-rock interface axial and lateral interaction effects is established within the discontinuous deformation analysis (DDA). The effectiveness of the developed bolt model is first verified by comparing the DDA simulation results of bolt pull-out tests and bolt single and double-structural plane shear tests with experimental and theoretical results. Correspondingly, in the pull-out tests, the relationships between pull-out force and displacement, and the characteristics of interface shear stress and bolt axial force are investigated. In the structural plane shear tests, the relationships between bolt shear resistance and joint shear displacement, and the bolt bending deformation and force characteristics are investigated. Moreover, comparative simulation studies of a jointed rock tunnel without and with bolt reinforcement are conducted to verify the feasibility of the developed rock bolt model in practical simulations of jointed rock mass reinforcement by bolts. Correspondingly, the deformation and failure responses of the tunnel surrounding rock, as well as the deformation and force characteristics of the bolts, are comprehensively investigated. This work enhances the rock bolting simulation capability of DDA and provides an optional numerical approach for rock bolting problem investigations, especially for jointed rock.
{"title":"Development and verifications of rock bolts with axial-bending coupling deformation and bolt-rock interface effect in discontinuous deformation analysis (DDA)","authors":"Xinyang Lv , Youjun Ning","doi":"10.1016/j.compgeo.2026.107922","DOIUrl":"10.1016/j.compgeo.2026.107922","url":null,"abstract":"<div><div>Rock bolting serves as a crucial reinforcement measure by mobilizing and enhancing the strength and self-stability of rock masses. In this work, a rock bolt model that incorporates the axial-bending coupling deformation and the bolt-rock interface axial and lateral interaction effects is established within the discontinuous deformation analysis (DDA). The effectiveness of the developed bolt model is first verified by comparing the DDA simulation results of bolt pull-out tests and bolt single and double-structural plane shear tests with experimental and theoretical results. Correspondingly, in the pull-out tests, the relationships between pull-out force and displacement, and the characteristics of interface shear stress and bolt axial force are investigated. In the structural plane shear tests, the relationships between bolt shear resistance and joint shear displacement, and the bolt bending deformation and force characteristics are investigated. Moreover, comparative simulation studies of a jointed rock tunnel without and with bolt reinforcement are conducted to verify the feasibility of the developed rock bolt model in practical simulations of jointed rock mass reinforcement by bolts. Correspondingly, the deformation and failure responses of the tunnel surrounding rock, as well as the deformation and force characteristics of the bolts, are comprehensively investigated. This work enhances the rock bolting simulation capability of DDA and provides an optional numerical approach for rock bolting problem investigations, especially for jointed rock.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"192 ","pages":"Article 107922"},"PeriodicalIF":6.2,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976083","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}
Pub Date : 2026-01-15DOI: 10.1016/j.compgeo.2026.107913
Xindong Zhai, Long Yu, Qing Yang, Chunlei Li, Yunrui Han
Deriving a sufficiently simple and accurate model from the soil constitutive behaviors—a highly complex nonlinear system—remains a fundamental yet challenging problem in geotechnical engineering. Data-driven discovery methods have shown significant potential for advancing constitutive knowledge. However, current data-driven discovery methods still face challenges in identifying quotient‑form nonlinearity (defined as the ratio of user‑defined basis terms), which is ubiquitous in most soil constitutive models. In this study, a novel implicit data-driven approach is proposed for the automatic discovery of governing equation(s) for quotient‑form nonlinear constitutive systems. The approach is straightforward and integrates implicit sparse identification, Recursive Feature Elimination (RFE), and unsupervised Pareto optimization to achieve automated, parsimonious model selection without requiring hyperparameter tuning. Validation on synthetic triaxial data with artificial noise demonstrates the reliability of the approach in automatically rediscovering the true underlying constitutive equations including nonlinear elasticity, hyperelasticity, and elastoplasticity. Results indicate that the discovered equations closely match the true hidden models in predicting the stress–strain behaviors of soil along triaxial stress paths. Its data dependency is also analyzed with respect to data size and richness, highlighting the importance of diverse stress paths for data-driven discovery. The proposed data-driven approach is generic, capable of describing and extracting the constitutive behavior of geotechnical materials, and has the potential to advance the understanding of other complex geotechnical systems.
{"title":"Implicit data‑driven discovery of constitutive equations for soil","authors":"Xindong Zhai, Long Yu, Qing Yang, Chunlei Li, Yunrui Han","doi":"10.1016/j.compgeo.2026.107913","DOIUrl":"10.1016/j.compgeo.2026.107913","url":null,"abstract":"<div><div>Deriving a sufficiently simple and accurate model from the soil constitutive behaviors—a highly complex nonlinear system—remains a fundamental yet challenging problem in geotechnical engineering. Data-driven discovery methods have shown significant potential for advancing constitutive knowledge. However, current data-driven discovery methods still face challenges in identifying quotient‑form nonlinearity (defined as the ratio of user‑defined basis terms), which is ubiquitous in most soil constitutive models. In this study, a novel implicit data-driven approach is proposed for the automatic discovery of governing equation(s) for quotient‑form nonlinear constitutive systems. The approach is straightforward and integrates implicit sparse identification, Recursive Feature Elimination (RFE), and unsupervised Pareto optimization to achieve automated, parsimonious model selection without requiring hyperparameter tuning. Validation on synthetic triaxial data with artificial noise demonstrates the reliability of the approach in automatically rediscovering the true underlying constitutive equations including nonlinear elasticity, hyperelasticity, and elastoplasticity. Results indicate that the discovered equations closely match the true hidden models in predicting the stress–strain behaviors of soil along triaxial stress paths. Its data dependency is also analyzed with respect to data size and richness, highlighting the importance of diverse stress paths for data-driven discovery. The proposed data-driven approach is generic, capable of describing and extracting the constitutive behavior of geotechnical materials, and has the potential to advance the understanding of other complex geotechnical systems.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"192 ","pages":"Article 107913"},"PeriodicalIF":6.2,"publicationDate":"2026-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976082","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}
Pub Date : 2026-01-14DOI: 10.1016/j.compgeo.2026.107915
Jun-Cheng Yao , Yu Wang , Kostas Senetakis
To protect the environment and minimize reclamation-induced disruption to marine ecosystems in land reclamation projects, soft soils (e.g., marine clay) below seabed may be stabilized in-situ using non-dredged ground improvement methods such as deep cement mixing (DCM). Design of DCM requires accurate information on three-dimensional (3D) spatial distribution of soft soils, including detailed locations of soft soil pockets, to determine the DCM termination depth and ensure a safe and sustainable reclamation. In engineering practice, it is challenging to accurately delineate 3D spatial variations of soft soil pockets below seabed, because subsurface site investigation data (e.g., cone penetration test (CPT) data) is often limited and there is a lack of effective methods for modelling 3D soil stratigraphy from limited CPTs. To tackle this challenge, a data-driven method is proposed in which, a 3D point cloud model is developed based on two cross-correlated CPT quantities, i.e., the normalized tip resistance Qt and the normalized friction ratio FR. Consecutively, many 3D random field sample (RFS) pairs of the cross-correlated Qt and FR are generated under a Bayesian framework, leading to probable samples of soil behavior types based on Robertson’s soil classification chart at each point within the 3D domain. Ultimately, the 3D spatial distribution of soft soil pockets is delineated automatically in a data-driven manner, with quantified uncertainty. The method is applied to a real reclamation site, and its performance is evaluated. The effect of CPT number on the performance of proposed method is also investigated.
{"title":"Data-driven identification of three-dimensional spatial distribution of soft soil pockets below seabed for land reclamation using limited cone penetration tests","authors":"Jun-Cheng Yao , Yu Wang , Kostas Senetakis","doi":"10.1016/j.compgeo.2026.107915","DOIUrl":"10.1016/j.compgeo.2026.107915","url":null,"abstract":"<div><div>To protect the environment and minimize reclamation-induced disruption to marine ecosystems in land reclamation projects, soft soils (e.g., marine clay) below seabed may be stabilized in-situ using non-dredged ground improvement methods such as deep cement mixing (DCM). Design of DCM requires accurate information on three-dimensional (3D) spatial distribution of soft soils, including detailed locations of soft soil pockets, to determine the DCM termination depth and ensure a safe and sustainable reclamation. In engineering practice, it is challenging to accurately delineate 3D spatial variations of soft soil pockets below seabed, because subsurface site investigation data (e.g., cone penetration test (CPT) data) is often limited and there is a lack of effective methods for modelling 3D soil stratigraphy from limited CPTs. To tackle this challenge, a data-driven method is proposed in which, a 3D point cloud model is developed based on two cross-correlated CPT quantities, i.e., the normalized tip resistance <em>Q</em><sub>t</sub> and the normalized friction ratio <em>F</em><sub>R</sub>. Consecutively, many 3D random field sample (RFS) pairs of the cross-correlated <em>Q</em><sub>t</sub> and <em>F</em><sub>R</sub> are generated under a Bayesian framework, leading to probable samples of soil behavior types based on Robertson’s soil classification chart at each point within the 3D domain. Ultimately, the 3D spatial distribution of soft soil pockets is delineated automatically in a data-driven manner, with quantified uncertainty. The method is applied to a real reclamation site, and its performance is evaluated. The effect of CPT number on the performance of proposed method is also investigated.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"192 ","pages":"Article 107915"},"PeriodicalIF":6.2,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976085","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}
Pub Date : 2026-01-13DOI: 10.1016/j.compgeo.2026.107923
Can Yi , Jianyu Chen , Dianlei Feng
Submarine landslides are common and destructive geological hazards that pose severe threats to marine engineering infrastructure. Quantitative analysis and prediction of the associated impact damage are therefore crucial. However, these processes involve large deformation flows, fluid–structure interaction (FSI), and flow regime transitions, which present significant challenges for numerical modeling. To address these issues, we propose a GPU-accelerated three-dimensional Smoothed Particle Hydrodynamics fluid–structure interaction (SPH-FSI) approach using the updated Lagrangian (UL) formulation and the total Lagrangian (TL) formulation for solving the fluid and solid governing equations, respectively. This model incorporates spatial expansion and particle-mapping techniques to achieve large-scale parallel particle splitting, enabling effective treatment of flow regime transitions and strong FSI processes. The model is first applied to simulate the transition from debris flow to turbidity currents in submarine landslides, demonstrating its capability to capture the evolution of complex flow regime transitions. Then we investigate the impact of landslides on rigid structures, providing both qualitative and quantitative insights into the loading characteristics. Finally, the dynamic response of elastic structures is analyzed to assess structural behavior under different mechanical conditions. Numerical results demonstrate that the proposed model is robust and accurate, providing an effective tool for investigating flow regime transitions in submarine landslides and their impact on engineering structures.
{"title":"A novel GPU-accelerated debris flow-turbidity currents transition model for simulating underwater sliding impacts on deformable pipelines using total and updated Lagrangian WCSPH method","authors":"Can Yi , Jianyu Chen , Dianlei Feng","doi":"10.1016/j.compgeo.2026.107923","DOIUrl":"10.1016/j.compgeo.2026.107923","url":null,"abstract":"<div><div>Submarine landslides are common and destructive geological hazards that pose severe threats to marine engineering infrastructure. Quantitative analysis and prediction of the associated impact damage are therefore crucial. However, these processes involve large deformation flows, fluid–structure interaction (FSI), and flow regime transitions, which present significant challenges for numerical modeling. To address these issues, we propose a GPU-accelerated three-dimensional Smoothed Particle Hydrodynamics fluid–structure interaction (SPH-FSI) approach using the updated Lagrangian (UL) formulation and the total Lagrangian (TL) formulation for solving the fluid and solid governing equations, respectively. This model incorporates spatial expansion and particle-mapping techniques to achieve large-scale parallel particle splitting, enabling effective treatment of flow regime transitions and strong FSI processes. The model is first applied to simulate the transition from debris flow to turbidity currents in submarine landslides, demonstrating its capability to capture the evolution of complex flow regime transitions. Then we investigate the impact of landslides on rigid structures, providing both qualitative and quantitative insights into the loading characteristics. Finally, the dynamic response of elastic structures is analyzed to assess structural behavior under different mechanical conditions. Numerical results demonstrate that the proposed model is robust and accurate, providing an effective tool for investigating flow regime transitions in submarine landslides and their impact on engineering structures.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"192 ","pages":"Article 107923"},"PeriodicalIF":6.2,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976084","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}
Pub Date : 2026-01-12DOI: 10.1016/j.compgeo.2025.107861
Jiadian Liu , Weizhong Chen , Runze Yang , Shenhua Liu
The prediction of crack initiation and propagation is of vital importance to engineering safety in geotechnical engineering. However, the nonlinear damage characteristics of quasi-brittle materials, coupled with the high computational cost of nonlocal methods, present significant challenges to the simulation of crack evolution. Thus, this study introduces a quasi-brittle peridynamic (QB-PD) model based on the classical prototype micro-elastic brittle peridynamic (PMB-PD) formulation and further develops an efficient GPU-accelerated computational framework. Unlike the PMB-PD model, which accounts for only linear elastic tensile failure, the QB-PD model incorporates a bond stiffness degradation function and a repulsive force mechanism between material points, enabling the characterisation of nonlinear damage and compressive failure. To enable large-scale simulations, a GPU-parallel computing framework is constructed leveraging the inherent parallel characteristics of peridynamics, with a point-pair mapping strategy as the core logic. This framework systematically optimises the data structure and computational workflow of the peridynamic solver. The QB-PD model is validated through several benchmark numerical examples, and the performance of the parallel framework is thoroughly evaluated in the final case. Results demonstrate that the proposed model can more accurately capture the crack paths and nonlinear mechanical responses of quasi-brittle materials. Meanwhile, the GPU-based framework significantly enhances computational efficiency, reducing memory usage by nearly 50 % and achieving millisecond-level preprocessing for million-point models. During the solution phase, it achieves up to 103-fold speedup compared to serial execution and provides approximately 3 × 102-fold and 5 × 101-fold speedups over serial and OpenMP implementations, respectively, under high-precision settings. This approach greatly facilitates efficient, large-scale simulation of geotechnical failure processes.
{"title":"GPU-accelerated peridynamic simulation for quasi-brittle materials: model development and efficient parallel framework","authors":"Jiadian Liu , Weizhong Chen , Runze Yang , Shenhua Liu","doi":"10.1016/j.compgeo.2025.107861","DOIUrl":"10.1016/j.compgeo.2025.107861","url":null,"abstract":"<div><div>The prediction of crack initiation and propagation is of vital importance to engineering safety in geotechnical engineering. However, the nonlinear damage characteristics of quasi-brittle materials, coupled with the high computational cost of nonlocal methods, present significant challenges to the simulation of crack evolution. Thus, this study introduces a quasi-brittle peridynamic (QB-PD) model based on the classical prototype micro-elastic brittle peridynamic (PMB-PD) formulation and further develops an efficient GPU-accelerated computational framework. Unlike the PMB-PD model, which accounts for only linear elastic tensile failure, the QB-PD model incorporates a bond stiffness degradation function and a repulsive force mechanism between material points, enabling the characterisation of nonlinear damage and compressive failure. To enable large-scale simulations, a GPU-parallel computing framework is constructed leveraging the inherent parallel characteristics of peridynamics, with a point-pair mapping strategy as the core logic. This framework systematically optimises the data structure and computational workflow of the peridynamic solver. The QB-PD model is validated through several benchmark numerical examples, and the performance of the parallel framework is thoroughly evaluated in the final case. Results demonstrate that the proposed model can more accurately capture the crack paths and nonlinear mechanical responses of quasi-brittle materials. Meanwhile, the GPU-based framework significantly enhances computational efficiency, reducing memory usage by nearly 50 % and achieving millisecond-level preprocessing for million-point models. During the solution phase, it achieves up to 10<sup>3</sup>-fold speedup compared to serial execution and provides approximately 3 × 10<sup>2</sup>-fold and 5 × 10<sup>1</sup>-fold speedups over serial and OpenMP implementations, respectively, under high-precision settings. This approach greatly facilitates efficient, large-scale simulation of geotechnical failure processes.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"192 ","pages":"Article 107861"},"PeriodicalIF":6.2,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976087","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}
Pub Date : 2026-01-12DOI: 10.1016/j.compgeo.2026.107912
Jiale Fu , Shu Jiang , Linhao Zhang , Pengfei Xiong , Hongji Liu , Ruyang Yu , Zhiping Zhang
A comprehensive understanding of rock deformation and failure behaviors, along with brittleness characteristics under high-temperature conditions, is crucial for enhancing the fracturing efficiency in unconventional energy reservoirs and ensuring the stability of horizontal wellbores. This study presents a novel damage constitutive model (CEED model) that incorporates thermal expansion, compaction effects, and energy evolution, offering a comprehensive framework for characterizing the whole stress–strain behavior of rock at the macroscale. The modeling process is divided into two stages, with the closure strain of characteristic points serving as the boundary. Initially, rock is conceptualized as a porous medium comprising a mineral matrix (hard spring) and voids (soft spring), with their respective deformation behaviors governed by distinct formulations of Hooke’s law. By incorporating the effects of thermal stress into the effective stress framework, a stress–strain relationship is established to capture the nonlinear behavior of rock during the compaction stage. In the subsequent phase, dissipation energy is utilized to represent the strength of rock micro-elements, enabling the construction of a statistical damage constitutive model for the post-closure strain behavior. The proposed CEED model is validated using triaxial compression experimental data for coal, shale, and tight sandstone under varying temperature conditions. The results demonstrate that the theoretical curves produced by the CEED model closely match the experimental observations, especially in accurately capturing the nonlinear deformation behavior of rock during the compaction stage. Moreover, an energy-based method for evaluating the brittleness index is proposed, introducing the brittleness thermal sensitivity factor to quantify the dependence of rock brittleness on temperature. With a minimal number of parameters and clear physical significance, the proposed CEED model and brittleness index evaluation method can be readily applied in conventional triaxial compression experiments. This study provides a novel framework for optimizing reservoir stimulation designs and improving the efficiency of unconventional gas exploitation.
{"title":"A damage constitutive model for brittle rock considering compaction effect and energy dissipation characteristics","authors":"Jiale Fu , Shu Jiang , Linhao Zhang , Pengfei Xiong , Hongji Liu , Ruyang Yu , Zhiping Zhang","doi":"10.1016/j.compgeo.2026.107912","DOIUrl":"10.1016/j.compgeo.2026.107912","url":null,"abstract":"<div><div>A comprehensive understanding of rock deformation and failure behaviors, along with brittleness characteristics under high-temperature conditions, is crucial for enhancing the fracturing efficiency in unconventional energy reservoirs and ensuring the stability of horizontal wellbores. This study presents a novel damage constitutive model (CEED model) that incorporates thermal expansion, compaction effects, and energy evolution, offering a comprehensive framework for characterizing the whole stress–strain behavior of rock at the macroscale. The modeling process is divided into two stages, with the closure strain of characteristic points serving as the boundary. Initially, rock is conceptualized as a porous medium comprising a mineral matrix (hard spring) and voids (soft spring), with their respective deformation behaviors governed by distinct formulations of Hooke’s law. By incorporating the effects of thermal stress into the effective stress framework, a stress–strain relationship is established to capture the nonlinear behavior of rock during the compaction stage. In the subsequent phase, dissipation energy is utilized to represent the strength of rock micro-elements, enabling the construction of a statistical damage constitutive model for the post-closure strain behavior. The proposed CEED model is validated using triaxial compression experimental data for coal, shale, and tight sandstone under varying temperature conditions. The results demonstrate that the theoretical curves produced by the CEED model closely match the experimental observations, especially in accurately capturing the nonlinear deformation behavior of rock during the compaction stage. Moreover, an energy-based method for evaluating the brittleness index is proposed, introducing the brittleness thermal sensitivity factor to quantify the dependence of rock brittleness on temperature. With a minimal number of parameters and clear physical significance, the proposed CEED model and brittleness index evaluation method can be readily applied in conventional triaxial compression experiments. This study provides a novel framework for optimizing reservoir stimulation designs and improving the efficiency of unconventional gas exploitation.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"192 ","pages":"Article 107912"},"PeriodicalIF":6.2,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976634","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}
Pub Date : 2026-01-12DOI: 10.1016/j.compgeo.2026.107909
Ahmet Can Mert , Tuan A. Pham , Xiangfeng Guo
Piles are vital foundation systems that require careful design optimization. However, engineers often overlook soil uncertainties in optimizing pile designs. Moreover, exploring the entire design space for optimization remains a challenge due to the extensive computational time and complexity associated with numerical models. To address these challenges, this study introduces a novel multi-objective reliability-based design optimization (MO-RBDO) framework for pile foundations, explicitly incorporating soil spatial variability. Our novelty in this work is integrating soil spatial variability into an extended simplified model with calibration, yielding an efficient surrogate over complex numerical models that face challenges in exploring the entire design space in MO-RBDO. The proposed framework consists of three main components: (1) a calibrated simplified nonlinear load-settlement model capturing the interactions between piles and soil; (2) random field modeling to represent critical soil properties identified through sensitivity analysis; and (3) an MO-RBDO procedure that minimizes costs while maximizing pile reliability and design robustness. A case study demonstrated the framework’s effectiveness, highlighting the impact of spatial variability on optimal pile design and the trade-offs among cost, reliability, and robustness. This approach offers engineers a more practical and economically sound design framework for pile foundations in heterogeneous ground conditions.
{"title":"Multi-objective reliability-based design optimization of piles considering soil-structure interaction and soil spatial variability","authors":"Ahmet Can Mert , Tuan A. Pham , Xiangfeng Guo","doi":"10.1016/j.compgeo.2026.107909","DOIUrl":"10.1016/j.compgeo.2026.107909","url":null,"abstract":"<div><div>Piles are vital foundation systems that require careful design optimization. However, engineers often overlook soil uncertainties in optimizing pile designs. Moreover, exploring the entire design space for optimization remains a challenge due to the extensive computational time and complexity associated with numerical models. To address these challenges, this study introduces a novel multi-objective reliability-based design optimization (MO-RBDO) framework for pile foundations, explicitly incorporating soil spatial variability. Our novelty in this work is integrating soil spatial variability into an extended simplified model with calibration, yielding an efficient surrogate over complex numerical models that face challenges in exploring the entire design space in MO-RBDO. The proposed framework consists of three main components: (1) a calibrated simplified nonlinear load-settlement model capturing the interactions between piles and soil; (2) random field modeling to represent critical soil properties identified through sensitivity analysis; and (3) an MO-RBDO procedure that minimizes costs while maximizing pile reliability and design robustness. A case study demonstrated the framework’s effectiveness, highlighting the impact of spatial variability on optimal pile design and the trade-offs among cost, reliability, and robustness. This approach offers engineers a more practical and economically sound design framework for pile foundations in heterogeneous ground conditions.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"192 ","pages":"Article 107909"},"PeriodicalIF":6.2,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976086","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}
Pub Date : 2026-01-10DOI: 10.1016/j.compgeo.2025.107894
Octavianus Arvin Sukiwan, Arman Khoshghalb, Babak Shahbodagh, Asal Bidarmaghz
Soil laboratory testing often requires the removal of oversized particles to satisfy specimen-size limitations, resulting in a modified particle size distribution (PSD) that can significantly influence the measured shear strength and volume-change response. This study presents a physically based framework, grounded in fractal theory, for relating the critical state line (CSL) of a scalped soil to that of the original field material. The approach quantifies the vertical shift of the CSL in the – space induced by PSD truncation, while preserving the intrinsic critical state parameters and . This provides a practical tool for estimating the CSL of field-scale materials from laboratory-scaled specimens. Validation against multiple published datasets demonstrates that the predicted CSLs closely match experimental trends, and remain consistent with the observed volume-change behaviour and peak shear strength measurements. The findings show that conventional laboratory results on scalped specimens may substantially misrepresent the behaviour of the in-situ material unless properly corrected. The proposed framework therefore enables more reliable interpretation of strength and state-parameter-dependent behaviour in coarse granular soils where full-scale testing is not feasible.
{"title":"Practical guidelines for connecting critical states, strengths and dilatancies of scalped and natural soils","authors":"Octavianus Arvin Sukiwan, Arman Khoshghalb, Babak Shahbodagh, Asal Bidarmaghz","doi":"10.1016/j.compgeo.2025.107894","DOIUrl":"10.1016/j.compgeo.2025.107894","url":null,"abstract":"<div><div>Soil laboratory testing often requires the removal of oversized particles to satisfy specimen-size limitations, resulting in a modified particle size distribution (PSD) that can significantly influence the measured shear strength and volume-change response. This study presents a physically based framework, grounded in fractal theory, for relating the critical state line (CSL) of a scalped soil to that of the original field material. The approach quantifies the vertical shift of the CSL in the <span><math><mrow><mi>ln</mi><mi>e</mi></mrow></math></span>–<span><math><mrow><mi>ln</mi><msup><mrow><mi>p</mi></mrow><mo>′</mo></msup></mrow></math></span> space induced by PSD truncation, while preserving the intrinsic critical state parameters <span><math><mrow><mi>M</mi></mrow></math></span> and <span><math><mrow><mi>λ</mi></mrow></math></span>. This provides a practical tool for estimating the CSL of field-scale materials from laboratory-scaled specimens. Validation against multiple published datasets demonstrates that the predicted CSLs closely match experimental trends, and remain consistent with the observed volume-change behaviour and peak shear strength measurements. The findings show that conventional laboratory results on scalped specimens may substantially misrepresent the behaviour of the in-situ material unless properly corrected. The proposed framework therefore enables more reliable interpretation of strength and state-parameter-dependent behaviour in coarse granular soils where full-scale testing is not feasible.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"192 ","pages":"Article 107894"},"PeriodicalIF":6.2,"publicationDate":"2026-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145924599","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}
Pub Date : 2026-01-08DOI: 10.1016/j.compgeo.2026.107908
Fei Wang , Dehao Meng , Heinz Konietzky , Eleni Gerolymatou , Paul W.J. Glover , Ben-Guo He
In fractured geothermal energy storage systems, repeated heating and cooling cycles and fluid interactions cause non-linear and non-monotonic fracture deformations, requiring sophisticated modeling of complex thermo-hydro-mechanical (THM) behaviors. This paper proposes a new cohesive crack model for the discrete element method (DEM), aiming to enhance the characterization of the entire fracturing process in rocks during loading–unloading-reloading while considering thermo-hydraulic conditions. Specifically, the model proposed allows for flexible adjustment of post-peak tension behavior and is able to capture the progressive evolution of fracture opening and closing under cyclic THM loadings. Validation of the new model was performed under a range of thermo-hydraulic conditions, confirming its ability to replicate diverse fracture behaviors, and offering a comprehensive solution to modeling the complex interplay of thermal, hydraulic, and mechanical factors influencing rock fractures in the context of geothermal energy storage and extraction systems.
{"title":"A discrete element approach for simulating progressive fracturing in geothermal reservoirs via a new cohesive crack model","authors":"Fei Wang , Dehao Meng , Heinz Konietzky , Eleni Gerolymatou , Paul W.J. Glover , Ben-Guo He","doi":"10.1016/j.compgeo.2026.107908","DOIUrl":"10.1016/j.compgeo.2026.107908","url":null,"abstract":"<div><div>In fractured geothermal energy storage systems, repeated heating and cooling cycles and fluid interactions cause non-linear and non-monotonic fracture deformations, requiring sophisticated modeling of complex thermo-hydro-mechanical (THM) behaviors. This paper proposes a new cohesive crack model for the discrete element method (DEM), aiming to enhance the characterization of the entire fracturing process in rocks during loading–unloading-reloading while considering thermo-hydraulic conditions. Specifically, the model proposed allows for flexible adjustment of post-peak tension behavior and is able to capture the progressive evolution of fracture opening and closing under cyclic THM loadings. Validation of the new model was performed under a range of thermo-hydraulic conditions, confirming its ability to replicate diverse fracture behaviors, and offering a comprehensive solution to modeling the complex interplay of thermal, hydraulic, and mechanical factors influencing rock fractures in the context of geothermal energy storage and extraction systems.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"192 ","pages":"Article 107908"},"PeriodicalIF":6.2,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145924595","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}
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