Pub Date : 2024-10-14DOI: 10.1016/j.compgeo.2024.106817
Jie Qi , Wenbin Fei , Guillermo A. Narsilio
The estimation of permeability in granular materials such as sands is essential to various engineering applications. The permeability of granular assemblies is fundamentally influenced by their microstructures, especially for irregular particle assemblies. However, the links between such intrinsic morphological complexity of natural geo-materials and the hydraulic properties are still largely unexplored. This research bridges this gap with an advanced workflow that combines image processing, Lattice Boltzmann Method (LBM), and the non-spherical Discrete Element Method (DEM). The geometries of five natural sand particles with distinct shapes are extracted from micro–Computed Tomography images. Each of them is used to generate monodisperse assemblies with varied porosity, through a sphero-polyhedra-based DEM for irregular particles. Then, the pore fluid flow patterns inside the assemblies are unveiled using LBM. Results show that particle shape has a significant impact on fluid flow and velocity distribution and thus on permeability, tortuosity, and the hydraulic anisotropy.
{"title":"An LBM study on the local fluid flow in irregular monodisperse granular assemblies from DEM: Effects of particle shape","authors":"Jie Qi , Wenbin Fei , Guillermo A. Narsilio","doi":"10.1016/j.compgeo.2024.106817","DOIUrl":"10.1016/j.compgeo.2024.106817","url":null,"abstract":"<div><div>The estimation of permeability in granular materials such as sands is essential to various engineering applications. The permeability of granular assemblies is fundamentally influenced by their microstructures, especially for irregular particle assemblies. However, the links between such intrinsic morphological complexity of natural geo-materials and the hydraulic properties are still largely unexplored. This research bridges this gap with an advanced workflow that combines image processing, Lattice Boltzmann Method (LBM), and the non-spherical Discrete Element Method (DEM). The geometries of five natural sand particles with distinct shapes are extracted from micro–Computed Tomography images. Each of them is used to generate monodisperse assemblies with varied porosity, through a sphero-polyhedra-based DEM for irregular particles. Then, the pore fluid flow patterns inside the assemblies are unveiled using LBM. Results show that particle shape has a significant impact on fluid flow and velocity distribution and thus on permeability, tortuosity, and the hydraulic anisotropy.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"177 ","pages":"Article 106817"},"PeriodicalIF":5.3,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142433358","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 : 2024-10-12DOI: 10.1016/j.compgeo.2024.106824
Hui Wang, Bo Zhou
The presence of methane hydrates (MH) and fine-grained materials introduces complex mechanical behaviors in methane hydrate-bearing sediments (MHBS), such as pronounced non-linearity and significant strain-softening characteristics. This study proposes a three-step homogenization procedure for the elastic parameters of bonded elements in MHBS, accounting for the effects of microscopic composition with varying mechanical properties and porosity. Moving from the mesoscopic to the macroscopic scale, and following the binary medium concept (BMC), external loading is jointly borne by mesoscopic bonded elements and frictional elements. The mechanical behavior of bonded elements is modelled using an elastic-brittleness framework, while frictional elements are described by the hyperbolic Duncan-Chang model. This approach enables a detailed analysis of the mesoscale deformation mechanisms in MHBS. A multi-scale damage model for MHBS (MSDM-MHBS) is then proposed, integrating the effects of micro-components and mesoscopic deformation mechanisms. The physical significance of the model parameters is explored by comparing the stress partitioning and damage evolution within MHBS. The validity and practicality of the proposed multi-scale damage constitutive model are confirmed through comparison with triaxial compression test results on MHBS with varying fine content and MH saturation. The MSDM-MHBS effectively models the nonlinearity, strain-hardening, and strain-softening characteristics influenced by the presence of methane hydrate and fine-grained particles. Moreover, it establishes a cross-scale relationship without introducing additional model parameters, offering valuable insights into the deformation mechanisms of MHBS and providing a theoretical foundation for the safe exploitation of methane hydrate in future research.
{"title":"MSDM-MHBS: A novel multi-scale damage constitutive model for methane hydrate-bearing sediments considering the influence of fine content and hydrate saturation","authors":"Hui Wang, Bo Zhou","doi":"10.1016/j.compgeo.2024.106824","DOIUrl":"10.1016/j.compgeo.2024.106824","url":null,"abstract":"<div><div>The presence of methane hydrates (MH) and fine-grained materials introduces complex mechanical behaviors in methane hydrate-bearing sediments (MHBS), such as pronounced non-linearity and significant strain-softening characteristics. This study proposes a three-step homogenization procedure for the elastic parameters of bonded elements in MHBS, accounting for the effects of microscopic composition with varying mechanical properties and porosity. Moving from the mesoscopic to the macroscopic scale, and following the binary medium concept (BMC), external loading is jointly borne by mesoscopic bonded elements and frictional elements. The mechanical behavior of bonded elements is modelled using an elastic-brittleness framework, while frictional elements are described by the hyperbolic Duncan-Chang model. This approach enables a detailed analysis of the mesoscale deformation mechanisms in MHBS. A multi-scale damage model for MHBS (MSDM-MHBS) is then proposed, integrating the effects of micro-components and mesoscopic deformation mechanisms. The physical significance of the model parameters is explored by comparing the stress partitioning and damage evolution within MHBS. The validity and practicality of the proposed multi-scale damage constitutive model are confirmed through comparison with triaxial compression test results on MHBS with varying fine content and MH saturation. The MSDM-MHBS effectively models the nonlinearity, strain-hardening, and strain-softening characteristics influenced by the presence of methane hydrate and fine-grained particles. Moreover, it establishes a cross-scale relationship without introducing additional model parameters, offering valuable insights into the deformation mechanisms of MHBS and providing a theoretical foundation for the safe exploitation of methane hydrate in future research.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"177 ","pages":"Article 106824"},"PeriodicalIF":5.3,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421220","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 : 2024-10-12DOI: 10.1016/j.compgeo.2024.106805
Yangyang Chen , Wen Liu , Demi Ai , Hongping Zhu , Yanliang Du
Ground settlement resulting from shield tunnelling in densely populated areas has a significant impact on the surrounding environment, while accurate prediction of max ground settlement (MGS) is challenging under uncertain construction conditions. This paper investigates the vine copula probabilistic dependence approach for MGS predictions with incomplete information. A Monte Carlo simulation framework is established to incorporates vine copula analysis for eight identified soil parameters. Finite element (FE) method was used to model construction tunnels with different parameters and determine the MGS induced by excavation. The modelling results were used to construct six MGS base learners, which were created using six machine learning models combined with hybrid particle swarm optimisation (PSO) and gravity search algorithms (GSA). The integrated learning model combined six distinct base learners to generate a meta-learner. Improved hybrid GSA and PSO leveraged the global search capabilities of PSO and the local search abilities of GSA to optimize the integrated learning model. The FE model and meta-model predictions of MGS were validated using twelve uncertain input parameters. The results suggested that the hybrid GSA and PSO enhanced the precision of regression in the integrated learning model, and the resulting meta-model improved the reliability of MGS predictions in situations with uncertain information.
{"title":"Probabilistic reliability assessment method for max ground settlement prediction of subway tunnel under uncertain construction information","authors":"Yangyang Chen , Wen Liu , Demi Ai , Hongping Zhu , Yanliang Du","doi":"10.1016/j.compgeo.2024.106805","DOIUrl":"10.1016/j.compgeo.2024.106805","url":null,"abstract":"<div><div>Ground settlement resulting from shield tunnelling in densely populated areas has a significant impact on the surrounding environment, while accurate prediction of max ground settlement (MGS) is challenging under uncertain construction conditions. This paper investigates the vine copula probabilistic dependence approach for MGS predictions with incomplete information. A Monte Carlo simulation framework is established to incorporates vine copula analysis for eight identified soil parameters. Finite element (FE) method was used to model construction tunnels with different parameters and determine the MGS induced by excavation. The modelling results were used to construct six MGS base learners, which were created using six machine learning models combined with hybrid particle swarm optimisation (PSO) and gravity search algorithms (GSA). The integrated learning model combined six distinct base learners to generate a <em>meta</em>-learner. Improved hybrid GSA and PSO leveraged the global search capabilities of PSO and the local search abilities of GSA to optimize the integrated learning model. The FE model and <em>meta</em>-model predictions of MGS were validated using twelve uncertain input parameters. The results suggested that the hybrid GSA and PSO enhanced the precision of regression in the integrated learning model, and the resulting <em>meta</em>-model improved the reliability of MGS predictions in situations with uncertain information.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"177 ","pages":"Article 106805"},"PeriodicalIF":5.3,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421221","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 : 2024-10-11DOI: 10.1016/j.compgeo.2024.106792
Rui Zhan, Bo Zhang, Lang Liu, Chao Huan, Yujiao Zhao, Xiaoyan Zhang, Xueli Wang
One of the most effective methods for geothermal energy extraction in deep mine stopes is the installation of heat exchange tubes within cemented backfill bodies. However, the complex underground environment can cause fracture in the backfill, which may negatively affect the geothermal extraction performance, especially in the presence of groundwater flow. This study establishes a three-dimensional seepage and heat transfer coupling model of cemented backfill heat exchangers with horizontal penetrating rough fractures via a finite element software platform. The model employs the Monte Carlo method combined with linear filtering to generate a rough fracture. The findings demonstrate that for fracture apertures ranging from 0 to 0.3 mm, the predominant mechanism of heat transfer is thermal conduction, with a negligible contribution from groundwater flow. However, as apertures expand from 0.3 mm to 2 mm, groundwater flow significantly enhances heat transfer, stabilizing beyond 2 mm. Increased fracture roughness at a 0.2 mm aperture does not enhance the heat recovery performance of the heat exchange tubes, but at a 4 mm aperture, a strong positive correlation between roughness and heat transfer is observed. Thus, narrow fractures can be treated as smooth, whereas roughness must be considered for wider fractures. The interaction between fracture flow and Darcy seepage increases with increasing groundwater hydraulic head, resulting in a notable improvement in the heat extraction performance of the heat exchange tube. When the relative position transitions from 0.75 °C to 0 °C, the outlet water temperature of the heat exchanger tube increases by approximately 9 °C.
{"title":"Study on the heat transfer characteristics of cemented backfill heat exchangers with a horizontally penetrating rough fracture under groundwater advection","authors":"Rui Zhan, Bo Zhang, Lang Liu, Chao Huan, Yujiao Zhao, Xiaoyan Zhang, Xueli Wang","doi":"10.1016/j.compgeo.2024.106792","DOIUrl":"10.1016/j.compgeo.2024.106792","url":null,"abstract":"<div><div>One of the most effective methods for geothermal energy extraction in deep mine stopes is the installation of heat exchange tubes within cemented backfill bodies. However, the complex underground environment can cause fracture in the backfill, which may negatively affect the geothermal extraction performance, especially in the presence of groundwater flow. This study establishes a three-dimensional seepage and heat transfer coupling model of cemented backfill heat exchangers with horizontal penetrating rough fractures via a finite element software platform. The model employs the Monte Carlo method combined with linear filtering to generate a rough fracture. The findings demonstrate that for fracture apertures ranging from 0 to 0.3 mm, the predominant mechanism of heat transfer is thermal conduction, with a negligible contribution from groundwater flow. However, as apertures expand from 0.3 mm to 2 mm, groundwater flow significantly enhances heat transfer, stabilizing beyond 2 mm. Increased fracture roughness at a 0.2 mm aperture does not enhance the heat recovery performance of the heat exchange tubes, but at a 4 mm aperture, a strong positive correlation between roughness and heat transfer is observed. Thus, narrow fractures can be treated as smooth, whereas roughness must be considered for wider fractures. The interaction between fracture flow and Darcy seepage increases with increasing groundwater hydraulic head, resulting in a notable improvement in the heat extraction performance of the heat exchange tube. When the relative position transitions from 0.75 °C to 0 °C, the outlet water temperature of the heat exchanger tube increases by approximately 9 °C.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"177 ","pages":"Article 106792"},"PeriodicalIF":5.3,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421137","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 : 2024-10-10DOI: 10.1016/j.compgeo.2024.106813
Jiang Hai-yan , Wang Sheng-nian , Gao Xinqun , Wu Zhi-jian , Li Mingwei , Gu Leilei
Due to material composition and structure effects, the permeability characteristics of cementitious soil rock mixtures (CSRMs) significantly differ from homogeneous rock and soil mass, and the great discreteness in limited indoor or in-situ experimental data has always shown up. This study established the stochastic mesostructure models of CSRMs with a self-developed modeling technology. Their saturated and unsaturated seepage parameters were determined by laboratory tests. Then, saturated and unsaturated numerical seepage simulations of CSRMs were carried out. The influences of rock block content, occurrence, shape, and permeability difference in soil and rock mass on their permeability coefficient were investigated. The empirical permeability coefficient prediction formulas about influencing factors were discussed. The results showed that the seepage characteristics of CSRMs conformed to Darcy’s law. Their permeability coefficient decreased first and then increased with the rock block content, and they achieved the minimum value when it was about 40 %. Their permeability coefficient increased with the rock block inclination and decreased with the aspect ratio of rock blocks. When the difference of soil and rock mass in permeability coefficient exceeded 1 × 103 in magnitude, their permeability coefficient should be mainly controlled by the side with the large permeability. Three empirical permeability prediction formulas for CSRMs were proposed. This study could provide theoretical and methodological references for the permeability cognition of CSRMs.
{"title":"Permeability characteristics and empirical prediction of cementitious soil rock mixtures based on numerical experiments of mesostructure","authors":"Jiang Hai-yan , Wang Sheng-nian , Gao Xinqun , Wu Zhi-jian , Li Mingwei , Gu Leilei","doi":"10.1016/j.compgeo.2024.106813","DOIUrl":"10.1016/j.compgeo.2024.106813","url":null,"abstract":"<div><div>Due to material composition and structure effects, the permeability characteristics of cementitious soil rock mixtures (CSRMs) significantly differ from homogeneous rock and soil mass, and the great discreteness in limited indoor or in-situ experimental data has always shown up. This study established the stochastic mesostructure models of CSRMs with a self-developed modeling technology. Their saturated and unsaturated seepage parameters were determined by laboratory tests. Then, saturated and unsaturated numerical seepage simulations of CSRMs were carried out. The influences of rock block content, occurrence, shape, and permeability difference in soil and rock mass on their permeability coefficient were investigated. The empirical permeability coefficient prediction formulas about influencing factors were discussed. The results showed that the seepage characteristics of CSRMs conformed to Darcy’s law. Their permeability coefficient decreased first and then increased with the rock block content, and they achieved the minimum value when it was about 40 %. Their permeability coefficient increased with the rock block inclination and decreased with the aspect ratio of rock blocks. When the difference of soil and rock mass in permeability coefficient exceeded 1 × 10<sup>3</sup> in magnitude, their permeability coefficient should be mainly controlled by the side with the large permeability. Three empirical permeability prediction formulas for CSRMs were proposed. This study could provide theoretical and methodological references for the permeability cognition of CSRMs.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"177 ","pages":"Article 106813"},"PeriodicalIF":5.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421119","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 : 2024-10-10DOI: 10.1016/j.compgeo.2024.106820
Weichi Xu, Yuande Zhou, Yutai Guo, Feng Jin
A thorough characterization of the mesostructure of concrete serves as a fundamental cornerstone for investigating its complex mechanical response at the mesoscale. A coupled FEM-SBFEM (Finite element method − scaled boundary finite element method) model is developed for mesoscopic modeling of conventional concrete (CC) and rock-filled concrete (RFC). This model incorporates a novel RAM (Random Aggregate Model) generation procedure based on Laguerre tessellation, allowing for the construction of coarse polyhedral aggregates with diverse grading schemes and adjustable aggregate volume fractions. Moreover, a framework has been developed for the automatic generation of prelaid rock skeletons, which accurately encapsulate the distinctive self-sustaining skeletal characteristics inherent to RFC. In a departure from conventional FEM, the SBFEM in this approach discretizes each coarse aggregate using a singular polyhedral element, resulting in a significant reduction in degrees of freedom. The proposed mesoscopic construction method is adopted for the prediction of elastic properties for both CC and RFC. Numerical samples of 48 CC specimens and 13 RFC specimens, with various aggregate volume fractions and rockfill ratios, are constructed using Monte Carlo simulations, and the results are compared with experimental and numerical data in literature. Statistical analyses are performed to investigate the impacts of aggregate volume fraction and anisotropic behavior on the elastic properties of CC and RFC. The results demonstrate that RFC exhibited an elastic modulus approximately 7.32 % higher than CC at the same coarse aggregate volume fractions. Furthermore, RFC exhibits a more substantial degree of anisotropy than CC. The proposed FEM-SBFEM coupled approach presents the capability to accurately predict the elastic behavior of concrete materials, and can be extended for a comprehensive investigation of the linear and nonlinear properties of actual RFC that comprises extremely coarse aggregates.
对混凝土中观结构的全面描述是研究其在中观尺度上复杂力学响应的基础。我们开发了一种 FEM-SBFEM（有限元法-比例边界有限元法）耦合模型，用于传统混凝土（CC）和岩石填充混凝土（RFC）的中观建模。该模型采用了基于拉盖尔网格的新颖 RAM（随机骨料模型）生成程序，允许构建具有不同级配方案和可调骨料体积分数的粗多面体骨料。此外，还开发了一个自动生成预铺岩石骨架的框架，该框架准确地概括了 RFC 固有的独特自持骨架特征。与传统的有限元法不同，该方法中的 SBFEM 使用奇异多面体元素对每个粗集料进行离散，从而显著降低了自由度。在预测 CC 和 RFC 的弹性特性时，采用了所提出的介观构造方法。采用蒙特卡洛模拟构建了 48 个 CC 试件和 13 个 RFC 试件的数值样本，试件具有不同的骨料体积分数和填石比，并将结果与文献中的实验和数值数据进行了比较。通过统计分析，研究了骨料体积分数和各向异性行为对 CC 和 RFC 弹性特性的影响。结果表明，在粗骨料体积分数相同的情况下，RFC 的弹性模量比 CC 高出约 7.32%。此外，RFC 比 CC 表现出更大程度的各向异性。所提出的 FEM-SBFEM 耦合方法能够准确预测混凝土材料的弹性行为，并可扩展用于全面研究由极粗骨料组成的实际 RFC 的线性和非线性特性。
{"title":"Mesoscopic representation of conventional concrete and rock-filled concrete: A novel FEM-SBFEM coupled approach","authors":"Weichi Xu, Yuande Zhou, Yutai Guo, Feng Jin","doi":"10.1016/j.compgeo.2024.106820","DOIUrl":"10.1016/j.compgeo.2024.106820","url":null,"abstract":"<div><div>A thorough characterization of the mesostructure of concrete serves as a fundamental cornerstone for investigating its complex mechanical response at the mesoscale. A coupled FEM-SBFEM (Finite element method − scaled boundary finite element method) model is developed for mesoscopic modeling of conventional concrete (CC) and rock-filled concrete (RFC). This model incorporates a novel RAM (Random Aggregate Model) generation procedure based on Laguerre tessellation, allowing for the construction of coarse polyhedral aggregates with diverse grading schemes and adjustable aggregate volume fractions. Moreover, a framework has been developed for the automatic generation of prelaid rock skeletons, which accurately encapsulate the distinctive self-sustaining skeletal characteristics inherent to RFC. In a departure from conventional FEM, the SBFEM in this approach discretizes each coarse aggregate using a singular polyhedral element, resulting in a significant reduction in degrees of freedom. The proposed mesoscopic construction method is adopted for the prediction of elastic properties for both CC and RFC. Numerical samples of 48 CC specimens and 13 RFC specimens, with various aggregate volume fractions and rockfill ratios, are constructed using Monte Carlo simulations, and the results are compared with experimental and numerical data in literature. Statistical analyses are performed to investigate the impacts of aggregate volume fraction and anisotropic behavior on the elastic properties of CC and RFC. The results demonstrate that RFC exhibited an elastic modulus approximately 7.32 % higher than CC at the same coarse aggregate volume fractions. Furthermore, RFC exhibits a more substantial degree of anisotropy than CC. The proposed FEM-SBFEM coupled approach presents the capability to accurately predict the elastic behavior of concrete materials, and can be extended for a comprehensive investigation of the linear and nonlinear properties of actual RFC that comprises extremely coarse aggregates.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"177 ","pages":"Article 106820"},"PeriodicalIF":5.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421139","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 : 2024-10-10DOI: 10.1016/j.compgeo.2024.106809
Mingze Li , Ming Chen , Wenbo Lu , Fengze Zhao , Peng Yan , Jie Liu
Accurately and promptly identifying rock fragments and particle size distribution after blasting is crucial for rock transportation and aggregate control in hydraulic and hydropower engineering. Manual screening and traditional edge detection methods suffer from subjectivity and inefficiency, resulting in considerable processing time. Images of rock fragments post-blasting, captured in open-air conditions, present challenges due to overlapping fragments, complicating intelligent recognition. To address this, an instance segmentation model, RDT-FragNet, is designed for rock fragment segmentation. RDT-FragNet is a hybrid model that integrates the Deformable Convolutional Network (DCN) and the Transformer Attention Mechanism (TAM). The DCN-Transformer structure adaptively preserves global and local features, enhancing the segmentation and recognition of rock fragment edges. Comparative analyses and rigorous ablation studies demonstrate RDT-FragNet’s competitive advantages. RDT-FragNet outperforms other advanced models in both quantitative metrics and visual results. The visualization results and the characteristic and maximum particle size of rock fragments closely match the actual situation. The robustness and applicability of the RDT-FragNet model are validated using images from two additional engineering projects. This research introduces an intelligent, efficient, and objective method for rock fragment analysis in open-air settings.
{"title":"RDT-FragNet: A DCN-Transformer network for intelligent rock fragment recognition and particle size distribution acquisition","authors":"Mingze Li , Ming Chen , Wenbo Lu , Fengze Zhao , Peng Yan , Jie Liu","doi":"10.1016/j.compgeo.2024.106809","DOIUrl":"10.1016/j.compgeo.2024.106809","url":null,"abstract":"<div><div>Accurately and promptly identifying rock fragments and particle size distribution after blasting is crucial for rock transportation and aggregate control in hydraulic and hydropower engineering. Manual screening and traditional edge detection methods suffer from subjectivity and inefficiency, resulting in considerable processing time. Images of rock fragments post-blasting, captured in open-air conditions, present challenges due to overlapping fragments, complicating intelligent recognition. To address this, an instance segmentation model, RDT-FragNet, is designed for rock fragment segmentation. RDT-FragNet is a hybrid model that integrates the Deformable Convolutional Network (DCN) and the Transformer Attention Mechanism (TAM). The DCN-Transformer structure adaptively preserves global and local features, enhancing the segmentation and recognition of rock fragment edges. Comparative analyses and rigorous ablation studies demonstrate RDT-FragNet’s competitive advantages. RDT-FragNet outperforms other advanced models in both quantitative metrics and visual results. The visualization results and the characteristic and maximum particle size of rock fragments closely match the actual situation. The robustness and applicability of the RDT-FragNet model are validated using images from two additional engineering projects. This research introduces an intelligent, efficient, and objective method for rock fragment analysis in open-air settings.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"177 ","pages":"Article 106809"},"PeriodicalIF":5.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421140","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 : 2024-10-10DOI: 10.1016/j.compgeo.2024.106821
Daosheng Zhang , Zongqing Zhou , Chenglu Gao , Panpan Gai , Xiaochu Chen , Jinbo Chen , Fanlin Bu
To enhance the computational efficiency of fluid–solid coupling in peridynamics (PD), a hybrid modeling approach based on the classical Biot theory is proposed for simulating hydraulic crack propagation in saturated porous media. The deformation and damage of solids are described by the coupling of the finite element method (FEM) and PD. Based on Darcy’s law, the finite volume method (FVM) is used to describe fluid seepage and calculate pore water pressure. The mutual transfer of fluid pressure and solid deformation is realized through the transition layer between the solid layer and the fluid layer. Firstly, the effectiveness of the proposed method is verified by a porous media seepage simulation example. Secondly, the ability and efficiency of this method to simulate crack propagation in saturated porous media are verified by several examples of hydraulic fracturing of rock with a single pre-existing crack. Finally, the synchronous hydraulic fracturing process of rock with double cracks is simulated. The ability of this method to simulate the simultaneous propagation of multiple fractures in the rock under fluid–solid coupling is further illustrated. The aforementioned studies demonstrate that the novel hybrid PD-FEM-FVM approach not only ensures computational accuracy and effectiveness but also significantly enhances computational efficiency.
{"title":"A novel hybrid PD-FEM-FVM approach for simulating hydraulic fracture propagation in saturated porous media","authors":"Daosheng Zhang , Zongqing Zhou , Chenglu Gao , Panpan Gai , Xiaochu Chen , Jinbo Chen , Fanlin Bu","doi":"10.1016/j.compgeo.2024.106821","DOIUrl":"10.1016/j.compgeo.2024.106821","url":null,"abstract":"<div><div>To enhance the computational efficiency of fluid–solid coupling in peridynamics (PD), a hybrid modeling approach based on the classical Biot theory is proposed for simulating hydraulic crack propagation in saturated porous media. The deformation and damage of solids are described by the coupling of the finite element method (FEM) and PD. Based on Darcy’s law, the finite volume method (FVM) is used to describe fluid seepage and calculate pore water pressure. The mutual transfer of fluid pressure and solid deformation is realized through the transition layer between the solid layer and the fluid layer. Firstly, the effectiveness of the proposed method is verified by a porous media seepage simulation example. Secondly, the ability and efficiency of this method to simulate crack propagation in saturated porous media are verified by several examples of hydraulic fracturing of rock with a single pre-existing crack. Finally, the synchronous hydraulic fracturing process of rock with double cracks is simulated. The ability of this method to simulate the simultaneous propagation of multiple fractures in the rock under fluid–solid coupling is further illustrated. The aforementioned studies demonstrate that the novel hybrid PD-FEM-FVM approach not only ensures computational accuracy and effectiveness but also significantly enhances computational efficiency.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"177 ","pages":"Article 106821"},"PeriodicalIF":5.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421120","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 : 2024-10-10DOI: 10.1016/j.compgeo.2024.106825
Mohammad Nikooei, Clarence Edward Choi, Jiaqi Zhang
Geophysical flows involving granular masses exhibit complex dynamics with transient mass and momentum changes due to deposition. Geophysical flows are typically simulated using depth-averaged (DA) models, which rely on empirical closures for deposition. However, these models typically overlook the detailed grain-scale physics involved in deposition, treating the flow as an equivalent fluid at the macro-scale. This study introduces a multiscale framework to integrate grain-scale deposition physics into macro-scale DA models without relying on empirical closures. The framework utilizes a surrogate model, trained on discrete element modeling (DEM) datasets, to capture changes in effective flow depth. This surrogate model is integrated with a DA model to create a multiscale approach, improving the deposition physics within an efficient computational framework. The effectiveness of the proposed multiscale framework is assessed by studying how a granular mass, initially in motion, settles when the slope angle is suddenly reduced to zero. Predictions from the multiscale model of effective flow depth (i.e., not including deposited material) and DA velocity are compared with DEM results. It is demonstrated that the proposed framework has potential to streamline upscaling simulations and facilitate field-scale hazard assessments in the future.
涉及粒状物质的地球物理流表现出复杂的动力学特征，由于沉积作用而产生瞬时质量和动量变化。地球物理流动通常使用深度平均（DA）模型进行模拟，这些模型依赖于沉积的经验闭合。然而，这些模型通常忽略了沉积过程中涉及的详细晶粒尺度物理现象，而将流动视为宏观尺度上的等效流体。本研究引入了一个多尺度框架，在不依赖经验闭合的情况下，将颗粒尺度沉积物理学整合到宏观尺度 DA 模型中。该框架利用在离散元建模（DEM）数据集上训练的代用模型来捕捉有效流深的变化。该代用模型与大尺度模型相结合，创建了一种多尺度方法，在一个高效的计算框架内改进了沉积物理学。通过研究最初处于运动状态的颗粒质量在坡度角突然减小为零时如何沉降，对所提出的多尺度框架的有效性进行了评估。多尺度模型对有效流深（即不包括沉积物）和DA速度的预测结果与DEM结果进行了比较。结果表明，所提出的框架具有简化升级模拟的潜力，并有助于未来进行实地规模的灾害评估。
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Pub Date : 2024-10-10DOI: 10.1016/j.compgeo.2024.106814
Xiaohua Bao , Junhong Li , Jun Shen , Xiangsheng Chen , Cong Zhang , Hongzhi Cui
In this study, we propose a multivariate joint distribution model for marine soft soil using D-vine copula function. The model is based on detailed investigation data from a tunnel constructed in marine soft soil. The variation patterns of the mechanical and physical parameters of quaternary marine–land interaction sedimentary soft soil layers were analysed. First, a comprehensive database of marine soft soils was established on the basis of detailed field investigation data. The variability and correlations among the physical and mechanical performance indices of the soft soil were then analysed. Subsequently, optimal marginal functions for nine soil parameters were proposed on the basis of the fitting characteristics of the physical and mechanical performance parameters of the soft soil. Finally, 15 copula functions were used to establish a multivariate joint distribution model of the D-vine copula function for marine soft soil, and the effectiveness of the model was verified. This model offers flexibility for constructing multivariate joint distributions tailored to various characteristics of the correlation structure by leveraging several bivariate correlation structures. It can provide an effective method for accurately delineating the features of the correlation structure among multivariate geotechnical parameters and establishing a probabilistic transformation model for marine soft soil parameters.
{"title":"Comprehensive multivariate joint distribution model for marine soft soil based on the vine copula","authors":"Xiaohua Bao , Junhong Li , Jun Shen , Xiangsheng Chen , Cong Zhang , Hongzhi Cui","doi":"10.1016/j.compgeo.2024.106814","DOIUrl":"10.1016/j.compgeo.2024.106814","url":null,"abstract":"<div><div>In this study, we propose a multivariate joint distribution model for marine soft soil using D-vine copula function. The model is based on detailed investigation data from a tunnel constructed in marine soft soil. The variation patterns of the mechanical and physical parameters of quaternary marine–land interaction sedimentary soft soil layers were analysed. First, a comprehensive database of marine soft soils was established on the basis of detailed field investigation data. The variability and correlations among the physical and mechanical performance indices of the soft soil were then analysed. Subsequently, optimal marginal functions for nine soil parameters were proposed on the basis of the fitting characteristics of the physical and mechanical performance parameters of the soft soil. Finally, 15 copula functions were used to establish a multivariate joint distribution model of the D-vine copula function for marine soft soil, and the effectiveness of the model was verified. This model offers flexibility for constructing multivariate joint distributions tailored to various characteristics of the correlation structure by leveraging several bivariate correlation structures. It can provide an effective method for accurately delineating the features of the correlation structure among multivariate geotechnical parameters and establishing a probabilistic transformation model for marine soft soil parameters.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":"177 ","pages":"Article 106814"},"PeriodicalIF":5.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142421138","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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