AbstractUnderstanding the effect of particle size on the shear strength of granular materials is important for geotechnical design and construction. However, previous studies show contradicting ...results on the relationship between particle size and shear strength. Additionally, the effect of particle breakage on this relationship has not been fully revealed. In this study, a series of biaxial tests have been simulated with the discrete element method to explore the particle-size effect of sand considering the role of particle breakage. The sand specimens have parallel particle-size distributions. The sequential breakage model has been used to simulate particle breakage, which is a combination of replacement and cluster methods. The main conclusions of this study are: (1) the relationship of peak shear strength and particle size depends on the crushability of particles and relative density of specimens; (2) the particle size and crushability have a very slight effect on the residual shear strength; and (3) at the microscale, the relationship between shear strength and particle size is positively related to the friction utilization ratio.
This study adopts the Bayesian neural network (BNN) integrated with a strong non-linear fitting capability and uncertainty, which has not previously been used in geotechnical engineering, to propose ...a modelling strategy in developing prediction models for soil properties. The compression index C
c
and undrained shear strength s
u
of clays are selected as examples. Variational inference (VI) and Monte Carlo dropout (MCD), two theoretical frameworks for solving and approximating BNN, respectively, are employed and compared. The results indicate that the BNN focused on identifying patterns in datasets, and the predicted C
c
and s
u
show excellent agreement with the actual values. The reliability of the predicted results using BNN is high in the area of dense datasets. In contrast, the BNN demonstrates low reliability in the predicted result in the area of sparse datasets. Additionally, a novel parametric analysis method in combination with the cumulative distribution function is proposed. The analysis results indicate that the BNN-based models are capable of capturing the relationships of input parameters to the C
c
and s
u
. BNN, with its strong prediction capability and reliable evaluation, therefore, shows great potential to be applied in geotechnical design.
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Fractured media have been extensively studied due to their significant impact on hydraulic properties of subsurface systems. However, accurately modeling and simulating flow and transport in complex ...3D fractured media still remains a challenge. For this purpose, this work aims to develop a new 3D modeling approach and investigate flow and mass transport in fractured media. First, a modeling approach is presented for generating 3D complex structures and high quality finite element grids. This approach allows for the presence of a range of complex geometries, including curved fracture, multiple fractures and the coexistence of fracture‐inclusions. The resulting models and grids are of high quality, enabling accurate simulation and analysis of complex systems. Furthermore, stress‐dependent aperture and roughness are integrated in the computational scheme using Barton–Bandis law. The Galerkin finite element method is used for numerical discretization, then pressure and concentration are calculated in a unified formulation. Later, numerical tests are performed to analyze the role of 3D fractures in flow and mass transport. Simulation results show that fractures have a larger impact on pressure distribution and flow rate compared to inclusions. Fracture roughness increases the aperture then the effective conductivity is improved as well. Curved fractures may reduce flow rate more than planar fractures due to the tortuosity effect. The variation of equivalent permeability tensor is analyzed with varying orientation, roughness, and number of fractures. The impact of stress and fracture roughness causes a variation of fracture permeability and a high pressure gradient on the fracture‐matrix interface, resulting in different patterns of concentration evolution. Overall, this investigation provides insights into the role of 3D fractures in subsurface flow and transport, with implications for various applications.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Summary
A comparative study of optimization techniques for identifying soil parameters in geotechnical engineering was first presented. The identification methodology with its 3 main parts, error ...function, search strategy, and identification procedure, was introduced and summarized. Then, current optimization methods were reviewed and classified into 3 categories with an introduction to their basic principles and applications in geotechnical engineering. A comparative study on the identification of model parameters from a synthetic pressuremeter and an excavation tests was then performed by using 5 among the mostly common optimization methods, including genetic algorithms, particle swarm optimization, simulated annealing, the differential evolution algorithm and the artificial bee colony algorithm. The results demonstrated that the differential evolution had the strongest search ability but the slowest convergence speed. All the selected methods could reach approximate solutions with very small objective errors, but these solutions were different from the preset parameters. To improve the identification performance, an enhanced algorithm was developed by implementing the Nelder‐Mead simplex method in a differential algorithm to accelerate the convergence speed with strong reliable search ability. The performance of the enhanced optimization algorithm was finally highlighted by identifying the Mohr‐Coulomb parameters from the 2 same synthetic cases and from 2 real pressuremeter tests in sand, and ANICREEP parameters from 2 real pressuremeter tests in soft clay.
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Machine learning (ML) may provide a new methodology to directly learn from raw data to develop constitutive models for soils by using pure mathematic skills. It has presented success and versatility ...in cases of simple stress paths due to its strong non-linear mapping capacity without limitations of constitutive formulations. However, current studies on the ML-based constitutive modeling of soils is still very limited. This study comprehensively reviews the application of ML algorithms in the development of constitutive models of soils and compares the performance of different ML algorithms. First, the basic principles of typical ML algorithms used in describing soil behaviors are briefly elaborated. The main characteristics and the limitations of such ML algorithms are summarized and compared. Then, the methodology of developing a ML-based soil model is reviewed from six aspects, such as adopted ML algorithms, data source, framework of the ML-based model, training strategy, generalization ability and application scope. Finally, five new ML-based models are developed using five typical ML algorithms (i.e. BPNN, RBF, LSTM, GRU and BiLSTM that can predict multi outputs together) based on same set of experimental results of sand, and compare each other in terms of the predictive accuracy and generalization ability. Results show the long short-term memory (LSTM) neural network and its variants are most suitable for developing constitutive models. Moreover, some useful suggestions for developing the ML-based soil model are also provided for the community.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Summary
In this paper, an enhanced backtracking search algorithm (so‐called MBSA‐LS) for parameter identification is proposed with two modifications: (a) modifying the mutation of original ...backtracking search algorithm (BSA) considering the contribution of current best individual for accelerating convergence speed and (b) novelly incorporating an efficient differential evolution (DE) as local search for improving the quality of population. The proposed MBSA‐LS is first validated with better performance than the original BSA and some other typical state‐of‐the‐art optimization algorithms on a benchmark of soil parameter identification in terms of effectiveness, efficiency, and robustness. Then, the efficiency of the MBSA‐LS is further illustrated by two representative cases: identifying soil parameters from both laboratory tests and field measurements. All comparisons demonstrate that the proposed MBSA‐LS algorithm can give accurate results in a short time. Finally, to conveniently solve the problems of parameter identification, a practical tool ErosOpt for parameter identification is developed by integrating the proposed MBSA‐LS and some other efficient algorithms for readers to conduct the parameter identification using optimisation algorithms.
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Although particle corner breakage has been proved to be the primary mode of particle breakage for coral sand, current studies of pile penetration have continued to present the particle fracture ...breakage mode, causing the mechanism of pile behaviours in coral sand to remain unclear. This study investigates the particle corner-breakage effect on pile penetration in coral sand at both the macro- and microscales via indoor pile penetration model testing and three-dimensional discrete element method (DEM) simulations. According to the study findings, DEM simulations revealed that particle corner breakage has a more obvious soil contraction effect than fracture breakage. Thus, this study is the first to explain the particular turn of the pile skin friction in coral sand by the dual effects of breakable corners. Next, relationships between the particle breakage mode and the controversial breakage zone around pile tips have been accomplished. Moreover, the decrease in effective contacts and the change in soil skeleton have been proved to be essential factors behind the narrower penetration-affected width in breakable corner grains. The study suggests that neglecting the particle corner-breakage effect can lead to a hidden danger affecting engineering safety in angular granular soil.
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Suffusion involves fine particles migration within the matrix of coarse fraction under seepage flow, which usually occurs in the gap‐graded material of dams and levees. Key factors controlling the ...soil erodibility include confining pressure (p′) and fines content (Fc), of which the coupling effect on suffusion still remains contradictory, as concluded from different studies considering narrow scope of these factors. For this reason, a systematical numerical simulation that considers a relative wide range of p′ and Fc was performed with the coupled discrete element method and computational fluid dynamics approach. Two distinct macroresponses of soil suffusion to p′ were revealed, ie, for a given hydraulic gradient i = 2, an increase in p′ intensifies the suffusion of soil with fines overfilling the voids (eg, Fc = 35%), but have negligible effects on the suffusion of gap‐graded soil containing fines underfilling the voids (eg, Fc = 20%). The micromechanical analyses, including force chain buckling and strain energy release, reveal that when the fines overfilled the voids between coarse particles (eg, Fc = 35%) and participated heavily in load‐bearing, the erosion of fines under high i could cause the collapse of the original force transmission structure. The release of higher strain energy within samples under higher p′ accelerated particle movement and intensified suffusion. Conversely, in the case where the fines underfilled the voids between coarse particles (eg, Fc = 20%), the selective erosion of fines had little influence on the force network. High p′ in this case prevented suffusion.
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This paper aims to develop the nonlinear incremental modeling approach for describing both monotonic and cyclic behaviors of the soil‐structure interface. An exponential function is adopted as an ...example to reproduce the asymptotic relationship between the interface shear stress ratio and the shear displacement. A stress‐dilatancy relation is developed for the shear‐induced change of interface thickness. A shear stress reversal technique is incorporated for cyclic loading effect. Then, three numerical schemes for simulating constant thickness, constant normal load, and constant normal stiffness tests are established respectively. Next, three modifications are made to enhance the model by introducing a nonlinear shear modulus, the critical state concept, and the grain breakage effect. The enhanced model is evaluated with satisfactory performance in simulating interface tests under various loading conditions. Furthermore, the extensions to other nonlinear incremental interface model and clay‐structure interface modeling with rate effect relating to drainage conditions are successfully demonstrated and discussed.
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This paper attempts to formulate a coupled practical model in the framework of continuum mechanics to evaluate the phenomenon of internal erosion and its consequences on the mechanical behavior of ...soils. For this purpose, a four-constituent numerical approach has been developed to describe the internal erosion process. The detachment and transport of the fine particles have been described by a mass exchange formulation between the solid and fluid phases. The stress–strain relationship of the soil is represented by a nonlinear incremental model. Based on experimental data, this constitutive model has been enhanced by the introduction of a fines content–dependent critical state, which allows accounting for the influence of fines on soil deformation and strength. The applicability of the practical approach to capture the main features of the internal erosion process and its impact on the mechanical behavior of the eroded soil have been validated by comparing numerical and experimental results of internal erosion tests on Hong Kong completely decomposed granite (HK-CDG) mixtures, which demonstrated that the practical model was able to reproduce, with reasonable success, the experimental data. Furthermore, the influence of the stress state, the initial soil density, and the initial fraction of fines have been analyzed through numerical simulations using the proposed model.
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