Micro-mechanical analysis of caisson foundation in sand using DEM: Particle shape effect

Yin, Zhen‐Yu; Wang, Pei

doi:10.1016/j.apor.2021.102630

Cited by 23 publications

(3 citation statements)

References 84 publications

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“…Note that unacceptable computational efficiency will result if particle details in a DEM simulation are the same as those in model tests [34,38,[52][53][54]. Therefore, it is widely accepted that, in DEM-based simulations, many factors such as particle size, shape, and size distribution are simplified compared to those observed in model tests, in order to achieve acceptable computational efficiency [77][78][79][80][81][82]. Consequently, rather than aiming for precise numerical values, simulations based on the DEM often prioritize providing valuable insights into the micromechanical mechanisms and trends in soil behavior.…”

Section: Methodology Of Coupled Dem-femmentioning

confidence: 99%

Micromechanical Analysis of Lateral Pipe–Soil Interaction Instability on Sloping Sandy Seabeds

Peng,

2024

JMSE

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The micromechanical mechanism of pipe instability under lateral force actions on sloping sandy seabeds is unclear. This study investigated the effects of slope angle and instability direction (upslope or downslope) on pipe–soil interaction instability for freely laid and anti-rolling pipes using coupled discrete element method and finite element method (DEM–FEM) simulations. The numerical results were analyzed at both macro- and microscales and compared with the experimental results. The findings revealed that the ultimate drag force on anti-rolling pipes increased with slope angle and was significantly larger than that on freely laid pipes for both downslope and upslope instabilities. Additionally, the rotation-induced upward traction force was proved to be the essential reason for the smaller soil deformation around freely laid pipes. Moreover, the shape differences in the motion trajectories of pipes were successfully explained by variations in the soil supporting force distributions under different slope conditions. Additionally, synchronous movement between the pipe and adjacent particles was identified as the underlying mechanism for the reduced particle collision and shear wear on pipe surfaces under a high interface coefficient. Furthermore, an investigation of particle-scale behaviors revealed conclusive mechanistic patterns of pipe–soil interaction instability under different slope conditions. This study could be useful for the design of pipelines in marine pipeline engineering.

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Section: Methodology Of Coupled Dem-femmentioning

confidence: 99%

Micromechanical Analysis of Lateral Pipe–Soil Interaction Instability on Sloping Sandy Seabeds

Peng,

2024

JMSE

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“…This method is able to reproduce both macro-and micro-scopic behaviors of slightly elongated granular material when the rolling resistance coefficient is smaller than 0.3 [68][69][70]. In this study, a low rolling resistance coefficient of 0.1 is adopted to simulate rounded particles with slight elongation according to a series of biaxial tests with DEM conducted by the authors [71]. The model parameters are summarized in Table 1, which were validated in previous DEM studies by the authors [2,34,72].…”

Section:    mentioning

confidence: 99%

Micro-mechanical analysis of soil–structure interface behavior under constant normal stiffness condition with DEM

et al. 2021

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The mechanical behavior at soil-structure interface (SSI) has a crucial influence on the safety and stability of geotechnical structures. However, the behavior of SSI under constant normal stiffness condition from micro to macro scale receives little attention. In this study, the frictional characteristics of SSI and the associated displacement localization under constant normal stiffness condition are investigated at both macro-and microscales by simulating a series of interface shear tests with discrete element method (DEM). The algorithm to achieve a constant normal stiffness is first developed. The macroscopic mechanical response of the interface shear tests with both loose and dense specimens at various normal stiffness is discussed in terms of shear stress, normal stress, vertical displacement, horizontal displacement and stress ratio. Then the microscopic behaviors and properties, including shear zone formation, localized void ratio, coordination number, force chains and soil fabric are investigated. The effect of normal stiffness is thus clarified at both macro-and microscales.

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“…The discrete element method (DEM) pioneered by Cundall and Strack can obtain detailed micro information at the grain scale level when analysing the mechanical behaviours of granular systems and is widely used to simulate geomaterials. 11 A large number of studies have investigated the influences of structure [12][13][14][15] with circular/spherical particles and inherent anisotropy [16][17][18][19] with irregularly shaped particles (e.g., elliptical/ellipsoidal particles, clumps consisting of a collection of circular/spherical particles, irregular convex-polygonal) on the mechanical behaviours of sand by the DEM simulation, respectively. The results were confirmed to be able to capture the main mechanical behaviours of structured sand or pure sand with inherent anisotropy.…”

Section: Introductionmentioning

confidence: 99%

A multi‐fidelity residual neural network based surrogate model for mechanical behaviour of structured sand

Zhou,

Yin,

et al. 2024

Num Anal Meth Geomechanics

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The structured sand presents significant interparticle bonding and anisotropy, resulting in significant differences in the physical and mechanical properties from the pure sand. This study proposes a new surrogate model based on the concept of multi‐fidelity residual neural network (MR‐NN) as an alternative to DEM simulation for predicting the mechanical behaviours of structured sand with different initial anisotropy and saving largely computational costs. The model is initially trained using low‐fidelity (LF) data to focus on capturing the main underpinning correlations between macroscopic mechanical parameters with inter‐particle properties and anisotropic state variables (i.e., microscopic fabric and tilting angle of sand), where the LF data are generated from previously proposed anisotropic macro‐micro quantitative correlation. Subsequent training on sparser high‐fidelity (HF) data is used to calibrate and refine the model with HF data generated from DEM simulations for anisotropic structured sand. Feedforward neural network (FNN) is adopted as the baseline algorithm for training models. The macroscopic anisotropic parameters of structured sand predicted by the surrogate model are compared with DEM simulations to examine its feasibility and generalization ability. Furthermore, the robustness of the surrogate model is examined by discussing the effect of LF data on the performance of MR‐NN. The superiority of the MR‐NN is further verified by comparing the performance of the trained MR‐NN with the one‐shot trained FNN based on the same HF data. All results demonstrate that the proposed surrogate model can provide a fast and accurate simulation of the anisotropic parameters of structured sand.

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Micro-mechanical analysis of caisson foundation in sand using DEM: Particle shape effect

Cited by 23 publications

References 84 publications

Micromechanical Analysis of Lateral Pipe–Soil Interaction Instability on Sloping Sandy Seabeds

Micromechanical Analysis of Lateral Pipe–Soil Interaction Instability on Sloping Sandy Seabeds

Micro-mechanical analysis of soil–structure interface behavior under constant normal stiffness condition with DEM

A multi‐fidelity residual neural network based surrogate model for mechanical behaviour of structured sand

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