Analysis of surface erosion of cohesionless soils using a three-dimensional coupled computational fluid dynamics – discrete element method (CFD–DEM) model

Guo, Yuan; Yu, Xiong

doi:10.1139/cgj-2016-0421

Cited by 10 publications

(3 citation statements)

References 49 publications

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“…They used Navier-Stokes equations to solve for continuous fluids and employed particle flow software (PFC) to simulate fine particles with internal piping erosion. Guo & Yu (2019) coupled computational fluid dynamics (CFD) and discrete element method (DEM) computational models, using CFD-DEM to simulate internal soil erosion and predict scouring depth and soil erosion rate. The study demonstrated the effectiveness of the particle flow software in calculating the degree of damage caused by internal erosion to the dam.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic analysis of backward erosion piping in an embankment dam considering the spatial variability of soil properties

CHI,

CARVAJAL,

BREUL

et al. 2024

Preprint

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The spatial variability of soil seepage parameters is an essential component of the uncertainty of earth dams. This paper presents a method for probabilistic backward erosion analysis that considers the spatial variability of seepage parameters in earth dams to assess the distribution of the Factor of Safety (FoS) and the failure probability (Pf). In this study, the Karhunen-Loeve method is used to generate Random Fields (RFs) of soil hydraulic properties, and Monte Carlo simulations (MCs) are used to generate realisations of these RFs, which are then introduced into the numerical model to assess the spatial variability of the seepage analysis results. The hydraulic gradient distribution is compared with the critical hydraulic gradient to assess the FoS and the Pf due to backward erosion at each point of the dam. This study also presents the effect of water level H, permeability anisotropy coefficient ξ, and RFs parameters (permeability covariance COVKs, correlation length Lh & Lv) on the FoS and Pf of Backward Erosion Piping (BEP). The results illustrate that the failure probability Pf increases with H, COVKs and ξ. The failure probability Pf is not sensitive to the vertical correlation length, but may decrease with the horizontal correlation length. Additionally, the study discusses on the potential location of the initiation of internal erosion as well as the results obtained with criteria based on the local and global hydraulic gradient.

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Section: Introductionmentioning

confidence: 99%

Probabilistic analysis of backward erosion piping in an embankment dam considering the spatial variability of soil properties

CHI,

CARVAJAL,

BREUL

et al. 2024

Preprint

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“…The finite element method (FEM) [28][29][30], the discrete element method (DEM) [19,[31][32][33], and computational fluid dynamics (CFD) [34][35][36] are the main numerical simulation methods used by scholars in the study of soil-tool interaction. In the classical finite element method (FEM), the nodes are fixed in the material, and the elements deform with the material.…”

Section: Introductionmentioning

confidence: 99%

Simulation of Mouldboard Plough Soil Cutting Based on Smooth Particle Hydrodynamics Method and FEM–SPH Coupling Method

Jin,

Ma,

Wang

et al. 2023

Agriculture

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In the field of agricultural machinery, various empirical field tests are performed to measure the tillage force for precision tillage. However, the field test performance is costly and time-consuming, and there are many constraints on weather and field soil conditions; the utilization of simulation studies is required to overcome these shortcomings. As a result, the SPH method and the coupled FEM-SPH method are used in this paper to investigate the mouldboard plough–soil interaction. In this paper, the finite element software LS-DYNA was used to build the SPH model and the FEM-SPH coupling model of soil cutting, as well as to investigate the change in cutting resistance during the soil cutting process. The simulation results are compared with those of the experiments, and the curves of the simulation and experiment are in good agreement, which verifies the reliability of the model. The validated simulation model was used to investigate the effects of the cutting speed, depth of cut, inclination angle, and lifting angle of the mouldboard plough on cutting resistance. The simulation studies show that the SPH model takes 5 h and 2 min to compute, while the FEM-SPH coupled model takes 38 min; obviously, the computational efficiency of the FEM-SPH coupled model is higher. The relative errors between the SPH model and the experiment are 2.17% and 3.65%, respectively. The relative errors between the FEM-SPH coupled model and the experiment are 5.96% and 10.67%, respectively. Obviously, the SPH model has a higher computational accuracy. The average cutting resistances predicted by the SPH model and the FEM-SPH coupled model, respectively, were 349.48 N and 306.25 N; these resistances are useful for precision tillage. The cutting resistance increases with the increase in cutting speed and is quadratic; the cutting resistance increases with the increase in cutting depth and is quadratic; the horizontal cutting resistance and the combined cutting resistance increase with the increase in inclination angle, while the vertical cutting resistance remains essentially constant with the increase in inclination angle; the horizontal cutting resistance and combined cutting resistance increase as the lifting angle increases, while the vertical cutting resistance decreases as the lifting angle increases.

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“…Thus, a further study of the particle distribution in and around the nozzle and its variation with the process parameters need to be conducted, which will be conducive to understanding the erosion mechanism and optimizing the setting parameters to improve the cutting performance of AAJ. Among the variety of numerical models available in the literatures [15][16][17][18][19], the computational fluid dynamics-discrete element method (CFD-DEM) is a frequently used approach to describe fluid-particle two-phase flow in industrial applications and it combines CFD for the fluid phase with the discrete element method (DEM) for the solid particles. A major advantage of CFD-DEM is that it can predict accurate particle-scale information, such as the trajectories of and forces acting on individual particles [16,17].…”

Section: Introductionmentioning

confidence: 99%

Semi-resolved CFD-DEM modeling of gas-particle two-phase flow in the micro-abrasive air jet machining

Zhu

Wang

et al. 2021

Powder Technology

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Analysis of surface erosion of cohesionless soils using a three-dimensional coupled computational fluid dynamics – discrete element method (CFD–DEM) model

Cited by 10 publications

References 49 publications

Probabilistic analysis of backward erosion piping in an embankment dam considering the spatial variability of soil properties

Probabilistic analysis of backward erosion piping in an embankment dam considering the spatial variability of soil properties

Simulation of Mouldboard Plough Soil Cutting Based on Smooth Particle Hydrodynamics Method and FEM–SPH Coupling Method

Semi-resolved CFD-DEM modeling of gas-particle two-phase flow in the micro-abrasive air jet machining

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