Lees-Edwards boundary conditions for the multi-sphere discrete element method

Berry, Nathan; Zhang, Yonghao; Haeri, Sina

doi:10.1016/j.powtec.2021.05.025

Cited by 7 publications

(4 citation statements)

References 60 publications

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“…To mitigate this issue, one can consider implementing Lees‐Edwards boundary conditions for example refs. [51, 52], to enforce the desired linear relation between

\langle v_x\rangle

and

z

.…”

Section: Simulation Resultsmentioning

confidence: 99%

Multiscale modeling of granular dynamics on flowslide triggering and runout

Yang,

Buscarnera

2024

Num Anal Meth Geomechanics

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A hierarchical multiscale modeling framework is proposed to simulate flowslide triggering and runout. It couples a system‐scale sliding‐consolidation model (SCM) resolving hydro‐mechanical feedbacks within a flowslide with a local‐scale solver based on the discrete element method (DEM) replicating the sand deformation response in the liquefied regime. This coupling allows for the simulation of a seamless transition from solid‐ to fluid‐like behavior following liquefaction, which is controlled by the grain‐scale dynamics. To investigate the role of grain‐scale interactions, the DEM simulations replace the constitutive model within the SCM framework, enabling the capture of the emergent rate‐dependent behavior of the sand during the inertial regime of motion. For this purpose, a novel algorithm is proposed to ensure the accurate passage of the strain rate from the global analysis to the local DEM solver under both quasi‐static (pre‐triggering) and dynamic (post‐triggering) regimes of motion. Our findings demonstrate that the specifics of the coupling algorithm do not bear significant consequences to the triggering analysis, in that the grain‐scale dynamics is negligible. By contrast, major differences between the results obtained with traditional algorithms and the proposed algorithm are found for the post‐triggering stage. Specifically, the existing algorithms suffer from loss of convergence and require proper numerical treatment to capture the micro‐inertial effects arising from the post‐liquefaction particle agitation responsible for viscous‐like effects that spontaneously regulate the flowslide velocity. These findings emphasize the important role of rate‐dependent feedback for the analysis of natural hazards involving granular materials, especially for post‐failure propagation analysis.

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“…To mitigate this issue, one can consider implementing Lees‐Edwards boundary conditions for example refs. [51, 52], to enforce the desired linear relation between

\langle v_x\rangle

and

z

.…”

Section: Simulation Resultsmentioning

confidence: 99%

Multiscale modeling of granular dynamics on flowslide triggering and runout

Yang,

Buscarnera

2024

Num Anal Meth Geomechanics

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“…However, this linear relation might deteriorate after soil liquefaction, as the collapse of the well-connected contact network leads to certain nonhomogeneities. An alternative shearing protocol, not explored in the present study, would involve employing Lees-Edwards boundary conditions [10,30] to enforce a desired linear relation between hv x i and z.…”

Section: Shearing Processmentioning

confidence: 99%

Effect of particle shape on cyclic liquefaction resistance of granular materials

Banerjee,

Yang,

Taiebat

2024

Acta Geotech.

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This study adopts three-dimensional discrete element method to examine how particle shape affects the cyclic liquefaction resistance of granular materials. A family of superquadric particles is employed to model different particle shapes by varying two shape parameters: aspect ratio (AR) and blockiness (B). Five smooth and convex particle shapes are considered in this study, with AR ranging from 0.5 to 1.5, and B varying from 2 to 8. These particles are used to create isotropically compressed samples at an initial confinement of 100 kPa and two relative densities (D r ) of 20% and 50%, resulting in ten samples. These samples are then subjected to constant-volume cyclic simple shearing with various levels of cyclic stress ratios until initial liquefaction occurs in 41 simulations. The results of these simulations reveal that at D r ¼ 20%, the spherical particles exhibit the highest liquefaction resistance compared to the non-spherical particles. However, this trend is reversed for the samples with D r ¼ 50%. By employing the overall regularity (OR) as a synthetic descriptor of particle shape, it is observed that liquefaction strength generally increases with higher OR at D r ¼ 20%, while it demonstrates an approximately decreasing trend at D r ¼ 50%. Furthermore, the initial coordination number and two critical state parameters based on the void ratio and the coordination number at the pre-shearing state of the samples, demonstrate a strong correlation with the cyclic liquefaction resistance within the ranges of particle shape and D r considered in this study.

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“…During the corn threshing operation, a break occurs between the kernel and the cob by repeated kneading of the threshing component [16]. Therefore, the force applied to the corn kernels by the threshing component is first loaded and then unloaded [22,23]. In this paper, the mechanics characteristic test of the loading and then unloading of the corn ear was carried out by the WDW-20 J electronic universal testing machine (Shanghai Hualong Testing Instrument Factory, the maximum test force 20 kN, relative error: ±0.5%), and then the change law of the bonding force between the kernels and the cob in the process of corn threshing was obtained.…”

Section: Elastic-plastic Damping Model For Kernel-cob Bonding Forcementioning

confidence: 99%

“…In recent years, discrete element simulation technology has been widely used in agricultural engineering, where it can provide high-precision observation and analysis of the kinematic and mechanical characteristics of granular objects [21]. The core of discrete element simulation is the establishment of a mechanical model [22]. Therefore, if a high-precision computational model of the corn kernel-cob bonding force can be established, the characteristics of the bonding force changes during the corn threshing operation can be simulated and analyzed with high precision by discrete element simulation, and then the influence of the threshing component rotation speed on the corn ear threshing rate can be revealed.…”

Section: Introductionmentioning

confidence: 99%

Discrete Element Simulation Based on Elastic–Plastic Damping Model of Corn Kernel–Cob Bonding Force for Rotation Speed Optimization of Threshing Component

Zhao

et al. 2021

Processes

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Current corn kernel-cob bonding mechanics models (LSD models) uniformly consider the bonding force changes during the maize threshing operation as an elastic change, resulting in computational errors of up to 10% or more in discrete element simulations. Due to the inability to perform high-precision discrete element simulation of the mechanics characteristics during the corn threshing operation, the core operating parameters of the corn thresher (rotation speed of the threshing component) rely mainly on empirical settings, resulting in a consistent difficulty in exceeding 85% of the corn ear threshing rate. In this paper, by testing the mechanics characteristics of corn kernels, the bonding force is found to have both elastic and plastic changes during the threshing process. An elastic–plastic (EP) damping model of the corn kernel–cob bonding force was established by introducing a bonding restitution coefficient e to achieve an integrated consideration of the two changes. By testing the relationship between the properties of the corn ear itself and the model parameters, the pattern of the effect of the corn ear moisture content and the loading direction of the ear by force on the EP model parameters was found. By establishing a model of the relationship between the corn cob’s own properties and the model parameters, the EP model parameter values can be determined by simply determining the moisture content of the ear. In this paper, the EP model was established and the high-precision simulation and analysis of the process of bonding force variation between corn kernel and cob is realized on the self-developed AgriDEM software. At the meantime, the optimal values of the threshing component rotation speed under different conditions of moisture content of corn ear were obtained by establishing an optimization model of threshing component rotation speed. The test results showed that the corn ear threshing rate could reach more than 92.40% after adopting the optimized speed value of the threshing component in this paper. Meanwhile, the test results showed that the discrete element simulation results based on the EP model did not significantly differ from the measured results of the thresher. Compared with the most widely used LSD model, the EP model can reduce the computational error by 3.35% to 6.05%.

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Lees-Edwards boundary conditions for the multi-sphere discrete element method

Cited by 7 publications

References 60 publications

Multiscale modeling of granular dynamics on flowslide triggering and runout

Multiscale modeling of granular dynamics on flowslide triggering and runout

Effect of particle shape on cyclic liquefaction resistance of granular materials

Discrete Element Simulation Based on Elastic–Plastic Damping Model of Corn Kernel–Cob Bonding Force for Rotation Speed Optimization of Threshing Component

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