Evaluation of link-track performances using DEM

Asaf, Z.; Rubinstein, D.; Shmulevich, I.

doi:10.1016/j.jterra.2004.10.004

Cited by 70 publications

(18 citation statements)

References 11 publications

(21 reference statements)

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“…Asaf et al [13] investigated the effect of particle structure on internal friction angle. They used two equally sized discs, clumped together (Fig.…”

Section: Particle Size and Shapementioning

confidence: 99%

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Calibration of granular material parameters for DEM modelling and numerical verification by blade–granular material interaction

Coetzee

Els

2009

Journal of Terramechanics

114

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“…Asaf et al [13] investigated the effect of particle structure on internal friction angle. They used two equally sized discs, clumped together (Fig.…”

Section: Particle Size and Shapementioning

confidence: 99%

“…The discrete element method is a promising approach to model soil-implement interaction [13] and can be used to overcome some of the difficulties encountered by analytical methods and FEM. In DEM, the failure patterns and shape of the up heave are not needed in advance.…”

Section: Introductionmentioning

confidence: 99%

Calibration of granular material parameters for DEM modelling and numerical verification by blade–granular material interaction

Coetzee

Els

2009

Journal of Terramechanics

114

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“…Therefore, some (or all) of the parameters may need to be determined by calibration, i.e., by varying the unknown DEM parameters until a good match is obtained between physical measurements of the response(s) of interest and the simulation results. Although DEM calibration is often used, e.g., [13,14,15], the main limitation of existing, commonly-used calibration methods is inefficiency. The parameters are often varied individually by trial-and-error while the user-defined response of interest is monitored.…”

Section: Dem Materials Parameter Identificationmentioning

confidence: 99%

Efficient Calibration of Discrete Element Material Model Parameters Using Latin Hypercube Sampling and Kriging

Rackl¹,

Görnig²,

Hanley³

et al. 2016

Proceedings of the VII European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2016)

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Abstract. Material model parameter identification for discrete element models (DEM) is typically done using a trial-and-error approach and its outcome depends largely on the experience of the DEM user. This paper describes a work flow which facilitates the efficient and systematic calibration of discrete element material models against experimental data. The described workflow comprises three steps. In the first step, an approach based on the design and analysis of computer experiments (DACE) is adopted in which data is generated for the parametrisation of Kriging models based on Latin hypercube sampling. In the second step, multi-objective optimisation is applied to the Kriging models. This study introduces an additional cost criterion, which includes the Rayleigh time step, in order to reduce the solution set size to one element. In the third step, the optimisation procedure is repeated with the actual DEM models, using the optimal parameter set from the Kriging models as the start value. This final step with the full DEM models refines the parameter set against experimental data. Since DEM material model calibration is time-consuming, the workflow is implemented into an automated process chain. In this paper, the methodology is described in detail and results are shown which illustrate the usefulness and effectiveness of this approach. Initial verification simulations run using the calibrated parameters give good agreement with experimental results.

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“…The micro parameters of the particle connections k k k k n s n s , , , , , , λ σ τ   ( ) can't be calculated directly, therefore in the previous DEM models were tried to set the appropriate similarity between the experiments and simulations [3,4,5,6]. We can compare the micromechanical parameters of the particle block with the results of the laboratory experiments.…”

Section: Introductionmentioning

confidence: 99%

The Evaluation of the Parallel Bond’s Properties in DEM Modeling of Soils

Kismányoky¹,

Kovács²,

Jóri³

2016

Period. Polytech. Mech. Eng.

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In this study we conducted the sensitivity analysis of the parallel bond used in the discrete element method (DEM, 3D) IntroductionIt is important for the developing engineers of tillage machines to get fast and accurate feedback on the functionality and effectiveness of new constructions, because of the evolved market competition and the increasing needs of users. We can reconstruct field measurements by the investigations conducted in simulated environments. To investigate the micro-and macro cracks appearing in soils we need to use discrete element methods (DEM), instead of using continuous material models (FEM). Nowadays, because of the development of computer science, the DEM method is the most promising approach for modeling the soil-tool (sweep) interaction.In case of the soil-tool dynamic connection the cracks appearing in the soil affect greatly the size of the emerging deformation zone in front of the tool and thus the tool's towing resistance.It is hard to set the mechanical parameters of the "synthetic" materials used by the DEM method so as they are almost the same as the mechanical parameters of real materials [2]. Whereas the input parameters of continuum material models can be given directly from the results of laboratory measurements (Young's modulus, Poisson ratio, stress, etc.), the macro parameters of the material used in case of the DEM model depend on the features of the micro particles' connections. The input parameters in the DEM model are the parameters of the microscopic particles' connections (for example the spring stiffness between two particles, friction factor, etc.), that is why it is important to calibrate our model with the micro parameters. The parallel bond contact model was used to describe the liquid bridges between the soil particles and to set the so-called capillary effect in the model. The use of the parallel bond contact model enables the realistic cohesion in the DEM model.The micro parameters of the particle connections k k k k

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Evaluation of link-track performances using DEM

Cited by 70 publications

References 11 publications

Calibration of granular material parameters for DEM modelling and numerical verification by blade–granular material interaction

Calibration of granular material parameters for DEM modelling and numerical verification by blade–granular material interaction

Efficient Calibration of Discrete Element Material Model Parameters Using Latin Hypercube Sampling and Kriging

The Evaluation of the Parallel Bond’s Properties in DEM Modeling of Soils

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