Determination of the mechanical properties of maize grains and olives required for use in DEM simulations

González-Montellano, C.; Fuentes, José María; Ayuga-Téllez, Esperanza; Ayuga, Francisco

doi:10.1016/j.jfoodeng.2012.03.017

Cited by 149 publications

(69 citation statements)

References 38 publications

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“…The effect of the average rotational velocity after impact on the normal coefficient of restitution of particles was also investigated [22,24]. The microscopic properties of quadrate maize grains and ellipsoidal olives, including density, Young's modulus of elasticity and the particle-wall normal coefficient of restitution, were tested when particles collided with the horizontal flat surface at different velocities [25]. A purely elastic contact between rock particles accompanied by energy dissipation was studied in [26].…”

Section: Introductionmentioning

confidence: 99%

Experimental determination of parameter effects on the coefficient of restitution of differently shaped maize in three-dimensions

et al. 2015

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Section: Introductionmentioning

confidence: 99%

Experimental determination of parameter effects on the coefficient of restitution of differently shaped maize in three-dimensions

et al. 2015

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“…To select the range of the experimental design (central composite design) for the studied parameters, we have used a wider range found in the literature [3,8,9,17,21,[24][25][26][27][28][29][30][31][32][33][34] for DEM simulations of agricultural materials. However, it is still important to highlight that the calibration methodology used in this work allowed us, besides to identify appropriate values of these parameters, also to quantify their effects, as well as the interaction between them on the repose angle of these materials (as monoparticles and binary mixtures).…”

Section: 2 Simulations Resultsmentioning

confidence: 99%

Repose angle of monoparticles and binary mixture: An experimental and simulation study

et al. 2016

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“…Since the range of the coefficients are continuous, unlimited combination of values for input material properties were selected from literature (Boac et al, 2010;Coetzee and Els, 2009;González-Montellano et al, 2012) and initial AOR trial runs. Twenty seven combination DOE values for interaction material properties.…”

Section: Dem Materials Interactions (Particle-particle and Particle-gementioning

confidence: 99%

“…The results from EDEM and lab test were compared to verify the DEM calibration approach was robust. For screw auger test, the corn-steel interaction properties were estimated from AOR optimized corn-acrylic values and multiplied by the ratio the laboratory individual measured corn-acrylic and corn-steel coefficient ratio after González-Montellano et al (2012).…”

Section: Verification Of Dem Simulation Using Screw Auger Conveyormentioning

confidence: 99%

Discrete Element Method (DEM) simulation of corn grain flow in commercial screw auger

Mousaviraad¹,

Tekeste²,

Rosentrater³

2016

2016 ASABE International Meeting

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Screw augers are primary grain conveying equipment. Quantitative prediction of screw auger performance requires better understanding and measurement of bulk particle-to-particle and particle-to-geometry interactions. Discrete Element Modeling (DEM) has the potential to simulate particle dynamics and flow within a screw auger, and thus to provide simulation-based guidance for screw auger design and operational parameters. The objective of this study was to calibrate DEM corn modeling using Angle of Repose (AOR) and to simulate DEM corn flow in a commercial screw auger. Experimental data was collected to characterize harvested corn, angle of repose, and grain flow from a screw auger.Corn particle was modeled using four types of DEM spheres represented as 1-sphere and clumped spheres 2-sphere, 5-sphere and 13-sphere matching to a physically measured corn shape with equivalent geometrical diameter, 2D axial dimension, 3D axial dimension, and parameterized CAD dimensions, respectively. For each DEM corn shape approximation, virtual Design Of Experiments (DOE) with four DEM material interaction coefficients as independent parameters and reproducing AOR test initial conditions were developed in EDEM to simulate AOR grain flow behavior. AOR values from quasi-static corn flow on flat plate were measured in lab and compared with the DOE DEM simulation. The DEM corn with 2-sphere and the material interaction coefficients showed good prediction to the experimental corn AOR test with minimum corn height test and DEM prediction difference of Mean Square Error (MSE) (5.31 mm 2 ) compared to 1-sphere, 5-sphere and 13-spheres. With computationally-inexpensive shape and calibrated DEM material properties from AOR, screw auger DEM simulation of corn model was performed to predict mass flow rate. Results from DEM, analytical solutions, and experimental data on mass flow rate were also compared.

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Determination of the mechanical properties of maize grains and olives required for use in DEM simulations

Cited by 149 publications

References 38 publications

Experimental determination of parameter effects on the coefficient of restitution of differently shaped maize in three-dimensions

Experimental determination of parameter effects on the coefficient of restitution of differently shaped maize in three-dimensions

Repose angle of monoparticles and binary mixture: An experimental and simulation study

Discrete Element Method (DEM) simulation of corn grain flow in commercial screw auger

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