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A discrete element method (DEM) calibration for a flexible wheat straw model for simulating direct shear test of wheat straw was investigated. The calibration process uses DEM simulated Design of Experiment (DOE) of a three-point bending test, DEM parameters initialised from previous cantilever beam test, and uniaxial compression test of wheat straw. Wheat straw samples from physiologically matured Winter wheat straw (Triticum aestivum) material were used to estimate shape of a flexible wheat straw model and to obtain material testing data. Using the DEM simulated DOE of a three-point bending test, a regression meta-model was established between particle contact Young's modulus, and bond Young's modulus and Poisson's ratio. An optimisation procedure that minimised a global error relative to the test data was utilised to determine the DEM parameters of particle contact Young's modulus, bond Young's modulus, and Poisson's ratio. From the three-point bending test of wheat straw (length of 55 mm, a diameter of 2.81 mm, and a thickness of 0.35 mm), and DOE based optimisation procedure, the DEM predicted Young's modulus of flexible wheat straw at a percent relative error (RE) of 3.11% compared to test data. Using the optimised DEM parameters of the flexible wheat straw model, the direct shear box test was simulated using the flexible fibre DEM model, as a validation experiment. DEM successfully simulated the direct shear behaviour of wheat straw from the ASTM laboratory direct shear box test, predicting wheat straw angle of internal friction (RE of 1.67%) and apparent cohesion close to zero.

HighlightsSimulation of uniaxial compression was performed with flexible fibers modeled in DEM.Bond-specific DEM parameters were found to be sensitive in uniaxial compression.A calibration technique that is not plunger-dependent is shown and validated.Abstract. To accurately simulate a discrete element method (DEM) model, the material properties must be calibrated to reproduce bulk material behavior. In this study, a method was developed to calibrate DEM parameters for bulk fibrous materials using uniaxial compression. Wheat straw was cut to 100.2 mm lengths. A 227 mm diameter cylindrical container was loosely filled with the cut straw. The material was pre-compressed to 1 kPa. A plunger (50, 150, or 225 mm diameter) was then lowered onto the compressed straw at a rate of 15 mm s-1. This experimental procedure was simulated using a DEM model for different material properties to generate a simulated design of experiment (DOE). The simulated plunger had a travel rate of 40 mm s-1. The contact Young’s modulus, bond Young’s modulus, and particle-to-particle friction DEM parameters were found to be statistically significant in the prediction of normal forces on the plunger in the uniaxial compression test. The DEM calibration procedure was used to approximate the mean laboratory results of wheat straw compression with root mean square (RMS) percent errors of 3.77%, 3.02%, and 13.90% for the 50, 150, and 225 mm plungers, respectively. Keywords: Calibration, DEM, DOE, Flexible DEM particle, Uniaxial compression, Wheat straw.

Variations in the moisture content (MC) of grains strongly influence machine performance analysis during crop harvesting and post-harvest grain handling operations. For experimental or numerical methods such as discrete element method (DEM) technique to include the effect of MC on physical and mechanical properties, comprehensive study was conducted to investigate the effect of maize MC on single kernel properties and bulk grain dynamic responses, which have relevance for DEM crop model calibration. Individual kernel properties of shape, size, coefficient of restitution, and stiffness, and bulk material responses of bulk density, angle of repose, direct shear test (angle of internal friction, apparent cohesion), hopper flowability, and grain-machine interaction (GMI) impact plate forces responses were measured on maize samples at 11%, 16%, and 26% MC levels. At individual particle responses of coefficient of restitution and stiffness, maize kernels at MC of 26% had significantly the lowest values compared to the values at the other MC (11% and 16%). Increasing maize MC reduced the hopper discharge flowability by 20% and GMI impact plate forces by 25%. Significant effects of MC on the material behaviours should be considered for calibration of DEM maize models.

Industrial-scale simulation of the interaction between rice grains and equipment using the discrete element method (DEM) is limited due to the high computing power requirement. Volume-based scaled-up modelling of DEM rice particle and calibration of DEM input parameters were investigated as an alternative approach towards realising industry scale simulation-based design support of rice grains flow behaviour. Calibration of DEM input parameters using scaled-up DEM particles is challenging because distortions in the DEM material properties due to unavoidable disparities between the true and DEM particle sizes. A DEM calibration methodology that applies virtual design of experiment (DOE) using scaled-up DEM rice particle model was applied to predict bulk angle of repose (AOR) of unshelled rice grains. Rice DEM particle shape was scaled-up by three times its original prolate spheroid particle shape and then approximated using seven-clumped DEM spheres matching the scaled-up spheroid rice particle. Using DEM parameter values of the rice model calibrated to match AOR at a relative error (RE) of 0.39%, the DEM model predicted hopper discharge rates from experiment and using the analytical solution of Beverloo et al analytical solution at relative errors (REs) of 0.66% and 0.03%, respectively. Hopper unloading time predicted by DEM had a RE of 0.93% when compared with experiment. A 60% saving in CPU time was achieved relative to the unscaled DEM rice particle model with good agreement to the rice flow test. This showed that the techniques of volume-based particle scaling and DOE calibration are effective methods for industry-scale simulation of small grains.

Limited studies have been conducted to establish scaling relationships of soil reaction forces and length scales of bulldozer blades using the Discrete Element Method (DEM) technique. With a DEM-based similitude scaling law, performance of industry-scale blades can be predicted at reduced simulation efforts provided a calibrated and validated DEM soil model is developed. DEM material properties were developed to match soil cone penetration testing. The objectives of the study were to develop a DEM soil model for Norfolk sandy loam soil, establish a scaled relationship of soil reaction forces to bulldozer blade length scales (n = 0.24, n = 0.14, n = 0.10, and n = 0.05), and validate the DEM-predicted soil reaction forces on the scaled bulldozer blades to the Norfolk sandy loam soil bin data. Using 3D-scanned and reconstructed DEM soil aggregate shapes, Design of Experiment (DOE) of soil cone penetration testing was used to develop a soil model and a soil-bulldozer blade simulation. A power fit best approximated the relationship between the DEM-predicted soil horizontal forces and the bulldozer blade length scale (n) (R2 = 0.9976). DEM prediction of soil horizontal forces on the bulldozer blades explained the Norfolk sandy loam soil data with a linear regression fit (R2 = 0.9965 and slope = 0.9634).

A method to calculate the local damping coefficient and the bond Young's modulus of a flexible fibre for use in the discrete element method (DEM) was proposed and validated. Segments of harvested wheat straw were clamped on one end while the other end was deflected a set distance, released, and allowed to vibrate freely. This cantilever beam motion was captured by a high-speed camera (960 fps). The red-band of the images were isolated and used to calculate the x-section height (mm) along the stem in time. This data was then fit to a non-linear function, which conforms to beam theory. The global bond damping coefficient, as a function of x-section height, was then calculated and found to be in the range of −0.5 to −0.2. The cantilever beam experiment was then repeated in the DEM software LIGGGHTS, where the wheat straw was modelled as a single line of spheres connected by stiff-flexible bonds. A design of experiment (DOE) was ran varying bond Young's modulus and local bond damping, to determine the linear relationships with the global bond damping coefficient and the frequency of oscillation of the DEM particle respectively. With the proposed method the DEM local bond damping coefficient and the DEM bond Young's modulus were calibrated with relative errors of 0.9% and 1.8% respectively to laboratory estimated values. Utilising the linear relationships found from the DEM simulations, the bond Young's modulus was found to be in the range of 0.42–4.84 GPa.

Simulation of tool-to-soil interaction provides opportunities to accelerate new equipment design and evaluate performance of tillage tools. Simulation based evaluation of worn tillage tools performance on soil flow has not been done. Discrete Element Modelling (DEM) has a potential to simulate worn tool to soil interaction problems, where worn tools CAD can be generated using 3D scanning. The DEM parameters of Hertz-Mindlin with Parallel Bond model were calibrated to match draft force and soil failure zone measured from a tool bar moving at 0.22 m/s and 38 mm cutting depth. The draft force and soil forward failure zone were predicted at 7% and 24% relative errors compared to measured values, respectively. Using the optimized DEM soil model, the interaction of three 3D reconstructed sweeps (new sweep, carbide treated-worn, untreated-worn) with soil were simulated to compare their geometric wear dimensional loss, performance on soil forces and soil flow. Results showed that the carbide treated-worn sweep had similar soil draft force and soil forward failure distance as the new sweep. The untreated-worn sweep showed lower vertical force (less suction) and its wing induced soil failure zone (front and lateral) showed poor soil tilth quality compared with the carbide treated-worn sweep and the new sweep.

Grain augers are primary grain conveying equipment in agriculture. Quantitative prediction of dynamic grain flow in grain augers using discrete element modeling (DEM) has potential to support simulation-based engineering design of grain handling equipment. The objective of this study was to develop a DEM corn model using a multi-response calibration methodology and validation of combine-harvested corn flow in a commercial grain auger. Using a Latin hypercube design of experiment (DOE) sampling from four particle interaction DEM parameters values, 27 DEM simulations were generated for four DEM corn shape approximations (1-sphere, 2-spheres, 5-spheres, and 13-spheres) to create virtual DEM experiments of bucket-discharged and anchor-lifted angle of repose (AOR) tests. A surface meta-model was developed using the DEM interaction parameters as predictor variables, and normalized AOR expressed as a mean square error (MSE), i.e., the sum of square differences between DEM simulations and laboratory-measured AOR. Analysis of the MSE percentiles with lower error differences between DEM simulations and laboratory AOR and the computational effort required per simulation (h per simulation) showed that the 2-spheres DEM model had better performance than the 1-sphere, 5-spheres, and 13-spheres models. Using the best stepwise linear regression models of bucket AOR MSE (R2 of 0.9423 and RMSE of 94.56) and anchor AOR MSE (R2 of 0.5412 and RMSE of 78.02) and a surface profiler optimization technique, an optimized 2-spheres DEM corn model was generated. The DEM predicted AOR with relative errors of 8.5% for bucket AOR and 7.0% for anchor AOR. A DEM grain auger simulation used as a validation step also showed good agreement with the laboratory-measured steady-state mass flow rate (kg s-1) and static AOR (degrees) of corn piled on a flat surface, with DEM prediction relative error ranging from 2.8% to 9.6% and from 8.55% to 1.26%, respectively. Keywords: Corn, DEM, Discharge angle of repose, Discrete element modeling, Grain auger, Lift angle of repose.

The accuracy of dense Discrete Element Method (DEM) simulations is sensitive to initial density, contact orientation, particle size and shape, and interparticle interaction parameters including contact stiffness, cohesion, coefficients of friction, and coefficients of restitution. Although studies have characterized the effects of individual particle interaction parameters on mechanical responses of loaded granular material, research combining DEM parameters for calibration is scarce. Robust DEM calibration methodology combining sliding and rolling friction coefficients was developed and validated to predict bulk residual soil strength of initially dense DEM particle assemblies.

Screw augers are primary grain conveying equipment in the agriculture industry. Quantitative prediction of grain conveyance using screw augers requires better understanding and measurement of bulk particle-particle and particle-rigid-body interactions. Discrete element modeling (DEM) has potential to simulate particle dynamics and flow within a screw auger and thus provide simulation-based guidance for auger design and operating parameters. The objective of this study was to develop a DEM corn model calibration methodology and validation for combine-harvested corn flow in a commercial screw auger. The methodology used a virtual design of experiment (DOE) varying DEM corn parameters and calibration to match grain pile formation expressed in a normalized angle of repose (AOR). DEM corn particle shape was approximated using 1-sphere and clumped spheres (2-sphere, 5-sphere, and 13-sphere) matching the measured physical parameters of equivalent geometrical diameter, 2D axial dimensions, 3D axial dimensions, and detailed CAD-approximated corn dimensions, respectively. For each DEM corn shape approximation, a virtual DOE using Latin square hypercube design with four independent DEM Hertz-Mindlin contact model interaction coefficients was developed. The DEM assembly of particles matching the initial conditions of the AOR test was created in EDEM 2.7. From the quasi-static AOR of corn flow in the AOR tests and EDEM simulations, the mean square error (MSE), a sum of square difference in grain heights in the AOR tests and EDEM simulations, was used as a bulk material dependent response for the calibration process. The DEM 2-sphere corn shape model and the material interaction coefficients showed the minimum MSE (5.31 mm) compared to the 1-sphere, 5-sphere, and 13-sphere models. With the best DEM corn shape model (2-sphere) and DEM model parameters with the minimum MSE, validation of the DEM in predicting corn flow in a commercial screw auger in laboratory tests at two rotational speeds (250 and 450 rpm) was performed and showed good prediction (within 5% relative error) in matching the change in mass flow rate with the change in auger rotational speed. Keywords: Angle of repose, Corn, Discrete element modeling (DEM), Screw grain auger.

Modeling soil-tool interaction is essential for equipment design and performance evaluation on soil behavior responses under loading. Computational tools based on particle-based mechanics such as Discrete Element Modeling (DEM) and Smoothed Particle Hydrodynamics (SPH) have potential in modeling large strain soil dynamic behaviors from soil-tool interaction. The objective of this study is to validate the accuracy and robustness of DEM calibration methodology as it relates to soil deformation during cone penetration on varying initial soil relative density. The influence of factors such as DEM material properties and cone to particle size ratio on DEM cone penetration simulation will be investigated. The paper presents a comparison of DEM predicted cone penetration resistance and laboratory measured penetration data on Norfolk sandy loam. Soil mechanical behavior was modeled with Hertz-Mindlin (HM) contact stiffness model and a new coupled frictional law for static and rolling resistance coefficients. The DEM material properties were calibrated using residual strength from direct shear test. DEM simulations were performed using LIGGGHTS, open source DEM code. Cone penetrometer experiments using an ASABE standard cone with 12.53 mm cone base diameter and 30-degree cone tip were used to validate the calibrated DEM model. DEM prediction of cone penetration resistance trend and steady state values were in close agreement with the laboratory measured data for relative density range from 5 to 30%. At higher dense states (relative density of 90%), DEM calibration requires further improvement.

Soil compaction has potential to reduce crop yield by resisting seed germination and root growth. Modern agricultural farm equipment is getting bigger in size and axle weight that could cause excessive soil compaction. Natures of soil compaction in agricultural fields are not predictable because of non-homogeneous soil condition, and inconsistent wheel trafficking in the field. In this study predicting soil compaction behaviour will be studied for under different three soil moisture using Discrete Element Method (DEM). Discrete Element Method (DEM) is capable to simulate the elastic-plastic soil compaction behavior. Selection of appropriate DEM contact model and calibration of the DEM material properties is essential to simulate bulk soil dynamic behavior under compaction loading. DEM soil model using parallel bond model (PBM) available in PFC 3D was calibrated to match soil penetration resistance from a conical probe penetration on three-layered soil column. DEM model predicted the mean values of soil penetration resistance for middle (soil density of 1400 kg m -3 ) and bottom (1550 kg m -3 ) within 10% relative error for “dry” and “wet” soil moisture conditions. With the DEM calibration approach utilized in this study, soil penetration resistance for loose top layer were under predicted The DEM soil can be used for simulation of tire-soil interaction under uniaxial loading cases for various soil types, soil conditions, loading..