Determination of the normal spring stiffness coefficient in the linear spring–dashpot contact model of discrete element method

Effect of Particle Shape on the Flow of an Hourglass

The flow rate of a granulate out of a cylindrical container is studied as a function of particle shape for flat and elongated ellipsoids experimentally and numerically. We find a nonmonotonic dependence of the flow rate on the grain aspect ratio a/b. Starting from spheres the flow rate grows and has two maxima around the aspect ratios of a/b≈0.6 (lentil-like ellipsoids) and a/b≈1.5 (ricelike ellipsoids) reaching a flow rate increase of about 15% for lentils compared to spheres. For even more anisometric shapes (a/b=0.25 and a/b=4) the flow rate drops. Our results reveal two contributing factors to the nonmonotonic nature of the flow rate: both the packing fraction and the particle velocity through the orifice are nonmonotonic functions of the grain shape. Thus, particles with slightly nonspherical shapes not only form a better packing in the silo but also move faster through the orifice than spheres. We also show that the resistance of the granulate against shearing increases with aspect ratio for both elongated and flat particles; thus change in the effective friction of the granulate due to changing particle shape does not coincide with the trend in the flow rate.

Investigating the Effect of Design Parameters on the Mechanical Performance of Contact Wave Springs Designed for Additive Manufacturing

Additive manufacturing (AM) enables design freedom to fabricate functionally graded wave springs designed by varying design parameters, which are not possible in traditional manufacturing. AM also enables optimization of the wave spring design for specific load-bearing requirements. Existing wave springs are manufactured by metal with constant dimensions (width and thickness of the strip, diameter) using customized traditional machines in which design variations are almost impossible. This study aims to investigate the effect of wave height, the overlap between the two consecutive coils, and the number of waves per coil on the mechanical properties, for example, load-bearing capacity, stiffness, and energy absorption of contact wave springs. Two designs, that is, rectangular and variable thickness wave springs, were chosen and the design of experiment was devised using Minitab software, resulting in 24 samples. HP MultiJet Fusion (MJF) printer was used to manufacture the samples for performing uniaxial compression tests up to 10 cycles and 90% of the compressible distance to study the variation in mechanical properties due to changes in parameters. Experimental and simulation results showed that variable thickness wave springs have better load bearing, stiffness, and energy absorption compared with the rectangular counterparts. In addition to that, the number of waves per coil and the overlap are directly proportional to the load-bearing capacity as well as stiffness of the wave springs, while the constant wave height is responsible for more uniformly distributed stresses throughout the coils. Load-bearing capacity was increased by 62%, stiffness by 37%, and energy absorption by 20% once the number of waves per coil is increased from 5 to 6 in rectangular wave springs. Overall, the parametric variations significantly affect the performance of wave springs; thus, designers can choose the optimized values of investigated parameters to design customized wave springs for specific applications as per load/stiffness requirements.

Efficient Discrete Element Modeling of Particle Dampers

Particle dampers’ dissipative characteristics can be difficult to predict because of their highly non-linear behavior. The application of such devices in deformable vibrating systems can require extensive experimental and numerical analyses; therefore, improving the efficiency when simulating particle dampers would help in this regard. Two techniques often proposed to speed up the simulation, namely the adoption of a simplified frictional moment and the reduction of the contact stiffness, are considered; their effect on the simulation run-time, on the ability of the particle bed to sustain shear deformation, and on the prediction of the dissipation performance is investigated for different numerical case studies. The reduction in contact stiffness is studied in relation to the maximum overlap between particles, as well as the contacts’ duration. These numerical simulations are carried out over a wide range of motion regimes, frequencies, and amplitude levels. Experimental results are considered as well. All the simulations are performed using a GPU-based discrete element simulation tool coupled with the multi-body code MBDyn; the results and execution time are compared with those of other solvers.

Numerical Simulation of a Single and Double-Rotor Impact Crusher Using Discrete Element Method

The Discrete element method (DEM) is an invaluable tool for studying comminution as it provides detailed information that can help with process analysis as well as trying out new equipment designs before the equipment is physically built. The DEM was used to analyse previous experimental work to gain some insight into the comminution process in an impact crusher with a single impeller. Further DEM simulations were done on a crusher with a second impeller installed. The energy spectra and threshold energy levels calculated from the drop-weight test were used as the basis of comparison. The simulations indicate that even at much lower speeds, the performance of a double impeller impact crusher is exceedingly superior. However, the energy associated with the double impeller impact crusher is much higher and energy intensification, rather than energy efficiency, is the main gain of the double impeller design. The double impeller also offers more operational flexibility, such as spacing between the impellers, which can be tailored to the particle size range being handled.

Robotic Manipulation and Capture in Space: A Survey

Space exploration and exploitation depend on the development of on-orbit robotic capabilities for tasks such as servicing of satellites, removing of orbital debris, or construction and maintenance of orbital assets. Manipulation and capture of objects on-orbit are key enablers for these capabilities. This survey addresses fundamental aspects of manipulation and capture, such as the dynamics of space manipulator systems (SMS), i.e., satellites equipped with manipulators, the contact dynamics between manipulator grippers/payloads and targets, and the methods for identifying properties of SMSs and their targets. Also, it presents recent work of sensing pose and system states, of motion planning for capturing a target, and of feedback control methods for SMS during motion or interaction tasks. Finally, the paper reviews major ground testing testbeds for capture operations, and several notable missions and technologies developed for capture of targets on-orbit.

Machine learning of lubrication correction based on GPR for the coupled DPD-DEM simulation of colloidal suspensions

Hydrodynamic interactions have a major impact on the suspension properties, but they are absent in atomic and molecular fluids due to a lack of intervening medium at close range. To reproduce the correct hydrodynamic interactions, lubrication correction is essential to compensate the missing short-range hydrodynamics from the fluids. However, lubrication correction requires many simulations in particle-based simulations of colloidal suspensions. To address the problem, we employ an active learning strategy based on Gaussian process regression (GPR) for normal and tangential lubrication corrections to significantly reduce the number of necessary simulations and apply the correction to the coupled multiscale simulation of monodisperse hard-sphere colloidal suspensions. In particular, a single-particle dissipative particle dynamics (DPD) model with parameter correction is used to describe the solvent-solvent and colloid-solvent interactions, and a discrete element method (DEM) model to depict the colloid-colloid frictional contacts. The lubrication correction results demonstrate that only six and four independent simulations (observation points for GPR training) are required to achieve accurate normal and tangential lubrication corrections, respectively. To validate the machine learning of lubrication correction based on GPR, we investigate the self-diffusion coefficients of colloids, suspension rheology and microstructure using the coupled DPD-DEM model with GPR lubrication correction. Our simulation results show that the machine learning of lubrication correction based on GPR is effective and the lubrication corrected DPD-DEM model is indeed capable of accurately capturing hydrodynamic interactions and correctly reproducing dynamical and rheological properties of colloidal suspensions. Moreover, the machine learning of lubrication correction based on GPR is not limited to the coupled DPD-DEM simulation of colloidal suspensions presented here, but can be easily applied to other particle-based simulations of particulate suspensions.

Virtual Experiments of Particle Mixing Process with the SPH-DEM Model

Particle mixing process is critical for the design and quality control of concrete and composite production. This paper develops an algorithm to simulate the high-shear mixing process of a granular flow containing a high proportion of solid particles mixed in a liquid. DEM is employed to simulate solid particle interactions; whereas SPH is implemented to simulate the liquid particles. The two-way coupling force between SPH and DEM particles is used to evaluate the solid-liquid interaction of a multi-phase flow. Using Darcy’s Law, this paper evaluates the coupling force as a function of local mixture porosity. After the model is verified by two benchmark case studies, i.e., a solid particle moving in a liquid and fluid flowing through a porous medium, this method is applied to a high shear mixing problem of two types of solid particles mixed in a viscous liquid by a four-bladed mixer. A homogeneity metric is introduced to characterize the mixing quality of the particulate mixture. The virtual experiments with the present algorithm show that adding more liquid or increasing liquid viscosity slows down the mixing process for a high solid load mix. Although the solid particles can be mixed well eventually, the liquid distribution is not homogeneous, especially when the viscosity of liquid is low. The present SPH-DEM model is versatile and suitable for virtual experiments of particle mixing process with different blades, solid particle densities and sizes, and liquid binders, and thus can expedite the design and development of concrete materials and particulate composites.

Exploring the End-Liner Forces Using DEM Software

The main roles of liners are to protect the mill shell and promote effective ball motion for grinding. For this reason the liner profile is carefully selected to ensure that the productivity is maximized and due liner replacement is made when this objective is no longer met. These issues have been extensively studied on shell liners as mill relining is a significant cost component of ball milling. To date, not much has been written about end-liners and the kind of forces they are subjected to. A discrete element method (DEM) simulation scheme is conducted to look at how ball size distribution, mill filling, end-liner configuration and shape affect the distribution of forces acting on the liners that were assessed to understand end-liner wear and damage. The results showed how forces varied both radially and tangentially for the different sections of end-liner, with important insights drawn for end-liner manufactures.