Recent progress on the discrete element method simulations for powder transport systems: A review

Powder transport systems are ubiquitous in various industries, where they can encounter single powder flow, two-phase flow with solids carried by gas or liquid, and gas–solid–liquid three-phase flow. System geometry, operating conditions, and particle properties have significant impacts on the flow behavior, making it difficult to achieve good transportation of granular materials. Compared to experimental trials and theoretical studies, the numerical approach provides unparalleled advantages over the investigation and prediction of detailed flow behavior, of which the discrete element method (DEM) can precisely capture complex particle-scale information and attract a plethora of research interests. This is the first study to review recent progress in the DEM and coupled DEM with computational fluid dynamics for extensive powder transport systems, including single-particle, gas–solid/solid–liquid, and gas–solid–liquid flows. Some important aspects (i.e., powder electrification during pneumatic conveying, pipe bend erosion, non-spherical particle transport) that have not been well summarized previously are given special attention, as is the application in some new-rising fields (ocean mining, hydraulic fracturing, and gas/oil production). Studies involving important large-scale computation methods, such as the coarse grained DEM, graphical processing unit-based technique, and periodic boundary condition, are also introduced to provide insight for industrial application. This review study conducts a comprehensive survey of the DEM studies in powder transport systems.     

A new signal processing-based islanding detection method using pyramidal algorithm with undecimated wavelet transform for distributed generators of hydrogen energy

Machine learning-based fault detection methods are frequently combined with wavelet transform (WT) to detect an unintentional islanding condition. In contrast to this condition, these methods have long detection and computation time. Thus, selecting a useful signal processing-based approach is required for reliable islanding detection, especially in real-time applications. This paper presents a new modified signal processing-based islanding detection method (IDM) for real-time applications of hydrogen energy-based distributed generators. In the study, a new IDM using a modified pyramidal algorithm approach with an undecimated wavelet transform (UWT) is presented. The proposed method is performed with different grid conditions with the presence of electric noise in real-time. Experimental results show that oscillations in the acquired signal can be reduced by the UWT, and noise sensitivity is lower than other WT-based methods. The non-detection zone is zero and the maximum detection and computational time is also 75 ms at a close power match.     

Direct shear behavior of gravel-rubber mixtures: Discrete element modeling and microscopic investigations

In this paper, a newly developed 3-dimentional discrete element model (DEM) for gravel-rubber mixtures (GRMs), namely DEM4GRM, that is capable of accurately describing the macro-scale shear response (from small to large deformation) of GRMs in a direct shear box apparatus is presented. Rigid gravel grains are modelled as simple multi-shape clumps, while soft rubber particles are modeled by using deformable 35-ball body-centered-cubic clusters. Mixtures are prepared with different volumetric rubber content (VRC) at 0, 10, 25, 40 and 100%, statically compressed under 30, 60 and 100 kPa vertical stress and then sheared, by closely simulating a reference laboratory test procedure. The variation of micro-scale factors such as fabric, normal and tangential force anisotropy is carefully examined throughout the shearing process and described by means of novel micro-mechanical relationships valid for GRMs. Moreover, strong-force chains are scrutinized to identify the transition from rigid to soft granular skeleton and gain insights on the load transfer and deformation mechanisms of GRMs. It is shown that the development of the fabric and force anisotropy during shearing is closely related to the macro-scale shear strength of GRMs, and strongly depends on the VRC. Besides, strong-force chains appear to be primarily formed by gravel-gravel contacts (resulting in a rigid-like mechanical behavior) up to VRC = 30%, and by rubber-rubber contacts (causing a soft-like mechanical response) beyond VRC = 60%. Alternatively, at 30% < VRC < 60%, gravel-rubber contacts are predominant in the strong-force network and an intermediate mechanical behavior is observed. This is consistent with the behavioral trends observed in the macro- and micro-mechanical responses.     

Anchor plate bearing capacity in flexible mesh facings

This work addresses the problem of the loading capacity of an anchor plate coupled with a steel wire mesh in soil retaining applications. The interaction mechanism between the flexible mesh facing, the underlying soil layer and the plate is studied starting from the results of several laboratory punch tests involving both the plate and the mesh only, and the whole soil-mesh-plate system. The experimental tests have been reproduced by adopting a 3D discrete element model where also the wire mesh is discretized as an assembly of interconnected nodal particles. The interaction between these particles is ruled by elasto-plastic tensile force–displacement laws in which a distortion is introduced in a stochastic manner to account for the wires’ geometrical irregularities. The mesh model is then validated with reference to a set of punch tests in which the shape and size of the punching element as well as the nominal wire diameter were varied. Subsequently, the model is extended to a punch against soil test configuration permitting an insight into the nontrivial local mechanism between the mesh facing and the underlying granular layer. The good agreement between the numerical predictions and the experimental observations at the laboratory scale allowed us to extend the model towards more realistic field conditions for which the role of the mesh panel boundary conditions, the mesh mechanical properties, the soil mechanical properties and the anchor plate geometry is investigated.     

Learn decision trees with deep visual primitives

In this paper, we strive to propose a self-interpretable framework, termed PrimitiveTree, that incorporates deep visual primitives condensed from deep features with a conventional decision tree, bridging the gap between deep features extracted from deep neural networks (DNNs) and trees’ transparent decision-making processes. Specifically, we utilize a codebook, which embeds the continuous deep features into a finite discrete space (deep visual primitives) to distill the most common semantic information. The decision tree adopts the spatial location information and the mapped primitives to present the decision-making process of the deep features in a tree hierarchy. Moreover, the trained interpretable PrimitiveTree can inversely explain the constituents of the deep features, highlighting the most critical and semantic-rich image patches attributing to the final predictions of the given DNN. Extensive experiments and visualization results validate the effectiveness and interpretability of our method.     

Numerical Investigation of the Capture of Polydisperse Particles by Charged Droplets

The capture of particles by charged droplets was simulated by considering the electrostatic interactions of droplet-droplet and droplet-particle. The results indicate that the electrostatic repulsion between droplets leads to a dynamic accumulation mode of particles. However, the droplet spacing has an insignificant effect on the capture efficiency when the electrostatic deposition predominates. The increase of droplet charge remarkably improves the capture efficiency, in which the capture of fine particles accounts for the largest proportion. Compared to the droplet charge, the droplet size shows a limited improvement in the capture efficiency. Reducing the droplet velocity prolongs the capture time instead of enhancing the capture capacity per unit time, thereby improving capture efficiency.     

Energy efficiency of fibre reinforced soil formation at small element scale: Laboratory and numerical investigation

This paper explores the aspects related to the energy consumption for the compaction of unreinforced and fibre reinforced samples fabricated in the laboratory. It is well known that, for a fixed soil density, the addition of fibres invariably results in an increased resistance to compaction. However, similar peak strength properties of a dense unreinforced sample can be obtained using looser granular soil matrices mixed with small quantities of fibres. Based on both experimental and discrete element modelling (DEM) procedures, this paper demonstrates that less compaction energy is required for building loose fibre reinforced sand samples than for denser unreinforced sand samples while both samples show similar peak strength properties. Beyond corroborating the macro-scale experimental observations, the result of the DEM analyses provides an insight into the local micro-scale mechanisms governing the fibre-grain interaction. These assessments focus on the evolution of the void ratio distribution, re-arrangement of soil particles, mobilisation of stresses in the fibres, and the evolution of the fibre orientation distribution during the stages of compaction.     

Influence of particle contact models on soil response of poorly graded sand during cavity expansion in discrete element simulation

The discrete element method (DEM) has been extensively adopted to investigate many complex geotechnical related problems due to its capability to incorporate the discontinuous nature of granular materials. In particular, when simulating large deformations or distortion of soil (e.g. cavity expansion), DEM can be very effective as other numerical solutions may experience convergence problems. Cavity expansion theory has widespread applications in geotechnical engineering, particularly to the problems concerning in situ testing, pile installation and so forth. In addition, the behaviour of geomaterials in a macro-level is utterly determined by microscopic properties, highlighting the importance of contact models. Despite the fact that there are numerous contact models proposed to mimic the realistic behaviour of granular materials, there are lack of studies on the effects of these contact models on the soil response. Hence, in this study, a series of three-dimensional numerical simulations with different contact constitutive models was conducted to simulate the response of sandy soils during cylindrical cavity expansion. In this numerical investigation, three contact models, i.e. linear contact model, rolling resistance contact model, and Hertz contact model, are considered. It should be noted that the former two models are linear based models, providing linearly elastic and frictional plasticity behaviours, whereas the latter one consists of nonlinear formulation based on an approximation of the theory of Mindlin and Deresiewicz. To examine the effects of these contact models, several cylindrical cavities were created and expanded gradually from an initial radius of 0.055 m to a final radius of 0.1 m. The numerical predictions confirm that the calibrated contact models produced similar results regarding the variations of cavity pressure, radial stress, deviatoric stress, volumetric strain, as well as the soil radial displacement. However, the linear contact model may result in inaccurate predictions when highly angular soil particles are involved. In addition, considering the excessive soil displacement induced by the pile installation (i.e. cavity expansion), a minimum distance of 11a (a is the cavity radius) is recommend for practicing engineers to avoid the potential damages to the existing piles and adjacent structures.     

Location Related Signals with Satellite Image Fusion Method Using Visual Image Integration Method

Investigations were performed on a group utilizing (General Purpose Unit) GPU and executions were evaluated for the utilization of the created parallel usages to process satellite pictures from satellite Landsat7.The usage on a realistic group gives execution change from 2 to 18 times. The nature of the considered techniques was assessed by relative dimensionless global error in synthesis (ERGAS) and Quality Without Reference (QNR) measurements. The outcomes demonstrate execution picks ups and holding of value with the bunch of GPU contrasted with the outcomes and different analysts for a CPU and single GPU. The errand of upgrading the view of a scene by combining data caught from various picture sensors is usually known as multisensor picture combination. This paper displays a territory based picture combination calculation to consolidate SAR (Synthetic Aperture Radar) and optical pictures. The co-enlistment of the two images is first led utilizing the proposed enrollment method prior to picture combination. The paper displays a parallel execution of existing picture combination techniques on a graphical group. Parallel executions of techniques in view of discrete wavelet changes are created. Division into dynamic and motionless regions is then executed on the SAR surface picture for particular injection of the SAR picture into panchromatic (PAN) picture. An integrated image in view of these two pictures is produced by the novel region based combination plot, which forces diverse combination rules for each fragmented region. At long last, this picture is melded into a multispectral(MS) picture through the half breed skillet honing technique proposed in past research. Exploratory outcomes exhibit that the proposed strategy demonstrates preferred execution over different fusion algorithms and can possibly be connected to the multisensory combination of SAR and optical pictures.