A 3D DEM Model for Air Sparging Technology in the Saturated Granular Soils

This work provides a three-dimensional discrete element simulation (DEM) model to study the air sparging technology. The simulations have taken into account the multi-phases of bubble (gas) - fluid (water) - soil (solid) particles. Bubbles are treated as discrete individual particles, with buoyancy and drag forces applied to bubbles and soil particles. The trajectory of each discrete bubble particle can be tracked using the discrete element model. It is found that the diffusion of the whole bubble is inverted conical though the motion behavior of a single bubble particle is random. Furthermore, the distribution of the radius of influence (ROI) is not uniform. The bubbles become more concentrated as in the center of the inverted cone. The number of bubbles dissipated from the water surface is normally distributed. The DEM simulation is a novel approach to studying air sparging technology that can provide us a deeper insight into bubble migration at the microscopic level.

CALIBRATION OF BONDING MODEL PARAMETERS FOR COATED FERTILIZERS BASED ON PSO-BP NEURAL NETWORK

In this paper, the ultimate crushing displacement and ultimate crushing load of the coated fertilizer granules were obtained by uniaxial compression test as 0.450 mm and 58.668 N, respectively. Then the DEM model of the encapsulated fertilizer was established, and the Plackett-Burman and Steepest ascent tests were taken to determine the factors that had significant effects on the results and their ranges of values, respectively. Finally, the PSO_BP neural network was trained using full-factor test data, and the correlation coefficients of training process, validation process, testing process and overall performance were obtained as 0.98057, 0.95781, 0.96724 and 0.97459, respectively, indicating that the trained PSO_BP neural network fits well and can predict the ultimate crushing displacement and ultimate crushing load. The ultimate crushing displacement Y1 and ultimate crushing load Y2 are 0.450 mm and 58.703 N, with a minimum relative error of 0.06% from the actual value. This study can provide new methods and ideas for the calibration of discrete element simulation parameters.

Grain roughness effect on the critical state line of crushable sands

A recently proposed DEM model for materials with rough crushable grains (Zhang et al. 2021; Ciantia et al. 2015; Otsubo et al. 2017) is here employed to examine the effect of contact roughness on the critical state line, a property of granular materials which is a) fundamental for the evaluation of liquefaction risk and liquefied responses and b) easily accessible through DEM simulation (Ciantia et al. 2019).

Calibration of the Discrete Element Method Parameters in Living Juvenile Manila Clam (Ruditapes philippinarum) and Seeding Verification

The Manila Clam is an important economic shellfish in China’s seafood industry. In order to improve the design of juvenile Manila Clam seeding equipment, a juvenile clam discrete element method (DEM) particle shape was established, which is based on 3D scanning and EDEM software. The DEM contact parameters of clam-stainless steel, and clam-acrylic were calibrated by combining direct measurements and test simulations (slope sliding and dropping). Then, clam DEM simulation and realistic seeding tests were carried out on a seeding wheel at different rotational speeds. The accuracy of the calibrated clam DEM model was evaluated in a clam seeding verification test by comparing the average error of the variation coefficient between the realistic and simulated seeding tests. The results showed that: (a) the static friction coefficients of clam-acrylic and clam-stainless steel were 0.31 and 0.23, respectively; (b) the restitution coefficients of clam-clam, clam-acrylic, and clam-stainless steel were 0.32, 0.48, and 0.32, respectively. Furthermore, the results of the static repose angle from response surface tests showed that when the contact wall was acrylic, the coefficient rolling friction and static friction of clam-clam were 0.17 and 1.12, respectively, and the coefficient rolling friction of clam-acrylic was 0.20. When the contact wall was formed of stainless steel, the coefficient rolling friction and static friction of clam-clam were 0.33 and 1.25, respectively, and the coefficient rolling friction of clam-stainless steel was 0.20. The results of the verification test showed that the average error between the realistic and simulated value was <5.00%. Following up from these results, the clam DEM model was applied in a clam seeding simulation.

Achtung! Hunde auf der Fahrbahn

Dawid Kasprowicz widmet sich in diesem Artikel wissenschafts- und medienhistorisch dem Model des Reinforcement Learning (RL), das bei der Modellierung autonomer Autos einen zentralen Stellenwert hat. Dabei wird dargelegt, dass die Verbreitung und Anwendung des bestärkenden Lernens nicht nur eine Folge des verbesserten Lernverhaltens durch das Trainieren Neuronaler Netzwerke in Spielsituationen darstellt. Es wird argumentiert, dass das RL eine deartige Relevanz für das Testen autonomer Autos hat, weil es die Steuerung von Kontingenz in Experimenten und Simulationen ermöglicht. Es ist diese Steuerung von Kontingenz, die für die Simulationen autonomer Autos unabdingbar wird. Sie eröffnet zugleich die Frage, was der Übergang aus Verhaltensexperimenten in Verkehrssimulationen über das RL-Modell und die Modellierung autonomer Autos aussagt.

Study on Initiation and Mechanism of Seepage-induced Slope Failure in Jianghan Plain, Central China

The problem of seepage erosion is widespread in occurrence, but is rarely recognized as one of landslide causes. This paper describes and explains one event of slope erosion in Jianghan plain and is focused on the role of seepage erosion. The laboratory test is performed to reconstruct the hydraulic processes leading to slope failure with the application of different hydraulic loads. The observation and measurement reveal that slope alteration experienced three stages under seepage, and hydraulic gradient played a key role during seepage erosion phase. Using these results, a CFD-DEM model is developed to investigate how the seepage-induced soil particle migration would affect the slope evolution. The geotechnical properties control the failure processes and cause a significant change to the toe erosion and loosened zone. Although the instability of slope is mainly attributed to seepage gradient force, the occurrence of seepage erosion affects the failure mode. This work provides new guidance for hydrodynamic landslide prevention.

Torque Analysis of a Gyratory Crusher with the Discrete Element Method

Comminution by gyratory crusher is the first stage in the size reduction operation in mineral processing. In the copper industry, these machines are widely utilized, and their reliability has become a relevant aspect. In order to optimize the design and to improve the availability of gyratory crushers, it is necessary to calculate their power and torque accurately. The discrete element method (DEM) has been commonly used in several mining applications and is a powerful tool to predict the necessary power required in the operation of mining machines. In this paper, a DEM model was applied to a copper mining gyratory crusher to perform a comprehensive analysis of the loads in the mantle, the crushing torque, and crushing power. A novel polar representation of the radial forces is proposed that may help designers, engineers, and operators to recognize the distribution of force loads on the mantle in an easier and intuitive way. Simulations with different operational conditions are presented and validated through a comparison with nominal data. A calculation procedure for the crushing power of crushers is presented, and recommendations for the selection of the minimum resolved particle size are given.

CFD-DEM Simulation of Fluidization of Polyhedral Particles in a Fluidized Bed

Fluidization of non-spherical particles is a common process in energy industries and chemical engineering. Understanding the fluidization of non-spherical particles is important to guide relevant processes. There already have been numerous studies which investigate the behaviors of different non-spherical particles during fluidization, but the investigations of the fluidization of polyhedral particles do not receive much attention. In this study, the investigation of the fluidization of polyhedral particles described by the polyhedron approach is conducted with a numerical CFD-DEM method. Experiments of the fluidization of three kinds of polyhedral particles are conducted under the same condition with corresponding simulations to validate the accuracy of our CFD-DEM model. The results indicate that our CFD-DEM model with the polyhedron approach can predict the behaviors of polyhedral particles with reasonable accuracy. Fluidization behaviors of different polyhedral particles are also investigated in this study. Compared to spherical particles, the motion of polyhedral particles is stronger, and mixing degree is higher under the same fluidization gas velocity.