United States

This paper presents a Computational Fluid Dynamics (CFD) model on the effect of capillary pressure on the retention behaviour of a granular material. The model proposes an unprecedented CFD insight into the onset of liquid menisci at the inter-particles contact under varying hydraulic conditions. The present work models the material grains as smooth spherical particles that define a porous network filled by two interstitial fluids: air and silicon oil. The numerical model has been subsequently validated against experimental measurements of the degree of saturation at different capillary pressures taken by Dullien et al. [F.A. Dullien, C. Zarcone, I.F. MacDonald, A. Collins, R.D. Bochard. J. Colloid Interface Sci. 127, 2 (1989)] in a system of smooth glass beads flooded with silicon oil. Results from the numerical simulations confirm the good capability of the model to reproduce the experimental retention behaviour of the granular material. Finally, the present paper laid the basis for future CFD studies on the effect of various factors (e.g. hydraulic hysteresis, surface roughness and/or grain shape) on the capillary pressure acting at the inter-particle contact.

Powders &amp; Grains 2021

CFD modelling of the effect of capillary pressure on retention behaviour of water menisci at inter-particle contacts

ICPR 2020 is the premier international conference on Pattern Recognition, gathering leading researchers from around the world to present their latest achievements in Pattern Analysis and Recognition, applied Artificial Intelligence and Machine Learning. The topic of the year is " Putting Artificial intelligence to work on Patterns". 
For the first time, ICPR has employed a two-round review process similar to journal submissions, with new papers allowed to be submitted in either the first or second round and papers submitted in the first round and not accepted allowed to be revised and re-submitted for second round review. 

In this edition of the **ICPR 2020** Conference, there are 1407 Oral/Poster presentations organized in five Tracks: 
- Artificial Intelligence, Machine Learning for Pattern Analysis; 
- Biometrics, Human Analysis and Behavior Understanding; Computer Vision, Robotics and Intelligent Systems; 
- Document and Media Analysis; and 
- Image and Signal Processing. 

The **ICPR 2020** Main Conference program also includes 7 Keynotes from prominent world-renowned scientists, 8 Tutorials, 28 Demos, 8 Challenges, 2 Panels, as well as an Industry/Sponsor Exhibition. In addition, 41 Workshops on a range of important current and emerging research topics complete the ICPR 2020 program. 


ICPR 2020

poster

[EPJ Web of Conferences, Volume 249 (2021)](https://www.epj-conferences.org/articles/epjconf/abs/2021/03/contents/contents.html)

Follow us on [Twitter](https://twitter.com/g2021_p)

**Meet the Organizers**

<center>
<figure class="video_container">
	  <iframe src="https://screencast-o-matic.com/watch/cr130qV10B3?v=6&ff=1&title=0&controls=1" width=826 height=526  frameborder="0" allowfullscreen="true"> </iframe>
</figure>
	</center>


Welcome to the 2021 Powders and Grains conference. Please review the event's **Code of Conduct** [here](https://drive.google.com/file/d/1P_bOrjI2jSE55twRPVzWl5VkfARR-qBL/view?usp=sharing). 


**Powders & Grains 2021 Walkthrough Screencast**

This video will demonstrate how to navigate the conference and virtual platform -- and network with other attendees and speakers.


<center>
<figure class="video_container">
	  <iframe src="https://screencast-o-matic.com/watch/cr1vnKV1pgn?v=6&ff=1&title=0&controls=1" width=826 height=526  frameborder="0" allowfullscreen="true"> </iframe>
</figure>
	</center>

To register for the event, please follow the link below. 

Powders & Grains 2021

Powders & Grains 2021 will be held in Buenos Aires (Argentina, VIRTUAL) July 5, 13, 21, 29 and Aug 6, 2021. The aim of the conference is to give an up-to-date picture of the broad research field of granular media, powders and grains. Contributions from experts around the world will focus on research topics that cover a wide range of open problems in the field.

The present study is on segregation of granular mixtures during heap formation in a quasi two-dimensional rectangular bin where binary mixture of a specified composition is poured intermittently into the auxiliary hopper and then allowed to pass through the gap (k = 10 mm) between the divider and the plate and finally settle on to the heap. The profiles of number fraction of big particles are plotted along the flow directions to study the segregation phenomena for surface profile. It shows that larger particles travel more distance and smaller particles settle near the pouring point for all cases studied.

Experimental investigation of segregation of granular mixtures during heap formation

A nonlinear programming problem was developed for the separation and classification of
Portland cement particles into different fractions through the optimal design of two cyclones classifier in
series. The equations and restrictions considered included the global mass balances, the equations for the
geometric design of the cyclones, the equations for the efficiency calculation, the operating limitations of
the process and the pressure drops of the equipment. The results show that an increase on the particles cut
size led to a greater dimensions cyclone, as expected. Moreover, fractional efficiencies obtained increase
with the reduction of the cut size. The solids load effect is also evaluated, reductions of the solids feed by
50% of its maximum value does not result in a remarkably decrease of efficiencies values. The proposed
model has provided useful information and constitutes a starting point for a better understanding of the
overall separation process of multi-component Portland cement mixtures. It is a valuable tool for the correct
design of this type of separators, given its versatility to optimize under different operating conditions and
with different materials.


Optimal design of cyclones in series for the separation of multi-component mixtures of Portland cement

Simple geometry and multiple applications such as drying, mixing, segregation, drying, granulation and heat conduction have inspired many researchers from the mechanical, chemical, pharmaceutical and mining engineering fields to study the dynamics of the particle flow inside rotating drums. Therefore, knowledge of the dynamics of particles in a drum is of high interest in engineering such as velocity profiles. Various experimental and numerical studies have been carried out to study the velocity profiles of the particles inside horizontal rotating drums. Little emphasis has been laid on inclined rotating drums, though these drums are extensively used in granular process industries. In this study Discrete Element Method (DEM) is used to analyse the effect of angle of inclination of the drum on the particles velocity profile.

Particle velocity profile in an inclined rotating drum

When a mechanical wave travels through a medium, its intensity diminishes with distance. The research focuses on the energy transfer with distance as well as across different wavenumbers, as the mechanical wave propagates. The diffusive characteristic of energy propagation has been discussed for one-dimensional chains composed of random, pre-stressed soft and stiff particles interacting through Hertzian repulsive forces, which can be solved analytically after linearization. The effect of soft-stiff ratio (disorder in property) on energy transfer across wavenumbers is examined using a standing sinusoidal wave initial condition (with a specific wavenumber). From the total energy signals in wavenumber space, as a function of time, it is observed that stronger disorder leads to a more rapid loss of energy of the signal and faster transfer of energy to other wavenumbers.

Energy propagation in 1D granular soft-stiff chain

This paper experimentally analyzes the collapse of conical granular columns made out of non-cohesive granular materials. Dimensionless run-out lengths were found, as a function of the aspect ratio a, similar to those occurring in the collapse of cylindrical columns, although in the case of conical columns of high aspect ration, at the end of the collapse, a layer of grains that rotates around the cone axis appears and it affects the final profiles of the mounds.

Collapse of conical granular columns

Acoustic emission (AE) or vibration signal has been applied in detecting operations of grinding mills in many industries. This paper proposes an approach to generate AE signals based on the particle-wall impacts. Through a combination of multi-mode vibrations and the calibration of the key parameters, the model was able to reproduce experimental data. The AE model was then implemented into a discrete element method (DEM) modelling of particle flow in a rotating mill. The AE signals of the mill under different filling levels and rotation speeds were generated and analysed, mainly focusing on the frequency and magnitude of each vibration mode. The link between the AE signals and the particle-wall impact energy was explored

Acoustic signals of rotating drums generated based on DEM simulations

The soil water retention curve (SWRC) is the most commonly used relationship in the study of
unsaturated soil. In this paper, the eect of porosity on the SWRC is investigated by numerically modeling
unsaturated soil using the Shan-Chen multiphase Lattice Boltzmann Method. The shape of simulated SWRCs
are compared against that predicted by the van Genuchten model, demonstrating a good fit except at low degrees
of saturation. The simulated SWRCs show an increase in the air-entry value as porosity decreases.

Investigating the effect of porosity on the soil water retention curve using the multiphase Lattice Boltzmann Method

We use three-dimensional particle dynamics simulations to investigate the microstructure evolution of granular material subjected to isochoric cyclic shearing, driving the system to a liquefaction state. The cyclically sheared assembly presents a realistic macroscopic response as observed in physical experiments. By analyzing the contact network evolution in the post-liquefaction period, we show that the onset of liquefaction state is characterized by a sudden drop of coordination number and a fragile particle connectivity network. The simulation suggests a critical coordination number for exiting the liquefaction state. Evolution of fabric anisotropy combined with coordination number implies the isotropic and anisotropic gain or loss of contacts at certain durations of a post-liquefaction loading cycle.

Geometrical network of granular materials under isochoric cyclic shearing

3D printing is emerging as one of the most promising methods to manufacture Pharmaceutical dosage forms as it offers multiple advantages such as personalization of dosage forms, polypill, fabrication of complex dosage forms etc. 3D printing came into existence in 1980s but its use was extended recently to pharmaceutical industry along with the approval of first 3D printed tablet Spritam by FDA in 2015. Spritam was manufactured by Aprecia pharmaceuticals using binder jetting technology. Binder jet 3D printing involves a hopper for powder discharge and printheads for ink jetting. The properties of tablets are highly dependent upon the discharge quality of powder mixture from the hopper and jetting of the ink/binder solution from the printhead nozzle. In this study, numerical models were developed using Discrete element method (DEM) to gain better understanding of the binder jet 3D printing process. The DEM modeling of hopper discharge was performed using in-house DEM code to study the effect of raw material attributes such as powder bed packing density (i.e. particle size, particle density etc.) on the printing process, especially during powder bed preparation. This DEM model was further validated experimentally, and the model demonstrated good agreement with experimental results.

DEM based investigation of powder packing in 3D printing of pharmaceutical tablets

We are numerically and experimentally studying the response of a 3d granular system to cyclic perturbations to investigate reversibility and memory effects. We are especially interested in translations and rotations of particles are affected by the inter-particle friction coefficient. We find that at low friction, the rotations are homogeneously distributed in the system; the motion of particles is mostly reversible and the system exhibit a very strong memory response. In contrast, at high friction, the rotations are located in a narrow shear band, and are mostly irreversible which leads to a much less pronounced memory response of the system. This can be explained by the need for the system to overcome a large sliding force limit which is only possible for a small proportion of particles, leading to a non-reversible motion.

Downloads

Next from Powders & Grains 2021

Experimental investigation of segregation of granular mixtures during heap formation

Similar lecture

Inferring Functional Properties from Fluid Dynamics Features