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The purpose of this study is to theoretically probe the shape impacts of nano-particle on boundary layer flow of nano-fluid toward a stretching cylinder with heat-transmission effects. The base fluid used for this study is pure water, and aluminum oxide nano-particles are suspended in it. Four different shapes of nano-particle, namely, cylindrical, brick, platelets and blades, are considered to carry out the study.

The problem is modelled mathematically and the nonlinear system of equations is attained by using appropriate transmutations. The solution of transmuted equations is achieved by utilizing a shooting technique with Fourth-Fifth order Runge–Kutta Fehlberg scheme. Numerically attained results are elucidated through graphs and tables which are further compared under limiting cases with existing literature to check the validity of the results.

It is observed that fluid velocity and temperature of cylindrical shaped water nano-fluids are more than the nano-fluid having brick-shaped nano-particles. Moreover, it is seen that the nano-fluids suspended with platelets-shaped nano-particles have higher velocity and temperature than the nano-fluids containing blade-shaped nano-particles. The curvature parameter and nano-particles volume fraction have increasing effects on flow velocity and temperature of nano-fluids containing all types of nano-particle shapes.

Numerous authors have examined the impacts of nano-particle shapes on characteristics of heat transfer and fluid flow. However, to the best of the authors’ knowledge, the shape impacts of nano-particles on boundary layer flow of nano-fluid toward a stretching cylinder with heat-transmission effects have not been discussed. So, to fulfill this gap, the present paper explicates the impacts of various nano-particle shapes on Al₂O₃–water-based nano-fluid flow past a stretching cylinder with heat-transfer effects.

This paper aims to numerically examine the mixed convection of SiO₂-water nanofluid flow in a three-dimensional (3D) cubic cavity with a conductive partition considering various shapes of the particles (spherical, cylindrical, blade, brick). The purpose is to analyze the effects of various pertinent parameters such as Richardson number (between 0.1 and 10), Hartmann number (between 0 and 10), solid nanoparticle volume fraction (between 0 and 0.04), particle shape (spherical, cylindrical, blade, brick) and different heights and lengths of the conductive partition on the fluid flow and heat transfer characteristics.

The numerical simulation was performed by using Galerkin-weighted residual finite element method for various values of Richardson number, Hartmann number, solid nanoparticle volume fraction, particle shape (spherical, cylindrical, blade, brick) and different heights and lengths of the conductive partition. Two models for the average Nusselt number were proposed for nanofluids with spherical and cylindrical particle by using multi-layer feed-forward neural networks.

It was observed that the average Nusselt number reduces for higher values of Richardson number and Hartmann number, while enhances for higher values of nanoparticle volume fraction. Among various types of particle shapes, blade ones perform the worst and cylindrical ones perform the best in terms of heat transfer enhancement, but this is not significant which is less than 3 per cent. The average Nusselt number deteriorates by about 6.53per cent for nanofluid at the highest volume fraction of spherical particle shapes, but it is 11.75per cent for the base fluid when Hartmann number is increased from 0 to 10. Conductive partition geometrical parameters (length and height) do not contribute to much to heat transfer process for the 3D cavity, except for the case when height of the partition reaches 0.8 times the height of the cubic cavity, the average Nusselt number value reduces by about 25per cent both for base fluid and for nanofluid when compared to case with cavity height which is 0.2 times the height of the cubic cavity.

Based on the literature survey, a 3D configuration for MHD mixed convection of nanofluid flow in a cavity with a conductive partition considering the effects of various particle shapes has never been studied in the literature. This study is a first attempt to use a conductive partition with nanofluid of various particle shapes to affect the fluid flow and heat transfer characteristics in a 3D cubic cavity under the influence of magnetic field. Partial or all findings of this study could be used for the design and optimization of realistic 3D thermal configurations that are encountered in practice and some of the applications were already mentioned above. In this study, thermal performance of the system was obtained in terms of average heat transfer coefficient along the hot surface, and it is modeled with multi-layer feed-forward neural networks.

The purpose of this paper is to study the particle shape effects on Marangoni convection boundary layer flow of a nanofluid. The paper aims to discuss diverse issues befell for the said model.

The work undertaken is a blend of numerical and analytical studies. Analytical and numerical solutions of nonlinear coupled equations are developed by means of Mathematica package BVPh 2.0 based on the homotopy analysis method.

The velocity of nanofluid decreases by increasing particle volume friction and similarity parameters. With the increase in particle volume friction and similarity parameter, temperature profile is correspondingly enhanced and decline. The lowest velocity and highest temperature of nanofluid is cause by needle- and disc-shaped particle. Consequence for interface velocity and the surface temperature gradient are perceived by numeric set of results. It is found that the interface velocity is declined by increasing particle volume friction and volume concentration of ethylene glycol in the water. The minimum interface velocity is seen by needle-shaped particle and 30 percent concentrations of ethylene glycol. With increase in volume friction and size of particle, the behaviors of surface temperature gradient are found decreasing and increasing function, respectively. The maximum heat transfer rate at the surface is achieved when we chose sphere nanoparticles and 90 percent concentrations of ethylene glycol as compared to other shapes and concentrations.

This model is investigated for the first time, as the authors know.

This paper aims to explore particle shape effect on Cu-H₂O nanoparticles over a moving plate in the presence of nonlinear thermal radiation. To characterize the effect, particle shape and viscous dissipation are considered. Convergent solutions for the resulting nonlinear systems are derived and the effects of embedded parameters of interest on velocity and temperature field are examined.

The Runge–Kutta–Fehlberg fourth-fifth order method along with shooting technique is used to solve the governing equations (6) and (7) with boundary conditions (8). A suitable finite value of η_∞ is considered in such a way that the boundary conditions are satisfied asymptotically.

The results show an increase in both the heat transfer and thermodynamic performance of the system. However, among the three nanoparticle shapes, disk shape exhibited better heat transfer characteristics and heat transfer rate. On the other hand, the velocity profile enhances with increasing values of ϕ in the first solution, but the opposite trend was found in the second solution.

The present paper deals with an exploration of particle shape effect on Cu-H₂O nanoparticles over a moving plate in the presence of nonlinear thermal radiation. To characterize the effect, particle shape and viscous dissipation are considered. Convergent solutions for the resulting nonlinear systems are derived and the effects of embedded parameters of interest on velocity and temperature field are examined. The skin friction coefficient and Nusselt number are numerically tabulated and discussed. The results show an increase in both heat transfer and thermodynamic performance of the system. However, among the three nanoparticle shapes, disk shape exhibited better heat-transfer characteristics and heat-transfer rate. On the other hand, the velocity profile enhances with increasing values of ϕ in the first solution, but the opposite trend was found in the second solution.

The purpose of this paper is to discretely model rockfill materials considering the irregular shape of the particles and their crushability. The scientific goal was to investigate the influence of particle crushability and shape on the mechanical behavior of rockfill materials.

The method of generating irregular-shaped particles was based on the observation that most rockfill grains can be approximately circumscribed by an ellipsoid. Two shape descriptors were used to make the virtual particles closely replicate the geometric features of natural rockfill grains. The combined finite-discrete element method (FDEM) was used to numerically simulate a drained, tri-axial compression test. The particle assemblies were subjected to tri-axial compression under strain controlled conditions while a constant confining pressure was maintained.

The non-breakable particles showed a remarkable ability to dilate as a result of a higher inter-particle locking effect. Dilation forces the particles to move from a lower potential energy state to a higher potential energy state, which causes the micro-structure to become less stable, resulting in a dramatic decline in the angle of friction from the peak state to the residual state. In addition, the elongated particles enhance the interlocking effect, but breakage is also more likely to occur. The net effect of those two mechanisms controls the overall shearing resistance of rockfill materials.

After calibration using a few micro-parameters, the combined FDEM was able to reproduce the typical behavior of rockfill materials without requiring a description of the complex relationship that exists between constituents; this relationship must be described in continuum mechanics. The simulation results showed that this approach is predictive. The combined FDEM also provides an opportunity for a quantitative study of the micro-structure of granular materials, and this study will help us to better understand the mechanical characteristics of rockfill materials.

This paper aims to propose a shape factor for granular materials based on particle shape. The scientific goal is to investigate the influence of particle shape on the mechanical properties of rockfill materials.

The method of generating four regular-shaped particles is based on the observation that most rockfill grains are regarded as like-triangle, like-rhombus, like-square and like-hexagon. A shape factor F that is developed using the Blaschke coefficient and a concave–convex degree is proposed. A biaxial compression test on rockfill materials under stress path is numerically simulated by discrete element method. The evolution of the shape factor F under the simulated stress paths is analyzed, and particle breakage rate, peak intensity and peak-related internal friction angle for rockfill materials are derived. A method of determining the shape factor F involved in the two functions is proposed.

A new micro-parameter is calibrated using the test data of one rockfill material. Particle shape greatly affects the particle breakage rate, peak intensity and peak-related internal friction angle for rockfill materials. The final experimental grading curves all approach the particle breakage grading curve proposed by Einav (the fractal dimension is 2.7).

This study proposes a shape factor F, which describes the geometric features of natural rockfill particles. The proposed shape factor F has a simple structure, and its parameters are easy to determine. The method provides an opportunity for a quantitative study on the particle shape of granular materials, and this study helps to better understand the influence of particle shape on the mechanical characteristics of rockfill materials.

This paper presents the results of a Discrete Element Method study on the influence of particle shape on the strength and deformation behaviour of two dimensional assemblages of ellipse‐shaped particles. Assemblages of particles with varying individual particle aspect ratio were formed with a preferred bedding plane, isotropically compressed with varying isotropic confining stresses and then sheared with biaxial compression. The results indicate that Discrete Element analysis using two dimensional ellipse‐shaped particles produces mechanical behaviour which is similar both quantitatively and qualitatively to the behaviour of real granular materials. Even small particle out‐of‐roundness increases the observed macroscopic strength significantly. In systems composed of flatter particles, particle rotations are greatly inhibited. Decomposing relative contact displacements into contributions due to particle rotation and translation demonstrates that most of the displacements in round particle systems are due to individual particle rotation.

The purpose of this study is to explore how particle shape influences the screening, including screening efficiency per unit time, and the relationship between vibration parameters and screening efficiency per unit time in discrete element method (DEM) numerical simulations.

In this paper, a three-dimensional discrete element model of vibrating screen with composite vibration form of swing and translation was proposed to simulate the screening process. In total, 11 kinds of non-spherical particles whose shapes changed in a continuous regularity gradual process were established using a multi-sphere method. In the DEM simulations, vibration parameters, including vibration frequency, vibration amplitude and stroke angle, and swing parameters, including swing frequency and swing angle, were changed to perform parametric studies.

It shows that the effect of particle shape on screening efficiency is quantitative actually. However, the trends of different shape particles’ screening efficiency per unit time are mainly consistent.

Some simple particle shapes can be expected to be explored to do screening simulation studies reasonably with modification of the simulation data in DEM numerical simulations. That may improve the computational efficiency of numerical simulations and provide guidance to the study of the screening process.

The purpose of this paper is to show how particle scale simulation of industrial particle flows using DEM (discrete element method) offers the opportunity for better understanding of the flow dynamics leading to improvements in equipment design and operation.

The paper explores the breadth of industrial applications that are now possible with a series of case studies.

The paper finds that the inclusion of cohesion, coupling to other physics such fluids, and its use in bubbly and reacting flows are becoming increasingly viable. Challenges remain in developing models that balance the depth of the physics with the computational expense that is affordable and in the development of measurement and characterization processes to provide this expanding array of input data required. Steadily increasing computer power has seen model sizes grow from thousands of particles to many millions over the last decade, which steadily increases the range of applications that can be modelled and the complexity of the physics that can be well represented.

The paper shows how better understanding of the flow dynamics leading to improvements in equipment design and operation can potentially lead to large increases in equipment and process efficiency, throughput and/or product quality. Industrial applications can be characterised as large, involving complex particulate behaviour in typically complex geometries. The critical importance of particle shape on the behaviour of granular systems is demonstrated. Shape needs to be adequately represented in order to obtain quantitative predictive accuracy for these systems.

The purpose of this paper is to examine several calibration techniques that have been developed to determine the discrete element method (DEM) parameters for slow and rapid unconfined flow of granular conical pile formation. This paper also aims to discuss some of the methods currently employed to scale particle properties to reduce computational resources and time to solve large DEM models.

DEM models have been calibrated against simple bench‐scale experimental results to examine the validity of selected parameters for the contact, material and mechanical models to simulate the dynamic and static behaviour of cohesionless polyethylene pellets. Methods to determine quantifiable single particle parameters such as static friction and the coefficient of restitution have been highlighted. Numerical and experimental granular pile formation has been investigated using different slumping and pouring techniques to examine the dependency of the type of flow mechanism on the DEM parameters.

The proposed methods can provide cost effective and simple techniques to determine suitable input parameters for DEM models. Rolling friction and particle shape representation has shown to have a significant influence on the bulk flow characteristics via a sensitivity analysis and needs to be accessed based on the environmental conditions.

This paper describes several effective known and novel methodologies to characterise granular materials that are needed to accurately model granular flow using the DEM to provide valuable quantitative data. For the DEM to be a viable predictive tool in industrial applications which often contain huge quantities of particles with random particle shapes and irregular properties, quick and validated techniques to “tune” DEM models are necessary.