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The purpose of this paper is to extend the previous study [Computer Methods in Applied Mechanics and Engineering 340: 70-89, 2018] on the development of a novel packing characterising system based on principal component analysis (PCA) to quantitatively reveal some fundamental features of spherical particle packings in three-dimensional.

Gaussian quadrature is adopted to obtain the volume matrix representation of a particle packing. Then, the digitalised image of the packing is obtained by converting cross-sectional images along one direction to column vectors of the packing image. Both a principal variance (PV) function and a dissimilarity coefficient (DC) are proposed to characterise differences between different packings (or images).

Differences between two packings with different packing features can be revealed by the PVs and DC. Furthermore, the values of PV and DC can indicate different levels of effects on packing caused by configuration randomness, particle distribution, packing density and particle size distribution. The uniformity and isotropy of a packing can also be investigated by this PCA based approach.

Develop an alternative novel approach to quantitatively characterise sphere packings, particularly their differences.

The purpose of this paper is to extend complex-shaped discrete element method simulations from a few thousand particles to millions of particles by using parallel computing on department of defense (DoD) supercomputers and to study the mechanical response of particle assemblies composed of a large number of particles in engineering practice and laboratory tests.

Parallel algorithm is designed and implemented with advanced features such as link-block, border layer and migration layer, adaptive compute gridding technique and message passing interface (MPI) transmission of C++ objects and pointers, for high performance optimization; performance analyses are conducted across five orders of magnitude of simulation scale on multiple DoD supercomputers; and three full-scale simulations of sand pluviation, constrained collapse and particle shape effect are carried out to study mechanical response of particle assemblies.

The parallel algorithm and implementation exhibit high speedup and excellent scalability, communication time is a decreasing function of the number of compute nodes and optimal computational granularity for each simulation scale is given. Nearly 50 per cent of wall clock time is spent on rebound phenomenon at the top of particle assembly in dynamic simulation of sand gravitational pluviation. Numerous particles are necessary to capture the pattern and shape of particle assembly in collapse tests; preliminary comparison between sphere assembly and ellipsoid assembly indicates a significant influence of particle shape on kinematic, kinetic and static behavior of particle assemblies.

The high-performance parallel code enables the simulation of a wide range of dynamic and static laboratory and field tests in engineering applications that involve a large number of granular and geotechnical material grains, such as sand pluviation process, buried explosion in various soils, earth penetrator interaction with soil, influence of grain size, shape and gradation on packing density and shear strength and mechanical behavior under different gravity environments such as on the Moon and Mars.

Micro-focus X-ray computed tomography (CT) can be used to quantitatively evaluate the packing density, pore connectivity and provide the basis for specimen derived simulations of gas permeability of sand mould. This non-destructive experiment or following simulations can be done on any section of any size sand mould just before casting to validate the required properties. This paper aims to describe the challenges of this method and use it to simulate the gas permeability of 3D printed sand moulds for a range of controlling parameters. The permeability simulations are compared against experimental results using traditional measurement techniques. It suggests that a minimum volume of only 700 × 700 × 700 µm³ is required to obtain, a reliable and most representative than the value obtained by the traditional measurement technique, the simulated permeability of a specimen.

X-ray tomography images were used to reconstruct 3D models to simulate them for gas permeability of the 3D printed sand mould specimens, and the results were compared with the experimental result of the same.

The influence of printing parameters, especially the re-coater speed, on the pore connectivity of the 3D printed sand mould and related permeability has been identified. Characterisation of these sand moulds using X-ray CT and its suitability, compared to the traditional means, are also studied. While density and 3PB strength are a measure of the quality of the moulds, the pore connectivity from the tomographic images precisely relates to the permeability. The main conclusions of the present study are provided below. A minimum required sample size of 700 × 700 × 700 µm³ is required to provide representative permeability results. This was obtained from sand specimens with an average sand grain size of 140 µm, using the tomographic volume images to define a 3D mesh to run permeability calculations. Z-direction permeability is always lower than that in the X-/Y-directions due to the lower values of X-(120/140 µm) and Y-(101.6 µm) resolutions of the furan droplets. The anisotropic permeability of the 3D printed sand mould is mainly due to, the only adjustable, X-directional resolution of the furan droplets; the Y-directional resolution is a fixed distance, 102.6 µm, between the printhead nozzles and the Z-directional one is usually, 280 µm, twice the size of an average sand grain.A non-destructive and most representative permeability value can be obtained, using the computer simulation, on the reconstructed 3D X-ray tomography images obtained on a specific location of a 3D printed sand mould. This saves time and effort on printing a separate specimen for the traditional test which may not be the most representative to the printed mould.

The experimental result is compared with the computer simulated results.

Accurate 3D experimental particle trajectory data, acquired from a laboratory tumbling mill using bi‐planar X‐ray filming, are used to validate the discrete element method (DEM). Novel numerical characterisation techniques are presented that provide a basis for comparing the experimental and simulated charge behaviour. These techniques are based on fundamental conservation principles, and provide robust, new interpretations of charge behaviour that are free of operator bias. Two‐ and three‐dimensional DEM simulations of the experimental tumbling mill are performed, and the relative merits of each discussed. The results indicate that in its current form DEM can simulate some of the salient features of the tumbling mill charge, however, comparison with the experiment indicate that the technique requires refinement to adequately simulate all aspects of the system.

To use distinct element simulation (PFC2D) to investigate the relationships between microparameters and macroproperties of the specimens that are modeled by bonded particles. To determine quantitative relationships between particle level parameters and mechanical properties of the specimens.

A combined theoretical and numerical approach is used to achieve the objectives. First, theoretical formulations are proposed for the relationships between microparameters and macroproperties. Then numerical simulations are conducted to quantify the relationships.

The Young's modulus is mainly determined by particle contact modulus and affected by particle stiffness ratio and slightly affected by particle size. The Poisson's ratio is mainly determined by particle stiffness ratio and slightly affected by particle size. The compressive strength can be scaled by either the bond shear strength or the bond normal strength depending on the ratio of the two quantities.

The quantitative relationships between microparameters and macroproperties for parallel‐bonded PFC2D specimens are empirical in nature. Some modifications may be needed to model a specific material. The effects of the particle distribution and bond strength distribution of a PFC2D specimen are very important aspects that deserve further investigation.

The results will provide guidance for people who use distinct element method, especially the PFC2D, to model brittle materials such as rocks and ceramics.

This paper offers some new quantitative relationships between microparameters and macroproperties of a synthetic specimen created using bonded particle model.

The main purpose of this paper is to derive a set of similarity principles for discrete element modelling so that a numerical model can exactly reproduce the physical phenomenon concerned.

The objective is achieved by introducing the concepts of particle “strain” and “stress” so that some equivalence between the physical system and the numerical model can be established.

Three similarity principles, namely geometric, mechanical and dynamic, under which the numerical model can exactly reproduce the mechanical behaviour of a physical model are proposed. In particular, the concept of the scale invariant interaction law is further introduced. The scalability of a number of most commonly used interaction laws in the discrete element modelling is examined.

This is a preliminary research for a very important and challenging topic. More research, particularly in the understanding of the convergent properties of discrete element models, is needed.

The paper provides some important theoretical guidances to computational modelling of particle systems using discrete element techniques.

Emerging technologies commonly known as “rapid prototyping” fabricate solid objects directly from computer models by building parts in thin layers. Three‐dimensional printing is one such process that creates engineering prototypes and tooling by joining powder particles selectively on a layer‐by‐layer basis. The powder‐based approach offers tremendous flexibility in geometry and materials, but it makes layer position accuracy a fundamental concern for dimensional control in the vertical direction. Ideally, each powder layer is generated at a vertical position that remains fixed, at a prescribed distance with respect to a machine reference. However, compressive loads imparted to a stack of layers (by the weight of subsequent layers, for example) may cause the layers to displace downward. Develops a model for layer displacement using experimental data for compressibility and applied load. Compares predictions made from the model to measured displacements, and the predictions successfully captured the relative magnitudes of actual errors at various positions within layered powder beds. Position changes were most severe in the middle regions of the powder beds, with diminishing magnitude towards the top and bottom. Uses aluminium oxide powder in two different sizes (approximately of 10‐micron and 30‐micron diameter) and two different shapes (platelet and spherical) in the studies. The average measured displacement in a 76.2mm deep bed ranged from 23 microns for a 30‐micron platelet‐shaped powder to over 260 microns for a 9‐micron platelet‐shaped sample.

This study aims to introduce a new theoretical approach to blend spherical and non‐spherical particles in a coating to improve its viscosity characteristics.

Theoretical analysis has been used to modify an existing model developed by this author to apply to a broad range of particle configurations.

Non‐spherical particles like fibres or discs in a suspension or coating have been found to have three different viscosity response regions. Consequently, the viscosity of suspensions or coatings with these types of particles appears to have two apparent maximums as a function of concentration. Improved viscosity control of coatings have been found to be directly achievable by blending particles with different shapes based on the concentration relative to this first maximum. This optimisation process has been found to be better understood using a new variable which has been described as the “sphericity”, s. The “sphericity”, s, as described in this study has been defined as the relative ratio of the surface to volume fraction for a non‐spherical particle to that of a sphere of equivalent volume.

Experimental data involving monodisperse particles of different configurations is often extremely difficult to obtain. However, the theoretical general concepts can still be applicable.

The model presented in this paper provides practical guidelines to blending pigments with different particle shapes to control the viscosity of coatings and suspensions.

The model presented in this paper provides the first apparent guidelines to control the blending of pigments in coatings and composites with different particle shapes using the “sphericity” of the pigment particle.

The purpose of this paper is to propose a novel method to prepare pure Ti powder for 3D printing with tailorable particle size distribution.

The main procedures of the present method consist of gas state reaction to synthesize TiH₂ nanoparticles, agglomeration to obtain micronscale powder particles by spray drying, and densification of particle interior by heat treatment.

The prepared Ti powder has a specific bimodal particle size distribution in a range of small sizes, good sphericity and high flowability. Particularly, this new technique is capable of controlling powder purity and adjusting particle size.

To the best knowledge of the authors, the approach for preparing 3D printing metallic powders from nanoparticles has not been reported in the literature so far. This work provides a novel method that is particularly applicable to prepare 3D printing metallic powders which have small initial particle sizes and high reactivity in the air.

This study aims to experimentally investigate the effect of the powder material characteristics on the qualities of the binder jetting additive manufacturing parts both before and after post processing (sintering).

Three different types of the 316L stainless steel powder feedstock with various mean particle sizes and size distributions were studied. The influence of the powder particle size distributions and pore sizes on the powder bed packing densities and on the dynamics of the binder droplet-powder bed interactions were characterized. In addition, the surface roughness and densities of these parts both in the green state and after sintering were studied.

The results revealed the significant role of the powder feedstock characteristics on the liquid binder/powder bed interaction and consequently on the dimensional accuracies of the green parts. It was observed that the parts printed with the smaller mean particle sizes resulted in better surface finish and higher final densities after sintering. Furthermore, the hardness of the sintered parts produced with smaller powder particles exhibited higher values compared to the parts fabricated with the larger particles. On the other hand, larger particle sizes are advantageous for various green part qualities including the dimensional accuracies, green part densities and surface roughness.

This study establishes more comprehensive correlations between the powder feedstock characteristics and various quality criteria of the printed binder jetting components in both green and sintered states. These correlation are of critical importance in choosing the optimal process parameters for a given material system.