Particle Packing Algorithm Research Articles

Investigation on unsteady thermal process of NEPE propellant based on an refined chemical kinetic model

This study presents a sophisticated investigation into the intricate heat and mass transfer mechanisms of NEPE composite propellant under realistic rocket motor conditions, with particular emphasis on the rapid depressurization effects. To accomplish this, we have developed an innovative particle packing algorithm coupled with a novel semi-global kinetics model. By integrating detailed chemical kinetics models for Ammonium perchlorate (AP) oxidizing powders, Cyclotetramethylene tetranitramine (HMX) oxidizing powders, and Nitroglycerin/1,2,4-Butane triol trinitrate (NG/BTTN) fuel-binder, we have constructed a meso-scale model of NEPE propellant based on comprehensive experimental data. Furthermore, a refined 9-step kinetic mechanism has been incorporated into the meso-scale model, along with a pressure drop model that accurately captures the intricate gas reaction domain. The predicted parameters of NEPE propellant have been meticulously compared with experimental results, demonstrating a remarkable level of agreement. Moreover, meticulous analyses have been carried out to investigate the complex thermal processes exhibited by this composite propellant under the challenging conditions of rapid depressurization combustion. These analyses primarily focus on unraveling the dynamic evolution of the gas-solid phase and the underlying thermal regression mechanism of the solid phase. Notably, our findings reveal intriguing temporal changes in local heat flux feedback spikes throughout the entire depressurization process, owing to the intricate topology structure of NEPE propellant, which comprises multiscale oxidizing micro-particles embedded within a fuel-binder matrix. This research significantly enhances our understanding of the thermal behavior and performance characteristics of NEPE composite propellant, thereby paving the way for future advancements in rocket propulsion technology.

Review of Mesoscale Geometric Models of Concrete Materials

Concrete can be regarded as a composite material comprising aggregates, cement mortar, and an interfacial transition zone (ITZ) at the mesoscale. The mechanical properties and durability of concrete are influenced by the properties of these three phases. The establishment of a mesoscale model of concrete and the execution of numerical simulations constitute an efficacious research method. It is an efficacious method to research concrete by establishing the mesoscale model of concrete and executing numerical simulations. By this method, the influence of an aggregate shape on concrete performance can be studied. This paper presents a systematic review of mesoscale modeling methods for concrete, with a focus on three aspects: the aggregate modeling method, the collision detection algorithm, and the particle-packing algorithm. The principal processes, advantages, and disadvantages of various methods are discussed for each aspect. The paper concludes by highlighting current challenges in the mesoscale modeling of concrete.

Isotropic packing algorithm for particle simulations

AbstractThis article introduces the R2 Fill method, which is an algorithm for filling a region with particles isotropically. The method's isotropy is tested geometrically and then mechanically with the Discrete Element Method (DEM). It applies to planar and three‐dimensional problems and is simpler to implement and has competitive metrics compared to other Advancing Front packing algorithms. The DEM formulation used in this paper provides a way to model solid materials and eliminate residual stress created in any particle packing algorithm. The R2 Fill method was tested over ranges of particle sizes. At large size ranges the method generated a higher coordinate number and denser particle packing, with 79.718% fill at the maximum tested size range. The geometric isotropy was improved at higher size ranges yielding less than a 1% isotropic error. The method also had fewer particles than the similar and more complex algorithm by Yongjun Li. Lastly we tested mechanical isotropy by using our DEM formulation to measure the stress–strain response under a tensile load at different orientations. The R2 Fill method produced mechanical isotropy within 2% error for the elastic moduli, shear moduli, and Poisson ratio.

Algorithms for uniform particle initialization in domains with complex boundaries

Accurate mesh-free simulation of fluid flows involving complex boundaries requires that the boundaries be captured accurately in terms of particles. In the context of incompressible/weakly-compressible fluid flow, the SPH method is more accurate when the particle distribution is uniform. Hence, for time-accurate simulation of flow in the presence of complex boundaries one must have both an accurate boundary discretization and a uniform distribution of particles to initialize the simulation. This process of obtaining an initial uniform distribution of particles is called “particle packing”. In this paper, we compare and implement various particle packing algorithms present in the literature. We propose an improved SPH-based algorithm which produces uniform particle distributions of both the fluid and solid domains in two and three dimensions. We demonstrate the accuracy of the new algorithm by constructing some challenging geometries. The implementation of the algorithm is open source, and the manuscript is fully reproducible. Program summaryProgram title: SPHGeomCPC Library link to program files:https://doi.org/10.17632/hz7pg3rhdb.1Code Ocean capsule:https://codeocean.com/capsule/5490642Licensing provisions: BSD 3-ClauseProgramming language: PythonExternal routines/libraries: PySPH (https://github.com/pypr/pysph), matplotlib (https://pypi.org/project/matplotlib/), automan (https://pypi.org/project/automan/), ParaView(https://www.paraview.org/download/).Nature of problem: Particle methods require that complex geometry be accurately represented when discretized with particles. The particles should be uniformly distributed inside, outside, and on the surface of the geometry. This can be achieved using the proposed particle packing algorithm. For a fluid flow past a solid body, the code generates a set of solid particles inside and on the surface surrounded by fluid particles such that the density is approximately constant. These particles can be placed in a larger simulation.Solution method: : The proposed algorithm uses a number density gradient, a repulsion force, and a damping force to move particles. Particles are constrained near the boundary to move along the surface. Particles are iteratively projected onto the boundary surface. Once a desired distribution of particles is achieved, the particles are separated into interior and exterior particles using the boundary information. This may be used directly as an input for particle-based simulation.Additional comments: : The source code for this repository can be found at https://gitlab.com/pypr/sph_geom.

SPH simulations of 3D dam-break flow against various forms of the obstacle: Toward an optimal design

Dams are an important part of a country's infrastructure. After the dam breaks, the collision force of the water column, if severe enough, would incur a great deal of destruction and damage and needs to be concerned specially. In this work, 3D dam-break flows against various forms of the obstacle are numerically simulated by the smoothed particle hydrodynamics (SPH) method. In order to tackle boundaries of irregular or curved shapes involved in the obstacle, both wall particles and dummy particles are adopted in SPH, in which dummy particles are arranged by a particle packing algorithm which allows the attainment of a regular particle distribution. To validate the SPH method, 3D dam-break flow against a vertical wall is first simulated, and the SPH results are compared with the experiment and those obtained by other numerical methods. Then, we extend the method to 3D dam-break flows against various forms of the obstacle. A number of challenging numerical examples including 3D dam-break flows against a right-angled obstacle, a sloping obstacle with the angle of inclination α = 60°, 45°, and 30°, and an arc obstacle with the arc angle β = 90°, 60°, and 45° are simulated. The time evolutions of the pressure on the obstacle surface are shown in details. It is demonstrated that the proposed SPH method can handle 3D large-deformation flows with any complex boundaries accurately. The arc obstacle with β = 60° may be selected as one of the optimal forms of the obstacle for reducing the collision force of the fluid after the dam breaks. The maximum pressure on this obstacle surface is less than ~40% of a right-angled obstacle.

A combined physical and DEM modelling approach to investigate particle shape effects on load movement in tumbling mills

The discrete element method (DEM) which is used to simulate granular flows often assumes spherical shape for particles. This assumption is legitimized by the added complexity of non-spherical shape representation, contact detection and computational cost. In this work, the difference between the dynamics of non-spherical and spherical particles was studied in detail by a combined physical and DEM modeling approach. An in-house developed DEM software called KMPCDEM©, which was coded to handle non-spherical particles, was used to simulate the behavior of particles. To calibrate the model parameters, a model tumbling mill (100 cm diameter and 10.8 cm length) with one transparent end was used which made accurate photography possible. The tests were performed at filling of 20% and mill speed of 85% of critical speed with steel balls and wood cubes. In the simulation, each cubical particle was represented with clusters of spheres (with identical size) by particle packing algorithm for contact detection and contact-force calculation. Comparison of the simulation and experimental results showed that the difference between the measured and predicted impact toe, shoulder angle and bulk toe angle were 3, 4 and 5°, respectively. The significant change in the charge movement and structure on account of non-spherical particles was reflected in the amount of in-flight charge, and positions of shoulder, impact toe and bulk toe. It found that there was a 17% difference in the amount of in-flight of charge between cubical and spherical particles. The marked difference was attributed to higher interlocking of non-spherical particles in comparison to spherical balls. The results showed that cubical particles participated 5% more in the high energy impact action compared to that of the spherical particles. The simulation computation time increased by 35 times when the shape of particles changed from spherical to cubical.

Fast and efficient particle packing algorithms based on triangular mesh

The point of departure for the particle-based discrete element simulations is the generation of disk or sphere packing of interest domain. In this paper, based on a triangular mesh, two geometric packing algorithms are proposed for 2D problems. New disk(s) are obtained element-wise by solving system of equations, which can be easily derived according to the local topological relationships. In this way, the adjacent disks are guaranteed to be in contact with each other exactly. Related issues are discussed in detail, such as boundary treatment for good definition of the boundaries, elimination of incorrect overlaps, random perturbation for avoiding over-homogeneous packing. The main advantages of these two algorithms are the high efficiency and applicability for arbitrary domains. Furthermore, with a refined mesh, a refined packing can be easily obtained, which is a potential alternative for multiscale simulations. The proposed methods are verified by several examples.

Advances in particle packing algorithms for generating the medium in the Discrete Element Method

Several theoretical contributions in order to establish a particle packing methodology are presented. In this respect, a generic formulation of a new method for packing particles based on a constructive advancing front method, which uses Monte Carlo techniques for the generation of particle dimensions, is also shown. The method can be used to obtain virtual dense packings of particles with several geometrical shapes. It employs continuous, discrete and empirical statistical distributions in order to generate the dimensions of particles. The packing algorithm is very flexible and allows alternatives for: 1- The direction of the advancing front (inwards or outwards), 2- The selection of the local advancing front, 3- The method for placing a mobile particle in contact with others and 4- The overlap checks. The algorithm also allows obtaining highly porous media when it is slightly modified. Practical applications of the formulations are presented in the end of this paper.

Computational modeling of the effective properties of spatially graded composites

In the present study, finite element- and representative volume element (RVE)-based models for estimation of the effective elastic, thermal, and thermoelastic properties of the multi-phase spatially graded particulate composites have been developed. Efficient particle packing algorithms were utilized to create high-resolution graded microstructures with spatial (more than one direction) variation of the composites’ constituents. The so-called continuously graded RVEs were generated and accounted for spatially continuously graded microstructures. Numerical homogenization of these RVEs enabled to preserve the influence of the particle interactions resulting from continuous grading. The developed models were verified by comparing the predicted effective properties to those obtained using the previously existed models and were validated using available experimental data.

Modelling of irregular-shaped cement particles and microstructural development of Portland cement

The shape of cement powder particles plays a crucial role in particle packing and hydration process of cement. However, cement powder is generally regarded as sphere for simplification in most cement hydration models. This paper aims to investigate the influence of cement particle shapes on hydration of Portland cement and microstructure of cement paste. A novel central growth model along with a particle packing algorithm is developed to generate cement particles with irregular shapes and reconstruct initial 3D microstructures of Portland cement. Afterwards, the hydration process of cement with different shapes are simulated using CEMHYD3D model. The results indicate that the generated irregular-shaped particles precisely reproduce the real cement particles in terms of surface area, particle size distribution and geometry. The effect of particle shapes on hydration is significant due to the difference in surface area and geometric discrepancy, whereas this effect becomes less obvious with decreasing water-to-cement ratio.

Virtual modeling of polycrystalline structures of materials using particle packing algorithms and Laguerre cells

The influence of the microstructural heterogeneities is an important topic in the study of materials. In the context of computational mechanics, it is therefore necessary to generate virtual materials that are statistically equivalent to the microstructure under study, and to connect that geometrical description to the different numerical methods. Herein, the authors present a procedure to model continuous solid polycrystalline materials, such as rocks and metals, preserving their representative statistical grain size distribution. The first phase of the procedure consists of segmenting an image of the material into adjacent polyhedral grains representing the individual crystals. This segmentation allows estimating the grain size distribution, which is used as the input for an advancing front sphere packing algorithm. Finally, Laguerre diagrams are calculated from the obtained sphere packings. The centers of the spheres give the centers of the Laguerre cells, and their radii determine the cells’ weights. The cell sizes in the obtained Laguerre diagrams have a distribution similar to that of the grains obtained from the image segmentation. That is why those diagrams are a convenient model of the original crystalline structure. The above-outlined procedure has been used to model real polycrystalline metallic materials. The main difference with previously existing methods lies in the use of a better particle packing algorithm.

Contributions to the generalization of advancing front particle packing algorithms

SummaryThe generation of a set of particles with high initial volume fraction is a major problem in the context of discrete element simulations. Advancing front algorithms provide an effective means to generate dense packings when spherical particles are assumed. The objective of this paper is to extend an advancing front algorithm to a wider class of particles with generic size and shape. In order to get a dense packing, each new particle is placed in contact with other two (or three in 3D) particles of the advancing front. The contact problem is solved analytically using wrapping intersection technique. The results presented herein will be useful in the application of these algorithms to a wide variety of practical problems. Examples of geometric models for applications to biomechanics and cutting tools are presented. Copyright © 2015 John Wiley & Sons, Ltd.

Evaluation of Mesostructure of Particulate Composites by Quantitative Stereology and Random Sequential Packing Model of Mono-/Polydisperse Convex Polyhedral Particles

Random packing of particles has served as a topic of intense research in the chemical, physical, engineering, and material fields. The majority of previous works focused on the random packing models of spherical, cylindrical, and ellipsoidal particles, whereas little is known about polyhedral particles. In this article, a modeling study of the random packing of convex polyhedral particles is presented in detail, using an interparticle contact detection algorithm, a particle-to-container wall intersection detection algorithm, and a random sequential packing algorithm for hard particles, and the accuracy and efficiency of the contact detection algorithm are compared with those of methods from the literature. With the random packing model and a specified particle size distribution, mesostructure models of particulate composites with mono-/polydisperse particles were generated and validated by a sectioning analysis algorithm. Based on quantitative stereological theories and the sectioning analysis algorithm, the effects of particle shape on the mesostructures composed of the monodisperse and polydisperse particles were evaluated. Further, the statistical results were verified by validation against experimental results from the literature and theoretical results.

Particle packing algorithm for SPH schemes

Using some intrinsic features of the Smoothed Particle Hydrodynamics (SPH) schemes, an innovative algorithm for the initialization of the particle distribution has been defined. The proposed particle packing algorithm allows a drastic reduction of the numerical noise due to particle resettlement during the early stages of the flow evolution. Moreover, thanks to its structure, it can be easily derived starting from whatever SPH scheme and applies under the hypotheses that the fluid is weakly-compressible or incompressible as well. A broad range of numerical test cases proved this tool to be fast, robust and reliable also for complex geometrical configurations.

Effective packing of 3-dimensional voxel-based arbitrarily shaped particles

In many research areas including medicine and paper coating, packing of particles together with numerical simulation is used for understanding important material functionalities such as optical and mass transfer properties. Computational packing of particles allows for analysing those problems not possible or difficult to approach experimentally, e.g., the influence of various shapes and size distributions of particles. In this paper a voxel-based algorithm by Jia et al. [X. Jia, R.A. Williams, A packing algorithm for particles of arbitrary shapes, Powder Technology 2001, vol. 120, pp. 175–186.] enabling the packing of arbitrarily shaped particles, is memory- and speed-optimised to allow for simulating significantly larger problems than before. Algorithmic optimisation is carried out using particle shell area reduction decreasing the amount of time spent on collision detection, fast rotation routines including lookup tables, and a bit packing algorithm to utilise memory effectively. Presently several hundreds of thousands of complex arbitrarily shaped particles can be simulated on a desktop machine in a simulation box consisting of more than 10 9 voxels.

A packing algorithm for three-dimensional convex particles

Simulation of granular particles is an important tool in many fields. However, simulation of particles of complex shapes remains largely out of reach even in two-dimension. One of the major hurdles is the difficulty in representing particles in an efficient, flexible, and accurate manner. By representing particles as convex polyhedrons which are themselves the intersection of a set of half spaces, we develop a method that allows one to efficiently carry out key operations, including particle–particle and particle–container wall overlapping detection, precise identification of the overlapping region, particle shifting, particle rotation, and others. The simulation of packing 1,000 particles into a container takes only a few minutes with this approach. We further demonstrate the potential of this approach with a simulation that re-generates the “Brazil nut” phenomenon by mixing and shaking particles of two different sizes.

Lattice approaches to packed column simulations

This work presents a review of the findings into the ability of a digitally based particle packing algorithm, called DigiPac, to predict bed structure in a variety of packed columns, for a range of generic pellet shapes frequently used in the chemical and process engineering industries. Resulting macroscopic properties are compared with experimental data derived from both invasive and non-destructive measurement techniques. Additionally, fluid velocity distributions, through samples of the resulting bed structures, are analysed using lattice Boltzmann method (LBM) simulations and are compared against experimental data from the literature.

A particle packing algorithm for packed beds with size distribution

A particle packing algorithm for simulating realistic packed beds of spheres with size distribution is described. The algorithm used the Monte Carlo method combined with the simulated annealing minimisation algorithm to solve the packed bed simulations. The objective function which was minimised was a combination of two functions, one describing the deviation from the target mean coordination number of the spheres in each size interval and the other the average fraction of overlapping volume of the spheres per contact. In this way a realistic bed structure was maintained while at the same time controlling the coordination number of the spheres. The algorithm used an experimentally validated model to predict the mean coordination number of the spheres in each size interval.

Three-Dimensional Structure of a Nanocomposite Material Consisting of Two Kinds of Nanofillers and Rubbery Matrix Studied by Transmission Electron Microtomography

The three-dimensional (3D) morphology of particulate fillers embedded in a rubbery matrix was examined by transmission electron microtomography (TEMT). Two types of nanofillers, i.e., carbon black (CB) and silica (Si) nanoparticles, were used as the nanofillers. Although the CB and Si nanoparticles were difficult to distinguish by conventional transmission electron microscopy (TEM), they appeared different by TEMT; the CB and Si nanoparticles appeared to be hollow and solid particles in the cross-sectional images of the TEMT 3D reconstruction, respectively, demonstrating that TEMT itself provided a unique particle-discriminative function. The nanoparticles were found to form aggregates in the matrix. It is intriguing that each aggregate was made of only one species; not a single aggregate contained both the CB and Si nanoparticles. A particle-packing algorithm was developed to estimate the positions of each primary nanoparticle inside the aggregates.

A particle packing algorithm for pellet design with a predetermined size distribution

In this paper a particle packing algorithm is proposed which is to be used to predict the behaviour of pellets in the blast furnace on a first principal basis. Pellets consist of particles of various mineralogical composition and the structure in which they pack together to form a pellet is dependant on the size distribution of the particles and the pellet porosity. This packing structure can result in isolated volumes within the pellet where the local composition deviates from the overall average composition. This can result in, for example, melt formation at lower temperatures than expected, which will have a detrimental effect on the pellet strength. These local compositions result from the contacts between particles of different minerals and can thus be quantified by the coordination number of the particles. By using a validated coordination number model, which is unique for a particle packing algorithm, virtual pellets were created for a range of particle size distributions and porosities. The algorithm used the Monte Carlo method combined with the simulated annealing minimisation algorithm to solve the pellet simulations. The objective function is a combination of two functions, one describing the deviation from the target coordination number of the particles and the other the average fraction of overlapping volume of the particles per contact. In this way a realistic pellet structure was maintained while at the same time controlling the coordination number of the particles.