Non-uniform Particle Distribution Research Articles

Crack Resistance of an Alloy of the Al – Cu – Mg – Ag System

Cyclic crack resistance of an aluminum alloy of the Al – Cu – Mg – Ag system with a high content of doping elements is studied. It is shown that the alloy possesses a high threshold value of the stress intensity factor for nucleation of fatigue cracks. However, the nonuniform distribution of second-phase particles in the material reduces the crack resistance. Special features and main differences of the relief of fatigue fracture surfaces of the alloy in various regions of the kinetic diagram are considered. Coefficients of the Paris’ equation for the region of linear fatigue-crack growth are determined.

Experimental investigations of adsorption characteristics and porosity of activated metal hydride powders

In the present work non-uniformities of microstructure, porosity and adsorption characteristics of La0.9Ce0.1Ni5 metal hydride by the height of the bed are investigated. A 500 g metal hydride bed was cycled inside a vertical metal hydride reactor and three samples was taken from top, middle and bottom of the bed. Non-uniform particle distributions and bed densification were observed, the bed porosity is around 0.58-0.67 at the top and middle parts of the bed and 0.46-0.54 at the bottom, where a dense and robust agglomerate was formed during the cycling. Specific surface area measured by nitrogen adsorption methods is 1.8-2.1 m2/g at the top of the bed, 4.2-5.4 m2/g in the middle and 1.1-1.5 m2/g at the bottom. The maximum is connected with higher degree of particle dispersion without effects from particle agglomeration.

Accurate signal reconstruction for higher order Lagrangian–Eulerian back-coupling in multiphase turbulence

Multiphase flow simulation serves a vital purpose in applications as diverse as engineering design, natural disaster prediction, and even study of astrophysical phenomena. In these scenarios, it can be very difficult, expensive, or even impossible to fully represent the physical system under consideration. Even still, many such real-world applications can be modeled as a two-phase flow containing both continuous and dispersed phases. Consequentially, the continuous phase is thought of as a fluid and the dispersed phase as particles. The continuous phase is typically treated in the Eulerian frame of reference and represented on a fixed grid, while the dispersed phase is treated in the Lagrangian frame and represented by a sample distribution of Lagrangian particles that approximate a cloud. Coupling between the phases requires interpolation of the continuous phase properties at the locations of the Lagrangian particles. This interpolation step is straightforward and can be performed at higher order accuracy. The reverse process of projecting the Lagrangian particle properties from the sample points to the Eulerian grid is complicated by the time-dependent non-uniform distribution of the Lagrangian particles. In this paper we numerically examine three reconstruction, or projection, methods: (i) direct summation (DS), (ii) least-squares, and (iii) sparse approximation. We choose a continuous representation of the dispersed phase property that is systematically varied from a simple single mode periodic signal to a more complex artificially constructed turbulent signal to see how each method performs in reconstruction. In these experiments, we show that there is a link between the number of dispersed Lagrangian sample points and the number of structured grid points to accurately represent the underlying functional representation to machine accuracy. The least-squares method outperforms the other methods in most cases, while the sparse approximation method is able to capture physically important flow features when under-sampled but at an increased cost. Interestingly, the DS method has been used in the past but in comparison to the other two methods it offers only first order convergence. The above three methods were also compared against standard linear and cubic interpolation techniques from non-uniform Lagrangian points to the Eulerian grid. The performance of these standard interpolation methods were only of the order of DS.

Broad first-order magnetic entropy change curve in directionally solidified polycrystalline Ni-Co-Mn-In

We present the thermal dependence of the magnetic entropy change ΔSM(T) across the martensitic transformation for a polycrystalline sample, which was cut from a directionally solidified rod, with a nominal composition Ni42Co8Mn38In12 grown by the Bridgman-Stockbarger technique. This material combines a first-order martensitic transformation expanded over a very large working temperature range with a large magnetization change of ∼86 A m2 kg−1. Accordingly, for a magnetic field change of 5 T (2 T), the coupled magneto-structural transition gives rise to a broad magnetic entropy change curve across the reverse martensitic transformation with a moderate maximum value of 6.8 (3.0) J kg−1 K−1 and a full-width at half-maximum δTFWHM for the ΔSM(T) curve of 49 (43) K. Such a broad structural transition may be due to the effect of chemical segregation introduced by the directional solidification which can be enhanced by the non-uniform distribution of second phase particles. Accompanying with such a wide working temperature range, a large refrigerant capacity of 334 J kg−1 was obtained for a field change of 5 T.

Sedimentation and Marangoni stress in slot coating flow of particle suspension

Slot coating is a common method in the manufacturing of a wide variety of functional films. In many applications, the coating liquid is a particle suspension and the performance of the final product is directly related to the micro structure of the film. Fundamental understanding of the suspension flow enables a better control of the particle distribution on the coated layer and, consequently, on the coating process and product performance optimization. A common simplified approach to study coating flow of non-colloidal particle suspension is to consider that the particles are uniformly distributed in the coating bead and that the liquid viscosity is constant and equal to the value of the bulk concentration. However, experimental evidences have shown that shear-induced migration leads to non-uniform particle distribution. The literature presents numerical predictions on surface inactive, neutrally buoyant particle suspension flow which have shown that particle distribution in the coated layer strongly depends on the process conditions. Here, we extend the previous analyses to explore the effect of different process conditions, including the effect of particle sedimentation and Marangoni stresses caused by surface-active particles. Results show how particle distribution changes with flow conditions and particle properties, and that Marangoni stresses can change the recirculation pattern of the flow.

Iterative load-balancing method with multigrid level relaxation for particle simulation with short-range interactions

We developed dynamic load-balancing algorithms for Particle Simulation Methods (PSM) involving short-range interactions, such as Smoothed Particle Hydrodynamics (SPH), Moving Particle Semi-implicit method (MPS), and Discrete Element method (DEM). These are needed to handle billions of particles modeled in large distributed-memory computer systems. Our method utilizes flexible orthogonal domain decomposition, allowing the sub-domain boundaries in the column to be different for each row. The imbalances in the execution time between parallel logical processes are treated as a nonlinear residual. Load-balancing is achieved by minimizing the residual within the framework of an iterative nonlinear solver, combined with a multigrid technique in the local smoother. Our iterative method is suitable for adjusting the sub-domain frequently by monitoring the performance of each computational process because it is computationally cheaper in terms of communication and memory costs than non-iterative methods. Numerical tests demonstrated the ability of our approach to handle workload imbalances arising from a non-uniform particle distribution, differences in particle types, or heterogeneous computer architecture which was difficult with previously proposed methods. We analyzed the parallel efficiency and scalability of our method using Earth simulator and K-computer supercomputer systems.

Enhancement of High-Density Polyethylene Properties by Impregnation with Inorganic Alumina Filler

The influence of filler size and content on the mechanical and rheological properties (thermal conductivity, impact strength, hardness and melt flow index (MFI) of Al 2 O 3 /high-density polyethylene (HDPE) composites have been studied. Concentration of alumina was varied up to 30% by weight. The composites were prepared using a two-roll mill and then test specimens were prepared by injection molding. Thermal conductivity, hardness, impact strength and melt flow rate of the composites increased with decreased particle sizes and increased particle content with exceptions at certain concentrations due to non-uniform distributions of particles and agglomerates formed by the particles. As an example, the best integrated thermal conductivity was shown by a 75 micron-Al 2 O 3 /HDPE composite at 15% wt. alumina content, while the 212 micron- Al 2 O 3 /HDPE composite at 20 wt.% alumina content. For the same alumina content of 15% concentration by weight out of the three particle sizes. 75, 212 and 850 microns, the 75 micron-Al 2 O 3 /HDPE composite gave the highest thermal conductivity, which was nearly 50% higher than that of pure HDPE. Enhancement in impact strength and Hardness Rockwell were up to 300% and 400% as compared to the pure HDPE respectively. The Al 2 O 3 with small particle size is generally more efficient for the enhancement of the impact strength.

Particle-grain boundary interactions: A phase field study

A detailed phase field model is used to investigate particle-grain boundary interactions. The model takes into consideration both the curvature-driven grain boundary motion and particle migration by surface diffusion. The phase field model relaxes all the restrictive assumptions usually employed in the classical and sharp-interface models of the problem. Our 2D and 3D simulations demonstrate that the model captures all possible particle-grain boundary interactions proposed in theoretical models and observed in experiments. For high enough surface mobility, the particles move along with the migrating boundary as a quasi-rigid-body (i.e., without change in shape or size), albeit hindering its migration rate as compared to the particle-free case. For less mobile particles, the migrating boundary can separate from the particles. For the case of steady-state motion of the particles with the migrating boundary, evolution equations for the grain size were derived that predict a strong dependence of the grain growth rate on the number of particles, particle size, and surface diffusivity. For the case of boundary breakaway, the separation condition was found to agree well with predictions from theoretical calculations. However, our results show that non-uniform particle distribution promotes boundary detachment. The results also demonstrate that it is easier for a migrating boundary to separate from a spherical particle than from a cylindrical particle, and hence 2D simulations underestimate boundary breakaway.

Improvement of moving particle semi‐implicit method for simulation of progressive water waves

SummaryPrecise simulation of the propagation of surface water waves, especially when involving breaking wave, takes a significant place in computational fluid dynamics. Because of the strong nonlinear properties, the treatment of large surface deformation of free surface flow has always been a challenging work in the development of numerical models. In this paper, the moving particle semi‐implicit (MPS) method, an entirely Lagrangian method, is modified to simulate wave motion in a 2‐D numerical wave flume preferably. In terms of consecutive pressure distribution, a new and simple free surface detection criterion is proposed to enhance the free surface recognition in the MPS method. In addition, a revised gradient model is deduced to diminish the effect of nonuniform particle distribution and then to reduce the numerical wave attenuation occurring in the original MPS model. The applicability and stability of the improved MPS method are firstly demonstrated by the calculation of hydrostatic problem. It is revealed that these modifications are effective to suppress the pressure oscillation, weaken the local particle clustering, and boost the stability of numerical algorithm. It is then applied to investigate the propagation of progressive waves on a flat bed and the wave breaking on a mild slope. Comparisons with the analytical solutions and experimental results indicate that the improved MPS model can give better results about the profiles and heights of surface waves in contrast with the previous MPS models. Copyright © 2017 John Wiley & Sons, Ltd.

Mathematical and experimental investigation on pressure drop of heterogeneous ice slurry flow in horizontal pipes

Ice slurry as an advanced secondary refrigerant has attracted much attention due to the growing concern about energy shortage and environment protection. To promote the practical applications of ice slurry, an extensive knowledge of the pressure drop of ice slurry flow in pipes is beneficial. The available research mainly focuses on the pressure drop of ice slurry flow without considering the non-uniform distribution of ice particles within. Furthermore, the impact of the carrier fluid and ice particles on the pressure drop of ice slurry is not well documented. This investigation combined numerical, analytical and experimental methods to analyze the distributions of concentration, velocity and pressure drop in heterogeneous ice slurry flow. An analytical pressure drop model was developed based on multiphase flow dynamics to quantify the pressure drop of each phase of ice slurry flow. Experiments for laminar and turbulent ice slurry flow in horizontal pipes were used to evaluate the proposed model. The analysis revealed good agreement between the proposed model and experimental data. Moreover, the proposed analytical model is computationally efficient, which can be applied to estimate the pressure drop of ice slurry flow for most practical applications.

Spectral analysis of energy transfer in turbulent flows laden with heated particles

In this study we consider particle-laden turbulent flows with significant heat transfer between the two phases due to sustained heating of the particle phase. The sustained heat source can be due to particle heating via an external radiation source as in the particle-based solar receivers or an exothermic reaction in the particles. Our objective is to investigate the effects of fluid heating by a dispersed phase on the turbulence evolution. An important feature in such settings is the preferential clustering phenomenon which is responsible for non-uniform distribution of particles in the fluid medium. Particularly, when the ratio of particle inertial relaxation time to the turbulence time scale, namely the Stokes number, is of order unity, particle clustering is maximized, leading to thin regions of heat source similar to the flames in turbulent combustion. However, unlike turbulent combustion, a particle-laden system involves a wide range of clustering scales that is mainly controlled by particle Stokes number. To study these effects, we considered a decaying homogeneous isotropic turbulence laden with heated particles over a wide range of Stokes numbers. Using a low-Mach-number formulation for the fluid energy equation and a Lagrangian framework for particle tracking, we performed numerical simulations of this coupled system. We then applied a high-fidelity framework to perform spectral analysis of kinetic energy in a variable-density fluid. Our results indicate that particle heating can considerably influence the turbulence cascade. We show that the pressure-dilatation term introduces turbulent kinetic energy at a range of scales consistent with the scales observed in particle clusters. This energy is then transferred to high wavenumbers via the energy transfer term. For low and moderate levels of particle heating intensity, quantified by a parameter $\unicode[STIX]{x1D6FC}$ defined as the ratio of eddy time to mean temperature increase time, turbulence modification occurs primarily in the dilatational modes of the velocity field. However, as the heating intensity is increased, the energy transfer term converts energy from dilatational modes to divergence-free modes. Interestingly, as the heating intensity is increased, the net modification of turbulence by heating is observed dominantly in divergence-free modes; the portion of turbulence modification in dilatational modes diminishes with higher heating. Moreover, we show that modification of divergence-free modes is more pronounced at intermediate Stokes numbers corresponding to the maximum particle clustering. We also present the influence of heating intensity on the energy transfer term itself. This term crosses over from negative to positive values beyond a threshold wavenumber, showing the cascade of energy from large scales to small scales. The threshold is shown to shift to higher wavenumbers with increasing heating, indicating a growth in the total energy transfer from large scales to small scales. The fundamental energy transfer analysis presented in this paper provides insightful guidelines for subgrid-scale modelling and large-eddy simulation of heated particle-laden turbulence.

Coherent spherical range-search for dynamic points on GPUs

We present an approach to accelerate spherical range-search (SRS) for dynamic points that employs the computational power of many-core GPUs. Unlike finding kapproximate nearest neighbours (ANNs), exact SRS is needed in geometry processing and physical simulation to avoid missing small features. The spatial coherence of query points and the temporal coherence of dynamic points are exploited in our approach to achieve very efficient range-search on AABB-trees. We test our coherent SRS in several applications including point-point-set geometry processing, distance-field generation and particle-based simulation, which are best scenarios to present the spatial and the temporal coherence of spherical queries on dynamic points. On a PC with NVIDIA GTX 660 Ti GPUs, our approach can take 1M queries on 1M dynamic points at a rate of 1600 queries/ms, where 49 neighbours are found on average within the range of 1/100 of the bounding-box’s diagonal length. We observe an increase of up to 4x compared with conventional voxel-based GPU searching approaches in the benchmark of particle-based fluid simulation. Moreover, the speedup can be scaled up to 150x when being applied to highly non-uniform distribution of particles in the simulation.

BTW Model with Probabilistically Nonuniform Distribution of Particles Coming from the Unstable Sites

BTW Model with Probabilistically Nonuniform Distribution of Particles Coming from the Unstable Sites

Microstructural stability of in-situ TiB2/Al composite during solution treatment

The microstructural stability including grain growth and texture of in-situ TiB2/Al composite during solution treatment (ST) at T4 state (natural aging) was investigated for the first time. The results show that the nano TiB2 particles have a strong influence on the stability of grain size (GS) and textures during ST. The composite has exhibited improved stability of GS attributing to the Zener pinning of TiB2 particles, resulting in no obvious increase in GS after the ST for 24h. A modified Zener equation has been proposed for the composite with non-uniform particle distribution, which can make a good prediction on the limiting GS. For textures of the 2024 alloy and TiB2/2024 composite, there is not much difference in the intensity of 〈111〉 fiber before the ST, while the 〈l00〉 fiber is stronger in the composite. The 〈111〉 and 〈l00〉 double fibers of the composite are stabilized by TiB2 particles during ST at T4 state. However, the 〈111〉 and 〈100〉 fibers of the alloy are gradually replaced by 〈113〉, 〈102〉 and 〈302〉 ones due to the recrystallization and grain growth. Accordingly, the composite exhibits much stronger fiber textures than the alloy after the heat treatment.

Particle transport characteristics in indoor environment with an air cleaner: The effect of nonuniform particle distributions.

Air cleaners are expected to improve the indoor air quality by removing the gaseous contaminants and fine particles. In our former work, the effects of the air cleaner on removing the uniformly distributed particles were numerically investigated. Based on those results, this work further explores the performances of the air cleaner in the reduction of two nonuniform particle distributions generated by smoking and coughing. The Lagrangian discrete trajectory model combined with the Eulerian fluid method is employed to simulate the airflow pattern and particle transport in a room. In general, the results show that the particle fates have been resulted from the interaction between the emitting source and the air cleaner. And the position of the air cleaner is a key parameter affecting the particle concentration, for which a shorter distance between the air cleaner and the human body corresponds to a lower concentration. Besides, the air velocity emitted from the human mouth and the orientation of the air cleaner can also influence the transport of particles.

Algorithm 967

The solution of a constant-coefficient elliptic Partial Differential Equation (PDE) can be computed using an integral transform: A convolution with the fundamental solution of the PDE, also known as a volume potential. We present a Fast Multipole Method (FMM) for computing volume potentials and use them to construct spatially adaptive solvers for the Poisson, Stokes, and low-frequency Helmholtz problems. Conventional N-body methods apply to discrete particle interactions. With volume potentials, one replaces the sums with volume integrals. Particle N-body methods can be used to accelerate such integrals. but it is more efficient to develop a special FMM. In this article, we discuss the efficient implementation of such an FMM. We use high-order piecewise Chebyshev polynomials and an octree data structure to represent the input and output fields and enable spectrally accurate approximation of the near-field and the Kernel Independent FMM (KIFMM) for the far-field approximation. For distributed-memory parallelism, we use space-filling curves, locally essential trees, and a hypercube-like communication scheme developed previously in our group. We present new near and far interaction traversals that optimize cache usage. Also, unlike particle N-body codes, we need a 2:1 balanced tree to allow for precomputations. We present a fast scheme for 2:1 balancing. Finally, we use vectorization, including the AVX instruction set on the Intel Sandy Bridge architecture to get better than 50% of peak floating-point performance. We use task parallelism to employ the Xeon Phi on the Stampede platform at the Texas Advanced Computing Center (TACC). We achieve about 600 gflop /s of double-precision performance on a single node. Our largest run on Stampede took 3.5s on 16K cores for a problem with 18 e +9 unknowns for a highly nonuniform particle distribution (corresponding to an effective resolution exceeding 3 e +23 unknowns since we used 23 levels in our octree).

Fracture mechanical model for tensile strength of particle reinforced elastomeric composites

The tensile strength of particle reinforced elastomeric composites (PRECs) was studied as functions of the particle volume content (loading) and particle size. The measured tensile strength increased with increasing particle loading and decreased with increasing particle size. The measured fracture toughness increased with increasing particle size. A fracture mechanical model to predict the tensile strength was developed to better understand the reinforcing effects of the particle and to provide a criterion for a better composite. Using a body center cubic (BCC) crystal system, the elastic energies of the undamaged and damaged cells were obtained. The tensile strength as a function of the measured fracture toughness (J value) and the modulus of the matrix can be calculated by comparing the energies. The predicted tensile strength decreased with increasing particle size in a similar manner to the experimental results. The analytical model predicted that the size of the poor interface up to 30° of the debonded angle on the tensile strength becomes less severe as the particle size is decreased. In addition, the specimen with smaller particles (<30 µm) should have a higher tensile strength than that of the experimentally measured values. The conglomeration and non-uniform distribution of smaller particles, and the entrapped void within the agglomerates while mixing and fabricating can be one reason.

Investigation of the mechanical properties of electrodeposited nickel and magnetron sputtered chromium nitride coatings deposited on mild steel substrate

Electrodeposition and magnetron sputtering techniques have been employed for the deposition of Ni and bilayer NiCrN coatings, respectively, on mild steel substrate. Ni electrodeposition was performed using sulfate Watt’s bath, while magnetron sputtering was performed on electrodeposited Ni using DC power 350 W and base pressure of 3 × 10−5 Torr in order to prepare bilayer NiCrN coatings. Structural and mechanical properties of Ni and bilayer NiCrN coatings have been investigated using various characterization techniques such as SEM-EDX, XRD, hardness, adhesion testing, etc. SEM analysis reflects the formation of spherical/nodular particles of varying sizes in NiCrN coating whereas Ni coating shows irregular, agglomerated, and non-uniform distribution of particles. Formation of hard CrN phase in NiCrN coating has been confirmed by XRD and EDX. NiCrN coating exhibits better hardness in comparison with Ni coating due to the formation of nitride phase. Micro scratch testing of bilayer NiCrN coating shows better interlayer adhesion and adhesion with mild steel substrate. The combination of electrodeposition and magnetron sputtering can produce inexpensive NiCrN coating containing hard CrN phase with better mechanical properties for automotive applications.

Measurement of Thermal and Electrical Properties of Multiwalled Carbon Nanotubes–Water Nanofluid

The use of high conductive nanoparticles, such as carbon nanotubes (CNT), enhances the thermal and electrical conductivities of the carrier fluid. Depending upon the volumetric concentration of particles and their distribution in the carrier fluid, multifold enhancement of thermal and electrical properties is possible. Therefore, in the present study, thermal and electrical properties of CNT–water mixture are assessed at microscopic level. Special distribution of the CNT in water is obtained experimentally at microscale for different durations of the heating situation. Thermal and electrical properties are predicted numerically incorporating the particle distributions obtained from the experiment. The mass based analysis is also introduced to determine the thermal properties of the mixture. The findings are compared for those obtained from the simulations based on experimentally obtained micro-images. Algebraic equations are introduced to formulate the data obtained from the simulations for temperature dependent properties. It is demonstrated that the mass based estimation of thermal properties are significantly different than those obtained from the experimental based simulations because of the nonuniform particles distribution and their localized conductivity in the carrier fluid.

Transformation of cast A356 ingots to wrought sheets with enhanced mechanical and tribological properties by different thermo-mechanical processing routes

The dendritic microstructure with non-uniform distribution of hard second phase particles degrades the mechanical and tribological properties of AlSi alloys. Severe plastic deformation methods are found effective in refining microstructure and enhancing the material properties. In our present study, two different thermo-mechanical processing routes were employed on a cast hypo-eutectic AlSi alloy to produce wrought sheets with refined microstructure. In one processing route, the material is subjected to cryorolling after solution treatment and in the other route, the material is subjected to a thermal-treatment between solution treatment and cryorolling. Cryorolling imposes severe plastic deformation onto the material resulting in refinement and redistribution of second phase particles leading to enhanced strength and ductility. Cryorolling with pre-roll thermal-treatment resulted in finer grain structures than the material without thermal-treatment. The tribological behaviour of processed materials are studied and compared with the base materials by pin-on-disk method. Maximum wear resistance is observed in thermal-treated material followed by cryorolled material with pre-roll thermal-treatment. Transformation from adhesion wear to oxidative-delamination wear is found to be the primary reason for the enhanced wear resistance in thermal-treated material. The various wear mechanisms involved are explained in detail based on the microstructural evolution and mechanical properties.