Influence Of Particle Concentration Research Articles

Effects of cavitation and erosion on submersible drainage pumps: A numerical study

Submersible drainage pumps are used around the world both residentially and industrially for draining water and sewage. However, these pumps are prone to wear and clogging when the flows inward contain particles and air bubbles, and the combined effects of cavitation and erosion directly affect the performance of such pumps and degrade their efficiency. Therefore, it is essential to design a submersible pump that mitigates the adverse effects of cavitation and erosion. Reported here is an energy-efficient submersible drainage pump for use in emergency response. The combined cavitation–erosion effects are established in order to reduce their adverse impact on the pump, and how erosion wear affects the cavitation characteristics of the water in the pump is investigated. An experiment was conducted to verify the numerical results pump, and then, the influences of particle concentration and size on two-stage existing and altered model submersible pumps were analyzed using computational fluid dynamics. The results show that the performance of the altered model pump increased by 4.34%, with the cavitation–erosion effects reduced significantly. In addition, higher particle concentration induced higher erosion rates at both the leading and trailing edges of the impeller blades. Furthermore, the altered model significantly reduced the cavitation–erosion impact on the pump impeller blades compared to the existing model.

A prediction model of fluid–solid erosion wear in hydraulic spool valve orifice

Fluid–solid erosion wear may damage the port structure and change the linear characteristics of the spool valve. They may also affect null characteristics and the control accuracy of the valve, resulting in production and safety accidents. In the present study, the prediction model of the orifice throttling coefficient and worn profile for engineering applications such as compensation control and life degradation assessment is established. The collision probability between particles and the wall surface is particularly considered based on the E/CRC erosion wear model. The relationship between the spool opening and the impact angle of particles is investigated numerically when developing collision probability model. Meanwhile, the influence of particle concentration, spool opening, and differential pressure on the orifice throttling coefficient and worn profile is analyzed by experiments, and the microcosmic surface morphology of the spool metering edge is analyzed by scanning electron microscopy (SEM). The results show that the impacting of solid particles on the orifice will result in extrusion-thin platelets flaking wear and deformation wear. The maximum relative error between the predicted results and the experimental measurements is 2.25%. Moreover, the predicted results of the model are in good agreement with the measured values under different particle concentrations, spool openings and differential pressure.

Investigation of particle laden gravity currents using the light attenuation technique

An extensional use of the light attenuation technique is described to study the dynamics of particle laden flows. The method is validated against an analytical absorption/scattering model. It is then applied to particle laden gravity currents (PLGCs) and provides access to quantitative measurements of the particle mass fraction field. The influence of particle concentration on the turbulent dynamics of the flow and the front velocity are evaluated and discussed. In all experiments heterogeneities in the particle distribution are measured, with the maximum particle concentration in the PLGC front and intermediate particle concentration at the turbulent interface. The results highlight two regimes. In the dilute case, particles have no measurable impact on the turbulent structures observed in the flow nor on the bulk velocity. Particle sedimentation occurs due to mixing between the carrier and surrounding fluids. In the dense case, turbulent structures strongly weaken and the bulk velocity of the PLGC quantitatively decreases as the effective flow viscosity grows.

Kinetics of evaporation of colloidal dispersion drops on inclined surfaces.

Evaporation of colloidal dispersion drops leaves a deposit pattern where more particles are accumulated at the edge, popularly known as the coffee-ring effect. Such patterns formed from dried sessile drops are azimuthally symmetric. When the substrate is inclined, the symmetry of the patterns is altered due to the influence of gravity. This is reflected in the changes in (i) pinning/depinning dynamics of the drop, (ii) the strength of the evaporation-driven flows, and (iii) ultimately, the lifetime of the drop. We present a systematic investigation of the kinetics of evaporation of particle-laden drops on hydrophilic inclined solid substrates. The angle of inclination of the substrate (ϕ) is varied from 0° to 90°. The temporal analysis of the drop shape profile is carried out to unearth the contribution of different processes to kinetics of evaporation of drops on inclined surfaces. The influence of particle concentration, drop volume, and angle of inclination on the kinetics of evaporation and the resulting deposit patterns are discussed.

Heat transfer enhancement of nanofluid flow at the entry region of microtubes

A numerical investigation on laminar nanofluid flow and convective heat transfer at the entry region of microtubes subjected to constant wall temperature and constant heat flux boundary conditions has been carried out employing a multiphase Eulerian–Lagrangian method. The impacts of the Peclet number (175 ≤ Pe ≤ 3500), nanoparticle volume fraction (0.1 ≤ φ ≤ 1.0%), and nanoparticle diameter (40 ≤ dp ≤ 130 nm) on thermal characteristics of Al2O3-water nanofluid flow through a microtube are analyzed in detail. The results indicate that the influence of the Reynolds number on apparent friction factor and the impact of the axial heat conduction on the Nusselt number for the nanofluids have to take into account in the entry region. Compared with the influences of particle concentration and particle size, the entrance effect dominates pressure drop and thermal performance of the nanofluids near the entrance of the channel. As the dimensionless axial distance increases, the entrance effect is weakened, and the influences of particle concentration and particle size are gradually reflected in flow and heat transfer results. Besides, the particle effects on thermal performance of the nanofluids are earlier and higher than that on flow resistance. Performance evaluation demonstrates that the nanofluids in the entrance region have not only heat transfer enhancement but also a good economy. When Pe = 175, the PEC of Al2O3-water nanofluids with particle concentrations of 0.1, 0.2, 0.5, and 1% increased by 104.0, 103.1, 113.8, and 128.5% under constant heat flux condition, respectively, at the dimensionless axial distance x* = 0.01 compared with deionized water; the PEC improved by 74.6, 77.2, 85.6, and 102.5% under constant wall temperature condition compared with deionized water, respectively.

The influence of particle concentration and bulk characteristics on polarized oceanographic lidar measurements.

Oceanographic lidar measurements of the linear depolarization ratio, δ, contain information on the bulk characteristics of marine particles that could improve our ability to study ocean biogeochemistry. However, a scarcity of information on the polarized light‐scattering properties of marine particles and the lack of a framework for separating single and multiple scattering effects on δ have hindered the development of polarization‐based retrievals of bulk particle properties. To address these knowledge gaps, we made single scattering measurements of δ for several compositionally and morphologically distinct marine particle assemblages. We then used a bio‐optical model to explore the influence of multiple scattering and particle characteristics on lidar measurements of δ made during an expedition to sample a mesoscale coccolithophore bloom. Laboratory measurements of linear depolarization revealed a complex dependency on particle shape, size, and composition that were consistent with scattering simulations for idealized nonspherical particles. Model results suggested that the variability in δ measured during the field expedition was driven predominantly by shifts in particle concentration rather than their bulk characteristics. However, model estimates of δ improved when calcite particles were represented by a distinct particle class, highlighting the influence of bulk particle properties on δ. To advance polarized lidar retrievals of bulk particle properties and to constrain the uncertainty in satellite lidar retrievals of particulate backscattering, these results point to the need for future efforts to characterize the variability of particulate depolarization in the ocean and to quantify the sensitivity of operational ocean lidar systems to multiple scattering.

Preparation and characterization of Cu-GO and Cu-GO-YSZ nanocomposite coating by electrochemical deposition for improved mechanical and anti-corrosion properties

Graphene oxide (GO) and yttria-stabilized zirconia (YSZ) nanoparticle reinforced copper (Cu) matrix nanocomposite coatings were successfully fabricated via direct current electroplating from a copper sulfate electrolyte. Influences of particle concentration (GO/YSZ) in electrolyte, electrodeposition time and applied current density on composition, microstructural and anti-corrosion performance of Cu-GO and Cu-GO-YSZ composite coatings were explored. The corrosion behaviors were evaluated by electrochemical measurement. Results indicated the composite coatings exhibit a uniform and compact surface which was made up of stacked granules, exhibiting morphologies that nanoflake-like structures dispersed on the pyramid-like copper matrix granule clusters network. The crystallite sizes of Cu-GO first increased and then decreased as GO, time and current density increased, while it varied little for Cu-GO-YSZ composite coating. The preferred orientation of Cu matrix composite coating was oriented (220) texture. The content of incorporated GO increased with the introduction of YSZ into the Gu-GO matrix. The Gu-GO coating contains 93.3 wt% Cu and 5.5 GO, and the Gu-GO-YSZ coating contains 91.7 wt% Cu and 7.6 wt% GO. The average roughness Ra of Cu-GO and Cu-GO-YSZ were 240 ± 7 nm and 236 ± 40 nm, respectively. The addition of GO nanosheets could improve the microhardness and decrease the COF of Cu matrix. Both self-lubrication effect and load-bearing capability were improved by introducing GO and YSZ together in the Cu matrix. Deposits obtained at 30 mA cm−2, 30 min, 0.1 g L−1 GO and 10 g L−1 YSZ particles own the optimal corrosion resistance with the maximum Rp. It reveals that corrosion resistance was enhanced by the presence of GO nanosheets in Cu matrix for physical isolation effect of GO and the preferred orientation (220) plane, which benefited the formation of passive film.

Study on dispersion behavior of submicron cerium oxide particles in concentrated suspensions by ultrasonic attenuation technique

Concentrated suspensions were prepared from submicron cerium oxide particles, and particle size distribution (PSD) and zeta potential of the particles were researched by ultrasonic attenuation technology and electroacoustic theory. The influences of particle concentration, base solution and pH value on particle dispersion behavior in suspensions were analyzed. It was found that for suspensions with concentration from 10 wt% to 30 wt%, the ceria particles were dispersed most sufficiently in the suspensions with sodium hexametaphosphate (SHP), while for suspensions with concentration 40 wt%, the particles were dispersed most sufficiently in the suspensions with deionized water (DIW) only. On the other hand, the particles agglomerated most remarkably in all suspensions with sodium carboxymethyl cellulose (CMC), and they had the lowest value of zeta potential. It was deduced that higher zeta potential could be helpful for particle dispersion in these concentrated suspensions, while non-DLVO interaction and dispersing process might play important roles too.

Influence of Particle Concentration on the Elemental Penetration Region and Properties of Ni-P-SiC Composite Coatings Prepared through Sandblasting and Scanning Electrodeposition on 45 Steel Surfaces

Ni-P-SiC composite coating was prepared on 45 steel surfaces through sandblasting and scanning electrodeposition to explore the relationship between element penetration region and composite coating properties. The single-factor control variable method with particle concentration as the research variable was used. Results showed that with the gradually increasing concentration of SiC nanoparticles, a trend of first increasing and then gradually decreasing was observed for the surface and cross-sectional microstructure of the coating, interpenetration ability of the elements, adhesion performance, and corrosion resistance. The best deposition quality of the coating was obtained when the concentration of SiC nanoparticles was 3 g·L−1. For cross-sectional microstructure, the scratch test revealed that the maximum coating thickness was 17.3 μm, the maximum range of elemental penetration region was 28.39 μm, and the maximum adhesion of the composite coating was 36.5 N. The electrochemical test showed that the composite coating had a −0.30 V self-corrosion potential and 8.45 × 10−7 A·cm−2 self-corrosion current density, the slowest corrosion rate. In addition, the composite coating had the best corrosion resistance and the largest impedance arc radius corresponding to an equivalent impedance value R2 of 3108 Ω.

The Influence of Particle Concentration on the Formation of Settling-Driven Gravitational Instabilities at the Base of Volcanic Clouds

Settling-driven gravitational instabilities observed at the base of volcanic ash clouds have the potential to play a substantial role in volcanic ash sedimentation. They originate from a narrow, gravitationally unstable region called a Particle Boundary Layer (PBL) that forms at the lower cloud-atmosphere interface and generates downward-moving ash fingers that enhance the ash sedimentation rate. We use scaled laboratory experiments in combination with particle imaging and Planar Laser Induced Fluorescence (PLIF) techniques to investigate the effect of particle concentration on PBL and finger formation. Results show that, as particles settle across an initial density interface and are incorporated within the dense underlying fluid, the PBL grows below the interface as a narrow region of small excess density. This detaches upon reaching a critical thickness, that scales with (ν2/g′)1/3, where ν is the kinematic viscosity and g′ is the reduced gravity of the PBL, leading to the formation of fingers. During this process, the fluid above and below the interface remains poorly mixed, with only small quantities of the upper fluid phase being injected through fingers. In addition, our measurements confirm previous findings over a wider set of initial conditions that show that both the number of fingers and their velocity increase with particle concentration. We also quantify how the vertical particle mass flux below the particle suspension evolves with time and with the particle concentration. Finally, we identify a dimensionless number that depends on the measurable cloud mass-loading and thickness, which can be used to assess the potential for settling-driven gravitational instabilities to form. Our results suggest that fingers from volcanic clouds characterised by high ash concentrations not only are more likely to develop, but they are also expected to form more quickly and propagate at higher velocities than fingers associated with ash-poor clouds.

Statistical analysis of thermal conductivity experimentally measured in water-based nanofluids

Nanofluids are suspensions of nanoparticles in a base heat-transfer liquid. They have been widely investigated to boost heat transfer since they were proposed in the 1990s. We present a statistical correlation analysis of experimentally measured thermal conductivity of water-based nanofluids available in the literature. The influences of particle concentration, particle size, temperature and surfactants are investigated. For specific particle materials (alumina, titania, copper oxide, copper, silica and silicon carbide), separate analyses are performed. The conductivity increases with the concentration in qualitative agreement with Maxwell’s theory of homogeneous media. The conductivity also increases with the temperature (in addition to the improvement due to the increased conductivity of water). Surprisingly, only silica nanofluids exhibit a statistically significant effect of the particle size, whereby smaller particles lead to faster heat transfer. Overall, the large scatter in the experimental data prevents a compelling, unambiguous assessment of these effects. Taken together, the results of our analysis suggest that more comprehensive experimental characterizations of nanofluids are necessary to estimate their practical potential.

Employing response surface methodology and neural network to accurately model thermal conductivity of TiO2–water nanofluid using experimental data

In this research, the thermal conductivity of the H2O–titania nanofluid is modeled versus the particle concentration and temperature via the Artificial Neural Network (ANN) and Response Surface Methodology (RSM). The experimental data include six particle concentrations and five temperatures from 30 to 70 °C. The thermal conductivity augments by the increment in nanoparticle concentration and temperature, such that the maximum thermal conductivity increment happens at the highest temperature and nanoparticle concentration (i.e., T = 70 °C and φ = 1%). It is observed that the impact of temperature on the thermal conductivity is more noticeable than the influence of particle concentration, however, the thermal conductivity demonstrates a more non-linear trend versus nanoparticle volume fraction compared with the temperature. The best structure of the neural network has 2 hidden layers with 2 and 4 neurons, respectively in the 1st and 2nd hidden layers. The results show that the prediction precision of the ANN correlation is better than that of the RSM correlation.

Effective Casting Technique of Nano-Particles Alloyed Austenitic Stainless Steel

In recent decades, considerable efforts have been made in the production of steel and the modification of its microstructure on the nano-scale in order to improve its mechanical properties. One possibility is through nano-particles incorporation and reinforcement. While typical production methods for Metal Matrix nano-Composites (MMnCs) are difficult and expensive, the main drawback of the casting method is the agglomeration of the nano-particles and a poor interface between the nano-particles and the metal matrix. Therefore, the aim of this study was to investigate the potential of adding nano-particles as reinforcement elements through the conventional liquid-metal casting process. The investigation was focused on the various approaches to the modification and addition of nano-particles in the melt, as well as the influence of particle concentration and size on their homogeneity and distribution within the steel matrix. The results show that also in the case of the conventional casting process, it is possible to produce a reinforced steel-matrix nano-composite with a homogeneous distribution of the Al2O3 nano-particles in the matrix. However, in order to obtain a homogeneous distribution of nano-particles in the steel matrix, a dispersion agent is required.

Numerical analysis of dilute gas-solid flows in a horizontal pipe and a 90° bend coupled with a newly developed drag model

The influence of particle concentration on the drag force of a particle deserves attention when using the Lagrangian Particle Tracking methods for the prediction of industrial type gas-solid flows. The Lagrangian approach is best suited to applications where the solids volume fraction is low, and the effect of particle concentration can be ignored. In the present work, a 3D time dependent numerical analysis is performed to study the effect of Lagrangian model improvements to replicate experimental studies of straight horizontal pipe flow and flow through a 90° horizontal-to-vertical bend. The present predictions are compared with published experimental data of Tsuji and Morikawa (1982), and Yilmaz (1997). Special attention is paid to influence of particle mass-flow rates and conveying velocity on the particle motion within the system. This study used a CFX-4 package, where the ability to modify the code was necessary to include particle model improvements. These improvements included implementing a newly drag force model developed as a part of this research work. Particle-wall collision and particle-particle collision models developed by Sommerfeld (1992), and Sommerfeld (2001) are also implemented in the CFD model. The standard k–ε dispersed turbulence model was utilized as the predictions for the gas phase only gave similar predicted axial velocity compared to the more computationally demanding Reynolds stress model. The results showed that the inclusion of the various improvements lead to reasonable predicted particle velocities in both the upper and lower regions of the straight horizontal pipe which denote the dilute and dense regions respectively. It was also found that the inclusion of the rough-wall particle wall collision model decreases the axial particle velocity in the lower region where the bulk of the particle wall collisions occur. While the inclusion of the particle collision models tends to disperse the particles away from the lower region resulting in a less dense lower section and a distinctly more homogenous particle distribution compared with the standard model predictions. Further, the increase in particle concentration leads to a reduction in axial velocity due to a loss of momentum through particle-wall and particle-particle collisions. Finally, the improved CFD model best predicted both the reduction and increase in the particle velocities in the different regions.

Experimental and numerical study of drag forces on particles in clusters

The influence of particle concentration on the drag force of a particle deserves attention when using the Lagrangian particle tracking methods for the prediction of industrial type gas-solid flows. The Lagrangian approach is best suited to applications where the solids volume fraction is low and the effect of particle concentration can be ignored. The paper successfully predicted the available experimental findings on the effects of particle arrangements on drag force. These successful predictions lead to the development of a new coefficient of drag for particles in cluster. Then a combined experimental and numerical study of free-falling particles was carried out in this study to investigate the behaviour of particles in cluster. The new coefficient of drag proposed in this study was used in the numerical simulations. The study highlighted the increase in terminal velocities of particles within cluster streams. The numerical simulations, obtained with the newly proposed coefficient of drag, showed improved results for the average size particles used. The improvements obtained for larger particle size particles were not as impressive.

Adhesive strength and tribological behaviour of Ni–nano-Al2O3 composite coating

The present work concentrates on the influence of particle concentration of α-nano-Al2O3 particles on adhesive strength, microhardness, specific wear rate, and friction behaviour in Ni–Al2O3 composite coating. Nano-Al2O3 particles are co-deposited with electrodeposition of Ni on Al6061 substrate in the standard Watt’s bath solution. Results reveal that at an optimum concentration of 4.5 g/L particle loading for the smooth, low coefficient of friction, enhanced microhardness, and better specific wear rate of the coating. Even though the adhesive strength of coating decreased with the addition of nanoparticles in the coating, it is marginally less but can withstand the higher traction loads. The composite coating has also resulted in the better scratch and specific wear rate with homogeneous distribution of particles.

Optimisation of thermo-optical properties of SiO2/Ag–CuO nanofluid for direct absorption solar collectors

Augmenting thermal and optical properties of working fluids used in solar thermal conversion systems using hybrid nanomaterials is gaining prominence. In the present study photo-thermal analysis and thermal conductivity investigations were performed on SiO2/Ag–CuO binary water based nanofluid. The influence of particle concentration and surfactant concentration on thermo-optical properties were investigated using the design of experiment concept. Analysis of variance (ANOVA) was employed to study the significance of the process parameters on thermal conductivity and solar weighted absorption fraction of nanofluid. The statistical optimisation of the process parameters was done using the desirability function. The optimum combination of nanoparticles and surfactant that yield good thermal conductivity and solar absorption was found to be SiO2/Ag: 206.3 mg/L, CuO: 864.7 mg/L, and SDS (surfactant): 1996.2 mg/L. The optimum mass fraction of constituents yielded a relative thermal conductivity of 1.234 and solar weighted absorption fraction of 82.82%.

Double-induced se-enriched peanut protein nanoparticles preparation, characterization and stabilized food-grade pickering emulsions

The work reports a novel double-induced peanut protein isolate (PPI) nanoparticles to be perform as Pickering emulsion. The nanoparticle aggregates of PPI were formed by thermal and Na+ induced aggregation. The particle size, zeta potential, and microstructure of these aggregates were characterized by dynamic light scattering and atomic force microscopy. The size of nanoparticle aggregates was 178~260 nm and with more surface hydrophobic compared to unheated PPI. The influence of particle concentration and increasing oil fraction on the droplet size and emulsion stability was investigated. The results showed that with the nanoparticle concentration increase the emulsion droplet size slight decreased and the stability against coalescence and creaming improved. The creaming stability was progressively increased by increasing the oil fraction. The observations are generally consistent with those observed for the conventional Pickering emulsions, confirming that PPI nanoparticles could be applied as a kind of effective Pickering-like stabilizer. The finding may have important implications for the design and fabrication of protein-based emulsion formulations, and even for the development of peanut protein products with some unique functions.

Influence of particle concentration on multiple droplet formation in Pickering emulsions

HypothesisMultiphase droplets form when oil and water are mixed together at the ambivalent conditions that occur close to phase inversion. In this paper we propose a mechanism for the stabilisation of multiphase droplets by a single population of particles. ExperimentsWe investigated the microstructure of emulsions formed when dodecane and water are mixed in the presence of hydrophobic fumed silica nanoparticles. We identified the range of compositions, mixing times and rates where water-in-oil-in-water emulsions are stabilised in a single mixing step. To explore how the particle availability and mixing conditions lead to multiple emulsion formation we used light scattering and microscopy techniques to probe the size and morphology of the drops, and the particle coverage of the interfaces. FindingsOur key finding is that to stabilise multiphase drops there should be sufficient particles available to coat water drops that are entrained within coalescing oil droplets. The size of an entrained drop is determined by the volume of the rupturing film that forms between the oil drops. The particle coating prevents the entrained drop from escaping into the external aqueous phase. These results suggest a simple route for controlling the formation and stability of multiple emulsions for encapsulation applications.

Analysis of inertial migration of neutrally buoyant particle suspensions in a planar Poiseuille flow with a coupled lattice Boltzmann method-discrete element method

In this study, a hybrid numerical framework for modelling solid-liquid multiphase flow is established with a single-relaxation-time lattice Boltzmann method and the discrete element method implemented with the Hertz contact theory. The numerical framework is then employed to systematically explore the effect of particle concentration on the inertial migration of neutrally buoyant particle suspensions in planar Poiseuille flow. The results show that the influence of particle concentration on the migration is primarily determined by the characteristic channel Reynolds number Re0. For relatively low Re0 (Re0 < 20), the migration behaviour can only be observed at a very low particle concentration (≤5%). However, when Re0 > 20 the migration behaviour can be observed at a high concentration (≥20%). Furthermore, a focusing number Fc is proposed to characterise the degree of inertial migration. It was found that the inertial migration can be classified into three regimes depending on two critical values of the focusing number, Fc+ and Fc−: (i) when Fc > Fc+, a full inertial migration occurs; (ii) when Fc < Fc−, particles are laterally unfocused; and (iii) when Fc− < Fc < Fc+, a partially inertial migration takes place.