Volume Fraction Of Solid Phase Research Articles

Simulating the distribution of electrochemical characteristics: A case study of 4.35 V LiCoO2/graphite pouch cell

Understanding the relationships between electrochemical characteristics and the corresponding parameters of the battery is crucial for optimizing cell design, which creates new ideas for safe management and optimized service life of lithium-ion batteries. Herein, a pseudo two-dimensional (P2D) electrochemical model of 4.35 V prismatically wound LiCoO2 pouch cell is established and optimized to predict its electrochemical behaviors. Based on the significant factors of cell design parameters by analysis of variance, the distribution characteristics of solid and electrolyte-phase Li+ concentration, potential of solid and electrolyte-phase, over-potential and local current density are investigated and verified, which is conducive to provide quantitative guidance for battery design and optimization. Simulation results show that the change of electrolyte-phase Li+ concentration gradient is 14.3% at 1C rate, and the concentration gradient decreases with the increase of the electrolyte phase diffusion coefficient and Li+ transference number. In addition, the particle size shows a positive correlation with the surface lithium ion concentration, while the electrode thickness, solid phase volume fraction and solid phase diffusion coefficient are negatively correlated with the surface lithium ion concentration. The model indicates that the polarization of anode is more than twice as larger as than that of the cathode at 1C discharge. Moreover, simulation results demonstrate that the peak of local current density moved from the separator interface to the current collector interface as discharge proceeded, which further reveal the non-uniform distribution of the electrochemical reaction rate in the cell.

Concentrated O/W Pickering emulsions stabilized by soy protein/cellulose nanofibrils: Influence of pH on the emulsification performance

In this work, concentrated Pickering emulsions had been prepared by using soybean protein isolate (SPI) and TEMPO-oxidized bacterial cellulose (TOBC) complex as solid stabilizers. The effects of solid particle content, pH and oil phase volume fraction on the morphology, stability and rheological behaviors of the emulsions had been investigated. It indicated that the emulsion droplets had uniform particle size distribution when the ratio of SPI/TOBC was controlled to 12.5:1 (wt/wt). The emulsification performance could be improved with the increase of solid complex particles content from 1.0% to 3.0%. Moreover, the pH played an important role in regulating the structure and properties of the emulsions. With microscopic observation, the emulsions at pH 7.0 had smaller droplet size (10–15 μm) than that (15–40 μm) of the emulsions at pH 3.0. While the emulsions at pH 3.0 maintained a low creaming index (CI) value than those at pH 7.0, and uniform cellular network structure could be seen by SEM observation. It suggested that the electrostatic complexation between soy proteins and anionic bacterial cellulose nanofibrils at pH 3.0 was more favorable for stabilizing emulsions than those at pH 7.0. This work would provide some guidance for regulating the properties of emulsions that stabilized by soy protein and cellulose nanofibrils.

Disengagement of dispersed cerium oxalate from nitric-oxalic acid medium in a batch settler: Measurements and CFD simulations

The understanding of hydrodynamic characteristics and particle size distribution (PSD) of solid–liquid disengagement is crucial to design a continuous thickener for the reconversion step of nuclear fuel reprocessing. Disengagement of dispersed cerium oxalate from nitric-oxalic acid medium in a batch settler is experimentally investigated to find out solid volume fraction and PSD with different overall solid fraction followed by simulations to determine the position of active interface (AI). Eulerian-Eulerian simulations of the disengagement process were performed and the predicted solid phase volume fraction at different heights of the settler was verified using the experimental data. The predicted AI followed a good trend for different overall solid fraction. Owing to the constant particle size considered in the simulation, a difference between the predicted and measured solid phase volume fraction was observed. The predicted AI, measured solid volume fraction and PSD could aid the design of continuous thickener for nuclear fuel reconversion.

A mechanical model for phase separation in debris flow

Understanding the physics of phase separation between solid and fluid phases as a mixture mass moves down-slope is a long-standing challenge. Here, we propose an extension of a two phase mass flow model (“Pudasaini (2012), A general two-phase debris flow model, Journal of Geophysical Research, 117, F03010, doi:10.1029/2011JF002186”) by including a new mechanism, called separation-flux, that leads to strong phase separation in avalanche and debris flows while balancing the enhanced solid flux with the reduced fluid flux. The relative velocity between the phases is key in triggering the phase separation mechanism, which is induced by the effective forces that appear in the system. The novel separation-flux can be written as a product of the separation-rate, solid and fluid volume fractions, and the flow depth which amplify the separation-flux. Its magnitude is further controlled by the separation-rate-intensities which are functions of volume fractions and the density ratio. The separation-fluxes are multi-directional. One of the most important characteristics of the separation-flux is that phase separation ceases as soon as one of the components in the mixture vanishes. As the solid density approaches the fluid density, the phase separation intensity is reduced. Furthermore, as the drag increases, the phase separation decreases. The separation velocity emerges from the separation-flux as a function of the relative phase velocity, volume fraction of solid or fluid, and the respective separation-rate-intensity. The separation-rate takes into account different dominant physical and mechanical aspects of the mixture flow, such as the hydraulic pressure gradients, topography induced pressure gradients, the gradients of the volume fractions of solid and fluid phases, flow depths, grain size, densities, friction, viscosities, and buoyancy. The separation-flux mechanism is capable of describing the dynamically evolving phase separation and levee formation in a multi-phase, geometrically three-dimensional debris flow. These are often observed phenomena in natural debris flows and industrial processes that involve the transportation of particulate solid-fluid mixture material. Due to the inherent separation mechanism, as the mass moves down-slope, more and more solid particles are transported to the front and the sides, resulting in solid-rich and mechanically strong frontal surge head, and lateral levees followed by a weaker tail largely consisting of viscous fluid. The primary frontal solid-rich surge head followed by secondary fluid-rich surges is the consequence of phase separation. Such typical and dominant phase separation phenomena are revealed for two-phase debris flow simulations. Finally, changes in flow composition, that are explicitly considered by the new modelling approach, result in significant changes of impact pressure estimates. These are highly important in hazard assessment and mitigation planning and highlight the application potential of the new approach.

Thermal conductivity modeling of nanofluids with ZnO particles by using approaches based on artificial neural network and MARS

Nanofluids are attractive alternatives for the current heat transfer fluids due to their remarkably higher thermal conductivity which leads to the improved thermal performance. Nanofluids are applicable in porous media for improving their heat transfer. Proposing accurate models for forecasting this feature of nanofluids can facilitate and accelerate the design and modeling of nanofluids’ thermal mediums with porous structure. In the present study, three methods including MARS, artificial neural network (ANN) with Levenberg–Marquardt for training and GMDH are employed for thermal conductivity of the nanofluids containing ZnO particles. The confidence of the models is compared according to various criteria. It is observed that the most accurate model is obtained by using ANN with Levenberg–Marquardt followed by GMDH and MARS. R2 of the mentioned models are 0.9987, 0.9980 and 0.9879, respectively. Finally, sensitivity analysis is performed to find the importance of the input variables and it is concluded that the thermal conductivity of the base fluids has the highest importance followed by volume fraction of solid phase, size of particles and temperature.

Thermal Conductivity Modeling of Nanofluids Contain MgO Particles by Employing Different Approaches

The existence of solid-phase nanoparticles remarkably improves the thermal conductivity of the fluids. The enhancement in this property of the nanofluids is affected by different items such as the solid-phase volume fraction and dimensions, temperature, etc. In the current paper, three different mathematical models, including polynomial correlation, Multivariate Adaptive Regression Spline (MARS), and Group Method of Data Handling (GMDH), are applied to forecast the thermal conductivity of nanofluids containing MgO particles. The inputs of the model are the base fluid thermal conductivity, volume concentration, and average dimension of solid-phase, and nanofluids’ temperature. Comparing the proposed models revealed higher confidence of GMDH in estimating the thermal conductivity, which is attributed to its complicated structure and more appropriate consideration of the input’s interaction. The values of R-squared for the correlation, MARS, and GMDH are 0.9949, 0.9952, and 0.9991, respectively. In addition, based on the sensitivity analysis, the effect of thermal conductivity of the base fluid on the overall thermal conductivity of nanofluids is more remarkable compared with the other inputs such as volume fraction, temperature, and dimensions of the particles which are used as the inputs of the models.

Evaluation of microstructural and mechanical properties of AlxCrFeMnNi high entropy alloys

The aim of this work is to investigate microstructural and mechanical properties of the AlxFeNiCrMn HEAs fabricated by arc-melting method followed by annealing at 1000 °C in air. Microstructural features and phase formation of the developed alloy were examined using scanning electron microscope (SEM) and X-ray diffraction (XRD) respectively. The microhardness and compressive strength measurement were performed with a diamond base indenter and Instron compression machine. It was noticed that Al addition encouraged the formation of dendrites in the alloys with dendritic cores and interdendritic regions. The microhardness decreased from 495 HV to 397 HV with increasing Al concentration. Adjusting the Al content above 10 at% increased the ultimate strength from 1200 MPa to 1429 MPa. However, ductility was reduced which significantly lowered the total elongation by around 5%. The alloy with x = 15, displayed a good combination of high strength and ductility due to a reasonable balance in the volume fraction of BCC and FCC solid solution phases. The addition of Al is beneficial to the mechanical performance of the AlxFeNiCrMn alloy, but inadequate amounts will be counterproductive.

Effects of temperature non‐uniformity and effective viscosity on pyrometric cone deformation

AbstractPyrometric cone deformation is used to measure heat work or the combined effect of temperature and time during ceramic firing. Finite‐element analysis shows that stationary‐state temperature non‐uniformity in a pyrometric cone during constant‐rate heating can account for differences in observed endpoint temperatures at different heating rates. Thermophysical modeling provides evidence that two‐phase viscous flow plays an important role in pyrometric cone deformation. The Einstein‐Roscoe equation is used to calculate the effective viscosity of partially molten pyrometric cones during viscous flow deformation, with the solid phase volume fraction determined through thermophysical modeling and the molten phase viscosity estimated with the Modified Quasichemical Model. A correlation was found between the endpoint deformation temperatures of pyrometric cones and corresponding Littleton softening point temperatures; however, the approach fails when viscous flow is not the principal deformation mechanism and when the initial glass fraction exceeds the equilibrium molten phase fraction predicted by thermophysical modeling.

Liquid-Solid Two-Phase Purification Performance of Ship Electrostatic Oil Purifier

Ye, X.-H., Wang, J.-F., and Shi, W.-D., 2019. Liquid-solid two-phase purification performance of ship electrostatic oil purifier. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 249–254. Coconut Creek (Florida), ISSN 0749-0208.This paper aims to disclose the oil purification features of electrostatic oil purifier through micro-scale numerical simulation of the liquid-solid two-phase flow. For this purpose, the scalar potential field, Huilin-Gidaspow liquid-solid drag force and particle electrophoresis force model were integrated into the Euler-Euler model. Then, the integrated model was applied to numerically simulate the performance of electrostatic oil purifier. The simulation reveals that the solid phase removal effect of the filter element directly bears on the solid phase content in the electrostatic oil purifier; particle movement in the purifier can be intensified by increasing the electric field strength, particle diameter or solid phase volume fraction, while the rise of flow rate suppresses the removal of the solid phase; the dimensionless criteria equation, which is obtained through the dimensionless analysis of relevant quantities based on the Buckingham p theorem, can accurately depict the oil purification rate.

Coupling multi-physics simulation and response surface methodology for the thermal optimization of ternary prismatic lithium-ion battery

A 3D electrochemical-thermal coupled finite element analysis (FEA) model is established on COMSOL Multiphysics® software for 40 A h ternary prismatic lithium-ion batteries. The input parameters in this model are current C-rate C, battery thickness Thbat, initial battery ambient temperature Tint, positive porous electrode thickness Thpos, positive particle diameter Dpos, positive electrode solid phase volume fraction ε1,pos, respectively. Response surface methodology (RSM) with variance analysis (ANOVA) and parametric scanning is employed for simulating and optimizing the data obtained from the Box-Behnken experimental design based on this model. After that, the optimized parameters are verified to evaluate the reliability of the model on heat generation. The results of response surface optimization show that the optimized model error is less than 0.76% and the final temperature drops is 0.55 K. This novel model is reliable and accurate, which is helpful to improving the electrochemical and thermal performance of the battery. Also, it can provide optimized and feasible solutions for other similar kind of batteries, which offer the reference for design and optimization of the battery management system.

Package fluids. Part 5: The NaCl-H2O system in fluid inclusion research and applications of the software AqSo_NaCl (Bakker, 2018)

The software AqSo_NaCl (Bakker, 2018) can be used to characterize the properties of phases that may exist in the binary H2O-NaCl system up to 1000 °C and 500 MPa. The model replaces all available correlation equations and other equation of state that are restricted to narrow temperature, pressure, and composition intervals. Liquid-vapour, liquid-solid, and vapour-solid immiscibility fields emerge with increasing salinity at relative high temperatures, and already occur at mass fractions of a few μg per gram. The liquid-vapour immiscibility is split in two fractions in solutions between x(NaCl) = 2·10−5 and 0.00025, at salinities that cannot be detected by microthermometry. Properties such as density, molar volume, composition, and volume fraction of liquid, vapour, and solid phases in fluid inclusions can be calculated in heating and freezing experiments. Isochores can be calculated within the homogeneous fluid field, within immiscibility fields, and along the SLV (solid-liquid-vapour) curve. Iso-Th lines are obtained by modifying the total volume of fluid inclusion with the volumetric properties of quartz. Bulk properties of fluid inclusions can be directly calculated from microthermometric data.

Impact of a Maturation Procedure on the Morphological Dynamics of Si-Based Anodes for Li-Ion Batteries Characterized By I n-Situ Synchrotron X-Ray Tomography

Thanks to its theoretical capacity ten times higher than graphite (3579 mAh g-1 for Li15Si4 versus 372 mAh g-1 for LiC6), substituting graphite by silicon as anode material in lithium-ion batteries is an attractive way to increase their energy density. However, the huge volume expansion/contraction of silicon (up to ~300%) during its lithiation/delithiation causes major morphological changes of the electrode, which severely degrade its cyclability. In this communication, the dynamics of their expansion and contraction, of their cracking in the bulk and of their debonding at the interface with the current collector are characterized by in situ synchrotron X-ray computed tomography. Two electrodes made with micrometric silicon material are compared: one fabricated according to a standard process and the other one prepared with a maturation step, which consists in storing the electrode in a humid atmosphere for a few days before drying and cell assembly [1]. Various morphological parameters are quantified and followed during the first lithiation/delithiation of the electrode, namely (i) the dimensional change of the electrode, (ii) the volume fraction, size and connectivity of the segmented solid, gas and electrolyte phases, (iii) the volume fraction, size and connectivity of the produced macrocracks, (iv) the surface area of the produced delaminated zones from the current collector and (v) the variation of the Si inter-particle distances. All morphological degradations are significantly restrained for the matured electrode, confirming the great efficiency of this maturation step to produce a more ductile and resilient electrode architecture, which is at the origin of the major improvement in their cyclability. [1] C.R. Hernandez, A. Etiemble, T. Douillard, D. Mazouzi, Z. Karkar, E. Maire, D. Guyomard, B. Lestriez, L. Roué, Adv. Energy Mat. 2017, 8, 1701787. Figure 1

Buoyancy-induced convection from a pair of heated and cooled horizontal circular cylinders inside an adiabatic tilted cavity filled with alumina/water nanofluids

Purpose This paper aims to investigate numerically buoyancy-induced convection from a pair of differentially heated horizontal circular cylinders set side by side in a nanofluid-filled adiabatic square enclosure, inclined with respect to gravity so that the heated cylinder is located below the cooled one, using a two-phase model based on the double-diffusive approach assuming that the Brownian diffusion and thermophoresis are the only slip mechanisms by which the solid phase can develop a significant relative velocity with respect to the liquid phase. Design/methodology/approach The system of the governing equations of continuity, momentum and energy for the nanofluid, and continuity for the nanoparticles, is solved by a computational code based on the SIMPLE-C algorithm. Numerical simulations are performed for Al2O3 + H2O nanofluids using the average volume fraction of the suspended solid phase, the tilting angle of the enclosure, the nanoparticle size, the average nanofluid temperature and the inter-cylinder spacing, as independent variables. Findings The main results obtained may be summarized as follows: at high temperatures, the nanofluid heat transfer performance relative to that of the pure base liquid increases with increasing the average volume fraction of the suspended solid phase, whereas at low temperatures it has a peak at an optimal particle loading; the relative heat transfer performance of the nanofluid has a peak at an optimal tilting angle of the enclosure; the relative heat transfer performance of the nanofluid increases notably as the average temperature is increased, and just moderately as inter-cylinder spacing is increased and the nanoparticle size is decreased. Originality/value The two-phase computational code used in the present study incorporates three empirical correlations for the evaluation of the effective thermal conductivity, the effective dynamic viscosity and the coefficient of thermophoretic diffusion, all based on a high number of literature experimental data.

Numerical simulation of shock wave – dense particles cloud interaction using Godunov solver for Baer–Nunziato equations

PurposeThis paper aims to clarify some aspects of the application of the Godunov method for the Baer–Nunziato equations solution on the example of the problem of shock wave – dense particles cloud interaction.Design/methodology/approachThe statement of the problem corresponds to the natural experiment. Mathematical model is based on the Baer–Nunziato system of equations with algebraic right-hand side source terms that takes into account the interphase friction force. Two numerical approaches are used: Harten-Lax-van Leer method and Godunov method.FindingsFor the robust simulation using Godunov method, the application of the pressure relaxation procedure is proposed. The comparative analysis of the simulation results using two methods is carried out. The Godunov method provides significantly smaller numerical diffusion of the solid phase volume fraction in the cloud that leads to the much better agreement of the pressure curves on transducers and the dynamics of the cloud motion with the experimental data.Originality/valueGodunov method for the Baer–Nunziato equations is applied for the simulation of the natural experiment on the shock wave particles cloud interaction. Up to now, the examples of the application of the Godunov method for the Baer–Nunziato equations to the investigation of the practical problems have been limited by the works of the authors of the method and the field of detonation in the heterogeneous explosives. For the robust simulations in the presence of interphase boundaries, it is proposed to use the Godunov method together with the pressure relaxation procedure.

Functional whole wheat breads: Compelling internal architecture

In this study, X-ray micro-computed tomography scanning coupled with image analysis was used to investigate the influence of bread formulation on micro-structural characteristics of bread particularly its crumb. Results for standard whole wheat flour bread (WWB) and two functional breads formulated by partial replacement of whole wheat flour by 10% (FGF10) and 20% (FGF20) cryo-ground fermented green gram flour showed a significant variation in their micro-structural properties. For example, the total volume of bread crumb and total surface area of pores were nearly reduced by 34% in FGF10 and 71% in FGF20 samples compared to WWB. Further, height of loaf along with crumb properties: porosity, total number of pores, interconnectivity index, diameter of open pore, and volume of open pore followed the order WWB > FGF10 > FGF20. These variations have resulted in 11.85–16.75% reduction in specific loaf volume of functional breads compared to WWB. Conversely, crumb properties such as wall thickness, volume fraction of solid phase, percentage of closed pore, diameter of closed pore, and volume of closed pore showed reverse trend resulting in rise in crumb hardness of functional breads by 22.57–37.21% compared to WWB. Three-dimensional images of breads also supported the quantitative results.

Analytical solution of an Eulerian dilute particle-laden flow problem

Dilute particle-laden flows are encountered in various natural processes and manmade applications. To reduce the computational resources used to simulate such flows, the particle phase could be formulated using the Eulerian approach, resulting in a continuum hydrodynamic model. The aim of this paper is to present the analytical solution of a steady two-dimensional flow problem using that model. The dispersed solid particles, considered in this problem, are immersed in a uniform fluid flow field. The solid phase is coupled to the fluid using a linear Stokes-drag, which is valid for low slip velocities. The general solution of the solid phase velocity field is obtained by solving its quasi-linear hyperbolic momentum equations using the method of characteristics. For the case of a uniform inlet particle velocity, the solid phase velocity field is obtained in terms of Lambert W function. Subsequently, this velocity field is substituted in the solid phase continuity equation; transforming it to a semi-linear hyperbolic partial differential equation, which is solved to obtain the solid phase volume fraction field.

CFD Modeling of the Feed Distribution System of a Gas-Solid Reactor

Granular flow simulation using CFD has received a lot of attention in recent years. In such cases, CFD is either, coupled with Discrete Element Method (DEM) techniques for appropriate incorporation of inter-particle collisions, or the Eulerian CFD approach is used in which granular particles are treated as they were fluid. In the present study, a CFD analysis was performed for granular flow in an industrial screw feeder to study the choking phenomena. Eulerian multiphase flow model, also known as two-fluid model in the case of two phases, was used along with the solids closures based on Kinetic Theory of Granular Flow (KTGF). The rotating effect of the half pitch screw was incorporated by using the immersed boundary method (IMB). Variation of mass flow through change in revolution per minute (RPM) and moisture content was studied in this work. A jump condition in the axial profiles of both the solid phase volume fraction and pressure was observed near the inlet. It was found that the jump condition in solid phase volume fraction and pressure profiles reduces by increase in the RPM of the screw.

Analysis of influencing factors on suction capacity in seabed natural gas hydrate by cutter-suction exploitation

The mathematical and simulation models of working head in the deep-sea working environment were built to analyze the effects of cutter-suction flow, cutter-head rotating speed, cutting depth and suction port position on the cutter-suction capacity. The efficiency of the cutter-suction is analyzed based on the analysis of the variation law of the solid-phase volume fraction of the flow field, the variation law of the velocity distribution in the flow field and the distribution law of the solid-phase concentration. The results show that the increase of cutter-suction flow can significantly improve the cutter-suction efficiency when it is less than 1000 m3/h. However, when it is more than 1000 m3/h, it is helpless. When the cutter-head rotate speed is within the range of 10–25 r/min, the cutter-suction efficiency stabilizes at about 95%. While the speed is greater than 25 r/min, the cutter-suction efficiency decreases sharply with the increase of cutter-head rotate speed. With the increase of cutting depth, the cutter-suction efficiency first increases and then remains stable and finally decreases. The cutter-suction efficiency remains at about 94% when the suction port position deviation ranges from 0° to 30°, but it has a sharply reduction when the deviation angle is more than 30°.

Buoyancy-induced convection of water-based nanofluids from an enclosed heated cylinder

PurposeLaminar natural convection of nanofluids in a square cooled cavity enclosing a heated horizontal cylinder is studied numerically. This paper aims to investigate in what measure the nanoparticle size and average volume fraction, the cavity width, the cylinder diameter and position, the average temperature of the nanofluid and the temperature difference imposed between the cylinder and the cavity walls, affects the basic heat and fluid flow features, as well as the thermal performance of the nanofluid relative to that of the base liquid.Design/methodology/approachThe four-equation system of the mass, momentum and energy transfer governing equations has been solved using a computational code incorporating three empirical correlations for the evaluation of the effective thermal conductivity, the effective dynamic viscosity and the coefficient of thermophoretic diffusion, all based on a high number of experimental data available in the literature. The SIMPLE-C algorithm has been used to handle the pressure-velocity coupling. Simulations have been performed using Al2O3 + H2O, for different values of the average volume fraction of the suspended solid phase in the range 0-0.04, the diameter of the nanoparticles in the range 25-75 nm, the temperature difference imposed between the cylinder and the cavity walls in the range 5-20 K, the average nanofluid temperature in the range 300-330 K, the ratio between the cylinder diameter and the cavity width in the range 0.1-0.5 m, the ratio between the distance of the cylinder axis from the bottom wall and the cavity width in the range 0.2-0.8 and the ratio between the distance of the cylinder axis from the left sidewall and the cavity width in the range 0.2-0.5.FindingsThe main results obtained may be summarized as follows: the overall solid phase migration from hot to cold results in a cooperating solutal buoyancy force which tends to compensate the friction increase consequent to the viscosity growth due to the dispersion of the nanoparticles into the base fluid; the effect of the increased thermal conductivity consequent to the nanoparticle dispersion into the base fluid plays the major role in determining the heat transfer enhancement of the nanofluid, at least in the upper range of the investigated average temperatures; at high temperatures, the nanofluid heat transfer performance relative to that of the pure base liquid increases with increasing the average volume fraction of the suspended solid phase, whereas at low temperatures, it has a peak at an optimal particle loading; the relative heat transfer performance of the nanofluid increases notably with increasing the average temperature, and just moderately as the imposed temperature difference, the width of the cavity and the distance of the cylinder from the bottom of the cavity, are increased; the relative heat transfer performance of the nanofluid increases as the nanoparticle size, the cylinder diameter and the distance of the cylinder from the sidewall, are decreased; as a consequence of the local competition between the thermal and the solutal buoyancy forces, a periodic flow arises when the cylinder is located in the vicinity of one of the cooled walls of the enclosure.Originality/valueFramed in this general background, a comprehensive numerical study on buoyancy-driven convection of alumina-water nanofluids inside a cooled square cavity containing a heated circular cylinder is executed by the way of a two-phase model based on the double-diffusive approach accounting for the effects of the Brownian diffusion and thermophoresis.

Detection of fast and slow waves propagating through porous media

Porous media can support two longitudinal waves, which often overlap in time and frequency domains. Each wave has its own attenuation coefficient and phase velocity. These properties are related to volume fraction of solid phase, tortuosity, viscous characteristic length, and elasticity. Therefore, knowledge of individual wave properties is useful for characterizing porous media. Accordingly, methods for recovering separate reconstructions of fast and slow waves are of interest. The transfer function of a porous sample may be expressed as a weighted sum of two complex exponentials. The Modified Least Squares Prony’s (MLSP) method may be used to recover the two individual components for non-dispersive media. Porous media are dispersive, however. The MLSP method may be augmented with curve-fitting (MSLP + CF) to account for dispersion. An alternative approach, based on Bayesian probability theory, is also powerful for recovering fast and slow waves. These approaches have been tested in through-transmission experiments on cancellous bone samples. Bayesian and MLSP + CF approaches successfully separated fast and slow waves and provided good estimates of the fast and slow wave properties even when the two wave modes overlapped in both time and frequency domains.