Krishna Pillai

The upscaling process of transport and adsorption of arsenic ions in rigid and homogeneous porous water filters incorporating iron oxide is carried out using the volume averaging method. As a result, two different versions of the macroscopic transport equations (referred to as the complete and simplified volume averaged models) are derived for predicting arsenic concentrations in the filters. The simplified upscaled model reflects the conventional convection-diffusion equation for studying the nonclassical mass transport problem, whereas the complete upscaled model incorporates an additional non-classical term christened as the adsorption-induced vector in this work. The order of magnitude estimates of closure variables are used to nondimensionalize the closure problems, effective coefficients, volume-averaged models, and the pore-scale model. Six scenarios were investigated by varying the dimensionless adsorption parameter (A = 0, 0.1) and the Péclet number (Pe = 10, 100, 1000). The complete volume averaged model demonstrated better accuracy than the simplified model, particularly at A = 0.1 and Pe = 1000, under the specified conditions. The numerical results also include validation of the total dispersion tensor coefficient, and exhibit the dependence of effective coefficients on the microstructure of the solid matrix and the influent flow rate via Péclet number. The average concentration profiles simulated in a two-dimensional macroscopic region using the macroscale models were validated and observed to be in very good agreement with direct numerical simulations at pore-scale level. The accuracy of the simplified upscaled model predictions was reinforced by using an analytical solution available in the literature for solving the classical convection-diffusion equation.

In porous water filters, the transport and entrapment of contaminants can be modeled as a classic mass transport problem, which employs the conventional convection–dispersion equation to predict the transport of species existing in trace amounts. Using the volume-averaging method (VAM), the upscaling has revealed two possible macroscopic equations for predicting contaminant concentrations in the filters. The first equation is the classical convection–dispersion equation, which incorporates a total dispersion tensor. The second equation involves an additional transport coefficient, identified as the adsorption-induced vector. In this study, the aforementioned equations were solved in 1D for column tests using 3D unit cells. The simulated breakthrough curves (BTCs), using the proposed micro–macro-coupling-based VAM model, are compared with the direct numerical simulation (DNS) results based on BCC-type unit cells arranged one-after-another in a daisy chain manner, as well as with three previously reported experimental works, in which the functionalized zeolite and zero-valent iron fillings were used as an adsorbent to remove phosphorous and arsenic from water, respectively. The disagreement of VAM BTC predictions with DNS and experimental results reveals the need for an alternative closure formulation in VAM. Detailed investigations reveal time constraint violations in all the three cases, suggesting this as the main cause of VAM’s failure.

To validate the experimental results of Part‐1, we conducted a two‐phase flow simulation of imbibition of a wetting liquid through 2D microstructures made of ellipses of varying aspect ratios. The flow simulation in the particulate microstructures, characterized by low (ellipse) aspect ratio, produced somewhat even micro‐fronts, thus replicating the sharp fronts at the visual (macroscopic) scale observed in Part‐1. Whereas simulations in the fibrous microstructures produced highly uneven micro‐fronts, suggesting the formation of semi‐sharp or diffuse visual fronts. Increasing the porosity from 50% to 70% resulted in solid‐phase clustering and led to further increase in the unevenness of micro‐fronts, pointing to purely diffuse visual fronts. The evolution of the saturation plots along the flow direction, obtained from area‐averaging of fluid‐distribution plots, pointed to diffusing of sharp fronts with time. The predictions matched our previous experimental and numerical observations, that is, the particulate media create sharp fronts while the fibrous media create semi‐sharp/diffuse fronts.

The fabrication of fiber-reinforced metal matrix composites (MMCs) mainly consists of two stages: infiltration and solidification, which have a significant influence on the properties of MMCs. The present study is primarily focused on the simulation of the solidification process and the effect of the active cooling of fibers with and without nickel coating for making the continuous carbon fiber-reinforced aluminum matrix composites. The thermomechanical finite element model was established to investigate the effects of different cooling conditions on the temperature profile and thermal stress distributions based on the simplified physical model. The predicted results of the temperature distribution agree well with the results of the references. Additionally, a three-dimensional cellular automata (CA) finite element (FE) model is used to simulate the microstructure evolution of the solidification process by using ProCAST software. The results show that adding a nickel coating can make the heat flux smaller in the melt, which is favorable for preventing debonding at the coating/fiber and alloy interface and obtaining a finer microstructure. In the presence of the nickel coating, the number of grains increases significantly, and the average grain size decreases, which can improve the properties of the resultant composite materials. Meanwhile, the predicting results also show that the interfaces of fiber–coating, fiber–melt, and coating–melt experience higher temperature gradients and thermal stresses. These results will lead to the phenomenon of stress concentration and interface failure. Thus, it was demonstrated that these simulation methods could be helpful for studying the solidification of fiber-reinforced MMCs and reducing the number of trial-and-error experiments.

A large set of industrial wicks made from sintered polymer beads and fibrous materials were studied. Three types of liquid fronts were observed: sharp, semi‐sharp, and diffuse. The bead‐like microstructure with lower porosity is found to support sharp fronts, while the aligned‐fiber microstructure with higher porosities leads to a smudging/diffusing of the fronts. The previously developed sharp‐front model is found to predict the front height as a function of time quite well in the sintered‐bead wicks and the two “semi‐sharp” fibrous wicks. The liquid‐front height calculated from the liquid mass‐gain data was validated through visual observations for all but the two fibrous wicks generating the diffuse fronts. These latter cases, observed to start off as a sharp fronts, faded with time.

The process of transport and trapping of arsenic ions in porous water filters is treated as a classic mass transport problem which, at the pore scale, is modeled using the traditional convection-diffusion equation, representing the migration of species present in very small (tracer) amounts in water. The upscaling, conducted using the volume averaging method, reveals the presence of two possible forms of the macroscopic equations for predicting arsenic concentrations in the filters. One is the classic convection-dispersion equation with the total dispersion tensor as its main transport coefficient, and which is obtained from a closure formulation similar to that of the passive diffusion problem. The other equation form includes an additional transport coefficient, hitherto ignored in the literature and identified here as the adsorption-induced vector. These two coefficients in the latter form are determined from a system of two closure problems that include the effects of both the passive diffusion as well as the adsorption of arsenic by the solid phase of the filter. This theoretical effort represents the first serious effort to introduce a detailed micro–macro coupling while modeling the transport of arsenic species in water filters representing homogeneous porous media.

Arsenic contamination of water sources is a global problem, affecting numerous (especially developing) countries across the world. Exposure to exorbi

A rigorous test of important theoretical models for permeability of glass‐fiber wicks, backed by numerical simulations, is conducted using a novel small‐scale experiment. The models include those for flow along and across aligned fibers and for flow through random fibers. The domains for numerical simulations were created by randomly distributed parallel fibers in a cube‐like unit‐cell using Geodict. Two separate simulations were considered: (1) Stokes‐flow solution using GeoDict, (2) Whitaker's closure‐formulation solution using COMSOL. The falling‐head parameter was adapted to measure the permeability along and across the fibers. Multiple measurements were conducted for each of the wicks to establish repeatability and estimate scatter. The permeabilities obtained through experiments matched with those from the theoretical and numerical methods. But numerical permeabilities for the longitudinal flow were exceptionally accurate. Also, the specialized models for longitudinal and transverse flows were more accurate than the random‐fiber models. © 2018 American Institute of Chemical Engineers AIChE J, 64: 3491–3501, 2018