Simulation Of Mass Transfer Research Articles

Comprehensive study on copper adsorption using an innovative graphene carbonate sand composite adsorbent: Batch, fixed-bed columns, and CFD modeling insights

This study focused on an innovative graphene carbonate sand composite adsorbent, synthesized from carbonated porous sand and sucrose as raw materials, for the removal of copper ions via the adsorption process. The characteristics of this adsorbent are determined through comprehensive experiments and numerical simulations in batch and fixed-bed column conditions, which has not been extensively explored. Extensive experimentation demonstrated a remarkable 100 % removal efficiency under optimal conditions, which included a copper ion concentration of 3 g/L, a contact time of 10 h, and an adsorbent dosage of 35 g/L. The adsorption kinetics and isotherm results exhibited that the Elovich model (R² = 0.998) and the Langmuir model (R² = 0.996 for linear with qm=123.91 mg g-1, and R² = 0.993 for nonlinear fitting) more effectively described the adsorption of copper onto the adsorbent. In the fixed-bed column studies, among the well-known analytical models, the Log-Gompertz model showed better compatibility (R2 = 0.97∼0.99) between breakthrough curves with experimental results for various copper inlet concentrations. Also, numerical results obtained using computational fluid dynamics and mass transfer simulations with the linear driving force model were successfully validated by experimental results, particularly in the initial and transition zones of the breakthrough curve.

Comparative Analysis and Application of Mass and Heat Transfer Simulation in Fractured Reservoirs Based on Two Fracture Models

The projection-based embedded discrete fracture model (pEDFM) and its counterpart, the embedded discrete fracture model (EDFM), have become standard tools for the depiction of the fractures in reservoir simulations. Despite their widespread use, there are still some unclear areas in modeling the complex processes of mass and heat transfer within fractured reservoirs, particularly in both single-phase and multiphase flow scenarios. Our research introduces a numerical methodology for simulating the mass and heat transfer in fractured reservoirs which is developed by extending the framework of the pEDFM and EDFM. To gauge the effectiveness of these models, we devised two cases which were designed to evaluate the adaptability of the pEDFM and EDFM in scenarios involving an ultra-low permeability fracture or a high permeability fracture under single-phase and multiphase conditions. By using local grid refinement (LGR) as a reference, the results of the pEDFM were in reasonably good agreement with the LGR in terms of pressure, temperature, and saturation distributions. This comparison suggests that the pEDFM has a significant advantage in depicting the mass and heat transfer at the matrix–fracture interface compared to the EDFM. Furthermore, a comprehensive analysis of the flow trajectories in both the pEDFM and EDFM provided a reasonable explanation for their differences. Furthermore, the numerical applications involving the heat extraction of Enhanced Geothermal Systems (EGSs) and the water flooding in fractured reservoirs illustrate the adaptability of the pEDFM in the numerical simulation for complex geological conditions. The insights and conclusions obtained in this paper can enhance our understanding of the distinctions between the pEDFM and EDFM, aiding in the selection of the most suitable method for characterizing the fractures in numerical simulations.

Real Case Study of 600 m3 Bubble Column Fermentations: Spatially Resolved Simulations Unveil Optimization Potentials for l-Phenylalanine Production With Escherichia coli.

Large-scale fermentations (»100 m³) often encounter concentration gradients which may significantly affect microbial activities and production performance. Reliably investigating such scenarios in silico would allow to optimize bioproduction. But related simulations are very rare in particular for large bubble columns. Here, we pioneer the spatially resolved investigation of a 600 m³ bubble column operating for Escherichia coli based l-phenylalanine fed-batch production. Microbial kinetics are derived from experimental data. Advanced Euler-Lagrange (EL) computational fluid dynamics (CFD) simulations are applied to track individual bubble dynamics that result from a recently developed bubble breakage model. Thereon, the complex nonlinear characteristics of hydrodynamics, mass transfer, and microbial activities are simulated for large scale and compared with real data. As a key characteristic, zones for upriser, downcomer, and circulation cells were identified that dominate mixing and mass transfer. This results in complex gradients of glucose, dissolved oxygen, and microbial rates dividing the bioreactor into sections. Consequently, alternate feed designs are evaluated splitting real feed rates in two feeds at different locations. The opposite reversed installation of feed spots and spargers improved the product synthesis by 6.24% while alternate scenarios increased the growth rate by 11.05%. The results demonstrate how sophisticated, spatially resolved simulations of hydrodynamics, mass transfer, and microbial kinetics help to optimize bioreactors in silico.

Integrated neural network based simulation of thermo solutal radiative double-diffusive convection of ternary hybrid nanofluid flow in an inclined annulus with thermophoretic particle deposition

Numerical simulation of magnetohydrodynamic radiative double-diffusive convective heat and mass transfer of a ternary hybrid nanofluid with thermophoretic particle deposition in an inclined annulus is studied. Both sides of cylinders are preserved at uniform temperatures, while the remaining sides are thermally insulated. The coupled nonlinear partial differential equations are solved using a finite difference approach. The detailed computational results of heat and mass transfer rate, temperature, concentration and flow fields are presented and discussed for a distinct range of significant physical parameters. The results demonstrated that increasing the angle of the inclination factor increases fluid flow. In light of buoyancy, when the annular cavity is set downward, the enhanced shear velocity is transported upwards, where it reaches its optimal temperature. The higher temperature difference leads to augmented dynamic fluid motion, particularly in the radial direction, as the system seeks to balance the thermal energy through convective transfer. The Brownian motion parameter has abrupt mobility of nanoparticles in liquid, which promotes particle collisions with liquid molecules, yielding kinetic energy. Increased values of thermophoretic parameters augment the thermophoresis force. Thermophoretic particle deposition increases the concentration of nanoparticles in an annulus due to the migration of particles from hot to cold regions under the influence of temperature gradient. The heat and mass transfer characteristics of ternary hybrid nanofluid are forecasted through an artificial neural network-based Levenberg–Marquardt backpropagated algorithm. The built model shows the heat and mass transfer rate root mean squared values through the Levenberg–Marquardt algorithm as one and mean squared error values as 1e-07 and 1e-08 respectively.

Physical and numerical simulation of heat and mass transfer in the furnace of a thermogravimetric analyzer

A numerical study of the processes of heat and mass transfer in the furnace of a thermogravimetric analyzer was carried out, aimed at improving the accuracy of determining the kinetic characteristics of samples during their thermal transformations in different media. Validation of the model and prognostic estimates were carried out in relation to specially conducted thermogravimetric studies of the conversion of fossil and renewable carbon-containing raw materials in successive processes of decarbonization (combustion) and carbonation (mineralization of ash residue). The application of the study results allows to calculate the actual concentrations of the reagent over the sample uncontrolled by the device during pulsed switching of media and the actual temperatures of the sample during its thermochemical transformations.

Numerical simulation of heat and mass transfer through hybrid nanofluid flow consists of polymer/CNT matrix nanocomposites across parallel sheets

The hybrid nanofluid (Hnf) flow with heat and mass transmission under the magnetic field and activation energy consequences across parallel double-rotating surfaces has been studied. In order to synthesize the Hnf, polymer/CNT matrix nanocomposites (MNCs) are dissolved in water. Polymer/CNT MNCs are highly efficient and have exceptional properties. These MNCs are helpful in various applications, from engineering to biomedical research, because of their incredible thermophysical properties. Keeping in view the significant uses of the polymer/CNT MNC hybrid nanofluid flow, we have formulated the fluid flow in the form of the system of PDEs (partial differential equations), which are reformed into the non-dimensional form of ODEs (ordinary differential equations) and then solved numerically through the Matlab package (bvp4c). The numerical outputs for velocity, heat and mass profiles are compared with another numerical approach ND-solve. It has been determined that the outputs are precisely correct and reliable. Furthermore, the fluid velocity drops with the influence of suction/injection, Reynold number, and polymer/CNT MNC. The increasing quantity of polymer/CNT MNC in water reduces the energy and mass profiles. The energy field enhances with the upshot of the heat source term, whereas the concentration field falloffs with the effect of Schmidt number.

Remarkable mass-transfer enhancement via constructing ordered framework structure by 3D-priniting strategy for stable pesticides removal

Heterogeneous electro-Fenton (HEF) processes are potential pathways for aquatic contaminants removal. However, synergies from catalysts dense accumulation, the sluggish inner diffusion and the loss of active sites inside the catalyst, have limited the practical application of traditional monolithic cathodes. In this work, it has been proofed that the highly controlled porosity in 3D-printed ordered framework shows obvious diffusion enhancement and offers more active sites. The stable and efficient HEF catalysts guarantee the removal and mineralization of aqueous pesticides. H2O2 is effectively generated in situ via 2-electron oxygen reduction reaction by the carbon lattice in the pH range of 4–10, which is then activated into hydroxyl radicals by the encapsulated Fe2P/Fe in 3D printed cathodes. Estimated by the mass-transfer simulation, the Grid structure has the largest convective transport velocity of 8 × 10-5 m∙s-1, which optimizing mass-transfer effect and maximizing the active sites utilization. Grid-2 % achieves 3.54 ± 0.05 mg∙g-1 napropamide degradation at neutral condition in one hour, which is 82 % and 269 % higher than degradation obtained by Star-2 % and Diamond-2 %, respectively.

Radiation hydrodynamical simulations of super-Eddington mass transfer and black hole growth in close binaries

ABSTRACT Radiation-driven outflows play a crucial role in extracting mass and angular momentum from binary systems undergoing rapid mass transfer at super-Eddington rates. To study the mass transfer process from a massive donor star to a stellar-mass black hole (BH), we perform multidimensional radiation-hydrodynamical simulations that follow accretion flows from the first Lagrange point down to about a hundred times the Schwarzschild radius of the accreting BH. Our simulations reveal that rapid mass transfer occurring at over a thousand times the Eddington rate leads to significant mass-loss from the accretion disc via radiation-driven outflows. Consequently, the inflow rates at the innermost radius are regulated by two orders of magnitude smaller than the transfer rates. We find that convective motions within the accretion disc drive outward energy and momentum transport, enhancing the radiation pressure in the outskirts of the disc and ultimately generating large-scale outflows with sufficient energy to leave the binary. Furthermore, we observe strong anisotropy in the outflows, which occur preferentially toward both the closest and furthest points from the donor star. However, when averaged over all directions, the specific angular momentum of the outflows is nearly comparable to the value predicted in the isotropic emission case. Based on our simulation results, we propose a formula that quantifies the mass growth rates on BHs and the mass-loss rates from binaries due to radiation-driven outflows. This formula provides important implications for the binary evolution and the formation of merging binary BHs.

Mass transfer at vapor-liquid interfaces of H2O + CO2 mixtures studied by molecular dynamics simulation

Abstract In many industrial applications as well as in nature, the mass transfer of CO2 at vapor-liquid interfaces in aqueous systems plays an important role. In this work, this process was studied on the atomistic level using non-equilibrium molecular dynamics simulations. In a first step, a molecular model of the system water + CO2 was developed that represents both bulk and interfacial equilibrium properties well. This system is characterized by a very large adsorption and enrichment of CO2 at the vapor-liquid interface. Then, non-equilibrium mass transfer simulations were carried out using a method that was developed recently: CO2 is inserted into the vapor phase of a simulation box which contains a liquid slab. Surprising effects are observed at the interface such as a net repulsion of CO2 particles from the interface and a complex time dependence of the amount of CO2 adsorbed at the interface.

Enhanced mass transfer by 3D printing to promote the degradation of organic pollutants in electro-Fenton system

In this study, researchers constructed a monolithic 3D-FeO/C electrode with a macro-ordered pore structure using direct-write 3D printing technology. Experimental results showed that the 3D-FeO/C electrode possessed excellent degradation performance for ornidazole (ONZ) (complete degradation within 120 min) and pharmaceutical wastewater (51.13 % in TOC and 63.72 % in COD removal within 420 min). The detailed reaction mechanism of the EF system was revealed through characterization analysis, mass transfer simulation, and experimental results, in which the excellent EF performance is mainly due to the confinement effect of FeO active sites encapsulated in the carbon layer, as well as the enhancement of mass transfer induced by 3D printing macro-ordered structure network. In addition, the degradation pathway of ONZ, the toxicity of its degradation intermediates, and the degradation pathway of actual pharmaceutical wastewater were revealed in detail. This study proposes a new 3D printing method to enhance the mass transfer of electrode materials in EF systems, which has good potential for application to real wastewater.

Numerical mass transfer simulations of Venturi-type solid phase oxygen control with mass exchanger in UPBEAT loop

The Venturi-type solid-phase oxygen control system with a bypass mass exchanger is widely regarded as an effective approach to keep the oxygen concentration in the LBE under reasonable ranges to reduce the corrosion. In this work, numerical simulations of the particle–fluid mass transfer of the oxygen concentration in LBE are performed for the 1:1 scale 3D UPBEAT loop under various conditions. The discrete element method is applied to generate the geometry of the packing of the PbO spheres. The velocity profile and oxygen concentration governing equations are solved by using the SST turbulence model. At the same temperature, the oxygen mass transfer coefficient increases monotonically with the flow rate. At the same mass flow rate, the mass transfer coefficient increases with the temperature, reaching a maximum at about 475 °C. It provides guidance for future research in the design and optimization of oxygen control systems under high temperature in lead–bismuth nuclear reactors.

Numerical modeling of mixed convective nanofluid flow with fractal stochastic heat and mass transfer using finite differences

This study presents the first comprehensive numerical simulation of heat and mass transfer in fractal-like mixed convective nanofluid flows. The flow of non-Newtonian nanofluids over flat and oscillating sheets is modelled mathematically, and a finite difference scheme is used to solve this model. The two-stage scheme can tackle fractal and fractal stochastic mathematical models of partial differential equations. The consistency in the mean square is proved, and Fourier series stability analysis is adopted to find stability conditions for fractal stochastic partial differential equation. The scheme is applied to solve the unsteady Casson nanofluid flow over the flat and oscillatory sheet, which affects thermal radiation, heat source, and chemical reaction. The existence of the solution is also provided for the Navier-Stokes equation of the considered flow model using fractal time derivative. The graph illustrates that the proposed fractal technique achieves faster convergence than the Crank-Nicolson approach. Applications in energy systems, materials science, and environmental engineering are just a few of the domains that could benefit from a better understanding of mixed convective nanofluid flows with fractal features, and that is what this research study hopes to accomplish. Scientists and engineers may better develop efficient and environmentally friendly systems by simulating and analyzing these complicated processes with the suggested finite difference technique.

Numerical simulation of mass and heat transfer for water extraction from icy lunar regolith

The confirmation of water ice’s existence in the permanent shadow area led to extensive research in the field of water ice mining from icy lunar regolith. A priori numerical simulation of water ice mining is necessary for guiding the development of lunar water ice mining schemes more reasonably. A 2D axisymmetric numerical simulation model capable of simulating the thermal extraction process about mining water ice from icy lunar regolith is constructed, which is executed in the COMSOL Multiphysics. The thermal extraction cases of lunar regolith with different initial water ice content and heating fluxes are simulated. The EER (energy efficiency ratio) is used to evaluate the efficiency of thermal extraction. The results show that the EER is higher as the initial water ice content is increased, which means more power is used to heat water and less power is used to heat the regolith. The icy lunar regolith with initial water ice content higher than 5.0 wt% is found to be more valuable, over which the EER at the end of thermal extraction will not increase much as the initial water ice content increases. However, the higher heating flux leads to the lower EER at the end of thermal extraction. The speed and economics of thermal extraction are suggested to be weighted before the mission’s implementation. The status of thermal diffusion (thermal transpiration) is studied, and the results indicate that thermal diffusion and advection both can be ignored in thermal extraction modeling, unless the average magnitude of temperature gradient and pressure gradient exceed the maximum of 75764 K/m and 11053 Pa/m in our calculation cases, respectively.

Development of coffee bean porosity and thermophysical properties during roasting

The development of coffee bean porosity during roasting was captured for a Kenyan Arabica coffee roasted under different constant inlet air temperature conditions in a pilot-scale spouted bed roaster. Coffee bean porosity was characterised using X-ray Micro Computed Tomography (Micro-CT). These data demonstrated a significant increase in coffee bean porosity of up to 60% during roasting. The coffee's intrinsic physical properties were also analysed to identify the relationship between porosity, thermophysical properties (density, thermal conductivity, specific heat capacity) and common process indicators (colour, mass, moisture, volume). Implications for heat transfer during roasting are also discussed. As Micro-CT, pycnometry and thermal properties analysers are not readily available tools, correlation of costly analytical methods with rapid discriminative tests are presented, allowing developers to utilise more accessible characterisation techniques to inform modulation of their processes and products. The data-driven approach to map coffee's physicochemical development during roasting provides comprehensive data that could be used to calibrate mechanistic or kinetic models. These physics-driven models could then be used as routine equations nested in heat and mass transfer simulations for developers to predict coffee's thermal evolution and subsequent physical transformation during roasting.

Additive manufactured metal lattice structures used as flow-through electrodes in a filter-press electrochemical reactor

This study deals with the electrochemical and hydraulic performances of additive manufactured metal periodic lattice structure electrodes. These electrodes are fabricated by Laser Powder Bed Fusion (LPBF) from the titanium alloy TA6V and two structures have been studied: diagonal and octet-truss. They are integrated, as flow-through electrodes, in an electrochemical filter-press reactor. Current–potential curves are experimentally obtained by linear sweep voltammetry when feeding the reactor with a ferricyanide solution. From the measurement of the limiting current of ferricyanide ions reduction, the volumetric mass transfer coefficient kAe is determined for several flow rates. Numerical simulations of fluid flow and mass transfer in these structures are also performed. Results show high values of kAe for these structures (competing with carbon felt electrodes) while maintaining a high permeability (low flow resistance). The surface roughness, inherent to the additive manufacturing process, is found to induce a low (≲10%) enhancement of mass transfer despite the roughness size (Ra in the range 10-20μm) is close to the average thickness of the diffusion layer (for the investigated fluid velocities). As a result, these electrode structures show promising potential to be used in intensified electrochemical reactors by being further optimized to find the optimal internal dimensions that maximize mass transfer while limiting flow resistance.

Numerical simulation of heat and mass transfer in laser directed energy deposition

In order to accurately predict the heat transfer and flow process of laser directed energy deposition, the numerical simulation of whole stage after the powder leaves the nozzle was carried out. First, the powder flow mode with laser body heat source in the first stage was established, and the average temperature and velocity of the powder at the convergence plane were obtained as 1300 K and 13 m/s, respectively. Based on this, the coupling model of heat flow between powder and substrate in the second stage is improved, and the influence of multiple source terms such as powder temperature, powder velocity, gas velocity, surface tension and thermal buoyancy is considered comprehensively. The evolution of the temperature and flow field of the cladding layer are analyzed in detail under the spatiotemporal variation, and it is clear that there are two convection currents with different clockwise directions in the molten pool, and the Marangoni convection occupies the main position. Finally, FeCrNiMo alloy powder was deposited on 42CrMo substrate, and its morphology, hardness and tensile strength in different directions were analyzed. The average height, width and depth deviations of the experiment and simulation are 17.3 %, 15.5 % and 22.9 %, respectively. The average strength of the tensile sample V2 prepared by the cladding layer is 11.8 % higher than that of the substrate.

A physics-informed neural network framework to investigate nonlinear and heterogenous shrinkage of drying plant cells

This paper introduces a novel Physics-Informed Neural Network-based (PINN-based) multi-domain computational framework to analyse nonlinear and heterogeneous morphological variations of plant cells during drying. Here, two distinct models are involved: PINN-MT to simulate mass transfer; and PINNNS to simulate nonlinear shrinkage. The models are coupled to examine cellular morphological changes resulting from moisture loss during drying. Firstly, the coupled framework, in tandem with homogeneous conditions, operates in parallel, allowing the mutual parameters to update between models. This approach demonstrates ability to approximate homogeneous cellular shrinkage within a tissue, factoring in the influence of surrounding plant cells. Secondly, non-uniform cell wall properties and heterogeneous boundary conditions are incorporated into this computational framework through domain decomposition. Inherent capabilities of neural networks allow for seamless integration of multiple domains, with additional loss terms introduced at interfaces. The framework shows capacity to account for drastic and non-uniform morphological variations of plant cells even under extreme drying conditions, which is the key novelty and has been a challenging task for existing traditional computational methods. Hence, the proposed computational approach offers an innovative avenue for understanding nonlinear and heterogeneous morphological variations not only for plant cells, but also for soft matter in general.

Heat and mass transfer simulation of the microwave-assisted toluene desorption for activated carbons regeneration

The low cost and high efficiency of microwave-assisted regeneration render it a viable alternative to conventional regeneration methods. To enhance the regeneration performance, we developed a coupled electromagnetic, heat, and mass transfer model to investigate the heat and mass transfer mechanisms of activated carbon during microwave-assisted regeneration. Simulation results demonstrated that the toluene desorption process is governed by temperature distribution. Changing the input power and flow rate can promote the intensity of hot spots and adjust their distribution, respectively, thereby accelerating toluene desorption, inhibiting readsorption, and promoting regeneration efficiency. Ultimately, controlling the input power and flow rate can flexibly adjust toluene emissions to satisfy the processing demands of desorbed toluene. Taken together, this study provides a comprehensive understanding of the heat and mass transfer mechanisms of microwave-assisted regeneration and insights into adsorbent regeneration.

Numerical Simulation of Mass Transfer in Hollow Fiber Membrane Module for Membrane-Based Artificial Organs.

The mass transfer behavior in a hollow fiber membrane module of membrane-based artificial organs (such as artificial liver or artificial kidney) were studied by numerical simulation. A new computational fluid dynamics (CFD) method coupled with K-K equation and the tortuous capillary pore diffusion model (TCPDM) was proposed for the simulations. The urea clearance rate predicted by the use of the numerical model agrees well with the experimental data, which verifies the validity of our numerical model. The distributions of concentration, pressure, and velocity in the hollow fiber membrane module were obtained to analyze the mass transfer behaviors of bilirubin and bovine serum albumin (BSA), and the effects of tube-side flow rate, shell-side flow rate, and fiber tube length on the bilirubin or BSA clearance rate were studied. The results show that the solute transport mainly occurred in the near inlet regions in the hollow fiber membrane module. Increasing the tube-side flow rate and the fiber tube length can effectively enhance the solute clearance rate, while the shell-side flow rate has less influence on the BSA clearance. The clearance of macromolecule BSA is dominated by convective solute transport, while the clearance of small molecule bilirubin is significantly affected by both convective and diffusive solute transport.

Simulation of Nanofiltration Mass Transfer for Magnesium and Lithium Separation in Salt Lakes.

A mass transfer model to predict the transport processes of magnesium and lithium ions through porous media in salt lakes has been proposed, which is a combination of the extended Nernst-Planck equation and Donnan effect, accounting for ion diffusion, electromigration, and convection within membrane pores. First, the morphological structure, thickness, surface roughness, and hydrophilicity of the membrane were characterized as fixed parameters, indicating that the surface of the nanofiltration membrane is smooth with low roughness and strong hydrophilicity, resulting in a lower desalination rate but higher water flux. Subsequently, numerical calculations based on the model were conducted to establish a reasonable transport equation for predicting the concentration and retention rate of the main magnesium and lithium ions. When compared with the experimental results, a deviation of less than 5.5% is obtained, confirming the accuracy of the model in describing ion mass transfer. Finally, computational fluid dynamics techniques were employed to simulate the model equations in both the feed and permeate subdomains, demonstrating that the flow characteristics align with reality. Thus, the established transport model exhibits higher predictive accuracy for NF ion separation than one-dimensional models.