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In this work, the Discrete Element Method (DEM) is used to simulate the dispersion process of Active Pharmaceutical Ingredients (API) after a wall collision in dry powders inhaler used for lung delivery. Any fluid dynamic effects are neglected in this analysis at the moment. A three-dimensional model is implemented with one carrier particle (diameter 100 μm) and 882 drug particles (diameter 5 μm). The effect of the impact velocity (varied between 1 and 20 m s−1), angle of impact (between 5° and 90°) and the carrier rotation (±100,000 rad s−1) are investigated for both elastic and sticky walls. The dispersion process shows a preferential area of drug detachment located in the southern hemisphere of the carrier. The angle of impact with the highest dispersion is 90° for the velocities over 9 m s−1 and between 30° and 45° for lower velocities. The rotation of the carrier before the impact, on the other hand, for velocities higher than 7 m s−1, plays a little role on the dispersion performance. The DEM results are finally “distilled” into a simplified analytic model that could be introduced as a sub-scale model in Euler/Lagrange CFD calculations linking fluid dynamics with the detachment probability of APIs in the inhaler.

Dissolution of highly porous particles is a ubiquitous process in formulation chemistry. Scientific challenges remain unsolved due to the complex of interfacial properties and physical interactions between solid, liquid and gas phases. Two spray-dried powders consisting of sodium sulphate and linear alkylbenzene sulfonate (LAS) were used to investigate the abrupt disintegration mechanism focusing on the residual air in the highly porous particle during wetting stage. Four typical dissolution phenomena were identified through individual particle dissolution experiments using optical microscopy. The images suggest for the first time a link between abrupt disintegration phenomenon and air behaviour. We have examined the hypothesis that, as well as chemical changes occurring during wetting, physical processes can lead to disintegration. Tensile tests of individual particles in both dry and hydrated conditions show significant weakening of the particle strength during hydration. Mathematical simulation shows that fast penetration of water through the open-ended pores compresses entrapped air and increases the internal pressure. Hoop stresses generated by internal pressure are of the same magnitude as breaking forces, suggesting that abrupt disintegration in the early stage of dissolution is driven by air compression.

Emboli, which are parts of blood clots, can be stuck in the vasculature of various organs (most frequently, lungs) and cause their malfunction or even death. In this work, using mathematical modelling, different types of emboli-like structures are studied in a double venous valve system. The model is implemented with a fully Lagrangian Discrete Multi-Physics technique and the flow is governed by flexible walls. The study shows the effect of different diameters and lengths of a free embolus in the flow surrounding the valve. The presence of an embolus strongly affects the dynamics of both the fluid and the leaflets in venous valves and the permanence of the embolus in the valve chamber is narrowly linked with its length.

The effects of the configuration and temperature on the Young’s modulus of poly (methyl methacrylate) (PMMA) have been studied using molecular dynamics simulations. For the DREIDING force field und...

In this paper, a unified particle-based solver is developed to solve complex fluid–solid​ mixture flow problem involving many elastic solid bodies. Our previous Fluid Structure Interaction (FSI) solver that incorporates Smoothed Particle Hydrodynamics (SPH) for fluid modelling and Volume Compensated Particle Method (VCPM) for elastic solid modelling is extended by incorporating the Discrete Element Method (DEM) for modelling the contact force between colliding elastic solid bodies. The contact force is modelled using the non-linear Hertzian formulation. The method is firstly validated by solving several benchmark FSI problems that involve only one solid body. Then, solid–solid interaction is modelled and the collision problem involving two elastic rings and the well-known Drafting, Kissing and Tumbling (DKT) phenomenon in a fluid domain are simulated. The results agree considerably well with other benchmark numerical solutions. The collapse of Aluminium cylinder layers (in dry and wet conditions) is then simulated and it is found that the numerical result is comparable to the experimental data. Following that, the SPH–VCPM–DEM method is used to solve a more complex problem involving the dumping of solid objects through solid and perforated fall pipes for scour protection. The results show the potential of the SPH–VCPM–DEM method in simulating complex fluid–solid mixture flow.

We performed Molecular Dynamics (MD) simulations to study the mechanism of the specific heat enhancement in nitrate salt based nanofluids. 26.6% enhancement of specific heat capacity was observed by introducing nanoparticles into the salt system. Our simulations showed that the nanoparticles caused a layering effect in the adjacent region of the liquid molten salt. Hence we attribute the enhancement in the specific heat capacity of molten salts with the addition of nanoparticles to a previously undiscovered structural arrangement of salt atoms around the nanoparticles.

In this study, we propose a smoothed particle hydrodynamics model for simulating a shock wave interacting with cylindrical gas inhomogeneities inside a shock tube. When the gas inhomogeneity interacts with the shock wave, it assumes different shapes depending on the difference in densities between the gas inhomogeneity and the external gas. The model uses a piecewise smoothing length approach and is validated by comparing the results obtained with experimental and CFD data available in the literature. In all the cases considered, the evolution of the inhomogeneity is similar to the experimental shadowgraphs and is at least as accurate as the CFD results in terms of timescale and shape of the gas inhomogeneity.

There are two common ways of coupling first-principles modelling and machine learning. In one case, data are transferred from the machine-learning algorithm to the first-principles model, in the other, from the first-principles model to the machine-learning algorithm. In both cases, the coupling is in series: the two components remain distinct, and data generated by one model are subsequently fed into the other. Several modelling problems, however, require in-parallel coupling, where the first-principle model and the machine-learning algorithm work together at the same time rather than one after the other. This study introduces deep multiphysics, a computational framework that couples first-principles modelling and machine learning in parallel rather than in series. Deep multiphysics works with particle-based first-principles modelling techniques. It is shown that the mathematical algorithms behind several particle methods and artificial neural networks are similar to the point that can be unified under the notion of particle&ndash, neuron duality. This study explains in detail the particle&ndash, neuron duality and how deep multiphysics works both theoretically and in practice. A case study, the design of a microfluidic device for separating cell populations with different levels of stiffness, is discussed to achieve this aim.

Molecular dynamics is used to simulate the self-healing process of asphalts mixed with a healing agent. Sulfoxide functional groups were introduced into the virgin asphalt to produce a short-term-aged asphalt model. The model is validated by comparing density, diffusion coefficient, solubility parameter, and viscosity with real measurements. Plant oil and Aromatic oil are chosen as typical healing agents. The molecular models of asphalt and healing agent are integrated into a micro-crack model, and the healing process is simulated with molecular dynamics. The results show that Plant oil is a better choice for improving the healing rate of virgin asphalt, while Aromatic oil is better for improving the healing rate of short-term aged asphalt. The higher the temperature is, the better effect the healing agent will have on the asphalt. Healing is maximized above 15 degrees C for virgin asphalt and above 45 degrees C for short-term-aged asphalt. Molecular simulations show that the healing process depends on the diffusion of the healing agent and asphalt into the micro-crack. After the crack is filled, bitumen and oil molecules continue to mix. Aromatic oil produces a better mixing that leads to a more uniform composition and better mechanical properties. (c) 2021 Elsevier Ltd. All rights reserved.

This paper demonstrates the use of peridynamics and discrete multiphysics to assess micro crack formation and propagation in asphalt at low temperatures and under freezing conditions. Three scenarios are investigated: (a) asphalt without air voids under compressive load, (b) asphalt with air voids and (c) voids filled with freezing water. The first two are computed with Peridynamics, the third with peridynamics combined with discrete multiphysics. The results show that the presence of voids changes the way cracks propagate in the material. In asphalt without voids, cracks tend to propagate at the interface between the mastic and the aggregate. In the presence of voids, they ‘jump’ from one void to the closest void. Water expansion is modelled by coupling Peridynamics with repulsive forces in the context of Discrete Multiphysics. Freezing water expands against the voids’ internal surface, building tension in the material. A network of cracks forms in the asphalt, weakening its mechanical properties. The proposed methodology provides a computational tool for generating samples of ‘digital asphalt’ that can be tested to assess the asphalt properties under different operating conditions.

This work presents both simulations and experiments showing that the use of silica nanoparticles enhances the thermal properties of molten salt based nanofluids which is a provisional candidate for solar thermal energy storage. Sodium nitrate, potassium nitrate and lithium nitrate were chosen as the base material for such nanofluids. Thermodynamic and transport properties for nitrate salts and nanofluids were computed from molecular dynamics simulations. In order to validate our simulation results, different scanning calorimetry (DSC) was employed to measure the thermal properties of salt based nanofluids at 270–400 °C. Both simulation and experimental results showed that the addition of nanoparticles increases the specific heat capacity. Material characterization analysis was carried out to investigate microstructural change of nanomaterials using a scanning electron microscopy (SEM). We observed a stripe-like arrangement of nanoparticles with SEM. That may be responsible for the enhancement of specific heat capacity of the nanofluids.

This work discusses the geopolymerization of lunar dust simulant JSC LUNAR-1A and Martian dust simulant JSC MARS-1A. The geopolymerization of JSC LUNAR-1A occurs easily and produces a hard, rock-like, material. The geopolymerization of JSC MARS-1A requires milling to reduce the particle size. Tests were carried out to measure, for both JSC LUNAR-1A and JSC MARS-1A geopolymers, the maximum compressive and flexural strengths. In the case of the lunar simulant, these are higher than those of conventional cements. In the case of the Martian simulant, they are close to those of common building bricks.

Mixtures of molten-salts (e.g. NaNO3, KNO3) with α-SiO2 nanoparticles have potential applications in concentrated solar power generation both as a thermal energy storage material and heat transfer fluid. In this study, a set of Lennard-Jones parameters for amorphous silica is proposed, aimed at understanding the molten-salt/amorphous-silica interface at the nanoscale through molecular dynamics simulations. Current force fields used for the simulation of α-SiO2 do not have validated rules for cross-term interactions or are computationally expensive. In this work, a novel set of Lennard-Jones parameters capable of accurately simulating the structure of amorphous SiO2 is presented. Its advantage is that it has precise validated mixing rules, which can be used to model cross term (different species) interactions, which are dominant in simulations involving interfaces. The proposed potential is validated by experimental results and data from previous studies: all the calculated properties (i.e. radial distribution, angular distribution, mean bond length, coordination number, density, thermal expansion coefficient and thermal conductivity) are in good agreement with the data in the literature. Additionally, the molten salt-amorphous silica interface is investigated. The existence of a compressed liquid layer at the liquid-nanoparticle interface is observed. The density of the molten salt mixture is found to be significantly higher and the self-diffusivity lower, in the proximity of the interface. Finally, the Na+ and K+ ions appear to be ordered in the proximity of the interface, indicating the existence of an ordered double-layer.

In this study, the agglomeration of settling particles in a dewatering process is studied numerically. The numerical model is based on the smoothed particle hydrodynamic method. The interaction between solid particles is governed by the Lennard-Jones potential. This paper presents a systematic study for evaluating the influence of various important parameters on the dewatering process, i.e., the Reynolds number, inter-particle pair potential, and phase loading. Several quantitative parameters are introduced to characterize the structure and behavior of agglomerates. It is observed that based on the interplay between the Reynolds number and the pair potential, the agglomerates form four different structures.

A new unified particle model that couples the Smoothed Particle Hydrodynamics (SPH) and a discontinuous approach known as the Volume Compensated Particle Method (VCPM) is developed to solve Fluid Structure Interaction (FSI) problems involving large deformation. Unlike the model that couples the Smoothed Particle Hydrodynamics and the Discrete Element Method (i.e. SPH-DEM) in which the applicable Poisson's ratio of the solid material should be less than certain critical values, the current unified particle model is able to model solid materials of large Poisson's ratio by using only axial interaction between solid particles. The coupling between SPH and VCPM is accomplished by treating the solid particles of VCPM at the solid-fluid interface as dummy particles in SPH. This paper presents the first SPH-VCPM coupled method for FSI with comprehensive validations. The VCPM solver is firstly verified for solving static and dynamic solid mechanics problems. Then, the proposed solver is used to solve several FSI problems involving free surface, i.e. water column on an Aluminum plate, flow under an elastic gate, dam break problems involving flexible structures and deformation of flexible structure in a rolling oil tank. The SPH-VCPM results match well with the published numerical results obtained from the literature.

The molecular model of asphalt binder was established by means of molecular dynamics (MD). The MD model was validated with respect of density, glass transition temperature, viscosity and solubility parameters. An interface system was created by inserting a vacuum pad of 50 A between 2 groups of asphalt binders to study the self-healing behavior of the asphalt binder, e.g. internal volume, diffusion rate of each component and energy variation of the model. The molecular diffusion of aged asphalt binder, SBS modified asphalt binder, and virgin asphalt binder are studied. The results show that the “compression” of asphalt binder volume and the “stretching” of the asphalt binder molecules is responsible for the disappearance of vacuum micro-cracks inside the asphalt binder. When the model volume is “compressed”, the volume of the asphalt model decreases until the micro-cracks in the asphalt binder disappear completely. The molecular volume of asphalt decreases greatly at the beginning of the MD simulation, and then becomes stable. The length of asphalt model increases in the OZ direction, while the length of the OX and OY directions decreases, indicating that asphalt “stretces” during the self-healing process. During the self-healing process, the diffusion coefficient of asphaltene molecule is the lowest, while the diffusion coefficient of the saturates is the highest at 360 K, aromatics and resins are close to the average value 6.227 × 10−4 cm2/s in the MD model. Self-healing is mainly based on the Van der Waals forces between non-bonded molecules. The aging of asphalt molecules reduces the diffusion rate of the asphalt model, and the SBS additive indirectly enhances the diffusion rate of asphalt.

In this work the γ - to α -Al2O3 phase transformation induced by mechanical milling was investigated as a function of the bead size for two laboratory scale high-energy mills: a planetary ball mill and an attritor mill. The alumina was texturally characterised, before and after milling, by Scanning Electron Microscopy (SEM) analysis, porosimetry by N2 physisorption with Brunauer-Emmett-Teller (BET) specific surface area analysis, and structurally characterised by X-Ray Diffraction (XRD), Differential Scanning Calorimetry (TGA-DSC) and Nuclear Magnetic Resonance (27Al-MAS NMR). SEM micrographs highlighted that the planetary ball mill had a better particle size reduction, while the BET surface area results indicated a greater surface area loss compared to the attritor mill. XRD patterns and 27Al MAS NMR spectra showed that depending on the intensity of the milling conditions the phase transformation was mechanically activated and most of the γ -Al2O3 was converted into α -Al2O3. The attritor mill did not supply the minimum stress energy to induce alumina crystal change; this was in contrast to the planetary ball mill which showed progressively more α -Al2O3 formation as bead size increased. For the planetary ball mill samples which did not exhibit phase transformation an exceptional fraction (15%) of pentacoordinate Al ions (AlO5) was observed, suggesting incipient transformation of the initial γ - Al2O3 structure. Consistent with the other characterisation techniques, differential scanning calorimetry (DSC) results showed that the reduction of the transformation temperature was directly proportional to the intensity of the milling conditions. The Discrete Element Method (DEM) simulations were used to model the bead motion inside the two mills and to estimate the specific energy and the stress energy for the considered experimental conditions. The simulation results coupled with the XRD patterns clearly suggested that the formation of α -Al2O3 nuclei was controlled by the stress energy. This finding could potentially be utilised as the basis scaling parameter to determine the conditions to reproduce the phase transformation in a different mill or to a different scale.

Objectives The objective of this study is to devise a modelling strategy for attaining in-silico models replicating human physiology and, in particular, the activity of the autonomic nervous system. Method Discrete Multiphysics (a multiphysics modelling technique) and Reinforcement Learning (a Machine Learning algorithm) are combined to achieve an in-silico model with the ability of self-learning and replicating feedback loops occurring in human physiology. Computational particles, used in Discrete Multiphysics to model biological systems, are associated to (computational) neurons: Reinforcement Learning trains these neurons to behave like they would in real biological systems. Results As benchmark/validation, we use the case of peristalsis in the oesophagus. Results show that the in-silico model effectively learns by itself how to propel the bolus in the oesophagus. Conclusions The combination of first principles modelling (e.g. multiphysics) and machine learning (e.g. Reinforcement Learning) represents a new powerful tool for in-silico modelling of human physiology. Biological feedback loops occurring, for instance, in peristaltic or metachronal motion, which until now could not be accounted for in in-silico models, can be tackled by the proposed technique.

A hybrid molecular mechanics-molecular dynamics (MM-MD) method is proposed to calculate the Young's modulus of polymers at various temperature. It overcomes the limitation that MD is restricted to extremely high strain rates. A case study based on poly-methyl-methacrylate demonstrates that, contrary to previous MD studies, the method is able to accurately reproduce the effect of temperature on the Young's modulus in close agreement with experimental data. The method can also predict a more clear transition between the glassy and rubbery states than previous MD studies.

The hemodynamics in flexible deep veins valves is modelled by means of discrete multi-physics and an agglomeration algorithm is implemented to account for blood accrual in the flow. Computer simulations of a number of valves typologies are carried out. The results show that the rigidity and the length of the valve leaflets play a crucial role on both mechanical stress and stagnation in the flow. Rigid and short membranes may be inefficient in preventing blood reflux, but reduce the volume of stagnant blood potentially lowering the chances of thrombosis. Additionally, we also show that in venous valves, cell agglomeration is driven by stagnation rather than mechanical stress.

SUMMARY In this work, a hybrid numerical approach, which combines elements of SPH and coarse-grained molecular dynamics, is used to investigate the effect of various flow conditions to deformable and breakable shell-structures such as capsules, vesicles or biological cells. Copyright © 2014 John Wiley & Sons, Ltd.

Molten salts have extended applications in concentrated solar power (CSP) installations, both as heat transfer and energy storage materials. In this study, a set of Lennard-Jones interatomic parameters are introduced for simulating NaNO3 and KNO3, as well as their most frequently industrially used mixture the so-called solar-salt (60% NaNO3 – 40% KNO3). Local structures are studied via radial distribution functions. Furthermore, density, thermal conductivity, self-diffusivity, viscosity and surface tension are calculated, from melting to decomposition temperature, and compared with experimental data. The local structures are calculated with both existing and presented interatomic potentials and are found to be in excellent agreement. Additionally, density, viscosity and surface tension present minor differences from literature data. Thermal conductivity, in terms of absolute values is in the proximity of reported data but is questionable in terms of trend. Finally, self-diffusion coefficients declinate from measured values, but are similar in terms of trend. Results are found to be in good agreement. This work represents the first extended validated effort in modelling molten nitrate salts and their mixtures at elevated temperatures using a Lennard-Jones potential, providing new tools that can aid in the fundamental understanding of molten salt structures at the molecular scale.

This paper develops a three-dimensional numerical model for the simulation of cells in simple shear flow. The model is based on Discrete Multi-Physics (DMP), a meshless particle-based method that couples the smoothed particle hydrodynamics and the mass-spring model. In this study, the effect of the nucleus in cells is investigated for a broad range of capillary numbers. It is shown that the nucleus size affects the deformation of the cell. Moreover, oscillations are observed in the tank-treading motion of the membrane when capillary number and nucleus size are both sufficiently large. Additionally, DMP shows that the cell and nuclei may experience rupture under extreme flow conditions.

The hybrid taxonomy — a means of characterizing different atomistic-continuum methods on the basis of the type of information exchanged between the atomistic and the continuum solver — is introduced. The formulation of the taxonomy raises a new hybrid possibility, called a ‘hybrid-hybrid’ method. Some examples of hybrid-hybrid simulations for dense fluids are discussed and validated against full molecular dynamics results.

We propose a new hybrid algorithm for incompressible micro and nanoflows that applies to non-isothermal steady-state flows and does not require the calculation of the Irving–Kirkwood stress tensor or heat flux vector. The method is validated by simulating the flow in a channel under the effect of a gravity-like force with bounding walls at two different temperatures and velocities. The model shows very accurate results compared to benchmark full MD simulations. In the temperature results, in particular, the contribution of viscous dissipation is correctly evaluated.

In this work, we develop a non-isothermal model for diesel particulate filters including exothermic and competing chemical reactions. We begin with an isothermal, single-reaction model and we gradually increase its complexity. By comparing various models, we aim at establishing the minimum degree of complexity required to effectively model the system under investigation. Based on the numerical simulations, we conclude that isothermal models are adequate only if the temperature of the catalyst is, at all times, completely below or completely above a critical temperature. However, if the goal is to predict the critical temperature, only non-isothermal models should be used. The results with competing reactions, on the other hand, show that the presence of competing reactions does not affect significantly the overall conversion in the filter.

We propose a mesh-free and discrete (particle-based) multi-physics approach for modelling the hydrodynamics in flexible biological valves. In the first part of this study, the method is successfully validated against both traditional modelling techniques and experimental data. In the second part, it is further developed to account for the formation of solid aggregates in the flow and at the membrane surface. Simulations of various types of aggregates highlight the main benefits of discrete multi-physics and indicate the potential of this approach for coupling the hydrodynamics with phenomena such as clotting and calcification in biological valves.

The importance of the fluid dynamics in the modelling of electrochemical systems is often underestimated. The knowledge of the flow velocity pattern in an electrochemical cell, in fact, can allow us to associate certain electrochemical reactions with specific fluid patterns to maximize the yield of some reaction and, conversely, to minimize unwanted or side reactions. The correct evaluation of the convective term in the Nernst–Planck equation, however, requires the solution of the so-called Navier–Stokes equations, and computational fluid dynamics (CFD) is today the established method to numerically solve these equations. In this work, a CFD model is employed to show that the gas–liquid flow pattern can be remarkably different in a single channel or in a multi-channel gas-evolving electrochemical system. In the single channel, in fact, under certain conditions, vortices and recirculation regions can appear in the flow, which does not appear in the multi-channel case. The reason of this difference is found in the uneven distribution of the small bubbles in the two cases. Additionally, a second, simplified, model of the flow is discussed to show how a higher concentration of small bubbles in the single channel system can destabilize the flow.

Three CFD (Computational Fluid Dynamics) models (single-phase. VOF and Euler-Euler) are employed to simulate the flow in a finite, rotating electrode cell under different operative conditions. The ...

Different flow regimes have been observed, both experimentally and in CFD simulations, in narrow channels with gas evolution. In this manuscript, we examine, using the Euler–Euler model, the flow in a narrow channel, where gas is evolved from a vertical wall. We find some pseudo-turbulent features at conditions described in this manuscript. The transition to this pseudo-turbulent regime is associated with the value of a specific dimensionless group.

The flow in a narrow (3 mm wide) vertical gap of an electrochemical cell with gas evolution at one electrode is modeled by means of the two-phase Euler–Euler model. The results indicate that at certain conditions an unsteady type of flow with vortices and recirculation regions can occur. Such flow pattern has been observed experimentally, but not reported in previous modeling studies. Further analysis establishes that the presence of a sufficient amount of small (∼10 μm) bubbles is the main factor causing this type of flow at high current densities.

There is limited information available to describe how the recycle ratios of the retentate and permeate streams can be used to counteract the effects of fluctuations in feed flowrate and composition on the flowrate and composition of the retentate stream from a whey ultrafiltration (UF) process. Based on dynamic modelling of a single membrane channel and a single-stage membrane module, it was found that the high retentate recycle ratio typically used in industrial UF of whey imposes slow dynamic responses and extensive oscillations on the flowrate and concentration of the retentate after a feedback controller is implemented. Even though the permeate recycle ratio can be used to control the specifications of the retentate, the high retentate recycle ratio used in typical whey UF processing places a limit on how fast the effects of fluctuations in feed flowrate and composition can be mitigated. Since a high retentate recycle ratio is required to improve the productivity of the whey UF process, a tradeoff must be obtained between the productivity and the time required to mitigate the effects of fluctuations in feed flowrate and composition.

There is limited information from literature on the dynamic operability of membrane processes with multiple stages or loops. Such information is useful for assessing the performance achievable by an automatic controller proposed for a process design before the actual controller is implemented. Based on dynamic modeling of an industrial whey ultrafiltration process with an increasing number of stages up to a maximum of 12, the dynamic responses of the flowrate and concentration of the retentate were obtained. Features of the dynamic responses were used to determine the performance, in terms of quality and speed, that can be achieved by automatic controllers. In particular, limitations on the performance are indicated by features of dynamic responses such as effective time delay and inverse responses. Changes in effective time delay and inverse responses with the number of stages in the whey ultrafiltration process demonstrate a trade-off between process performance and control performance. This trade-off should be considered during process and controller design to maximize the economic return from the production of whey protein concentrates.

Recently, computational fluid dynamics (CFD) models of flows in membrane channels have been proposed and validated against published simplified models available in the literature. In this paper, experimental and numerical analysis is performed for a reverse osmosis (RO) module and results compared in order to provide further validation of the model from a practical prospective. Our results show that, in order to improve the accuracy of the calculations at high pressure, a membrane permeability that varies with the operational pressure must be taken into account.

In this paper, a CFD model for bubbly-flow including break-up and coalescence is discussed. The probabilistic method, developed according to this model, is tested for an industrial configuration: numerical bubble-size distributions are compared with those derived by experiments.

Bubbles released from a porous plug into a gas-stirred ladle present different bubbly dispersion patterns that can be studied by CFD means. Recent modeling (Alexiadis et al.) has, in fact, led to numerical results in accord with experimental data. However, due to the high number of equations involved, it is not easy to understand the physical reasons of the transitions between these patterns. In the present paper, attention was focused on the role of fragmentation and coalescence and the pattern-transition modeled by means of intersection points between these functions.

A computational fluid dynamics (CFD) model was used to simulate the flow in a narrow spacer-filled channel, which represents the longitudinal section of a spiral-wound module membrane. The flow was computed for different geometries and Reynolds numbers. Calculations show the presence of different flow patterns in the laminar regime. Equations describing the critical Reynolds numbers at which the transition between different patterns occur were derived. It is shown that the critical Reynolds number determines the point at which good mixing conditions are achieved without excessive pressure drop.

In this paper, control theory is used to study the connection between human activities and global warming. A feedback model is proposed and tested against temperature and carbon dioxide concentration historical data. Four scenarios are taken into account and simulated by the model; stability analysis is also discussed. The model proposed here simulates the historical data correctly and the scenarios show that, even in the case of dramatic reduction of the anthropogenic carbon dioxide emission, the temperature will not decrease for a certain time. Stability analysis reveals a complex pole near the unit circle. This means that, although the system at the moment is stable, it is very close to becoming unstable with unpredictable consequences on climate change.

The particle-continuum hybrid Laplacian method is extended as a framework for modeling all transport phenomena in fluids at the micro and nanoscale including multicomponent mass transfer and chemical reactions. The method is explained, and the micro-to-macro and macro-to-micro coupling steps are discussed. Two techniques for noise reduction (namely, the bonsai box (BB) and the seamless strategy) are discussed. Comparisons with benchmark full-molecular dynamics (MD) cases for micro and nano thermal and reacting flows show excellent agreement and good computational efficiency.

Dynamic responses of a high-pressure (80 bar) reverse osmosis (RO) membrane system to pulse disturbances in pressure, concentration and velocity are investigated. Responses are calculated using computational fluid dynamics (CFD) and are used to develop transfer function models using system identification methods. The response of the flux to pressure changes is described by a 3-pole/3-zero model for both positive and negative pressure pulses. The transfer function, which relates the flux response to concentration changes, is a 3-pole model, while the response to flow velocity changes is a single pole model.

In this paper, a Monte Carlo model is used to predict the light intensity profile inside a photocatalytic monolith reactor where the internal walls of the reactor are coated with a light-absorbing and light-reflecting catalytically active film. Reactors with channels of square, rectangular, equilateral triangular and isosceles triangular sections are considered. These cases have not cylindrical symmetry and a 2-D approach must be used.

In this paper, the dynamic behavior of reverse osmosis (RO), high-pressure (60−80 bar) membranes is investigated using an approach that combines both computational fluid dynamics (CFD) and system identification methods. Detailed CFD models of membrane systems allow predictions of the response of such systems to operating parameter changes. These models, however, are complex and require significant computing resources, which make them impractical for use in membrane system operation. In the present work, system identification theory is applied to data generated from a CFD model in order to obtain approximate transfer functions, which describe the dynamics of the system. The transfer function parameters are then related to the dynamic changes in momentum and concentration. The results show that the local concentration plays a fundamental role in the membrane performance. A feedback model, which quantifies the effect of the concentration boundary layer on the permeate flux, is finally proposed.

This paper summarizes the results of a work aimed at the design of pilot and industrial size photocatalytic reactors for wastewaters treatment. The work is based on the findings of previous lab-scale experiments and model development. The physical reactor model was used to simulate the performance of the photocatalytic system in various configurations and different operating conditions. The cost of the water treatment was determined by considering both the energy consumption and the periodic renewal of commercial UV lamps. The results of this work show that the optimal conditions for a photocatalytic purification unit remarkably depend on the kinetics of the pollutants degradation. In the case of fast degradation reactions low-power UV sources and low absorption catalysts are preferable. On the contrary the use of high-power lamps and dense catalysts can reduce sensibly the treatment cost when the degradation processes is slow.

Many metallurgical processes are connected with gas injection into liquid metals for refining purposes. For this reason, considerable effort has been made during the past 2 decades to investigate gas-injection operations in steelmaking ladles. Numerous physical and mathematical models are available in the literature as well as experiments (most of them performed in the air-water model). In theoretical works, usually, the bubble size is assumed constant, but this approximation is good just at low gas flow rates. When the gas flow rate increases, three different types of bubble dispersion patterns are observed in experiments. This situation cannot be predicted by means of the turbulence multiphase models normally implemented in commercial CFD codes. Their results predict a smooth (and wrong) bubble-size increase and not a sudden transition from a pattern to another, as in experiments. In this articles a new idea for approaching the bubble turbulence in the ladle, called “spot turbulence,” is presented and comparison with experimental data shown.

In this paper, a mathematical model describing olefin polymerization with metallocene catalysts is presented. It is an improvement of a previous model, the “particle growth model” (PGM) proposed by, among others, one of the authors of the present work and derives from the so-called “multigrane model” (MGM). The main differences between this work and others is a more sophisticated approach to fragmentation with respect to the MGM. Additionally, there is a more specific modeling for the unfragmented core with respect to the PGM. The numerical results obtained by the model are compared with experimental data. The results of this work allow to extend the PGM to catalysts with lower activity. The importance of those catalysts depends on the fact that high activity catalysts could bring, in some cases, too poor polymer morphology.

On the electrode boundary conditions in the simulation of two phase flow in electrochemical cells

First-principles, predictive engineering models provide a sound theoretical basis for quantifying the inherent light energy utilization capabilities and performance limitations of candidate commercial photocatalytic oxidation reactor configurations. In particular, these models provide insight into the similarities and differences between photoreactors based on structured honeycombed monoliths, and those based on reticulated foams or other random catalyst supports. For honeycombed monoliths, a deterministic first-principles radiation field model provides the channel wall light intensity profile down the length of a single channel in the monolith. A three-dimensional developing flow convection–diffusion reaction model employing this radiation field submodel predicts the velocity and concentration fields. The model shows that light intensity gradients in a monolith of typical dimensions are severe, that only a fraction of the monolith can be effectively photo-activated, and as a consequence process performance is largely controlled by light distribution. For a given light source and photocatalyst combination, reactor performance scales according to the aspect ratio of the channeled monolith, the Reynolds number, and the Dahmkohler number. For randomly structured monoliths, the radiation field must be determined by probablistic methods. Monte Carlo simulations show that the radiation field in such random porous structure scales according to the pore size distribution and the void fraction, and the photocatalyst film thickness. Reactor performance scales by the radiation field, the Peclet number, the Stanton number, and the Dahmkohler number. The complex interrelationship between the random structure of the monolith and the resulting radiation field and mass transfer behavior makes scaling of these reactor types particularly difficult.

This work intends to develop a mathematical model of a fixed bed reactor and tests this model with experimental data. For this reason, we introduce some specific knowledge about light absorption from the catalyst, about the hydrodynamic interpretation of the reactor and the kinetic behaviour of photocatalytic reactions. Afterwards, we summarise this information and set up a complex mathematical model. We use this model in order to identify the kinetic constants of some reactions. We also formulate some simplified models to be used in particular circumstances and we compare the results of the complex model and the simplified models. Moreover, we compare experimental data of conversion and the results estimated with our model.