Particle Deposition Model Research Articles

A Markov chain model of particle deposition in the lung

Particle deposition in the lung during inhalation is of interest to a wide range of biomedical sciences due to the noninvasive therapeutic route to deliver drugs to the lung and other organs via the blood stream. Before reaching the alveoli, particles must transverse the bifurcating network of airways. Computational fluid mechanical studies are often used to estimate high-fidelity flow patterns through the large conducting airways, but there is a need for reduced-dimensional modeling that enables rapid parameter optimization while accommodating the complete airway network. Here, we introduce a Markov chain model with each state corresponding to an airway segment in which a particle may be located. The local flows and transition probabilities of the Markov chain, verified against computational fluid dynamics simulations, indicate that the independent effects of three fundamental forces (gravity, fluid drag, diffusion) provide a sufficient approximation of overall particle behavior. The model enables fast computation of how different inhalation strategies, called flow policies, determine total particle escape rates and local particle deposition. In a 3-dimensional airway tree model, the optimal flow policy minimizing the risk of deposition at each generation, compared to other inlet flow waveforms, predicted significantly higher probability of escape defined as the fraction of particles exiting the tree. The model also predicts a small influence of body orientation with respect to a gravitational field on total escape probability, but a significant effect of airway narrowing on regional deposition. In summary, this model provides insight into inhalation strategies for targeted drug delivery.

Regional Deposition: Deposition Models.

Modeling particle deposition in the human lung requires information about the morphology of the lung in terms of simple geometric units, e.g., characterizing bronchial airways by straight cylindrical tubes. Five different regional deposition models are discussed in this section with respect to morphometric lung models and related mathematical modeling techniques: 1) one-dimensional cross-section or "trumpet" model, 2) deterministic symmetric generation or "single-path" model, 3) deterministic asymmetric generation or "multiple-path" model, 4) stochastic asymmetric generation or "multiple-path" model, and 5) single-path computational fluid and particle dynamics (CFPD) model. Current deposition models can predict the following regional deposition quantities relevant for the administration of medical aerosols: 1) regional bronchial and alveolar deposition, 2) generational lung deposition, 3) lobar deposition, 4) generational lobar deposition, and 5) generational surface deposition. Although deposition fractions predicted by the different models depend on the selection of a specific morphometric lung model and a specific set of analytical deposition equations, all models predict the same trends as functions of particle diameter and breathing parameters. In general, the overall agreement between the modeling predictions obtained by the various deposition models and the available experimental evidence indicates that current deposition models correctly predict regional and generational deposition.

Numerical simulation of the migration and deposition of fine particles in a proppant-supported fracture

Many hydrocarbon-bearing geologic formations, especially shales, contain high clay contents. During hydrocarbon production, pore pressure reduces and the effective stress of the rock matrix increases, which may lead to formation failure and consequently fine particles production within the formation fluids. Invasion of fine particles into proppant assemblies in a hydraulic fracture can clog the pore spaces between proppant particles and consequently lead to loss of fracture permeability and conductivity. Although fine particle migration and clogging in a proppant-supported hydraulic fracture is critical to effective production of hydrocarbons, the role of effective stress, proppant particle size, and proppant size distribution is still unclear. In this study, a discrete element method-lattice Boltzmann (DEM-LB) numerical framework was developed to study the mechanisms that regulate the migration and deposition of fine particles in a proppant-supported fracture, which is subjected to a closure pressure. Specifically, DEM was used to generate proppant assemblies and to simulate effective stress increase and the resultant proppant particle compaction. The DEM-simulated pore structure of the compacted proppant assembly was then extracted and imported into the LB simulator as internal boundary conditions of fluid flow modeling. Fine particle transport in the pore spaces was numerically simulated based on the LB-simulated pore flow field, and three transport mechanisms that regulate fine particle migration, including interception collection, Brownian motion, and gravitational settling, were accounted for. The numerical results of pore-scale particle tracking and deposition were fitted using a continuum-scale fine particle deposition model to determine the macroscopic deposition coefficient, as well as how fine particle size, proppant size heterogeneity, and effective stress influence the macroscopic deposition coefficient. Good agreement between numerically-simulated and correlation-predicted deposition coefficients was observed. The simulation results confirmed the non-monotonic change of fine particle deposition coefficient as a function of fine particle size. This study indicates that proppant assemblies having the same mean proppant diameter but a more heterogeneous proppant diameter distribution (i.e., a wider distribution of proppant diameter) favors fine particle migration through the pore space under low to moderate closure stresses. The developed simulation framework can be used to effectively model the migration and deposition of fine particles having varying sizes at the pore scale.

Influence of surface roughness on particle deposition distribution around multi-slot cabin supply air nozzles of commercial airplanes

Enhanced soiling due to particle deposition is often observed around multi-slot cabin supply air nozzles in commercial airplanes. This study aimed to investigate the influence of surface roughness on the particle deposition distribution around multi-slot cabin supply air nozzles of commercial airplanes. This investigation constructed a half-row cabin mockup installed with three 3D-printed supply air nozzles of a twin-aisle commercial airplane. A cutting method was proposed to measure the detailed particle deposition velocity distribution on the target surface of the nozzles covered by different grades of sandpaper with different roughness heights. This study also conducted numerical calculations for the particle deposition velocity distribution using an Eulerian particle deposition model. Both the experimental and modeling results show that strong particle deposition occurred on the cut samples near the slot dividers. When the surface roughness height was greater than or equal to 6 μm, the particle deposition velocity increased significantly with the surface roughness height. However, when the surface roughness height was less than or equal to 3 μm, the particle deposition velocity was relatively insensitive to the surface roughness. The analysis indicated that polishing the surfaces of cabin supply air nozzles may not effectively solve the problem of enhanced soiling in the aircraft cabin.

FALL3D-8.0: a computational model for atmospheric transport and deposition of particles, aerosols and radionuclides – Part 1: Model physics and numerics

Abstract. This paper presents FALL3D-8.0, the last version release of an open-source code with 15+ years of track record and a growing number of users in the volcanological and atmospheric communities. The code has been redesigned and rewritten from scratch in the framework of the EU Centre of Excellence for Exascale in Solid Earth (ChEESE) in order to overcome legacy issues and allow for successive optimisations in the preparation of the code towards extreme-scale computing. However, this baseline version already contains substantial improvements in terms of model physics, solving algorithms, and code accuracy and performance. The code, originally conceived for atmospheric dispersal and deposition of tephra particles, has been extended to model other types of particles, aerosols and radionuclides. The solving strategy has also been changed, replacing the former central-difference scheme for a high-resolution central-upwind scheme derived from finite volumes, which minimises numerical diffusion even in the presence of sharp concentration gradients and discontinuities. The parallelisation strategy, input/output (I/O), model pre-process workflows and memory management have also been reconsidered, leading to substantial improvements on code scalability, efficiency and overall capability to handle much larger problems. All these new features and improvements have implications on operational model performance and allow, among others, adding data assimilation and ensemble forecast in future releases. This paper details the FALL3D-8.0 model physics and the numerical implementation of the code.

Identification of the Model of Solid Particle Deposition in the Gravity Separator

The unsteady process of deposition of a solid particle in a stationary liquid in a gravity separator is considered. To describe this process, a mathematical model is proposed that takes into account the gravity of the particle, the buoyant force of Archimedes and the resistance force of the liquid described by the quadratic Newton’s law of resistance. Within the framework of the proposed model, the problem of identifying the resistance coefficient according to an additional given condition regarding the position of the particle in the separator at a fixed time is posed. To solve the problem, the analytical solution of the model is first determined, and then the resulting solution is substituted in an additional condition specified in the integral form. After integration, the identification problem is reduced to a nonlinear transcendental equation with respect to the desired resistance coefficient. The method of simple iteration is used for the numerical solution of the obtained nonlinear equation. Based on the proposed computational algorithm, numerical experiments were carried out for the model data

Numerical Investigation of the Deposition Characteristics of Snow on the Bogie of a High-Speed Train

To investigate the deposition distribution of snow particles in the bogie surfaces of a high-speed train, a snow particle deposition model, based on the critical capture velocity and the critical shear velocity, was elabo... | Find, read and cite all the research you need on Tech Science Press

Numerical modeling of particle deposition in the conducting airways of asthmatic children

Mounting evidence has linked long- and short-term exposure to particulate air pollution with the incidence and exacerbation of asthma in children, but the biological pathogenesis is unclear. We examined the deposition of particles in the airways of asthmatic children. A planar and symmetric model of airways for 4-year-old asthmatic children was considered. Airflow and particle deposition in the upper (G3-G6) and lower (G9-G12) conducting airways were numerically investigated using computation fluid dynamics (CFD) method. We considered the manifestation of moderate (30% reduction in airway diameter) and severe (60% reduction) asthma. Micron particles (1–10 µm) were considered. We found that particle deposition in the asthmatic children was significantly higher than that in healthy children. The deposition efficiency increased slowly with particle size for healthy children, but increased rapidly for asthmatic children, such that smaller particles could be deposited in the conducting airways of asthmatics. For healthy children, particles were deposited by inertial impaction and gravitational sedimentation respectively in the upper and lower airways, but deposited by inertial impaction in asthmatic children. The severity of the asthma increased the particle deposition in the airways. Our study indicated that asthmatic children were more susceptible to the effect of particulate air pollution. The constricted airways increased the particle deposition by inertial impaction, which may be the biological pathogenesis that causes the hospitalization of asthma in children. Avoiding exposure during air pollution events will be an effective measure to reduce the asthma attack.

Numerical model of particle deposition on wet fin surfaces of heat exchanger under dehumidifying conditions

Dusty particles may easily deposit on fin surfaces of heat exchangers under dehumidifying conditions and thus seriously deteriorate the heat transfer performance. The purpose of this study is to develop a numerical model for simulating the dusty particle deposition on wet fin surfaces in practical working processes, including the shape and mass of the deposited dusty particles in the process of particle-capturing by condensate water and that of particle adhesion on wet particulate layer. The prediction method of the dusty particle deposition in the process of particle-capturing by condensate water is to simulate the motion trajectories of all particles in the air flow at first and then to choose those particles intersecting with the water surface as deposited. The prediction method of the dusty particle deposition in the process of particle adhesion on wet particulate layer is to calculate the critical sticking velocity at first and then to choose those particles with the impact velocity being smaller than the critical sticking velocity as deposited. The validation results show that, the predicted shape of wet particulate layer agrees well with the experimental images, and the predicted mass of deposited particles agrees with 91% of the experimental data within a deviation of ±20% and the mean deviation is 11.8%. Prediction results of the quantitative influence of operation conditions with this model show that the parameters of inlet air relative humidity and particle concentration are the two most important factors on dusty particle deposition on wet fin surfaces.

Simulation of particle deposition in a plate-fin heat exchanger using a particle deposition model with a random function method

The particle deposition characteristics of plate-fin heat exchangers were studied using a particle deposition model with a random function method. The effects of the inlet velocity, particle size, and temperature difference on particle deposition and the distribution of the particles deposited in plate-fin heat exchangers were investigated. The simulation results showed that the thermal diffusion–induced motion of small particles was obvious at low velocities, the deposition of large particles was mainly limited by the critical velocity, there was a maximum deposition velocity in particle deposition and the maximum deposition velocity decreases with increasing particle size. Finally, large particles would rebound and deposit after secondary impacts. The temperature difference will increase the average deposition efficiency of 1 μm particles, and reduce the average deposition efficiency of 7 μm particles. The plate-fin heat exchanger should be designed with consideration for the particle size range and velocity seen in the intended application.

Improvement of particle deposition model using random function method

Particles in the environment not only threaten people's health, but the adhesion of particles on the equipment also threatens the safe operation of the equipment and the adhesion of particles in the heat exchange field also causes a large amount of energy waste. In this paper, the transportation and deposition processes of particles with different particle sizes were studied by numerical simulation. A random function method is introduced to improve the particle deposition model in order to consider the different characteristics between clean and fouled surfaces. As an example, the particle deposition characteristics of a two-dimensional channel were simulated using the clean surface model, fouling layer model, and random function method. The results show that as the particle size and inlet velocity increase, the gap between the three models increase. In particular, in the simulation of mixed particle size, the random function method better simulates the change in deposition rate during formation of fouling layer and the composition of fouling layer. Furthermore, the growth of the fouling was accelerated by the first layer of sediments, and the first layer of the sediments usually consisted of small particles.

Numerical modeling of particle motion and deposition in turbulent wavy channel flows

This work investigates the turbulent flow and particles deposition in wavy duct flows. The v2f turbulence model was used for simulating the turbulent flow through the wavy channel. The instantaneous turbulence fluctuating velocities were simulated using the Kraichnan Gaussian random field model. For tracking particles in the fluid flow, the particle equation of motion was solved numerically. The drag, Saffman lift, Brownian, and gravity forces acting on a suspended particle were included in the particle equation of motion. The effects of duct wave amplitude and wave length on deposition of particles of different sizes were studied. A range of waves with different amplitudes and wave lengths were simulated. The particle tracking approach was validated for turbulent flow in a flat horizontal channel where good agreement with previous studies was found. The presented results showed that the duct wavy walls significantly increase the particle deposition rate.

Optimization of the contamination particle deposition model based on humidity and surface energy

The research on contamination accumulation characteristics of insulators is the basis of pollution flashover prevention work. The porcelain three-umbrella insulator used in the wind tunnel test at North China Electric Power University was taken as the research object. Using simulation software COMSOL Multiphysics, the original pollution particle deposition model was optimized in progressively based on humidity and surface energy to simulate their effect on the contamination accumulation characteristics of the insulator used in the wind tunnel. Using the wind tunnel test results for reference, the simulation results showed that the average relative error of the two optimized models (based on humidity and surface energy) was reduced from 61.25% in the original model to 27.64% and 12.18%, respectively. The rationality of each optimization model was verified. The variation trend of the simulation results of the final optimized model with DC voltage was more similar to that observed in the test results, which could provide a reference for the simulation study of the natural pollution characteristics of the considered insulator.

The deposition characteristics of micron particles in heat exchange pipelines

Comprehensive understanding of particles deposition in heat exchange pipelines is significant for environment and energy engineering applications. In this study, a numerical simulation method was used to investigate the deposition characteristics of micron particles in heat exchange pipelines based on Reynolds stress model and discrete particle model. Based on previous research, an improved particle deposition model combined with particle rebound was presented. Moreover, the improved model was used to study the effect of thermophoretic force (hot wall and cold wall), flow velocity, and particle diameter on the non-dimensional deposition rate of particles. The results showed that the non-dimensional deposition rate increased with the increase of non-dimensional relaxation time and then approached a certain value. After introducing the particle rebound, the non-dimensional deposition rate exhibited different trend, i.e., first increasing and then decreasing. When the gas had significant temperature gradient in the boundary layer, the effect of thermophoretic force on small particles was found to be significantly stronger than that of large particles. Moreover, the higher the temperature gradient, the more obvious the thermophoretic force of the particles. The results indicated that the thermophoretic forces prevented the deposition of particles on the hot wall, and promoted this process on the cold wall. Furthermore, the flow velocity also significantly affected the particle deposition rate. At the same flow velocity, the particles non-dimensional deposition rate first increased and then decreased with the increase in the particle diameter, and it showed a different maximum at different flow velocities.

CFD modelling of air and particle flows in different airway models

Since complex structure of the human respiratory system leads to the profound effect of the air flow and particle deposition, a realistic and flexible airway model is crucial for predicting in vivo lung deposition of pharmaceutical aerosol. This work presented a CFD study of air and particle flows in a realistic parametrically controlled airway model developed by Kitaoka under different inspiratory conditions. The results were analysed with simulation data obtained in the classic Weibel airway (WA) model and compared with previous experimental and simulation studies. The comparison showed both difference and similarity between two models. The inspiratory airflow was symmetric in the WA model, whereas in the Kitaoka model non-symmetrical airflow was dominated throughout airways. The Kitaoka model, in comparison to the WA model, also showed more complicated particle deposition pattern with larger particle deposition efficiency. The flow rate, however, showed a similar effect to both models; i.e. generally particle deposition efficiency was higher as flowrate was higher. The Kitaoka model was then extended from 7 generations (KG7) to 11 generations (KG11) to study the effect of airway generation. The simulations showed little difference between two structures in terms of inspiratory air velocity and particle deposition efficiency. This suggests that the KG7 model is sufficiently structured to obtain realistic particle deposition pattern. The study demonstrates the Kitaoka model has a great potential in modelling lung deposition of particles under different conditions.

Modeling of the molten blast furnace slag particle deposition on the wall including phase change and heat transfer

The blast furnace slag with extremely high discharge temperature is a by-product in iron and steel production process. Dry granulation method based on rotary disk atomizer shows great advantages in recovering sensible heat of blast furnace slag. However, during flight process, molten particles may impact on the wall which would greatly affect the stability of the device and the overall heat transfer efficiency. Moreover, during the deformation process of molten slag with high temperature and complex components, its physical properties change dramatically. In the current study, combining the volume-of-fluid method and solidification/melting model to track the free interface and deal with the phase change respectively, a three-dimensional symmetrical model was constructed to simulate the thermal process of molten particle collision. The solidification temperature range and variable physical properties were taken into consideration. As the results, the temperature and velocity distributions, spread factor, solidification time were obtained. And the effects of diameter, initial temperature, impact velocity of particles and initial temperature of the wall on the process were discussed. It was represented that a single slag particle impacting on the wall underwent process of spreading, retracting, and stabilizing. Two dimensionless correlations were developed to predict deformation behavior of slag particle and the maximum value of wall shear stress. Furthermore, the sequential impact of two slag particles with the same diameter was investigated and splashing and remelting occurred.

REGRESSION OF THE NAVIER-STOKES EQUATION SOLUTIONS FOR PULMONARY AIRWAY FLOW USING NEURAL NETWORKS.

Computerized fluid dynamics models of particle deposition in the human airways are used to characterize deposition patterns that enable the study of lung diseases like asthma and chronic obstructive pulmonary disease (COPD). Despite this fact, the influence of patient-specific geometry on the deposition efficiency and patterns is not well documented nor modeled. In part, this is due to the complexity of simulating the full Computational Fluid Dynamics (CFD) solution in patient-specific airway geometries, a factor that becomes a major hurdle for patient-specific studies given the complexity of the geometry of human lungs and their related airflow. In this paper, we present an approximation method based on neural networks to the Navier-Stokes equations that govern airway flow in a Physiologically Realistic Bifurcation (PRB) model for the conducting region of a single generation human airway branch. The flow distribution and deposition of tobacco particles have been simulated for the inspiratory regime using ANSYS Fluent and a neural network has been trained to regress the mean velocity and mass flow components. Our results show that the approximation works well under the modeled assumptions and the serial application of this model to a two-generation airway geometry provides reasonable approximations.

Modeling the particle deposition in the respiratory system during successive respiratory cycles

In this study, using a 5-lobe symmetric model, total, lobar and generational particle deposition in the lungs during successive cycles is investigated. It has been found that for the particle size between 0.05 and 2 μm and the tidal volumes greater than 1000 ml, considering the effect of successive cycles predicted more deposition fraction per cycle compared to a single cycle up to about 16 percent. The mentioned range of tidal volume is related to light or heavy physical activities. So, it can be understood that people exposed to particulate matter within the mentioned size range, when acting physically, are at more health risk compared not only to the resting state, but also to the same state calculations based on a single cycle. Finally, total and generational remaining mass fraction suspended in the respiratory tract after the completion of each cycle is calculated. This remaining mass fraction turned out to be negligible except for particles between 0.05 and 2 μm.

Nanoparticle administration method in cell culture alters particle-cell interaction

As a highly interdisciplinary field, working with nanoparticles in a biomedical context requires a robust understanding of soft matter physics, colloidal behaviors, nano-characterization methods, biology, and bio-nano interactions. When reporting results, it can be easy to overlook simple, seemingly trivial experimental details. In this context, we set out to understand how in vitro technique, specifically the way we administer particles in 2D culture, can influence experimental outcomes. Gold nanoparticles coated with poly(vinylpyrrolidone) were added to J774A.1 mouse monocyte/macrophage cultures as either a concentrated bolus, a bolus then mixed via aspiration, or pre-mixed in cell culture media. Particle-cell interaction was monitored via inductively coupled plasma-optical emission spectroscopy and we found that particles administered in a concentrated dose interacted more with cells compared to the pre-mixed administration method. Spectroscopy studies reveal that the initial formation of the protein corona upon introduction to cell culture media may be responsible for the differences in particle-cell interaction. Modeling of particle deposition using the in vitro sedimentation, diffusion and dosimetry model helped to clarify what particle phenomena may be occurring at the cellular interface. We found that particle administration method in vitro has an effect on particle-cell interactions (i.e. cellular adsorption and uptake). Initial introduction of particles in to complex biological media has a lasting effect on the formation of the protein corona, which in turn mediates particle-cell interaction. It is of note that a minor detail, the way in which we administer particles in cell culture, can have a significant effect on what we observe regarding particle interactions in vitro.

CFD model of fluid flow and particle deposition during cryogenic condensation

Cryogenic condensation is an attractive option for controlling VOC emissions. Cryogenic condensation can offer lower operational costs than conventional abatement technologies like thermal oxidation and adsorption. At the low temperatures (ca. −100 °C) used in cryogenic condensation, many high melting point VOCs will freeze or desublimate. A fine particulate solid could form under the temperature gradients inside the condenser, becoming entrained in the gas phase on exit. This paper reports results in modelling the process using CFD. In this paper we present an inert DPM model in 3D and a dynamic DPM model in 2D to investigate this problem through CFD.The 3D results demonstrate particles must grow beyond a certain size to prevent entrainment in the outlet gas flow. These sizes are: 12 μm at 150 Nm³/h (Stk99% = 0.18 at Redh = 4600); 16 μm at 100 Nm³/h (Stk99% = 0.22 at Redh = 3000); 23 μm at 50 Nm³/h (Stk99% = 0.23 at Redh = 1500). The 2D results demonstrate a DPM model (Eulerian–Lagrangian model) of nucleation and growth of particles during cryogenic condensation.