Particle deposition computational models

Elimelech, M., Gregory, J., Jia, X., and Williams, R., Particle Deposition and Aggregation Measurement, Modelling and Simulation, Butterworth-Heinemann, Oxford, England, 1995. (Graduate and research levels. A state-of-the-art treatment of deposition of colloidal particles and their dependence on colloidal forces. Includes theoretical, computational, and experimental approaches.)... 

The electrostatic effects on particle deposition illustrated by computational simulation may have implications on charged aerosol delivery. However, more clinical research is needed since these models have not been validated hitherto by in vivo data using charged aerosols. 

Oldham MJ, Phalen RF, Heistracher T. Computational fluid dynamics predictions and experimental results for particle deposition in an airway model. Aerosol Sci Technol 2000 32 61-71. 

Results of recent theoretical and computer simulation studies of phase transitions in monolayer films of Lennard-Jones particles deposited on crystalline solids are discussed. DiflFerent approaches based on lattice gas and continuous space models of adsorbed films are considered. Some new results of Monte Carlo simulation study for melting and ordering in monolayer films formed on the (100) face of an fee crystal are presented and confronted with theoretical predictions. In particular, it is demonstrated that the inner structure of solid films and the mechanism of melting transition depend strongly on the effects due to the periodic variation of the gas - solid potential. 

Freund and co-workers [253,254] showed by XPS and IR spectroscopy that deposition of Rh particles on hydroxylated alumina entailed a consiunption of surface OH groups. Simultaneously, XPS showed a stabilization of the Rh3J level by 0.3 eV (relative to the value of Rh particles on a OH-free surface). This finding can be rationalized by a direct chemical interaction of the metal particles with surface OH groups, including oxidation of some of the atoms to Rh, in line with trends of our computational models. 

Hosker, R. R and S. E. Lindberg (1989) Review Atmospheric deposition and plant assimilation of gases and particles. Atmospheric Environment 5, 889-920 Hough, A. M. and R. G. Derwent (1987) Computer modelling studies of the distribution of photochemical ozone production between different hydrocarbons. Atmospheric Environment 21, 2015-2034... 

Despite a number of studies on particle deposition in human lung, the Brownian diffusion and turbulent dispersion effects were generally ignored in the earlier computational models. Martonen et al. pointed out that the flow disturbances... 

Inhaled particles that are deposited on alveolar surfaces reduce their effective area, could cause significant damages to the surrounding tissues, and may even lead to cancer and serious heart problems. In this section, the process of particulate pollutant deposition in alveolar cavities is reviewed. Particular attention is given to computational modeling approach. 

In this chapter, fundamentals of particle transport, deposition, and removal were reviewed, and some of their biomedical applications were described. Particular attention was given to recent advances in computational modeling of nano and microparticle transport and deposition in human airways. Transport and deposition processes in lung bifurcations, nose and oral passages, as well as in alveolar cavities were discussed. Rheological properties of blood are also discussed, and sample simulation results are presented. The presented results showed the following ... 

Zhang, Z. and Kleinstreuer, C. (2004). Airflow Structures and Nano-Particle Deposition in a Human Upper Airway Model. J. Comput. Phys., Vol. 198, pp. 178-210. 

Ahmadi and McLaughlin describe biomedical applications of particle transport and deposition. Special attention is given to recent advances in the use of computational models for predicting the transport, dispersion, and deposition of particles in the human airway passages. These include airflow and particle transport in the nose, oral airways, lung bifurcation, and alveolar cavities. In addition, an overview of advances in blood flow simulations in various arteries is presented. 

The hydrodynamic forces acting on the suspended colloids determine the rate of cake buildup and therefore the fluid loss rate. A simple model has been proposed in literature [907] that predicts a power law relationship between the filtration rate and the shear stress at the cake surface. The model shows that the cake formed will be inhomogeneous with smaller and smaller particles being deposited as the filtration proceeds. An equilibrium cake thickness is achieved when no particles small enough to be deposited are available in the suspension. The cake thickness as a function of time can be computed from the model. 

A complete model for the description of plasma deposition of a-Si H should include the kinetic properties of ion, electron, and neutral fluxes towards the substrate and walls. The particle-in-cell/Monte Carlo (PIC/MC) model is known to provide a suitable way to study the electron and ion kinetics. Essentially, the method consists in the simulation of a (limited) number of computer particles, each of which represents a large number of physical particles (ions and electrons). The movement of the particles is simply calculated from Newton s laws of motion. Within the PIC method the movement of the particles and the evolution of the electric field are followed in finite time steps. In each calculation cycle, first the forces on each particle due to the electric field are determined. Then the... 

This filtration theory and a local re-computation of the evolving unit-cell geometry due to deposition of particles (Fig. 13) was employed and a transient filtration model has been derived and tested with very good success against experimental data with ceramic, metallic and fibrous filters (Bissett and Shadman, 1985 Zarvalis et al., 2003). In addition, the same unit-cell-based... 

The FSCBG aerial spray computer program is the result of more than a decade of refinement and verification of spray dispersion models used by the USDA Forest Service and the U. S. Army for predicting the drift, deposition and canopy penetration of particles and drops downwind from aircraft releases. This paper describes the mathematical framework of the models and selected applications of the models to military and Forest Service projects. 

Computer simulation is now used extensively as a tool to help to understand and predict the transport of radionuclides through environmental systems. Most models relate to waste disposal and are based on measured parameters such as water movements, salinity, suspended load and the radionuclide concentration in the solute, suspended particulate matter and bottom deposits. Comparatively few attempts appear to have been made to include chemical speciation into this type of model, presumably because of the added complexity involved. Some modellers have attempted to take into account the characteristics of the major chemical phases such as those present in different particles or coatings (e.g. Martinez-Aquirre et al., 1994). Others have noted the importance of including details of particular chemical species present in industrial waste releases when constructing models to predict dispersion (Abril and Fraga, 1996). 

Equations (33) - (35) are taken from Tardos et al (23), and are based on a low Reynold s number analysis. Eqn. (33) is the result of a "best-fit" of the theoretically computed values taken from Figure 7 of that same work. Similarly, Eqn. (36) for the electrical deposition, is obtained from a "best-fit" of the theoretically computed values taken from Figure 3 of Tardos and Pfeffer (21). Note that if the particle and collector charges are of the same sign, the electrical deposition efficiency becomes the negative of Eqn. (36). Consistent with the flow field models used in the development of Eqns. (33) - (36), the velocity employed is an assembly averaged velocity for each phase. For the multi-phase situation that exists in the fluidized bed, this is given by the superficial or empty-tower velocity divided by the phase volume fraction, ... 

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