Multicomponent fluid dynamics

Klimenko, A. Y. (1990). Multicomponent diffusion of various admixtures in turbulent flow. Fluid Dynamics 25, 327-334. 

Raffaella Ocone and Gianni Astarita, Kinetics and Thermodynamics in Multicomponent Mixtures Arvind Varma, Alexander S. Rogachev, Alexandra S. Mukasyan, and Stephen Hwang, Combustion Synthesis of Advanced Materials Principles and Applications J. A. M. Kuipers and W. P. Mo, van Swaaij, Computional Fluid Dynamics Applied to Chemical Reaction Engineering... 

The typical epi silicon reactor operates in the diffusion-controlled regime at high rates of deposition. The behavior of such a reactor is governed by the fluid dynamics of multicomponent gases. The gas phase reactions discussed in Chapter 1 are generally neglected. 

The linearized transport equations (7), the equations for the equilibrium time correlation functions (13), and the equation for collective mode spectrum (14) form a general basis for the study of the dynamic behavior of a multicomponent fluid in the memory function formalism. 

The basic fluid dynamics and heat- and mass-transfer processes for multicomponent condensation are poorly understood, and the computation is difficult available design methods are both heuristic and feasible only for computer solution. The basic model was developed by Silver [42] and put in more general form by Bell and Ghaly [43]. Computer-based design methods that have been validated against experimental data are commercially available. 

STUDIES IN THE KINEMATICS OF ISOTHERMAL DIFFUSION. A MACRO-DYNAMICAL THEORY OF MULTICOMPONENT FLUID DIFFUSION... 

Filippov, L.K., Coherent and incoherent frontal patterns of multicomponent adsorption dynamics for variable linear fluid velocity in the fixed bed Frontal patterns for linear adsorption isotherms. Chem. Eng. Sci., 49(20), 3499-3510(1994). 

The Eulerian equations of motion are more useful for numerical solution of highly distorted fluid flow than are Lagrangian equations of motion. Multicomponent Eulerian calculations require equations of state for mixed cells and methods for moving mass and its associated state values into and out of mixed cells. These complications are avoided by Lagrangian calculations. Harlow s particle-in-cell (PIC) method uses particles for the mass movement. The first reactive Eulerian hydrodynamic code EIC (Explosive-in-cell) used the PIC method, and it is described in reference 2. The discrete nature of the mass movement introduced pressure and temperature variations from cycle to cycle of the calculation that were unacceptable for many reactive fluid dynamic problems. A one-component continuous mass transport Eulerian code developed in 1966 proved useful for solving many one-component problems of interest in reactive fluid dynamics. The need for a multicomponent Eulerian code resulted in a second 2DE code, described in reference 4. Elastic-plastic flow and real viscosity were added in 1976. The technique was extended to three dimensions in the 1970 s and the resulting 3DE code is described in Appendix D. 

Laradji M, Hore MJA. Nanospheres in phase-separating multicomponent fluids a three-dimensional dissipative particle dynamics simulation. J Chem Phys 2004 121 10641-8. 

At present, computational fluid dynamics methods are finding many new and diverse applications in bioengineering and biomimetics. For example, CFD techniques can be used to predict (1) velocity and stress distribution maps in complex reactor performance studies as well as in vascular and bronchial models (2) strength of adhesion and dynamics of detachment for mammalian cells (3) transport properties for nonhomogeneous materials and nonideal interfaces (4) multicomponent diffusion rates using the Maxwell-Stefan transport model, as opposed to the limited traditional Fickian approach. 

Van Vlimmeren, B.A.C., Fraaije, J.G.E.M. Calculation of noise distribution in mesoscopic dynamics models for phase-separation of multicomponent complex fluids. Comput. Phys. Comm. 99 (1996) 21-28. 

Phase transitions in two-dimensional layers often have very interesting and surprising features. The phase diagram of the multicomponent Widom-Rowhnson model with purely repulsive interactions contains a nontrivial phase where only one of the sublattices is preferentially occupied. Fluids and molecules adsorbed on substrate surfaces often have phase transitions at low temperatures where quantum effects have to be considered. Examples are molecular layers of H2, D2, N2 and CO molecules on graphite substrates. We review the path integral Monte Carlo (PIMC) approach to such phenomena, clarify certain experimentally observed anomalies in H2 and D2 layers, and give predictions for the order of the N2 herringbone transition. Dynamical quantum phenomena in fluids are analyzed via PIMC as well. Comparisons with the results of approximate analytical theories demonstrate the importance of the PIMC approach to phase transitions where quantum effects play a role. 

Here va and va are the stoichiometric coefficients for the reaction. The formulation is easily extended to treat a set of coupled chemical reactions. Reactive MPC dynamics again consists of free streaming and collisions, which take place at discrete times x. We partition the system into cells in order to carry out the reactive multiparticle collisions. The partition of the multicomponent system into collision cells is shown schematically in Fig. 7. In each cell, independently of the other cells, reactive and nonreactive collisions occur at times x. The nonreactive collisions can be carried out as described earlier for multi-component systems. The reactive collisions occur by birth-death stochastic rules. Such rules can be constructed to conserve mass, momentum, and energy. This is especially useful for coupling reactions to fluid flow. The reactive collision model can also be applied to far-from-equilibrium situations, where certain species are held fixed by constraints. In this case conservation laws... 

The lattice Boltzmann method is a mesoscopic simulation method for complex fluid systems. The fluid is modeled as fictitious particles, and they propagate and coUide over a discrete lattice domain at discrete time steps. Macroscopic continuum equations can be obtained from this propagation-colhsion dynamics through a mathematical analysis. The particulate nature and local d3mamics also provide advantages for complex boundaries, multiphase/multicomponent flows, and parallel computation. 

We discuss current computational trends (beyond Mechanistic ID Models) related to flow assurance problems in the oil and gas sector. The developments needed to bring advanced Computational Fluid Multi-VXuid Dynamics (CFD CA/FD) techniques and models to a mature stage will also be discussed. The contribution presents the possibilities offered today by these simulation technologies to treat complex, multiphase multicomponent flow problems occurring in the gas and petroleum engineering. Examples of various degrees of sophistication will be presented. 

The MPCD method has been generalized to modd multiphase flows, viscodastic fluids, nonideal fluids, and multicomponent mixtures with a consolute point. It should be noted that in contrast to methods such as MD or DPD, which approximate the continuous-time dynamics of a system, the time step At in MPCD does not have to be small. As a result, MPCD simulations allow to explore larger timescales than DPD. 

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