Mesoscopic simulations

Greet R D and Warren P B 1997 Dissipative particle dynamics bridging the gap between atomistic and mesoscopic simulation J. Chem. Phys. 107 4423-35... 

Groot R D and P B Warren 1997. Dissipative Particle Dynamics Bridging the Gap Between Atomist and Mesoscopic Simulation. Journal of Chemical Physics 107 4423-4435. 

It is the interplay of universal and material-specific properties which causes the interesting macroscopic behavior of macromolecular materials. This introduction will not consider scales beyond the universal or scaling regime, such as finite element methods. First we will give a short discussion on which method can be used under which circumstances. Then a short account on microscopic methods will follow. The fourth section will contain some typical coarse-grained or mesoscopic simulations, followed by some short general conclusions. 

Short-time Brownian motion was simulated and compared with experiments [108]. The structural evolution and dynamics [109] and the translational and bond-orientational order [110] were simulated with Brownian dynamics (BD) for dense binary colloidal mixtures. The short-time dynamics was investigated through the velocity autocorrelation function [111] and an algebraic decay of velocity fluctuation in a confined liquid was found [112]. Dissipative particle dynamics [113] is an attempt to bridge the gap between atomistic and mesoscopic simulation. Colloidal adsorption was simulated with BD [114]. The hydrodynamic forces, usually friction forces, are found to be able to enhance the self-diffusion of colloidal particles [115]. A novel MC approach to the dynamics of fluids was proposed in Ref. 116. Spinodal decomposition [117] in binary fluids was simulated. BD simulations for hard spherocylinders in the isotropic [118] and in the nematic phase [119] were done. A two-site Yukawa system [120] was studied with... 

Since MPC dynamics yields the hydrodynamic equations on long distance and time scales, it provides a mesoscopic simulation algorithm for investigation of fluid flow that complements other mesoscopic methods. Since it is a particle-based scheme it incorporates fluctuations, which are essential in many applications. For macroscopic fluid flow averaging is required to obtain the deterministic flow fields. In spite of the additional averaging that is required the method has the advantage that it is numerically stable, does not suffer from lattice artifacts in the structure of the Navier-Stokes equations, and boundary conditions are easily implemented. 

Since hydrodynamic interactions are included in MPC dynamics, the collective motion of many self-propelled objects can be studied using this mesoscopic simulation method. 

The basic model has already been extended to treat more complex phenomena such as phase separating and immiscible mixtures. These developments are still at an early stage, both in terms of the theoretical underpinnings of the models and the applications that can be considered. Further research along such lines will provide even more powerful mesoscopic simulation tools for the study of complex systems. 

Y. Inoue, Y. Chen, and H. Ohashi, A mesoscopic simulation model for immiscible multiphase fluids, J. Comput. Phys. 201, 191 (2004). 

Y. Inoue, S. Takagi, and Y. Matsumoto, A mesoscopic simulation study of distributions of droplets in a bifurcating channel, Comp. Fluids 35, 971 (2006). 

Groot, R. D. and Rabone, K. L. (2001). Mesoscopic simulation of cell membrane damage, morphology change and rupture by nonionic surfactants, Biophys. J., 81, 725-736. 

Dickinson, E., Krishna, S. (2001). Aggregation in a concentrated model protein system a mesoscopic simulation of p-casein self-assembly. Food Hydrocolloids, 15, 107-115. 

Groot, R.D. (2000). Mesoscopic simulation of polymer-surfactant aggregation. Langmuir, 16, 7493-7502. 

Simulation techniques suitable for the description of phenomena at each length-scale are now relatively well established Monte Carlo (MC) and Molecular Dynamics (MD) methods at the molecular length-scale, various mesoscopic simulation methods such as Dissipative Particle Dynamics (Groot and Warren, 1997), Brownian Dynamics, or Lattice Boltzmann in the colloidal domain, Computational Fluid Dynamics at the continuum length-scale, and sequential-modular or equation-based methods at the unit operation/process-systems level. 

The correlation between rheology and thermodynamics is likely to prove a fruitful area for investigation in the future. Very little is as yet known about the detailed mechanisms of non-linear viscoelastic flows, such as those involved in large-amplitude oscillatory shear. Mesoscopic modelling will no doubt throw light on the role of defects in such flows. This is likely to involve both analytical models, and mesoscopic simulation techniques such as Lattice... 

Clark AT, Lai M, Ruddock JN, Warren PB (2000) Mesoscopic simulation of drops in gravitational and shear fields. Langmuir 16 6342-6350... 

A comparison of mesoscopic simulation methods with MD simulations has been performed by Denniston and Robbins.423 They study a binary mixture of simple Lennard-Jones fluids and map out the required parameters of the mesoscopic model from their MD simulation data. Their mapping scheme is more complete than those of previous workers because in addition to accounting for the interfacial order parameter and density profiles, they also consider the stress. Their mapping consists of using MD simulations to parameterise the popular mesoscale Lattice Boltzmann simulation technique and find that a... 

ABSTRACT It is very important to determine the thermal and mechanical parameters of mortar and concrete in mesoscopic simulation. In this paper, on the basis of the Mori-Tanaka formula of mesoscopic mechanics and the concrete is treated as a two-phase composite material constituted by aggregates and mortar, the inversion of coefficient of thermal expansion, autogenous shrinkage, elastic modulus and creep were studied. This paper proposed some inversion formulas regarding these four mechanical parameters of mortar in concrete. The accuracy of these formulas was verified by FEM numerical test and demonstrated by some examples. 

Until now, much research work has been done on the prediction of composite material coefficient of thermal expansion and elastic modulus by forefathers, and many prediction methods have been developed such as the sparse method (Guanhn Shen, et al. 2006), the Self-Consistent Method (Hill R.A. 1965), the Mori-Tanaka method (Mori T, Tanaka K. 1973) and so on. However, none of these formulas take into account the parameters variation with concrete age, and there is little research on the autogenous shrinkage and creep. In the mesoscopic simulation of concrete, thermal and mechanical parameters of mortar and aggregate (coefficient of thermal expansion, autogenous shrinkage, elasticity modulus, creep, strength) are important input parameters. In fact, there is abundant of test data on concrete, but much less data on mortar while it is one of the important components. Also parameter inversion is an essential method to obtain the data, but there are few studies on this so far. 

Mesoscopic simulation of drops in gravitational and shear fields. Langmuir... 

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. 

Mesoscopic simulations have been applied to understand phase separation in polymer blends and in polymer/nanofiller mixtures. 

Ayton G, Voth GA (2002) Bridging microscopic and mesoscopic simulations of lipid bilayers. Biophys J 83(6) 3357-3370... 

Kainourgiakis M E, Steriotis T A, Kikkinides E S et al (2005) Combinatitm of small angle nentron scattering data and mesoscopic simulation techniques as a tool for the structural characterization and prediction of... 

K. R. Sharma, Mesoscopic Simulation and Entropic Difference Model for Glass Transition Temperature of Partially Miscible Copolymers in Blends, 1999, ANTEC, New York. 

On the mesoscopic level of theory, the kinetic coefficients are input parameters for mesoscopic simulations they can be... 

Mesoscopic Simulations of Protein Adsorption at Different Surfaces 128... 

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