302 research outputs found
Coarse-Grained Lattice Monte Carlo Simulations with Continuous Interaction Potentials
A coarse-grained lattice Metropolis Monte Carlo (CG-MMC) method is presented for simulating fluid systems described by standard molecular force fields. First, a thermodynamically consistent coarse-grained interaction potential is obtained numerically and automatically from a continuous force field such as Lennard-Jones. The coarse-grained potential then is used to driveCG-MMC simulations of vapor-liquid equilibrium in Lennard-Jones, square-well, and simple point chargewater systems. The CG-MMC predicts vapor-liquid phase envelopes, as well as the particle density distributions in both the liquid and vapor phases, in excellent agreement with full-resolution Monte Carlo simulations, at a fraction of the computational cost
Coarse-grained lattice kinetic Monte Carlo simulation of systems of strongly interacting particles
A general approach is presented for spatially coarse-graining lattice kinetic Monte Carlo (LKMC) simulations of systems containing strongly interacting particles. While previous work has relied on approximations that are valid in the limit of weak interactions, here we show that it is possible to compute coarse-grained transition rates for strongly interacting systems without a large computational burden. A two-dimensional square lattice is employed on which a collection of (supersaturated) strongly interacting particles is allowed to reversibly evolve into clusters. A detailed analysis is presented of the various approximations applied in LKMC coarse graining, and a number of numerical closure rules are contrasted and compared. In each case, the overall cluster size distribution and individual cluster structures are used to assess the accuracy of the coarse-graining approach. The resulting closure approach is shown to provide an excellent coarse-grained representation of the systems considered in this study
On-lattice kinetic Monte Carlo simulations of point defect aggregation in entropically influenced crystalline systems
An on-lattice kinetic Monte Carlo model of vacancy aggregation in crystalline silicon is parametrized using direct regression to evolution data from nonequilibrium molecular dynamics simulations. The approach bypasses the need to manually compute an energy barrier for each possible transition and leads to an excellent, robust representation of the molecular dynamics data. We show that the resulting lattice kinetic Monte Carlo model correctly captures the behavior of the real, continuous space system by properly accounting for continuous space entropic effects, which are often neglected in lattice-based models of atomistic processes. These contributions are particularly important at the high temperatures relevant to many steps in semiconductor materials processing
Confined jet mixing in the entrance of a tubular reactor
The equations for the conservation of momentum and mass were solved numerically for the region downstream from the exit of an axial jet into a confined annular stream of the same fluid. An implicit, alternating direction method was used. Numerical results were obtained for radius ratios of 0.281, 0.470, and 0.563 over a range of jet-to-annular velocities from 0.85 to 2.77. The values for the limiting case of the entrance region in pipe flow are in good agreement with the values of Christiansen and Lemmon and Ventras, Duda, and Bargeron. Solution of the equations for the conservation of chemical components produced results for component transfer in agreement with the experimental compositions obtained by Wood for jet mixing. Representative calculations were carried out for a chemical reaction. The results indicate the efficiency of the mixing process for this type of reactor. Experiments were carried out with water and dye to define the conditions under which the assumption of steady, laminar jet mixing is valid. The experiments also indicated the conditions and location of turbulent breakup of the jet.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/37362/1/690170338_ftp.pd
Software for analytical nonlinear controller design
Proceedings of the 2006 American Control Conference, pp. 4848-4853.This paper presents a new software package that
carries out symbolic manipulations to generate automatically
analytical, model-based controllers and subsequently test the
performance of the designed controller implemented on the
process model. The software package has a user-friendly
interface that was developed using Visual Basic and linked to
MATHEMATICA using MathLink. The user enters the
process model (set of ordinary differential and algebraic
equations), and the software generates an analytical modelbased
controller (set of ordinary differential and algebraic
equations), that can be in FORTRAN, C, or MATLAB format.
The application and implementation of the software package
are shown using a chemical reactor example
Novel insights into host-fungal pathogen interactions derived from live-cell imaging
Acknowledgments The authors acknowledge funding from the Wellcome Trust (080088, 086827, 075470 and 099215) including a Wellcome Trust Strategic Award for Medical Mycology and Fungal Immunology 097377 and FP7-2007â2013 grant agreement HEALTH-F2-2010-260338âALLFUN to NARG.Peer reviewedPublisher PD
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