Effect of Vacancy Defects on the Young's Modulus and Fracture Strength of Graphene: A Molecular Dynamics Study

The Young's modulus of graphene with various rectangular and circular vacancy defects is investigated by molecular dynamics simulation. By comparing with the results calculated from an effective spring model, it is demonstrated that the Young's modulus of graphene is largely correlated to the size of vacancy defects perpendicular to the stretching direction. And a linear reduction of Young's modulus with the increasing concentration of mono‐atomic‐vacancy defects (i.e., the slope of ?0.03) is also observed. The fracture behavior of graphene, including the fracture strength, crack initiation and propagation are then studied by the molecular dynamics simulation, the effective spring model, and the quantized fracture mechanics. The blunting effect of vacancy edges is demonstrated, and the characterized crack tip radius of 4.44 Å is observed.     

Solid deformation induced by the adsorption of methane and methanol under sub- and supercritical conditions

Carbonaceous materials with some degree of flexibility in their physical structure can expand or contract under the influence of the forces exerted by adsorbed molecules. To gain insight into how adsorption of non-polar and polar fluids could deform a carbon solid, we present GCMC simulations of sub- and supercritical adsorption of methane and methanol in slit-shaped pores whose walls are made of graphene layers. Our extensive simulation study shows that there is a strong correlation between solvation pressure and solid deformation, and that the expansion or contraction of the pore strongly depends on adsorbate loading, temperature and pore size.     

A vectorial algorithm with finite element method for prediction of powder segregation in metal injection molding

The design of the mold and the choice of the injection parameters for metal injection molding (MIM) is required to maintain homogeneity of the filled mixture. However, powder segregation is unavoidable in MIM because of the significant difference in densities of the metallic powder and the polymer binder. To achieve an effective prediction of segregation effect, a biphasic model based on mixture theory is employed. The viscous behaviors of each phase and the interaction coefficient between the flows of the two phases should be determined. The solution of two coupled Navier–Stokes equations results in a tremendous computation effort. The previous development of an explicit algorithm makes the biphasic simulation much faster than that of the classic methods. However, it is strongly desired to reduce or even eliminate the numerous global solutions for pressure fields at each time step. Hence, a new vectorial algorithm is proposed and developed to perform the simulation only by vectorial operations. It provides the anticipated efficiency in the simulation of biphasic modeling, and the advantage to use the classic elements of equal‐order interpolations. Some results produced by the two algorithms are compared with the experimental values to validate the new vectorial algorithm. Copyright © 2012 John Wiley & Sons, Ltd.     

Mechanical properties of twist grain boundaries in Cu

In a previous paper we studied the Young's and shear modulus of a high-angle twist grain boundary (5) in Cu, using the EAM, and related it to the uniaxial strain derivatives of single crystals. In this paper, we discuss elastic properties of ten additional twist grain boundaries, from 8.8–43.6°. The monolayer Young's modulus at each boundary was calculated and found to be 20–50% higher than the bulk value for all eleven boundaries for both csl and type1 structures. The monolayer shear modulus at each boundary was calculated and found to be 93–98% lower than the bulk value for six grain boundaries with csl structure and found to decrease with increasing twist angle. The critical shear stress was also calculated for eleven boundaries with csl structure and found to roughly decrease with increasing twist angle.     

A spectroscopic investigation of turbulence in magnetized plasmas

We present a spectroscopic investigation of turbulence in the Tore-Supra edge plasma, where deuterium spectral lines are found to exhibit a power-law behavior in their wings. Such a feature is not predicted by the equilibrium line broadening theory in the conditions of the edge plasma, where the thermal Stark effect is negligible. Therefore, the possible role of turbulence is investigated along two separate paths. Indeed, both the Stark and the Doppler profiles may differ significantly from the equilibrium profiles.     

Wavelet filtering to study mixing in 2D isotropic turbulence

This paper presents the application of coherent vortex simulation (CVS) filtering, based on an orthogonal wavelet decomposition of vorticity, to study mixing in 2D homogeneous isotropic turbulent flows. The Eulerian and Lagrangian dynamics of the flow are studied by comparing the evolution of a passive scalar and of particles advected by the coherent and incoherent velocity fields, respectively. The former is responsible for strong mixing and produces the same anomalous diffusion as the total flow, due to transport by the coherent vortices, while mixing in the latter is much weaker and corresponds to classical diffusion.     

Simulating Multivariate Extreme Value Distributions of Logistic Type

Methods are given for simulating from symmetric and asymmetric versions of the multivariate logistic distribution, and from other multivariate extreme value distributions based on the well known logistic model. We consider two general approaches. The first approach uses transformations to derive random variables with a joint distribution function from which it is easy to simulate. The second approach derives from a specification of conditionally independent marginal components, conditioning on positive stable random variables. This specification extends to models of nested or hierarchical type and leads to an efficient way of incorporating marginal censoring. The algorithms presented in Sections 2 and 3 are available on request from the author. They are also included in the R (Ihaka and Gentleman, 1996) package evd (Stephenson, 2002), which is available from http://www.maths.lancs.ac.uk/~stephena/.     

Evaluating Individual Market Power in Electricity Markets via Agent-Based Simulation

We use agent-based simulation in a coordination game to analyse the possibility of market power abuse in a competitive electricity market. The context of this was a real application to the England and Wales electricity market as part of a Competition Commission Inquiry into whether two particular generators could profitably influence wholesale prices. The research contributions of this paper are both in the areas of market power and market design policy issues for electricity markets, and in the methodological use of large industry-wide evolutionary simulation models.     

Speeding up the FMMR perfect sampling algorithm: A case study revisited

In a previous paper by the second author, two Markov chain Monte Carlo perfect sampling algorithms—one called coupling from the past (CFTP) and the other (FMMR) based on rejection sampling—are compared using as a case study the move‐to‐front (MTF) self‐organizing list chain. Here we revisit that case study and, in particular, exploit the dependence of FMMR on the user‐chosen initial state. We give a stochastic monotonicity result for the running time of FMMR applied to MTF and thus identify the initial state that gives the stochastically smallest running time; by contrast, the initial state used in the previous study gives the stochastically largest running time. By changing from worst choice to best choice of initial state we achieve remarkable speedup of FMMR for MTF; for example, we reduce the running time (as measured in Markov chain steps) from exponential in the length n of the list nearly down to n when the items in the list are requested according to a geometric distribution. For this same example, the running time for CFTP grows exponentially in n. © 2003 Wiley Periodicals, Inc. Random Struct. Alg., 2003     

Minimax estimators for location vectors in elliptical distributions with unknown scale parameter and its application to variance reduction in simulation

In this paper, we give an ever wider and new class of minimax estimators for the location vector of an elliptical distribution (a scale mixture of normal densities) with an unknown scale parameter. The its application to variance reduction for Monte Carlo simulation when control variates are used is considered. The results obtained thus extend (i) Berger's result concerning minimax estimation of location vectors for scale mixtures of normal densities with known scale parameter and (ii) Strawderman's result on the estimation of the normal mean with common unknown variance.Research partially supported by National Science Foundation, Grant #DMS 8901922.