A methodology for high performance computation of fully inhomogeneous turbulent flows

A large‐eddy simulation methodology for high performance parallel computation of statistically fully inhomogeneous turbulent flows on structured grids is presented. Strategies and algorithms to improve the memory efficiency as well as the parallel performance of the subgrid‐scale model, the factored scheme, and the Poisson solver on shared‐memory parallel platforms are proposed and evaluated. A novel combination of one‐dimensional red–black/line Gauss–Seidel and two‐dimensional red–black/line Gauss–Seidel methods is shown to provide high efficiency and performance for multigrid relaxation of the Poisson equation. Parallel speedups are measured on various shared‐distributed memory systems. Validations of the code are performed in large‐eddy simulations of turbulent flows through a straight channel and a square duct. Results obtained from the present solver employing a Lagrangian dynamic subgrid‐scale model show good agreements with other available data. The capability of the code for more complex flows is assessed by performing a large‐eddy simulation of the tip‐leakage flow in a linear cascade. Copyright © 2006 John Wiley & Sons, Ltd.     

Self-focusing of electromagnetic waves in a magnetoplasma

The steady state self-focusing of a Gaussian electromagnetic beam in a magneto-plasma has been studied. On a short time scale, a non-linearity in the dielectric constant of a plasma appears due to the ponderomotive force. This force in the case of the extraordinary mode has opposite signs forω>ω _c andω<ω _c, whereω _c is the electron cyclotron frequency. The self-focusing due to this effect is predicted at frequencies except forω _c /2<ω<ω _c . The focusing of the ordinary mode is adversely affected by the magnetic field. On a larger time scale, the non-uniform heating of electrons by the beam and the resulting redistribution of the electron density is a source of non-linearity. This non-local non-linearity is several orders of magnitude higher than the ponderomotive non-linearity. We predict self-focusing of the extraordinary mode only above the gyroresonance (ω>ω _c ), while the ordinary mode can be focused at all frequencies.     

An FPTAS for optimizing a class of low-rank functions over a polytope

We present a fully polynomial time approximation scheme (FPTAS) for optimizing a very general class of non-linear functions of low rank over a polytope. Our approximation scheme relies on constructing an approximate Pareto-optimal front of the linear functions which constitute the given low-rank function. In contrast to existing results in the literature, our approximation scheme does not require the assumption of quasi-concavity on the objective function. For the special case of quasi-concave function minimization, we give an alternative FPTAS, which always returns a solution which is an extreme point of the polytope. Our technique can also be used to obtain an FPTAS for combinatorial optimization problems with non-linear objective functions, for example when the objective is a product of a fixed number of linear functions. We also show that it is not possible to approximate the minimum of a general concave function over the unit hypercube to within any factor, unless P = NP. We prove this by showing a similar hardness of approximation result for supermodular function minimization, a result that may be of independent interest.     

Multiobjective expected value model for portfolio selection in fuzzy environment

In this paper, we propose a credibilistic framework for portfolio selection problem using an expected value multiobjective model with fuzzy parameters. We consider short term return, long term return, risk and liquidity as key financial criteria. A solution procedure comprising fuzzy goal programming and fuzzy simulation based real-coded genetic algorithm is developed to solve the model. The proposed solution approach is considered advantageous particularly for the cases where the fuzzy parameters of the problem may assume any general functional form. An empirical study is included to illustrate the usefulness of the proposed model and solution approach in real-world applications of portfolio selection.     

Ion‐Specific Assembly of Strong,Tough, and Stiff Biofibers

Designing engineering materials with high stiffness and high toughness is challenging as stiff materials tend to be brittle. Many biological materials realize this objective through multiscale (i.e., atomic‐ to macroscale) mechanisms that are extremely difficult to replicate in synthetic materials. Inspired from the architecture of such biological structures, we here present flow‐assisted organization and assembly of renewable native cellulose nanofibrils (CNFs), which yields highly anisotropic biofibers characterized by a unique combination of high strength (1010 MPa), high toughness (62 MJ m^?3) and high stiffness (57 GPa). We observed that properties of the fibers are primarily governed by specific ion characteristics such as hydration enthalpy and polarizability. A fundamental facet of this study is thus to elucidate the role of specific anion binding following the Hofmeister series on the mechanical properties of wet fibrillar networks, and link this to the differences in properties of dry nanostructured fibers. This knowledge is useful for rational design of nanomaterials and is critical for validation of specific ion effect theories. The bioinspired assembly demonstrated here is relevant example for designing high‐performance materials with absolute structural control.