A modified steepest descent method with applications to maximizing likelihood functions

In maximizing a non-linear function G(), it is well known that the steepest descent method has a slow convergence rate. Here we propose a systematic procedure to obtain a 1–1 transformation on the variables , so that in the space of the transformed variables, the steepest descent method produces the solution faster. The final solution in the original space is obtained by taking the inverse transformation. We apply the procedure in maximizing the likelihood functions of some generalized distributions which are widely used in modeling count data. It was shown that for these distributions, the steepest descent method via transformations produced the solutions very fast. It is also observed that the proposed procedure can be used to expedite the convergence rate of the first derivative based algorithms, such as Polak-Ribiere, Fletcher and Reeves conjugate gradient methods as well.     

Efficient stochastic FEM for flow in heterogeneous porous media. Part 1: random Gaussian conductivity coefficients

This paper is concerned with the development of efficient iterative methods for solving the linear system of equations arising from stochastic FEMs for single‐phase fluid flow in porous media. It is assumed that the conductivity coefficient varies randomly in space according to some given correlation function and is approximated using a truncated Karhunen–Loève expansion. Distinct discretizations of the deterministic and stochastic spaces are required for implementations of the stochastic FEM. In this paper, the deterministic space is discretized using classical finite elements and the stochastic space using a polynomial chaos expansion. The highly structured linear systems which result from this discretization mean that Krylov subspace iterative solvers are extremely effective. The performance of a range of preconditioned iterative methods is investigated and evaluated in terms of robustness with respect to mesh size and variability of the conductivity coefficient. An efficient symmetric block Gauss–Seidel preconditioner is proposed for problems in which the conductivity coefficient has a large standard deviation.The companion paper, herein, referred to as Part 2, considers the situation in which Gaussian random fields are transformed into lognormal ones by projecting the truncated Karhunen–Loève expansion onto a polynomial chaos basis. This results in a stochastic nonlinear problem because the random fields are represented using polynomial chaos containing terms that are generally nonlinear in the random variables. Copyright © 2013 John Wiley & Sons, Ltd.     

Influence of cell and LC parameters on the dynamics of STN liquid crystal displays

The dynamics of super-twisted nematic (STN) liquid crystal displays have rarely been studied. In this article, the dynamic response of STN is analysed in detail. The evolution of director configuration with time was obtained by solving Ericksen–Leslie hydrodynamic equations. The time varying midlayer tilt angle is presented as a measure of dynamic response. The influence on STN dynamics of cell parameters including pretilt angle, twist angle, cell thickness, and of material parameters including d/p, K ₂₂, K ₃₃, were studied.     

Studies on the electro-optical and the light-scattering properties of PDLC films with the size gradient of the LC droplets

Polymer dispersed liquid crystal (PDLC) films with the size gradient of the LC droplets were prepared based on the epoxy/acrylate hybrid polymer matrix. The ultraviolet (UV) intensity gradient was induced by the UV-absorbing dye over the thickness of the samples. Taking advantage of the difference between the epoxy monomers and acrylate monomers in polymerisation rates and the UV intensity gradient, the gradient distribution of the LC droplet size was formed in PDLC films. The effect of the size gradient of the LC droplets on the electro-optical and the light-scattering properties of PDLC films was investigated. The results showed that due to the size gradient distribution of the LC droplets, PDLC films could exhibit the strong light scattering in the UV-visible-near infrared (VIS-NIR) region. Consequently, it provides a potential approach for modulating NIR light transmittance.     

Amphiphilic gradient copolymers of 2‐methyl‐ and 2‐phenyl‐2‐oxazoline: self‐organization in aqueous media and drug encapsulation

Gradient (or pseudo‐diblock) copolymers were synthesized from 2‐methyl‐2‐oxazoline and 2‐phenyl‐2‐oxazoline monomer mixtures via cationic polymerization. The self‐assembling properties of these biocompatible gradient copolymers in aqueous solutions were investigated, in an effort to use the produced nanostructures as nanocarriers for hydrophobic pharmaceutical molecules. Dynamic and static light scattering as well as AFM measurements showed that the copolymers assemble in different supramolecular nanostructures (spherical micelles, vesicles and aggregates) depending on copolymer composition. Fluorescence spectroscopy studies revealed a microenvironment of unusually high polarity inside the nanostructures. This observation is related partly to the gradient structure of the copolymers. The polymeric nanostructures were stable with time. Their structural properties in different aqueous media—PBS buffer, RPMI solution—simulating conditions used in pharmacological/medicinal studies, have been also investigated and a composition dependent behavior was observed. Finally, the hydrophobic drug indomethacin was successfully encapsulated within the gradient copolymer nanostructures and the properties of the mixed aggregates were studied in respect to the initial copolymer assemblies. The produced aggregates encapsulating indomethacin showed a significant increase of their mass and size compared to original purely polymeric ones. © 2011 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem, 2012     

Two optimal Dai–Liao conjugate gradient methods

Two adaptive choices for the parameter of Dai–Liao conjugate gradient (CG) method are suggested. One of which is obtained by minimizing the distance between search directions of Dai–Liao method and a three-term CG method proposed by Zhang et al. and the other one is obtained by minimizing Frobenius condition number of the search direction matrix. Global convergence analyses are made briefly. Numerical results are reported; they demonstrate effectiveness of the suggested adaptive choices.     

Improvement of moving particle semi‐implicit method for simulation of progressive water waves

Precise simulation of the propagation of surface water waves, especially when involving breaking wave, takes a significant place in computational fluid dynamics. Because of the strong nonlinear properties, the treatment of large surface deformation of free surface flow has always been a challenging work in the development of numerical models. In this paper, the moving particle semi‐implicit (MPS) method, an entirely Lagrangian method, is modified to simulate wave motion in a 2‐D numerical wave flume preferably. In terms of consecutive pressure distribution, a new and simple free surface detection criterion is proposed to enhance the free surface recognition in the MPS method. In addition, a revised gradient model is deduced to diminish the effect of nonuniform particle distribution and then to reduce the numerical wave attenuation occurring in the original MPS model. The applicability and stability of the improved MPS method are firstly demonstrated by the calculation of hydrostatic problem. It is revealed that these modifications are effective to suppress the pressure oscillation, weaken the local particle clustering, and boost the stability of numerical algorithm. It is then applied to investigate the propagation of progressive waves on a flat bed and the wave breaking on a mild slope. Comparisons with the analytical solutions and experimental results indicate that the improved MPS model can give better results about the profiles and heights of surface waves in contrast with the previous MPS models. Copyright © 2017 John Wiley & Sons, Ltd.     

Implicit–explicit schemes for nonlinear nonlocal equations with a gradient flow structure in one space dimension

Nonlinear convection–diffusion equations with nonlocal flux and possibly degenerate diffusion arise in various contexts including interacting gases, porous media flows, and collective behavior in biology. Their numerical solution by an explicit finite difference method is costly due to the necessity of discretizing a local spatial convolution for each evaluation of the convective numerical flux, and due to the disadvantageous Courant–Friedrichs–Lewy (CFL) condition incurred by the diffusion term. Based on explicit schemes for such models devised in the study of Carrillo et al. a second‐order implicit–explicit Runge–Kutta (IMEX‐RK) method can be formulated. This method avoids the restrictive time step limitation of explicit schemes since the diffusion term is handled implicitly, but entails the necessity to solve nonlinear algebraic systems in every time step. It is proven that this method is well defined. Numerical experiments illustrate that for fine discretizations it is more efficient in terms of reduction of error versus central processing unit time than the original explicit method. One of the test cases is given by a strongly degenerate parabolic, nonlocal equation modeling aggregation in study of Betancourt et al. This model can be transformed to a local partial differential equation that can be solved numerically easily to generate a reference solution for the IMEX‐RK method, but is limited to one space dimension.     

Statistics of reaction progress variable and mixture fraction gradients of a pulverised coal jet flame using Direct Numerical Simulation data

The statistical behaviour of the variances, covariance and gradients of the reaction progress variable (c), and the mixture fraction (ξ) have been analysed in a pulverised coal jet flame using a three-dimensional carrier phase direct numerical simulation (DNS) dataset. It has been observed that the Favre-probability density functions (PDFs) of c and ξ can be parametrised by the standard β function. Furthermore, the log-normal distribution has been found to accurately represent |?c| and |?ξ|. It is also found that ?c and ?ξ remain aligned throughout the flame brush. Finally the joint PDF of |?c| and |?ξ| has been compared with the product of the PDF of |?c| and PDF of |?ξ| extracted from carrier phase DNS, and it has been found that |?c| and |?ξ| are not statistically independent in the case investigated.The bivariate log-normal distributions with and without correlation have also been considered, and the former is found to be in better agreement with the carrier phase DNS data.