瑞利-泰勒不稳定性中尺度效应的数值模拟研究

 瑞利-泰勒不稳定性是一种由于密度梯度引起的界面不稳定性，在惯性约束聚变中具有重要的意义。利用被动标量输运模型对包含不同尺度初始扰动的界面演化过程进行数值模拟。计算结果表明界面的初始形状对不稳定性的发展具有很大的影响，狭长型扰动比正方型扰动发展慢。另外，不同尺度扰动的相互作用一般会减小沿界面发展方向运动的动能，使能量更多地用于平行于界面方向的运动。     

A concept of multi-scale modeling for radiative heat transfer in particle polydispersions

To take the local thermal nonequilibrium between particles and the nonuniformity of temperature within a single particle into account, a concept of multi-scale modeling of radiative transfer is presented. Particles are considered to interact with thermal radiation on both micro-scale of a single particle and meso-scale of a particle cell to produce radiative source term at the local or meso-scale level of a particle cell for the modeling of radiative transfer at macro-scale of overall particle system. The accurate modeling of radiative transfer in particle polydispersions are related to the modeling of radiative transfer in following three different scales: macro-scale of the overall particle system, meso-scale of particle cell, and micro-scale of single particle. Two examples are taken to show the necessity of multi-scale modeling for radiative transfer in particle polydispersions. The results show that omitting local thermal nonequilibrium and nonuniformity will result in errors for the solution of radiative heat transfer to some extent, and the multi-scale modeling is necessary for the radiative transfer in particle system with large local thermal nonequilibrium and nonuniformity.     

Multi-scale analysis in elasto-viscoplasticity coupled with damage

The purpose of this study is to present a micromechanical approach, based on the transformation field analysis (TFA), proposed by Dvorak, which has been generalized at Onera in order to analyze the nonlinear behavior of heterogeneous materials in elasto-viscoplasticity coupled with damage. In such analysis, the macroscopic constitutive equations are not purely phenomenological but are built up from multi-scale approaches starting from the knowledge of the properties of the constituents at the microscopic or mesoscopic scales. The model can take into account some local characteristics that can evolve during the thermo-mechanical applied loads or the manufacturing process, like the grain size for metallic alloys or the fiber volume fraction for composites.The determination of some specific tensors which are present in this formulation is closely linked to the microstructure morphology of heterogeneous materials constituting the macroscopic structure. For example, an Eshelby’s based approach is more appropriate to characterize polycrystalline materials with a random microstructure, while the homogenization of periodic media technique can be used for composite materials with a sufficiently regular microstructure. The proposed methodologies allowing to perform this nonlinear analysis across the scales are illustrated with examples based on the behavior of structures reinforced with a long fiber unidirectional metal matrix composite.     

A bridging technique to analyze the influence of boundary conditions on instability patterns

In this paper, we present a new numerical technique that permits to analyse the effect of boundary conditions on the appearance of instability patterns. Envelope equations of Landau–Ginzburg type are classically used to predict pattern formation, but it is not easy to associate boundary conditions for these macroscopic models. Indeed, envelope equations ignore boundary layers that can be important, for instance in cases where the instability starts first near the boundary. In this work, the full model is considered close to the boundary, an envelope equation in the core and they are bridged by the Arlequin method [1]. Simulation results are presented for the problem of buckling of long beams lying on a non-linear elastic foundation.     

An energy- and charge-conserving,implicit, electrostatic particle-in-cell algorithm

This paper discusses a novel fully implicit formulation for a one-dimensional electrostatic particle-in-cell (PIC) plasma simulation approach. Unlike earlier implicit electrostatic PIC approaches (which are based on a linearized Vlasov–Poisson formulation), ours is based on a nonlinearly converged Vlasov–Ampére (VA) model. By iterating particles and fields to a tight nonlinear convergence tolerance, the approach features superior stability and accuracy properties, avoiding most of the accuracy pitfalls in earlier implicit PIC implementations. In particular, the formulation is stable against temporal (Courant–Friedrichs–Lewy) and spatial (aliasing) instabilities. It is charge- and energy-conserving to numerical round-off for arbitrary implicit time steps (unlike the earlier “energy-conserving” explicit PIC formulation, which only conserves energy in the limit of arbitrarily small time steps). While momentum is not exactly conserved, errors are kept small by an adaptive particle sub-stepping orbit integrator, which is instrumental to prevent particle tunneling (a deleterious effect for long-term accuracy). The VA model is orbit-averaged along particle orbits to enforce an energy conservation theorem with particle sub-stepping. As a result, very large time steps, constrained only by the dynamical time scale of interest, are possible without accuracy loss. Algorithmically, the approach features a Jacobian-free Newton–Krylov solver. A main development in this study is the nonlinear elimination of the new-time particle variables (positions and velocities). Such nonlinear elimination, which we term particle enslavement, results in a nonlinear formulation with memory requirements comparable to those of a fluid computation, and affords us substantial freedom in regards to the particle orbit integrator. Numerical examples are presented that demonstrate the advertised properties of the scheme. In particular, long-time ion acoustic wave simulations show that numerical accuracy does not degrade even with very large implicit time steps, and that significant CPU gains are possible.     

A new electromagnetic particle-in-cell model with adaptive mesh refinement for high-performance parallel computation

A new electromagnetic particle-in-cell (EMPIC) model with adaptive mesh refinement (AMR) has been developed to achieve high-performance parallel computation in distributed memory system. For minimizing the amount and frequency of inter-processor communications, the present study uses the staggering grid scheme with the charge conservation method, which consists only of the local operations. However, the scheme provides no numerical damping for electromagnetic waves regardless of the wavenumber, which results in significant noise in the refinement region that eventually covers over physical signals. In order to suppress the electromagnetic noise, the present study introduces a smoothing method which gives numerical damping preferentially for short wavelength modes. The test simulations show that only a weak smoothing results in drastic reduction in the noise, so that the implementation of the AMR is possible in the staggering grid scheme. The computational load balance among the processors is maintained by a new method termed the adaptive block technique for the domain decomposition parallelization. The adaptive block technique controls the subdomain (block) structure dynamically associated with the system evolution, such that all the blocks have almost the same number of particles. The performance of the present code is evaluated for the simulations of the current sheet evolution. The test simulations demonstrate that the usage of the adaptive block technique as well as the staggering grid scheme enhances significantly the parallel efficiency of the AMR-EMPIC model.     

Theoretical study and numerical simulation of textiles

We propose a new approach for developing continuum models fit to describe the mechanical behavior of textiles. We develop a physically motivated model, based on the properties of the yarns, which can predict and simulate the textile behavior. The approach relies on the selection of a suitable topological model for the patch of the textile, coupled with constitutive models for the yarn behavior. The textile structural configuration is related to the deformation through an energy functional, which depends on both the macroscopic deformation and the distribution of internal nodes. We determine the equilibrium positions of these latter, constrained to an assigned macroscopic deformation. As a result, we derive a macroscopic strain energy function, which reflects the possibly nonlinear character of the yarns as well as the anisotropy induced by the microscopic topological pattern. By means of both analytical estimates and numerical experiments, we show that our model is well suited for both academic test cases and real industrial textiles, with particular emphasis on the tricot textile.     

多尺度无监督彩色图像分割

非采样Contourlet变换是一种新的多尺度多分辨率分析工具,本文提出了一种基于非采样Contourlet变换的彩色图像无监督分割算法.首先利用非采样Contourlet变换的平移不变性在其变换域应用梯度向量法提取图像多尺度边缘;然后在Contourlet变换域的低频子带和高频子带中分别提取局部低频能量纹理特征与高频...     

Image fusion through local feature extraction by using multi-scale top-hat by reconstruction operators

The purpose of image fusion is to combine useful image features of different original images into the final fusion image, which will produce one useful result image for different applications. One of the main difficulties of image fusion is extracting useful image features of different original images. In some cases, useful image features are local image features of the whole image. To efficiently extract local image features and produce an efficient fusion result, an image fusion algorithm based on the extracted local image features by using multi-scale top-hat by reconstruction operators is proposed in this paper. Firstly, multi-scale local feature extraction using multi-scale top-hat by reconstruction operators is discussed. Then, based on the extracted multi-scale local features of different original images, the useful image features for image fusion are constructed. Finally, the constructed useful image features for image fusion are combined into the final fusion image. Experimental results on different types of images show that, the proposed algorithm performs well for image fusion.     

Acoustical properties of materials made of vegetable particles with several scales of porosity

This article is devoted to the acoustical properties of hemp concrete, a “green” building material. In the study, hemp concretes made of different binders and different kinds of particles were characterised, and then modeled using equivalent-fluid models. Further, it is shown that the sound absorption of these materials can be controlled and significantly enhanced by means of suitable constituents and fabrication processes. Finally, good results are provided by the models.