Adaptive remeshing for ductile fracture prediction in metal formingRemaillage adaptatif pour la prévision de la rupture ductile en mise en forme

The analysis of mechanical structures using the Finite Element Method in the framework of large elastoplastic strain, needs frequent remeshing of the deformed domain during computation. Indeed, the remeshing is due to the large geometrical distortion of finite elements and the adaptation to the physical behavior of the solution. This paper gives the necessary steps to remesh a mechanical structure during large elastoplastic deformations with damage. An important part of this process is constituted by geometrical and physical error estimates. The proposed method is integrated in a computational environment using the ABAQUS/Explicit solver and the BL2D-V2 adaptive mesher. To cite this article: H. Borouchaki et al., C. R. Mecanique 330 (2002) 709–716.     

Dextran-modified iron oxide nanoparticles

Dextran-modified iron oxide nanoparticles were prepared by precipitation of Fe（Ⅱ） and Fe（Ⅲ） salts with ammonium hydroxide by two methods. Iron oxide was precipitated either in the presence of dextran solution, or the dextran solution was added after precipitation. In the second method, the iron oxide particle size and size distribution could be controlled depending on the concentration of dextran in the solution. The nanoparticles were characterized by size-exclusion chromatography, transmission electron microscopy and dynamic light scattering. Optimal conditions for preparation of stable iron oxide colloid particles were determined, The dextran/iron oxide ratio 0-0,16 used in precipitation of iron salts can be recommended for synthesis of nanoparticles suitable for biomedical applications, as the colloid does not contain excess dextran and does not coagulate.     

Sensitivity of depolarized lidar signals to cloud and aerosol particle properties

Measurements from depolarized lidars provide a promising method to retrieve both cloud and aerosol properties and a versatile complement to passive satellite-based sensors. For lidar observations of clouds and aerosols, multiple scattering plays an important role in the scattering process. Monte Carlo simulations are carried out to investigate the sensitivity of lidar backscattering depolarization to cloud and aerosol properties. Lidar parameters are chosen to be similar to those of the upcoming space-based CALIPSO lidar. Cases are considered that consist of a single cloud or aerosol layer, as well as a case in which cirrus clouds overlay different types of aerosols. It is demonstrated that besides thermodynamic cloud phase, the depolarized lidar signal may provide additional information on ice or aerosol particle shapes. However, our results show little sensitivity to ice or aerosol particle sizes. Additionally, for the case of multiple but overlapping layers involving both clouds and aerosols, the depolarized lidar contains information that can help identify the particle properties of each layer.     

Improved holographic particle sizing by using absolute values of the wavelet transform

A new method for sizing particle from in-line particle holograms by using absolute values of the wavelet transform is proposed in order to improve accuracy in measurements. The proposed method provides direct calculation of the particle size by using spatial frequency information of a chirp signal at minima position of an envelope function. Simulation and experimental results are presented.     

短脉冲强激光在稀薄等离子体中传播时的电磁类孤立子

 采用二维粒子模拟方法，研究了短脉冲强激光在稀薄等离子体中传播时电磁类孤立子的产生和时空演化过程。通过分析电磁场与等离子体波的非线性能量交换和激光场的频率谱结构等，给出了电磁类孤立子形成的基本物理图像，讨论了等离子体参数对电磁类孤立子形成的影响。模拟结果表明：类孤立子的形成是由于局部电磁波振荡频率减小至等离子体频率引起的，初始等离子体密度越高越容易形成空间局域结构。     

偏滤器靶板磁预鞘层边界的离子流

利用流体力学模型研究了偏滤器等离子体条件下磁预鞘层边界离子流和预鞘层宽度之间的关系，并分析了粒子碰撞对预鞘层边界离子流的影响。由于粒子碰撞对离子的驱动效益，预鞘层边界离子流速度随着预鞘层宽度的增加而减少；只有当预鞘层宽度趋于零时，边界离子流沿磁力线的速度才趋近于离子声速。在固定预鞘层宽度的条件下，计算了预鞘层边界离子流速度与碰撞频率之间的函数关系。     

Neutrino astronomy: Present and future

I briefly review the present and future status of the burgeoning field of neutrino astronomy. I outline the astrophysics and particle physics goals, design, and performance of the various current and proposed neutrino telescopes. Also described are present results and future expectations.     

Characterization of spherical particles using high-order neural networks and scanning flow cytometry

We retrieve the radius R, real n and imaginary k parts of the refractive index of homogeneous spherical particles using angular distribution of the light-scattering intensity. To solve the inverse light-scattering problem we use a high-order neural-network technique. The effect of network parameters on optimization is examined. The technique is evaluated for noise-corrupted input data at 0.6 μm<R<10.6 μm, 1.02<n<1.38, and 0<k<0.03. The errors of retrieval for nonabsorbing particles do not exceed 0.05 μm for radius and 0.015 for refractive index. The experimental verification is fulfilled by experimental data retrieved by means of a scanning flow cytometer. The light-scattering profiles of polystyrene beads and spherized red blood cells are processed with the high-order neural networks and a non-linear regression at Mie theory. The parameters retrieved by the high-order neural networks correlate well with the parameters retrieved by the least-square method.     

单链表在离子发动机光学系统粒子模拟中的应用

 目前离子发动机光学系统数值模拟大多采用PIC方法，由于该方法需要跟踪单个粒子的运动，因此需要存储每个粒子的位置信息与运动信息。传统的粒子模拟程序中，保存粒子信息大多采用数组的方式，但是采用这种方式存在弊端，例如对粒子总数变化的自适应不好。基于此开发了一种使用链式存储结构的粒子模拟程序，该程序使用带头节点的单向链表存储粒子信息。使用基于链式存储结构的PIC方法对离子发动机光学系统进行了粒子模拟，验证了链式粒子信息存储方法在粒子模拟中的可用性。模拟表明：（1）在粒子模拟中采用链式存储结构存储粒子信息，无需预先指定最大粒子总数，程序可自适应粒子总数的变化，因此无需进行试算，节省了计算时间；（2）在粒子模拟中采用链式存储结构，由于不存在内存资源的浪费，因而可显著提高程序的存储效率与计算效率。     

Hybrid systems: Modelling and analysis using emergent dynamics

In this paper, we discuss modelling and analysis of hybrid systems with physical interaction dynamics. Such systems are typically considered complex and they are modelled using abstractions. Abstractions may, however, unintentionally exclude critical details, leading to partial or false results. Therefore, we study here use of a particle system in modelling and analysis. The novelty of the particle system is that it is designed to reveal interaction dynamics as emergent dynamics; thus, supporting analysis of complex and intricate interaction dynamics with acceptable modelling effort. As the main contribution, we formalize the particle system, and use it to model and analyze hybrid systems, both mechanical and biological, with nontrivial interaction dynamics.