Strain Regularity and Stiffness Tensor of Reinforcers in Dense Particle Reinforced Composites

针对高体积份数、随机分布、等轴状颗粒增强复合材料 ,研究了材料的应变分布规律 ,给出了基体和增强体应变平均值与材料微观结构参数之间的定量关系。结果表明 ,除应变平均值外 ,应变涨落是影响刚度张量的另一个重要因素 ,研究了应变涨落与材料微观结构参数之间的关系 ,并推导出了复合材料的刚度张量。与实验结果和以往的理论比较 ,预测结果与实验结果吻合良好

Moment Tensor Analysis of the Acoustic Emission Source in the Rock Damage Process

To further investigate the mechanism of acoustic emission (AE) in the rock fracture experiment, moment tensor analysis was carried out. The AE sources characterized by crack sizes, orientations and fracture modes, are represented by a time-dependent momen

Prefrontal white matter abnormalities in young adult with major depressive disorder: A diffusion tensor imaging study

Prefrontal impairments have been hypothesized to be most strongly associated with the cognitive and emotional dysfunction in depression. Recently, white matter microstructural abnormalities in prefrontal lobe have been reported in elderly patients with ma

Biologically Inspired Tensor Features

According to the research results reported in the past decades, it is well acknowledged that face recognition is not a trivial task. With the development of electronic devices, we are gradually revealing the secret of object recognition in the primate's visual cortex. Therefore, it is time to reconsider face recognition by using biologically inspired features. In this paper, we represent face images by utilizing the C1 units, which correspond to complex cells in the visual cortex, and pool over S1 units by using a maximum operation to reserve only the maximum response of each local area of S1 units. The new representation is termed C1 Face. Because C1 Face is naturally a third-order tensor (or a three dimensional array), we propose three-way discriminative locality alignment (TWDLA), an extension of the discriminative locality alignment, which is a top-level discriminate manifold learning-based subspace learning algorithm. TWDLA has the following advantages: (1) it takes third-order tensors as input directly so the structure information can be well preserved; (2) it models the local geometry over every modality of the input tensors so the spatial relations of input tensors within a class can be preserved; (3) it maximizes the margin between a tensor and tensors from other classes over each modality so it performs well for recognition tasks and (4) it has no under sampling problem. Extensive experiments on YALE and FERET datasets show (1) the proposed C1Face representation can better represent face images than raw pixels and (2) TWDLA can duly preserve both the local geometry and the discriminative information over every modality for recognition.

Spin and spin-isospin instabilities and Landau parameters of Skyrme interactions with tensor correlations

The Landau parameters of Skyrme interactions in the spin and spin-isospin channels are studied using various Skyrme effective interactions with and without tensor correlations. We focus on the role of the tensor terms on the spin and spin-isospin instabilities that can occur in nuclear matter above saturation density. We point out that these instabilities are realized in nuclear matter at the critical density of about two times the saturation density for all the adopted parameter sets. The critical density is shown to be very much dependent not only on the choice of the Skyrme parameter set, but also on the inclusion of the tensor terms.

A Unified Tensor Level Set for Image Segmentation

This paper presents a new region-based unified tensor level set model for image segmentation. This model introduces a three-order tensor to comprehensively depict features of pixels, e.g., gray value and the local geometrical features, such as orientation and gradient, and then, by defining a weighted distance, we generalized the representative region-based level set method from scalar to tensor. The proposed model has four main advantages compared with the traditional representative method as follows. First, involving the Gaussian filter bank, the model is robust against noise, particularly the salt-and pepper-type noise. Second, considering the local geometrical features, e. g., orientation and gradient, the model pays more attention to boundaries and makes the evolving curve stop more easily at the boundary location. Third, due to the unified tensor pixel representation representing the pixels, the model segments images more accurately and naturally. Fourth, based on a weighted distance definition, the model possesses the capacity to cope with data varying from scalar to vector, then to high-order tensor. We apply the proposed method to synthetic, medical, and natural images, and the result suggests that the proposed method is superior to the available representative region-based level set method.

Robust Tensor Analysis With L1-Norm

Tensor analysis plays an important role in modern image and vision computing problems. Most of the existing tensor analysis approaches are based on the Frobenius norm, which makes them sensitive to outliers. In this paper, we propose L1-norm-based tensor analysis (TPCA-L1), which is robust to outliers. Experimental results upon face and other datasets demonstrate the advantages of the proposed approach.

Tensor density matrix theory for determining population and alignment of symmetric top molecule using rotationally unresolved fluorescence

General expressions used for transforming raw laser-induced fluorescence (LIF) intensity into the population and alignment parameters of a symmetric top molecule are derived by employing the density matrix approach. The molecular population and alignment are described by molecular state multipoles. The results are presented for a general excitation-detection geometry and then applied to some special geometries. In general cases, the LIF intensity is a complex function of the initial molecular state multipoles, the dynamic factors and the excitation-detection geometrical factors. It contains a population and 14 alignment multipoles. How to extract all initial state multipoles from the rotationally unresolved emission LIF intensity is discussed in detail.

Strain gradient theory with couple stress for crystalline solids

A new phenomenological strain gradient theory for crystalline solid is proposed. It fits within the framework of general couple stress theory and involves a single material length scale Ics. In the present theory three rotational degrees of freedom omega (i) are introduced, which denote part of the material angular displacement theta (i) and are induced accompanying the plastic deformation. omega (i) has no direct dependence upon u(i) while theta = (1 /2) curl u. The strain energy density omega is assumed to consist of two parts: one is a function of the strain tensor epsilon (ij) and the curvature tensor chi (ij), where chi (ij) = omega (i,j); the other is a function of the relative rotation tensor alpha (ij). alpha (ij) = e(ijk) (omega (k) - theta (k)) plays the role of elastic rotation reason The anti-symmetric part of Cauchy stress tau (ij) is only the function of alpha (ij) and alpha (ij) has no effect on the symmetric part of Cauchy stress sigma (ij) and the couple stress m(ij). A minimum potential principle is developed for the strain gradient deformation theory. In the limit of vanishing l(cs), it reduces to the conventional counterparts: J(2) deformation theory. Equilibrium equations, constitutive relations and boundary conditions are given in detail. For simplicity, the elastic relation between the anti-symmetric part of Cauchy stress tau (ij), and alpha (ij) is established and only one elastic constant exists between the two tensors. Combining the same hardening law as that used in previously by other groups, the present theory is used to investigate two typical examples, i.e., thin metallic wire torsion and ultra-thin metallic beam bend, the analytical results agree well with the experiment results. While considering the, stretching gradient, a new hardening law is presented and used to analyze the two typical problems. The flow theory version of the present theory is also given.

3D Anisotropic Elastoplastic-Damage Model and its Application in Simulating the Behavior of Rock Materials

A 3D anisotropic elastoplastic-damage model was presented based on continuum damage mechanics theory. In this model, the tensor decomposition technique is employed. Combined with the plastic yield rule and damage evolution, the stress tensor in incremental format is obtained. The derivate eigenmodes in the proposed model are assumed to be related with the uniaxial behavior of the rock material. Each eigenmode has a corresponding damage variable due to the fact that damage is a function of the magnitude of the eigenstrain. Within an eigenmodes, different damage evolution can be used for tensile and compressive loadings. This model was also developed into finite element code in explicit format, and the code was integrated into the well-known computational environment ABAQUS using the ABAQUS/Explicit Solver. Numerical simulation of an uniaxial compressive test for a rock sample is used to examine the performance of the proposed model, and the progressive failure process of the rock sample is unveiled.

Coherent Structures in Transition of a Flat-Plate Boundary Layer at Ma=0.7

Direct numerical simulation (DNS) of a spatially evolving flat-plate boundary layer transition process at free stream Mach number 0.7 is performed. Tollmien-Schlichting (T-S) waves are added on the inlet boundary as the disturbances before transition. Typical coherent structures in the transition process are investigated based on the second invariant of velocity gradient tensor. The instantaneous shear stress and the mean velocity profile in the transition region are studied. In our view, the fact that the peak value of shear stress in the stress concentration area increases and exceeds a threshold value during the later stage of the transition process plays an important role in the laminar breakdown process.