Stress Intensity Factors for an Interface Kinked Crack in a Bi-Material Plate Loaded Normal to the Interface

Stress intensity factors for a kinked crack originating at interface of two bonded dissimilar materials subjected to normal tension are found by the finite element method.     

Implications of warping restraint on statics and dynamics of elastically tailored thin-walled composite beams

Static response and free vibration of elastically tailored thin-walled beams accounting for the warping restraint effect are investigated via an exact solution methodology within the context of a refined beam model. Analytical results obtained from the restrained warping model are compared with those based on its Saint-Venant model counterpart. It is revealed that the beam slenderness and thickness ratio, as well as the elastic anisotropy, considered in conjunction with the warping restraint have profound effects on the static and dynamic response characteristics. It is also shown that even for anisotropic composite thin-walled beams with high slenderness ratios, warping restraint can still be significant, implying the inadequacy of merely considering the geometric aspects in the modeling of anisotropic composite thin-walled beams.     

In vitro antioxidant capacity of honeybee-collected pollen of selected floral origin harvested from Romania

Total phenolic phytochemical concentration was measured in 12 honeybee-collected pollens of selected floral species as well as their antioxidant capacity. The content of total polyphenols was measured spectrophotometrically using the Folin–Ciocalteu reagent with gallic acid as standard. The antioxidant properties were evaluated by 2,2-diphenyl-picrylhydrazyl radical scavenging capacity (DPPH) assay, Trolox equivalent antioxidant Capacity procedure and Ferric ion reducing antioxidant power assay. A great variability regarding the correspondence between the antioxidant activity and the content of total polyphenols of honeybee-collected pollens with different botanical origin was found. Antioxidant activities were different for each floral species and were not clearly associated to their total phenolic content.     

Forward electric field calculation using BEM for time-varying magnetic field gradients and motion in strong static fields

A boundary element method for evaluating the electric fields induced in conducting bodies exposed to magnetic fields varying at low frequency has been developed and applied to sources of magnetic field variation that are of relevance in magnetic resonance imaging. An integral formulation based on constant boundary elements which can be used to study the effects of both temporally varying magnetic field gradients and rigid body movement in a static magnetic field is presented. The validity of this approach has been demonstrated for simple geometries with known analytical solutions and it has also been applied to the evaluation of the induced fields in more realistic models of the human head.     

Synthesis and characterization of nanocrystalline Zn ferrites substituted with Ni

Nanocrystalline powders of nickel substituted zinc ferrite with general formula Ni_xZn_1−xFe₂O₄ (x = 0, 0.2, 0.4, 0.6, 0.8, 1) have been synthesized via sol-gel auto-combustion method using tartaric acid as combustion-complexing agent. Samples were sintered at 773 K and 973 K in static air atmosphere. The absence of the organic phase and the spinel formation were monitored by using Fourier transform infrared spectroscopy. The structure and crystallite size were analyzed from X-ray diffraction data revealing spinel mono-phase formation in the range of nanometric crystallite size confirmed also through scanning electron microscopy. Mean size of crystallites lay in the range 20-40 nm. The influence of nickel content on the microstructure was investigated considering the crystallite size, distance between adjacent crystal planes, lattice parameter and porosity. The variation of magnetic properties of the samples was studied by using vibrating samples magnetometer and discussed considering the proposed cation distribution, relative bond angles and canting angles. The highest maximum value of the magnetization (63 emu/g) was found for Ni_0.8Zn_0.2Fe₂O₄.     

Electron transport properties of some new 4-tert-butylcalix[4]arene derivatives in thin films

Temperature dependences of electric conductivity and thermoelectric power of some recently synthesized organic compounds, 4-tert-butylcalix[4]arene derivatives, are studied. Thin-film samples (d = 0.10–0.40 μm) spin-coated from chloroform solutions onto glass substrates were used. Organic films with reproducible electron transport properties can be obtained if, after deposition, they are submitted to a heat treatment within temperature range of 295–575 K.     

A meshless method for the stable solution of singular inverse problems for two-dimensional Helmholtz-type equations

We investigate a meshless method for the stable and accurate solution of inverse problems associated with two-dimensional Helmholtz-type equations in the presence of boundary singularities. The governing equation and boundary conditions are discretized by the method of fundamental solutions (MFS). The existence of boundary singularities affects adversely the accuracy and convergence of standard numerical methods. Solutions to such problems and/or their corresponding derivatives may have unbounded values in the vicinity of the singularity. Moreover, when dealing with inverse problems, the stability of solutions is a key issue and this is usually taken into account by employing a regularization method. These difficulties are overcome by combining the Tikhonov regularization method (TRM) with the subtraction from the original MFS solution of the corresponding singular solutions, without an appreciable increase in the computational effort and at the same time keeping the same MFS discretization. Three examples for both the Helmholtz and the modified Helmholtz equations are carefully investigated.     

Stable Boundary and Internal Data Reconstruction in Two-Dimensional Anisotropic Heat Conduction Cauchy Problems Using Relaxation Procedures for an Iterative MFS Algorithm

We investigate two algorithms involving the relaxation of either the given boundary temperatures (Dirichlet data) or the prescribed normal heat fluxes (Neumann data) on the over-specified boundary in the case of the iterative algorithm of Kozlov91 applied to Cauchy problems for two-dimensional steady-state anisotropic heat conduction (the Laplace-Beltrami equation). The two mixed, well-posed and direct problems corresponding to every iteration of the numerical procedure are solved using the method of fundamental solutions (MFS), in conjunction with the Tikhonov regularization method. For each direct problem considered, the optimal value of the regularization parameter is chosen according to the generalized cross-validation (GCV) criterion. The iterative MFS algorithms with relaxation are tested for over-, equally and under-determined Cauchy problems associated with the steady-state anisotropic heat conduction in various two-dimensional geometries to confirm the numerical convergence, stability, accuracy and computational efficiency of the method.     

Boundary reconstruction in two-dimensional steady state anisotropic heat conduction using a regularized meshless method

We study the stable numerical identification of an unknown portion of the boundary on which either a Dirichlet or a Robin boundary condition is provided, while additional Cauchy data are given on the remaining known part of the boundary of a two-dimensional domain, in the case of steady state anisotropic heat conduction problems. This inverse geometric problem is solved using the method of fundamental solutions (MFS) in conjunction with the Tikhonov regularization method [53]. The optimal value for the regularization parameter is chosen according to Hansen’s L-curve criterion [17]. The stability, convergence, accuracy and efficiency of the proposed method are investigated by considering several examples in both smooth and piecewise smooth geometries.     

The Supervised Network Self-Organizing Map for Classification of Large Data Sets

Complex application domains involve difficult pattern classification problems. The state space of these problems consists of regions that lie near class separation boundaries and require the construction of complex discriminants while for the rest regions the classification task is significantly simpler. The motivation for developing the Supervised Network Self-Organizing Map (SNet-SOM) model is to exploit this fact for designing computationally effective solutions. Specifically, the SNet-SOM utilizes unsupervised learning for classifying at the simple regions and supervised learning for the difficult ones in a two stage learning process. The unsupervised learning approach is based on the Self-Organizing Map (SOM) of Kohonen. The basic SOM is modified with a dynamic node insertion/deletion process controlled with an entropy based criterion that allows an adaptive extension of the SOM. This extension proceeds until the total number of training patterns that are mapped to neurons with high entropy (and therefore with ambiguous classification) reduces to a size manageable numerically with a capable supervised model. The second learning phase (the supervised training) has the objective of constructing better decision boundaries at the ambiguous regions. At this phase, a special supervised network is trained for the computationally reduced task of performing the classification at the ambiguous regions only. The performance of the SNet-SOM has been evaluated on both synthetic data and on an ischemia detection application with data extracted from the European ST-T database. In all cases, the utilization of SNet-SOM with supervised learning based on both Radial Basis Functions and Support Vector Machines has improved the results significantly related to those obtained with the unsupervised SOM and has enhanced the scalability of the supervised learning schemes. The highly disciplined design of the generalization performance of the Support Vector Machine allows to design the proper model for the particular training set.