Effect of Armature Design on Thermal and Electromagnetic Distribution of an Electromagnetic Launcher

The purpose of this study is to investigate the effect of armature design on the thermal and magnetic induction distribution of the rails and the armature in an electromagnetic launcher. In our formulation of governing, non-linear differential equations, Maxwell equations coupled with energy equation are applied to the rails and the armatures. To solve the non-linear governing differential equations, a finite difference code based on alternative directional implicit method is utilized. For different armatures, the length, shape, and input current of the rails stay the same. In addition, armature-melting latent heat and the friction force between the armatures and the rails are considered. First, armature speed is calculated; then, temperature and magnetic induction distribution is calculated by the energy equation. Temperature and magnetic induction distribution obtained for the rails and different armatures show that the maximum temperature occurs at the trailing edge of each armature. The best design shows the lowest temperature, which is about 600 K. This is due to aerodynamic shape and stability of this armature. However, for all armatures, the temperature of one meter rail stays around 360 K.     

Effects of electron beam irradiation on the structure–property behavior of blends based on low density polyethylene and styrene-ethylene-butylene-styrene-block copolymers

Low density polyethylene (LDPE) blends with different additives were exposed to various doses of electron beam irradiation. The additives used were styrene-ethylene-butylene-styrene-block copolymers (SEBS), styrene-ethylene-butylene-styrene-block copolymer grafted with maleic anhydride (SEBS-g-MA) and mineral compounds. The structure–property behavior of electron beam irradiated blends was characterized in terms of mechanical, thermal, and electrical resistivity properties. The results indicated that the unirradiated LDPE blends with the different compositions showed improved mechanical properties, thermal and volume resistivity properties than pure LDPE. However, the improvement in properties of unirradiated blends by using SEBS-g-MA was higher than using SEBS copolymer. Further improvement in the mechanical, thermal and electrical properties of the LDPE blends was achieved after electron beam irradiation. The limited oxygen index (LOI) data revealed that the LDPE/SEBS-g-MA/ATH blend was changed from combustible to self-extinguishing material after electron beam irradiation to a dose of 100 kGy. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

The synthesis of multilayer graphene materials by the fluorination of carbon nanodiscs/nanocones

Multilayer carbonaceous nanomaterial has been synthesized using a two-step process: carbon nanodiscs/nanocones were fluorinated using either the direct reaction with pure F₂ gas or the thermal decomposition of solid fluorinating agent (TbF₄). Then the fluorinated parts were removed by treatment at 600 °C in air. When the fluorine atoms are homogenously dispersed, using fluorination by TbF₄, thinning due to thermal defluorination results in multilayer materials with 7–10 nm of thickness and 400–500 nm of width. Such resulting materials and the fluorinated precursors have been characterized by solid state NMR, TGA, XRD, SEM, TEM, AFM and Raman spectroscopy.     

Correlation between the dimensionality and the constants of elasticity of rare-earth doped borate glasses

This work was devoted to explore the correlation between the dimensionality and the computed theoretically constants of elasticity of borate based glasses doped with rare-earth oxides. The dimensionality of the glassy network has been calculated in terms of the d ratio which is equal to 4 C ₄₄/K _e and discussed in terms of the cross-link density and number of network bonds per unit volume of these glasses. Constants of elasticity were calculated in terms of the bond compression model and the Makishima-Mackenzie model. The average cross-link density, the number of network bonds per unit volume, the average stretching-force constant, and the ratio of the estimated bulk modulus (K _bc) to the experimentally determined (K _e) have been calculated and discussed in terms of the bond-compression model. Young??s modulus, the packing density, and the dissociation energy have been calculated and analyzed in terms of the Makishima-Mackenzie model. The results showed that the computed elastic moduli and the dimensionality of the borate glasses containing La₂O₃ or Gd₂O₃ are strongly dependent on the concentration of the structural units of the constituent oxides and types of bonds between these units.     

A comparative study to predict the interphase modulus in polymer nanocomposites

In this study, the interphase modulus (E_i) in polymer nanocomposites is calculated by two methods and the calculated results are compared at different conditions. In the first method, the experimental moduli of samples are applied to Ji model and suitable “E_i” is calculated. In the second method, a multilayered interphase is considered, in which the Young's moduli of layers (E_k) depend to the distance between the nanoparticle surface and the polymer matrix by power function of “Y” parameter. The “E_i” is calculated for multilayered interphase assuming the same and different layer thicknesses (t_k) by Parallel and Series models. Finally, the “E_i” values calculated by the explained methods are compared for two reported samples. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 44076.     

Real-time speckle reduction and coherence enhancement in ultrasound imaging via nonlinear anisotropic diffusion

This paper presents a novel approach for speckle reduction and coherence enhancement of ultrasound images based on nonlinear coherent diffusion (NCD) model. The proposed NCD model combines three different models. According to speckle extent and image anisotropy, the NCD model changes progressively from isotropic diffusion through anisotropic coherent diffusion to, finally, mean curvature motion. This structure maximally low-pass filters those parts of the image that correspond to fully developed speckle, while substantially preserving information associated with resolved-object structures. The proposed implementation algorithm utilizes an efficient discretization scheme that allows for real-time implementation on commercial systems. The theory and implementation of the new technique are presented and verified using phantom and clinical ultrasound images. In addition, the results from previous techniques are compared with the new method to demonstrate its performance.     

Fault tolerance in co-evolutionary communication of EHW modules

Evolvable Hardware (EHW) is a new concept that applies evolutionary algorithms to hardware design. Based on previous work on co-evolutionary communication of EHW modules, this paper investigates the new feature of fault tolerance for this model. A fault model is built for the communication line between EHW modules. The experiment demonstrated in the presentation is the simulation of injecting stuck/bridging faults into an EHW-based serial adder that has been previously developed. The outcomes imply an outstanding feature of fault tolerance in this system with 100% fault coverage, which paves the way for bio-inspired approaches to fault tolerant design instead of the classic ones.     

Controlling gaze with an embodied interactive control architecture

Human-Robot Interaction (HRI) is a growing field of research that targets the development of robots which are easy to operate, more engaging and more entertaining. Natural human-like behavior is considered by many researchers as an important target of HRI. Research in Human-Human communications revealed that gaze control is one of the major interactive behaviors used by humans in close encounters. Human-like gaze control is then one of the important behaviors that a robot should have in order to provide natural interactions with human partners. To develop human-like natural gaze control that can integrate easily with other behaviors of the robot, a flexible robotic architecture is needed. Most robotic architectures available were developed with autonomous robots in mind. Although robots developed for HRI are usually autonomous, their autonomy is combined with interactivity, which adds more challenges on the design of the robotic architectures supporting them. This paper reports the development and evaluation of two gaze controllers using a new cross-platform robotic architecture for HRI applications called EICA (The Embodied Interactive Control Architecture), that was designed to meet those challenges emphasizing how low level attention focusing and action integration are implemented. Evaluation of the gaze controllers revealed human-like behavior in terms of mutual attention, gaze toward partner, and mutual gaze. The paper also reports a novel Floating Point Genetic Algorithm (FPGA) for learning the parameters of various processes of the gaze controller.     

Realistically coupled neural mass models can generate EEG rhythms

We study the generation of EEG rhythms by means of realistically coupled neural mass models. Previous neural mass models were used to model cortical voxels and the thalamus. Interactions between voxels of the same and other cortical areas and with the thalamus were taken into account. Voxels within the same cortical area were coupled (short-range connections) with both excitatory and inhibitory connections, while coupling between areas (long-range connections) was considered to be excitatory only. Short-range connection strengths were modeled by using a connectivity function depending on the distance between voxels. Coupling strength parameters between areas were defined from empirical anatomical data employing the information obtained from probabilistic paths, which were tracked by water diffusion imaging techniques and used to quantify white matter tracts in the brain. Each cortical voxel was then described by a set of 16 random differential equations, while the thalamus was described by a set of 12 random differential equations. Thus, for analyzing the neuronal dynamics emerging from the interaction of several areas, a large system of differential equations needs to be solved. The sparseness of the estimated anatomical connectivity matrix reduces the number of connection parameters substantially, making the solution of this system faster. Simulations of human brain rhythms were carried out in order to test the model. Physiologically plausible results were obtained based on this anatomically constrained neural mass model.