A study of tailored blank welding between mild steel sheet and zn-coated steel sheet by CO2 laser beam

Research was conducted on tailored blank welding between mild steel sheet and Zn-coated steel sheet using CO₂ laser beam. The materials used in this study were low carbon steel sheets with a thickness of 1.2 mm and Zn-coated steel sheet with the same thickness and 6.3 μm Zn coating. Experiments were conducted by applying the Taguchi method to obtain optimum conditions for the application of this tailored blank laser welding method in practical manufacturing processes. Optical microscopy, XRD, SEM and TEM analysis were performed to observe the microstructures and to determine the structures of welded zone. In addition, mechanical properties were measured by the microhardness test, tensile test and Erichsen test to evaluate the formability of the welded specimen. There was no trapped Zn in the fusion zone, and the phases of this region consisted of polygonal ferrite, quasi-polygonal ferrite, banitic ferrite and martensite. The elongation value of welded specimen was more than 80% of the value in substrate metal, and the LDH value was more than 90% of the value in substrate metal.     

Discharge characteristics of lead dioxide electrode prepared with cementation lead oxide

Lead acid batteries have had restricted applications because of relatively low energy density below 50Wh/kg. Many efforts have achieved lighter battery components such as separators, connections and containers etc. Thus, the most important problem of the lead acid battery is to improve the low capacity of the active material in the positive electrode. The purpose of this study is to improve the utilization of the active material in the lead dioxide electrode for the lead acid battery through the production of lead oxide with better physicochemical characteristics through cementation. A cementation reaction was performed in 1.0wt.%HCl solution using pure magnesium plate as the reductant. We investigated the utilization of the active material and discharge characteristics of the positive electrode with a current density ranging from 3.4 to 108.8mAcm⁻². As a result, the active material utilization was about 72% at 3.48 mAcm⁻² and increased with decreasing current density. The discharge characteristics according to current density are especially very good at high current density     

Microstructure and mechanical property of irradiated Zr−2.5Nb pressure tube in Wolsong unit-1

With the aim of assessing the degradation of Zr−2.5Nb pressure tubes operating in the Wolsong unit-1 nuclear power plant, characterization tests are being conducted on irradiated Zr−2.5Nb tubes removed after 10-year operation. The examined tube had been exposed to temperatures ranging from 264 to 306°C and a neutron fluence of 8.9×10²¹ n/cm² (E>1 MeV) at the maximum. Tensile tests were carried out at temperatures ranging from RT to 300°C. The density of a-type and c-type dislocations was examined on the irradiated Zr-2.5Nb tube using a transmission electron microscope. Neutron irradiation up to 8.9×10²¹ n/cm² (E>1 MeV) yielded an increase in a-type dislocation density of the Zr−2.5Nb pressure tube to 7.5×10¹⁴ m⁻², which was highest at the inlet of the tube exposed to the low temperature of 275°C. In contranst, the c-component dislocation density did not change with irradiation, keeping an initial dislocation density of 0.8×10¹⁴ m⁻² over the whole length of the tube. As expected, the neutron irradiation increased mechanical strength by about 17–26% in the transverse direction and by 34–39% in the longitudinal direction compared to that of the unirradiated tube at 300°C. The change in the mechanical properties with irradiation is discussed in association with the microstructural change as a function of temperature and neutron fluence.     

Partial consensus of identical feedforward dynamic systems with input saturations

This paper studies the partial consensus problem for identical feedforward dynamic systems with input saturations. We construct two consensus protocols using the partial‐state information and full‐state information, respectively. Applying a change of coordinates, feedforward system is transformed into the block diagonal form. Then, by utilizing the bounded real lemma and small gain theorem, we solve the partial consensus problem, and the existence of each protocol is derived. Copyright © 2015 John Wiley & Sons, Ltd.     

Experiencing Nature: Embodying Animals in Immersive Virtual Environments Increases Inclusion of Nature in Self and Involvement With Nature

Immersive virtual environments (IVEs) produce simulations that mimic unmediated sensory experiences. 3 experiments (N = 228) tested how different modalities increase environmental involvement by allowing users to inhabit the body of animals in IVEs or watch the experience on video. Embodying sensory‐rich experiences of animals in IVEs led to greater feeling of embodiment, perception of being present in the virtual world, and interconnection between the self and nature compared to video. Heightened interconnection with nature elicited greater perceptions of imminence of the environmental risk and involvement with nature, which persisted for 1 week. Although the effect sizes were small to moderate, findings suggest that embodied experiences in IVEs may be an effective tool to promote involvement with environmental issues.     

DCT statistics-based digital dropout detection in degraded archived media

With the rapid development of visual digital media, the demand for better quality of service has increased the pressure on broadcasters to automate their error detection and restoration activities for preserving their archives. Digital dropout is one of the defects that affect archived visual materials and tends to occur in block by block basis (size of 8 × 8). It is well established that human visual system (HVS) is highly adapted to the statistics of its visual natural environment. Consequently, in this paper, we have formulated digital dropout detection as a classification problem which predicts block label based on statistical features. These statistical features are indicative of perceptual quality relevant to human visual perception, and allow pristine images to be distinguished from distorted ones. Here, the idea is to extract discriminant block statistical features based on discrete cosine transform (DCT) coefficients and determine an optimal neighborhood sampling strategy to enhance the discrimination ability of block representation. Since this spatial frame based approach is free from any motion computation dependency, it works perfectly in the presence of fast moving objects. Experiments are performed on video archives to evaluate the efficacy of the proposed technique.     

A noninvasive method to predict fluid viscosity and nanoparticle size using total internal reflection fluorescence microscopy (TIRFM) imaging

This study examines the development of an automated particle tracking algorithm to predict the hindered Brownian movement of fluorescent nanoparticles within an evanescent wave field created using total internal reflection fluorescent microscopy. The two-dimensional motion of the fluorescent nanoparticles was tracked, with sub-pixel resolution, by fitting the intensity distribution of the particles to a known Gaussian distribution, thus providing the particle center within a single pixel. Spherical yellow-green polystyrene nanoparticles (200, 500, and 1000 nm in diameter) were suspended in deionized water (control), 10 wt% d-glucose, and 10 wt% glycerol solutions, with 1 mM of NaCl added to each. The motion of tracked nanoparticles was compared with the theoretical tangential hindered Brownian motion to estimate particle diameters and fluid viscosity using a nonlinear regression technique. The automatic tracking algorithm was initially validated by comparing the automated results with manually tracked particles, 1 µm in size. Our results showed that both particle size and solution viscosity were accurately predicted from the experimental mean square displacement. Specifically, the results show that the error of particle size prediction is below 10 % and the error of solution viscosity prediction is less than 1 %. The proposed automatic analysis tool could prove to be useful in bio-application fields for examination of single protein tracking, drug delivery, and cytotoxicity. Furthermore, the proposed tool could be useful in microfluidic areas such as particle tracking velocimetry and noninvasive viscosimetry.     

Formation stabilization and resizing based on the control of inter‐agent distances

We propose a control strategy that could steer the group of mobile agents in the plane to achieve a specified formation. The control law could be implemented in a fully decentralized manner so that each agent moves on their own local reference frame. Under the acyclic minimally persistent graph topology, each agent measures the relative displacements of neighboring agents and then adjusts the distances between them to achieve the desired formation. As well as achieving a fixed formation, we could resize the formation only by changing the leader edge, which connects the leader with the first‐follower in acyclic minimally persistent graph, without changing the structures of the control law. Copyright © 2014 John Wiley & Sons, Ltd.     

Window annealing for pixel-labeling problems

The pixel labeling problems in computer vision are often formulated as energy minimization tasks. Algorithms such as graph cuts and belief propagation are prominent; however, they are only applicable for specific energy forms. For general optimization, Markov Chain Monte Carlo (MCMC) based simulated annealing can estimate the minima states very slowly.This paper presents a sampling paradigm for faster optimization. First, in contrast to previous MCMCs, the role of detailed balance constraint is eliminated. The reversible Markov chain jumps are essential for sampling an arbitrary posterior distribution, but they are not essential for optimization tasks. This allows a computationally simple window cluster sample. Second, the proposal states are generated from combined sets of local minima which achieve a substantial increase in speed compared to uniformly labeled cluster proposals. Third, under the coarse-to-fine strategy, the maximum window size variable is incorporated along with the temperature variable during simulated annealing. The proposed window annealing is experimentally shown to be many times faster and capable of finding lower energy compared to the previous Gibbs and Swendsen-Wang cut (SW-cut) sampler. In addition, the proposed method is compared with other deterministic algorithms like graph cut, belief propagation, and spectral method in their own specific energy forms. Window annealing displays competitive performance in all domains.