Corrosion-passivation processes in a cellular automata based simulation study

A short survey of cellular automata based models for corrosion and passivation phenomena is given. Results of simulations based on the model of spatially separated anodic and cathodic reactions are presented for a cavity development from a point-like damage of a protective layer and from an initially flat unprotected surface. We show some new peculiar examples of the symmetry breaking in the cavity development. The results for the initially flat surface show roughening of the surface at the beginning of the corrosion process. After that, pit merging causes a resmoothing of the surface. An oscillatory behavior of the surface roughness is observed caused by a peninsula formation with subsequent island detachment. These results are obtained in 2D because of computational limitations. We plan simulations in 3D and point out the problems we encounter in their realization.     

Microstructure Evolution as an Effect of Strain Reversal During the Hot Deformation of Microalloyed Steels

Susceptibility of the steel for further cold processing strongly depends on the whole prior history of deformation in the hot working regime.In the industrial hot working processes,e.g.at the roughing stage of hot rolling,or forging,material undergoes complex deformation modes that leads to gradients of both microstructure and properties across the deformed cross-section.Torsion and multiaxial compression tests with different amounts of strain reversals were conducted at elevated temperatures to study the effect of applied strain path on the phenomena occurring during microstructure evolution of Nb-microalloyed steels.Gathered results will provide data for the modification of existing constitutive equations that mostly do not account for the strain path changes.Better through-process modelling will then enable to achieve better properties and quality of the products for further cold processing.     

Subsampling models and anti-alias filters for 3-D automultiscopic displays.

A new type of three-dimensional (3-D) display recently introduced on the market holds great promise for the future of 3-D visualization, communication, and entertainment. This so-called automultiscopic display can deliver multiple views without glasses, thus allowing a limited "look-around" (correct motion-parallax). Central to this technology is the process of multiplexing several views into a single viewable image. This multiplexing is a complex process involving irregular subsampling of the original views. If not preceded by low-pass filtering, it results in aliasing that leads to texture as well as depth distortions. In order to eliminate this aliasing, we propose to model the multiplexing process with lattices, find their parameters and then design optimal anti-alias filters. To this effect, we use multidimensional sampling theory and basic optimization tools. We derive optimal anti-alias filters for a specific automultiscopic monitor using three models: the orthogonal lattice, the nonorthogonal lattice, and the union of shifted lattices. In the first case, the resulting separable low-pass filter offers significant aliasing reduction that is further improved by hexagonal-passband low-pass filter for the nonorthogonal lattice model. A more accurate model is obtained using union of shifted lattices, but due to the complex nature of repeated spectra, practical filters designed in this case offer no additional improvement. We also describe a practical method to design finite-precision, low-complexity filters that can be implemented using modern graphics cards.     

Space-time image sequence analysis: object tunnels and occlusion volumes.

We address the issue of image sequence analysis jointly in space and time. While typical approaches to such an analysis consider two image frames at a time, we propose to perform this analysis jointly over multiple frames. We concentrate on spatiotemporal segmentation of image sequences and on analysis of occlusion effects therein. The segmentation process is three-dimensional (3-D); we search for a volume carved out by each moving object in the image sequence domain, or "object tunnel," a new space-time concept. We pose the problem in variational framework by using only motion information (no intensity edges). The resulting formulation can be viewed as volume competition, a 3-D generalization of region competition. We parameterize the unknown surface to be estimated, but rather than using an active-surface approach, we embed it into a higher dimensional function and apply the level-set methodology. We first develop simple models for the detection of moving objects over static background; no motion models are needed. Then, in order to improve segmentation accuracy, we incorporate motion models for objects and background. We further extend the method by including explicit models for occluded and newly exposed areas that lead to "occlusion volumes," another new space-time concept. Since, in this case, multiple volumes are sought, we apply a multiphase variant of the level-set method. We present various experimental results for synthetic and natural image sequences.     

Packet dispatching using module matching in the modified MSM Clos-network switch

A modified memory-space-memory (MSM) Clos-network switch, called MCNS, with a module-level matching packet dispatching scheme, is presented in the paper. The MCNS is a modification of the MSM Clos-network switch proposed to simplify the packet dispatching scheme. In this paper, we evaluate the combinatorial properties of the MCNS, as well as a new module-level matching packet dispatching algorithm. We also show how this algorithm can be implemented in an field-programmable gate array chip. Selected simulation results obtained for the MCNS are compared with the results obtained for the MSM Clos-network switch using other module-level matching algorithms.     

ZnO Nanoplatelets with Controlled Thickness: Atomic Insight into Facet-Specific Bimodal Ligand Binding Using DNP NMR

Colloidal nanoplatelets (NPLs) and nanosheets with controlled thickness have recently emerged as an exciting new class of quantum-sized nanomaterials with substantially distinct optical properties compared to 0D quantum dots. Zn-based NPLs are an attractive heavy-metal-free alternative to the so far most widespread cadmium chalcogenide colloidal 2D semiconductor nanostructures, but their synthesis remains challenging to achieve. The authors describe herein, to the best of their knowledge, the first synthesis of highly stable ZnO NPLs with the atomically precise thickness, which for the smallest NPLs is 3.2 nm (corresponding to 12 ZnO layers). Furthermore, by means of dynamic nuclear polarization-enhanced solid-state ¹⁵N NMR, the original role of the benzamidine ligands in stabilizing the surface of these nanomaterials is revealed, which can bind to both the polar and non-polar ZnO facets, acting either as X- or L-type ligands, respectively. This bimodal stabilization allows obtaining hexagonal NPLs for which the surface energy of the facets is modulated by the presence of the ligands. Thus, in-depth study of the interactions at the organic–inorganic interfaces provides a deeper understanding of the ligand–surface interface and should facilitate the future chemistry of stable-by-design nano-objects.     

Isolation of Failing Scan Cells through Convolutional Test Response Compaction

This paper describes a non-recursive fault diagnosis technique for scan-based designs with convolutional test response compaction. The proposed approach allows a time-efficient and accurate identification of failing scan cells using Gauss–Jordan elimination method.

Wireless link prediction and triggering using modified Ornstein–Uhlenbeck jump diffusion process

Through time domain observation, typical wireless signal strength values seems to exhibit some forms of mean-reverting and discontinuous “jumps” behaviour. Motivated by this fact, we propose a wireless link prediction and triggering (LPT) technique using a modified mean-reverting Ornstein–Uhlenbeck (OU) jump diffusion process. The proposed technique which we refer as OU-LPT is an integral component of wireless mesh network monitoring system developed by ICT FP7 CARrier grade wireless MEsh Network project. In particular, we demonstrate how this technique can be applied in the context of wireless mesh networks to support link switching or handover in the event of predicted link degradation or failure. The proposed technique has also been implemented and evaluated in a real-time experimental testbed. The results show that OU-LPT technique can significantly enhance the reliability of wireless links by reducing the rate of false triggers compared to a conventional linear prediction technique and therefore offers a new direction on how wireless link prediction, triggering and switching process can be conducted in the future.