Effect of artificial aging on intergranular corrosion of extruded AlMgSi alloy with small Cu content

The effect of artificial aging parameters on the corrosion performance of air cooled AlMgSi(Cu) model alloy extrusions was investigated. Accelerated corrosion test revealed that the extrusions were highly susceptible to intergranular corrosion (IGC) in the naturally aged condition. However, IGC susceptibility was reduced, and finally eliminated, by artificial aging. Overaging introduced slight pitting susceptibility. EDS X-ray mapping in FE-TEM revealed Mg₂Si and Q-phase (Al₄Cu₂Mg₈Si₇) grain boundary precipitates and a continuous Cu-enriched grain boundary film. IGC susceptibility was related to the Cu-enriched grain boundary film. Increased IGC resistance was caused by coarsening of the grain boundary film by aging. Pitting susceptibility by over aging evolved due to coarsening of the Q-phase particles in the grain bodies.     

Cathodic disbonding of paint films-transport of charge

Cathodic disbonding and charge transport through paint films were studied as a function of polarization potential, temperature, dry-film thickness and cation type in the electrolyte. It was found that both the disbonding rate and the charge transport were linearly related to the polarization potential. The activation energy for the disbonding process and the charge transport were quite different. The disbonding rate was linearly related to the dry-film thickness and was dependent on the cation type in the electrolyte. This was not the case for the charge transport. The results indicate a rate controlling factor for the disbonding process involving transport of cations through the film where the film is already disbonded. A fundamental difference in the conductive properties of the paint film on either side of the disbonding front is also proposed.     

Self-organized porous TiO2 and ZrO2 produced by anodization

The present work investigates the electrochemical formation of self-organized high aspect ratio TiO₂ and ZrO₂ nanotube layers. The formation and growth of a self-organized porous layer can be achieved directly by anodization without any templates in fluoride containing electrolytes. The morphology of the porous layers is affected by the electrochemical conditions such as the electrolyte composition, the pH and the exact polarization treatment (such as the potential sweep rate from the open-circuit potential to the anodizing potential). For Ti, nanotube layers are formed with diameters varying from approx. 20 nm to 100 nm and lengths from approx. 0.25 μm to 2.5 μm depending on the electrolytes and pH. On the other hand, for Zr, tubes of 50 nm in diameter and up to approx. 17 μm in length can be grown—a key parameter in this case is the potential sweep rate. The large difference between Ti and Zr in the achievable thickness of nanotube layers indicates a difference in the growth mechanism which may be based on the different chemical dissolution rates of electrochemically formed oxides.     

Perfect Laplacians for Polygon Meshes

A discrete Laplace‐Beltrami operator is called perfect if it possesses all the important properties of its smooth counterpart. It is known which triangle meshes admit perfect Laplace operators and how to fix any other mesh by changing the combinatorics. We extend the characterization of meshes that admit perfect Laplacians to general polygon meshes. More importantly, we provide an algorithm that computes a perfect Laplace operator for any polygon mesh without changing the combinatorics, although, possibly changing the embedding. We evaluate this algorithm and demonstrate it at applications.     

A two‐level detector of short‐term unique changes in time series based on a similarity method

In the paper, a novel two‐level algorithm of time‐series change detection is presented. In the first level, to identify non‐stationary sequences in a processed signal, preliminary detection of events is performed with a short‐term prediction comparison. In the second stage, to confirm the changes detected in the first level, a similarity method aimed at identification of unique changes is employed. The detection of changes in a non‐stationary time series is discussed, implemented algorithms are described and the results produced on a sample four financial time series are shown. General conditions for implementing the proposed algorithm as an immune‐like event detector are discussed.     

Robustness of ISS systems to inputs with limited moving average: Application to spacecraft formations

We provide a theoretical framework that fits realistic challenges related to spacecraft formation with disturbances. We show that the input‐to‐state stability of such systems guarantees some robustness with respect to a class of signals with bounded average‐energy, which encompasses the typical disturbances acting on spacecraft formations. Solutions are shown to converge to the desired formation, up to an offset, which is somewhat proportional to the considered moving average of disturbances. In the presence of fast peaking perturbations, the approach provides a tighter evaluation of the disturbances' influence, which allows for the use of more parsimonious control gains. Copyright © 2015 John Wiley & Sons, Ltd.     

GpoSolver: a Matlab/C++ toolbox for global polynomial optimization

Global polynomial optimization can be a powerful tool when applied to engineering problems. One of the most successful methods for solving such problems is based on convex linear matrix inequality (LMI) relaxations. Software implementations of this approach can be found for example in Matlab toolboxes GloptiPoly and YALMIP. Matlab language makes it very easy when it comes to modelling polynomial problems. However, when using these toolboxes, Matlab is also required for the problem solving. GpoSolver aims at bridging this gap by providing a Matlab-based problem modelling toolbox supplemented by a problem-solving back end in a form of a C++ template library. Once a problem is conveniently modelled and parametrized in Matlab, a C++ class is automatically generated by GpoSolver. This class can be easily included into an existing codebase and used to solve different instances of the problem based on the supplied parameters.     

Support Vector machine and duration-aware conditional random field for identification of spatio-temporal activity patterns by combined indoor positioning and heart rate sensors

Tracking the spatio-temporal activity is highly relevant for domains like security, health, and quality management. Since animal welfare became a topic in politics and legislation locomotion patterns of livestock have received increasing interest. In contrast to the monitoring of pedestrians cattle activity tracking poses special challenges to both sensors and data analysis. Interesting states are not directly observable by a single sensor. In addition, sensors must be accepted by cattle and need to be robust enough to cope with a rough environment. In this article, we introduce the novel combination of heart rate and positioning sensors. Attached to neck and chest they are less interfering than accelerometers at the ankles. Exploiting the potential of such combined sensor system that records locomotion and non-spatial information from the heart rate sensor however is challenging. We introduce a novel two level method for the activity tracking focused on the duration and sequence of activity states. We combine Support Vector Machine (SVM) with Conditional Random Field (CRF) and extend Conditional Random fields by an explicit representation of duration. The SVM characterizes local activity states, whereas the CRF addresses sequences of local states to sequences incorporating spatial and non-spatial contextual knowledge. This combination provides a reliable and comprehensive identification of defined activity patterns, as well as their chronology and durations, suitable for the integration in an activity data base. This data base is used to extract physiological parameters and promises insights into internal states such as fitness, well-being and stress. Interestingly we were able to demonstrate a significant correlation between resting pulse rate and the day of pregnancy.