Experimental and numerical life prediction of thermally cycled thermal barrier coatings

This article addresses the predominant degradation modes and life prediction of a plasma-sprayed thermal barrier coating (TBC). The studied TBC system consists of an air-plasma-sprayed bond coat and an air-plasma-sprayed, yttria partially stabilized zirconia top layer on a conventional Hastelloy X substrate. Thermal shock tests of as-sprayed TBC and pre-oxidized TBC specimens were conducted under different burner flame conditions at Volvo Aero Corporation (Trollhättan, Sweden). Finite element models were used to simulate the thermal shock tests. Transient temperature distributions and thermal mismatch stresses in different layers of the coatings during thermal cycling were calculated. The roughness of the interface between the ceramic top coat and the bond coat was modeled through an ideally sinusoidal wavy surface. Bond coat oxidation was simulated through adding an aluminum oxide layer between the ceramic top coat and the bond coat. The calculated stresses indicated that interfacial delamination cracks, initiated in the ceramic top coat at the peak of the asperity of the interface, together with surface cracking, are the main reasons for coating failure. A phenomenological life prediction model for the coating was proposed. This model is accurate within a factor of 3.     

Application of particle swarm optimization in epileptic spike EEG source localization

Surgical therapy has become an important therapeutic alternative for patients with medically intractable epilepsy. Correct and anatomically precise localization of an epileptic focus is essential to decide if resection of brain tissue is possible. The inverse problem in EEG-based source localization is to determine the location of the brain sources that are responsible for the measured potentials at the scalp electrodes. We propose a new global optimization method based on particle swarm optimization (PSO) to solve the epileptic spike EEG source localization inverse problem. In a forward problem a modified subtraction method is proposed to reduce the computational time. The good accuracy and fast convergence are demonstrated for 2D and 3D cases with realistic head models. The results from the new method are promising for use in the pre-surgical clinic in the future.     

A bio-inspired predictive sensory-motor coordination scheme for robot reaching and preshaping

This paper presents a sensory-motor coordination scheme for a robot hand-arm-head system that provides the robot with the capability to reach an object while pre-shaping the fingers to the required grasp configuration and while predicting the tactile image that will be perceived after grasping. A model for sensory-motor coordination derived from studies in humans inspired the development of this scheme. A peculiar feature of this model is the prediction of the tactile image. The implementation of the proposed scheme is based on a neuro-fuzzy module that, after a learning phase, starting from visual data, calculates the position and orientation of the hand for reaching, selects the best-suited hand configuration, and predicts the tactile feedback. The implementation of the scheme on a humanoid robot allowed experimental validation of its effectiveness in robotics and provided perspectives on applications of sensory predictions in robot motor control.     

Agent based simulation architecture for evaluating operational policies in transshipping containers

An agent based simulator for evaluating operational policies in the transshipment of containers in a container terminal is described. The simulation tool, called SimPort, is a decentralized approach to simulating managers and entities in a container terminal. Real data from two container terminals are used as input for evaluating eight transshipment policies. The policies concern the sequencing of ships, berth allocation, and stacking rule. They are evaluated with respect to a number of aspects, such as, turn-around time for ships and traveled distance of straddle carriers. The simulation results indicate that a good choice in yard stacking and berthing position policies can lead to faster ship turn-around times. For instance, in the terminal studied the Overall-Time-Shortening policy offers fast turn-around times when combined with a Shortest-Job-First sequencing of arriving ships.     

Nano-Scratching resistance of high-chromium white cast iron and its correlation with wear of cBN tool in machining

In this paper, a nano-scratch testing approach was used to measure and evaluate the abrasion wear resistance of high-chromium white cast irons in order to understand the wear mechanism in the interaction between the high-chromium white cast iron and the cBN cutting tool during the machining process. Scratch testing was performed on a nanoindentation instrument using a diamond indenter as the scratch tool. Linear multi-pass scratches in the same path were made on pre-worn surfaces of test materials. The correlation of the scratching resistance and tool wear measured from the machining is presented by the flank wear and maximum scratch depth. The appearance of the cutting edge on a cBN tool suggests that the abrasion wear is mainly related with a combined effect of the carbides and the matrix during machining the high-chromium white cast iron.     

Cyclic Nanoindentation for Local High Cycle Fatigue Investigations: A Methodological Approach Accounting for Thermal Drift

Cyclic nanoindentation allows characterizing the influence of single phases and their interactions on fatigue mechanisms. Herein, a method for high cycle fatigue testing by nanoindentation is presented. By combining high- and low-frequency indentation modes, high cycle numbers are achieved while obtaining sufficient data points to reconstruct force–displacement hysteresis loops. A challenge is the stochastic course of thermal drift which is addressed by measuring drift rate in regular low-force holding segments. Drift rates are used to correct the displacement values, yielding reproducible cyclic deformation data as it is shown for two very different materials, a ductile metal and a brittle ceramic.     

Plasma-derived proteins in airway defence, disease and repair of epithelial injury

One significant characteristic of the airway mucosa in vivo, that cannot easily be mimicked in vitro, is its microcirculation, which generates a highly dynamic, biologically active milieu of plasma-derived molecules that may pass to the airway lumen in vivo. New data on the mechanisms of airway mucosal exudation indicate that the protein systems of circulating plasma may contribute significantly to the biology and immunology of the lamina propria, its surface epithelium and the luminal surface, not only in injured airways, but also in airways that are activated but display no sign of oedema, epithelial disruption, or increased absorption capacity. We suggest that present knowledge of the mechanisms of plasma exudation, together with rapidly emerging information (not detailed herein) on receptors, target cells and cellular responses to the plasma-derived molecules, must be considered in any realistic model that investigates "immuno-inflammatory" mechanisms of the airway mucosa.     

Poly-bagging predictors for classification modelling for credit scoring

Credit scoring modelling comprises one of the leading formal tools for supporting the granting of credit. Its core objective consists of the generation of a score by means of which potential clients can be listed in the order of the probability of default. A critical factor is whether a credit scoring model is accurate enough in order to provide correct classification of the client as a good or bad payer. In this context the concept of bootstraping aggregating (bagging) arises. The basic idea is to generate multiple classifiers by obtaining the predicted values from the fitted models to several replicated datasets and then combining them into a single predictive classification in order to improve the classification accuracy. In this paper we propose a new bagging-type variant procedure, which we call poly-bagging, consisting of combining predictors over a succession of resamplings. The study is derived by credit scoring modelling. The proposed poly-bagging procedure was applied to some different artificial datasets and to a real granting of credit dataset up to three successions of resamplings. We observed better classification accuracy for the two-bagged and the three-bagged models for all considered setups. These results lead to a strong indication that the poly-bagging approach may promote improvement on the modelling performance measures, while keeping a flexible and straightforward bagging-type structure easy to implement.     

Input-output properties of the Page-Hinkley detector

We consider the stochastic input-output properties of a simple non-linear dynamical system, the so-called Page-Hinkley detector, playing a key role in change detection, and also in queuing theory. We show that for L-mixing inputs with negative expectation the output process of this system is L-mixing. The result is applied to get an upper bound for the false alarm rate. The proof is then adapted to get a similar result for the case of random i.i.d. inputs. Possible extensions and open problems are given in the discussion.