Corrosion behaviors of Cr2AlC/α-Al2O3 composites in 3.5 wt. % NaCl aqueous solution

Cr₂AlC and its composites containing α-Al₂O₃ (6.1 and 15.2 wt %) were prepared by hot pressing and their corrosion behaviors in air-saturated 3.5 wt % NaCl aqueous solution were investigated by electrochemical testing methods. It was revealed that the secondary phase of Al₂O₃ particles mainly distributed along grain boundaries of Cr₂AlC matrix. The potentiodynamic polarization measurements showed that the corrosion current densities of these Cr₂AlC composites were lower than that of the pure Cr₂AlC. The Aluminum in Cr₂AlC was prone to be attacked more easily. When immersed at open circuit potential (OCP), Al readily slipped out from Cr₂AlC matrix into NaCl solution in the form of dissoluble species. But in the case of polarization, regardless of potentiostatic polarization or potentiodynamic polarization, more de-intercalated Al, reacted with the electrolyte to form corrosion products of Al₂O₃ and/or AlOOH and deposited on the sample surface. For Cr₂AlC/α-Al₂O₃ composites, the presence of Al₂O₃ weakened the corrosion along grain boundaries by partly blocking the permeation of electrolyte and inhibiting the anodic dissolution process.     

ECG heart beat classification method based on modified ABC algorithm

Electrocardiogram is the most commonly used tool for the diagnosis of cardiologic diseases. In order to help cardiologists to diagnose the arrhythmias automatically, new methods for automated, computer aided ECG analysis are being developed. In this paper, a Modified Artificial Bee Colony (MABC) algorithm for ECG heart beat classification is introduced. It is applied to ECG data set which is obtained from MITBIH database and the result of MABC is compared with seventeen other classifier's accuracy.In classification problem, some features have higher distinctiveness than others. In this study, in order to find higher distinctive features, a detailed analysis has been done on time domain features. By using the right features in MABC algorithm, high classification success rate (99.30%) is obtained. Other methods generally have high classification accuracy on examined data set, but they have relatively low or even poor sensitivities for some beat types. Different data sets, unbalanced sample numbers in different classes have effect on classification result. When a balanced data set is used, MABC provided the best result as 97.96% among all classifiers.Not only part of the records from examined MITBIH database, but also all data from selected records are used to be able to use developed algorithm on a real time system in the future by using additional software modules and making adaptation on a specific hardware.     

Effect of stoichiometry and Cu-substitution on the phase structure and hydrogen storage properties of Ml-Mg-Ni-based alloys

To improve the electrochemical properties of rare-earth–Mg–Ni-based hydrogen storage alloys, the effects of stoichiometry and Cu-substitution on the phase structure and thermodynamic properties of the ...     

The implementation of a smartphone-based fall detection system using a high-level fuzzy Petri net

The falling down problem has become one of the very important issues of global public health in an aging society. The specific equipment was adopted as the detection device of falling-down in the early studies, but it is inconvenient for the elderly and difficult for future application. The smart phone more commonly used than the specific fall detection equipment is selected as a mobile device for human fall detection, and a fall detection algorithm is developed for this purpose. What the user has to do is to put the smart phone in his/her thigh pocket for falling down detection. The signals detected by the tri-axial G-sensor are converted into signal vector magnitudes as the basis of detecting a human body in a stalling condition. The Z-axis data sets are captured for identification of human body inclination and the occurrence frequencies at the peak of the area of use are used as the input parameters. A high-level fuzzy Petri net is used for the analysis and the development of identifying human actions, including normal action, exercising, and falling down. The results of this study can be used in the relevant equipments or in the field of home nursing.     

Study on metamerism degree evaluation based on wavelength sensitive cone weighting algorithm

Metamerism phenomenon can be used in illuminant detection to ensure the accuracy of light source. A method based on Long‐, Middle‐, Short‐ wavelength cones(LMS) weighting algorithm to evaluate metamerism degree is proposed. The chromatic relationship between the degree of metamerism mismatch and the light source is studied. Herein, the consistency between the metameric indices (MIs) and CIE1976 L*a*b* color difference ranking is analyzed by SRCC, KRCC, PLCC and RMSE. A statistically sampling method to obtain practical LMS cone fundamentals to evaluate metamerism degree is employed. The analysis results obtained show that the method based on LMS weighting algorithm has good evaluation ability and stability in simulation experiments and statistically sampling experiments, which are in line with visual characteristics of human. Proposed method meets the requirements of selecting metameric pairs used in light source detection. The analysis results have certain guiding significance.     

Applications of Diglycolamide Based Solvent Extraction Processes in Spent Nuclear Fuel Reprocessing,Part 1: TODGA

Over the last decade there has been much interest in the applications of diglycolamide (DGA) ligands for the extraction of the trivalent lanthanide and actinide ions from PUREX high active raffinates or dissolved spent nuclear fuel. Of the DGAs, the N,N,N’,N’-tetraoctyldiglycolamide (TODGA) is the best known and most widely studied. A number of new actinide separation processes have been proposed based on extraction with TODGA. This review covers TODGA-based processes and extraction data, specifically focusing on how phase modifiers have been used to increase metal loading and thus enhance the operating process envelopes. Effects of third phase formation and the organic phase speciation are reviewed in this context. Relevant aspects of the extraction chemistry of important solvents (TODGA-modifier-diluent combinations) are described and their performances demonstrated by a consideration of the published flowsheet tests. It is seen that modifiers are successfully enabling the use of TODGA in actinide separation processes but to date the identification and testing of suitable modifiers has been rather empirical. There is a growing understanding of the fundamental chemistry occurring in the organic phase and how that affects extractant speciation and metal loading capacity but studies are still needed if TODGA-based flowsheets are to become an industrially deployable option for minor actinide (MA) recovery processes.     

Preparation of ZrC/SiC porous self-supporting monoliths via sol-gel process using polyethylene glycol as phase separation inducer

We present a straightforward method via sol-gel process using polyethylene glycol (PEG) as phase separation inducer to prepare zirconium carbide/silicon carbide (ZrC/SiC) porous monoliths. Organic/inorganic hybrid gels are prepared using zirconium oxychloride, furfuryl alcohol, and tetraethyl orthosilicate as major starting materials. In the presence of PEG, crack-free hybrid monoliths are obtained by drying the wet gels under ambient pressure, whereas in the absence of PEG, the wet gels break into pieces as expected. PEG plays a key role in maintaining the macroscopic shape of the monoliths. After ceramization at 1300–1500?°C, ZrC/SiC porous monoliths are obtained. SEM and mercury intrusion porosimetry data show that PEG also has strong influence on the microstructures of the monoliths. The compressive strengths of the ceramic monoliths are in the range of 0.3 to 0.7?MPa. And their compressive behavior starts to differ due to the changes in their microstructures, especially the pore structure.     

Molten salt synthesis of MAX phases in the Ti-Al-C system

The molten salt method was used to synthesise the MAX phase compounds Ti₂AlC and Ti₃AlC₂ from elemental powders. Between 900–1000?°C, Ti₂AlC was formed alongside ancillary phases TiC and TiAl, which decreased in abundance with increasing synthesis temperature. Changing the stoichiometry and increasing the synthesis temperature to 1300?°C resulted in formation of Ti₃AlC₂ alongside Ti₂AlC and TiC. The type of salt flux used had little effect on the product formation. The reaction pathway for Ti₂AlC was determined to be the initial formation of TiC_1-x templating on the graphite and titanium aluminides.     

Classification and regression models of audio and vibration signals for machine state monitoring in precision machining systems

We present a data-driven method for monitoring machine status in manufacturing processes. Audio and vibration data from precision machining are used for inference in two operating scenarios: (a) variable machine health states (anomaly detection); and (b) settings of machine operation (state estimation). Audio and vibration signals are first processed through Fast Fourier Transform and Principal Component Analysis to extract transformed and informative features. These features are then used in the training of classification and regression models for machine state monitoring. Specifically, three classifiers (K-nearest neighbors, convolutional neural networks and support vector machines) and two regressors (support vector regression and neural network regression) were explored, in terms of their accuracy in machine state prediction. It is shown that the audio and vibration signals are sufficiently rich in information about the machine that 100% state classification accuracy could be accomplished. Data fusion was also explored, showing overall superior accuracy of data-driven regression models.