Nondestructive Evaluation of Metal Matrix Composites

The objective of the subject program was to apply nondestructive evaluation (NDE) methods to assess the integrity of FP/Mg composites. The material investigated was ZE41A magnesium alloy reinforced with FP (aluminum oxide) fiber. Twenty-one specimens (three specimens of each of six flawed and three unflawed specimens) were evaluated using ultrasonic scanning, wave propagation velocity, wave attenuation coefficient, and x-ray radiograph inspection techniques. The results for two of the 21 specimens are included herein. After the NDE inspections were completed, a representative specimen from each of the seven groups was sectioned and micrographs were made for comparison with the NDE records. It was found that ultrasonic scanning using a 15 MHz compression wave, focused transducer operated in the pulse-echo mode generating an analog C-scan gave the best pictorial results. The wave attenuation and wave propagation velocity measurements were found to be consistent with the ultrasonic C-scans, but x-ray radiography was useful only at locations of gross material defects.</p

The stability of miniplate fixation for osteotomies in facial fibrous dysplasia

Ultrasonic flaw sizing based on signal analysis and classification techniques was applied to linear welding flaws of sizes ranging from 1mm to 3mm generated under controlled laboratory conditions. Over 400 ultrasonic signals were captured digitally at various positions along these linear flaws and analyzed by an advanced pattern recognition package with regard to flaw sizes. Very encouraging results were observed and in some cases 100% correct flaw sizing performance has been achieved

Morphology and electrochemical performance of Li[Ni1/3Co1/3Mn1/3]O2 cathode material by a slurry spray drying method

The spherical Li[Ni1/3Co1/3Mn1/3]O2 powders with appropriate porosity, small particle size and good particle size distribution were successfully prepared by a slurry spray drying method. The Li[Ni1/3Co1/3Mn1/3]O2 powders were characterized by XRD, SEM, ICP, BET, EIS and galvanostatic charge/discharge testing. The material calcined at 950 °C had the best electrochemical performance. Its initial discharge capacity was 188.9 mAh g-1 at the discharge rate of 0.2 C (32 mA g-1), and retained 91.4% of the capacity on going from 0.2 to 4 C rate. From the EIS result, it was found that the favorable electrochemical performance of the Li[Ni1/3Co1/3Mn1/3]O2 cathode material was primarily attributed to the particular morphology formed by the spray drying process which was favorable for the charge transfer during the deintercalation and intercalation cycling. © 2007 Elsevier B.V. All rights reserved.link_to_subscribed_fulltex

A Review and Empirical Evaluation of Feature Weighting Methods for a Class of Lazy Learning Algorithms

Many lazy learning algorithms are derivatives of the k-nearest neighbor (k-NN) classifier, which uses a distance function to generate predictions from stored instances. Several studies have shown that k-NN&apos;s performance is highly sensitive to the definition of its distance function. Many k-NN variants have been proposed to reduce this sensitivity by parameterizing the distance function with feature weights. However, these variants have not been categorized nor empirically compared. This paper reviews a class of weight-setting methods for lazy learning algorithms. We introduce a framework for distinguishing these methods and empirically compare them. We observed four trends from our experiments and conducted further studies to highlight them. Our results suggest that methods which use performance feedback to assign weight settings demonstrated three advantages over other methods: they require less pre-processing, perform better in the presence of interacting features, and generally require less training data to learn good settings. We also found that continuous weighting methods tend to outperform feature selection algorithms for tasks where some features are useful but less important than others