“ENVIRONMENTAL EFFECTS ON THE MECHANICAL BEHAVIOR OF COVETIC ALUMINUM MEMS COMPONENTS”, International Mechanical Engineering Congress and Exposition, Nov. 11-7, 2017, Tampa, FL
Covetic aluminum has been researched for its mechanical properties. It has been credited with higher strength in tensile and fatigue loading [1,2]. Modest changes in temperature during tensile testing of covetic aluminum causes significant changes in the ductility and tensile strength. Increasing the temperature from 15 °C to 44 °C causes a decrease in the tensile strength down to 63.8% but an increase in the ductility up to 117% . To further study the environmental effects, microtensile testing was carried out in an environmentally-controlled chamber using a hybrid microtester at high and low relative humidity. MEMS-scale dog-bone shaped specimens with a cross section of 200x250 microns were machined from bulk covetic aluminum using a CNC for milling their contours and a ram-type EDM for detaching them from the work piece. The chamber was purged with gases low or high in moisture maintaining a positive pressure. An Omega sensor controller unit was used to regulate the temperature and relative humidity of the chamber. The results of the tests show a reduction of ductility at high relative humidity. The implications of the results are discussed in relation to the reliability of MEMS structures.
Using Sequential LiDAR to Monitor & Catalog Recently Active Landslides in Kenton and Campbell Counties in Northern Kentucky, Roger Olson, Ben Roenker, Sarah Johnson
Landslides are a well-known but costly natural hazard in Cincinnati & Northern Kentucky, but are difficult to catalog and monitor because of the steep forested slopes that characterize the region. Using elevation change maps derived from successive LiDAR surveys from 2007 and 2012, locations of previously reported and cataloged landslides were observed, and new uncatalogued landslides were searched for. In the initial study area representing 1.6% of Kenton & Campbell counties, six out of ten previously cataloged landslides showed signs of activity, and eight previously uncatalogued landslides were identified. Both thin colluvial slides and slumps were identified using this method, and previously uncataloged landslides were either field checked or confirmed using air photos in Google Earth. The use of sequential LiDAR in this area of heavy vegetation and steep slopes appears to be a useful tool for monitoring known landslides and for delineating and cataloging new landslides, and will support further study into the character of slope movement in the region.