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I remember waking up in a lot of pain in my joints and my chest which persisted for days and a gallon of pineapple juice was needed to erase the copper taste in my mouth (perhaps from salts forming). After the incident I disassembled and inspected the lamp. A wire insulation had cracked open and contacted the metal body from inside. There was no apparent mechanical reason or signs or aging to provoke it, but it had happened anyway, at a place impossible to see. Perhaps it was there when lamp was purchased, and been there all along, but nobody noticed it because we were always insulated by the thick carpet and touching the lamp had never grounded anybody.
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They come in all sizes, and the strategic advantage UAV platforms offer for US Military and National interests is undeniable. For the military it is the ultimate intelligence platform, and a force multiplier. For civilian use, UAV could save countless lives in an urban conflagration or natural disaster; search-and-rescue in environments that preclude or discourage direct human involvement (fire, floods, etc), disaster response for nuclear facilities, inspecting bridges, wind turbines, and dams for dangerous cracks and flaws, as well as monitoring the mechanical and structural health of the electric power infrastructure are some of the many applications. However the UAV depends on GPS technology and it is not a question of if, but when, GPS will fail us at a critical time of need. Satellites are ageing, our orbit is a shooting gallery of debris, we are flooding the airwaves with a deluge of radio-conflict, and multi-path errors are already a cause of concern for small UAV platforms. We do not have the same economy when we first launched the satellites, but the future of intelligence, surveillance and reconnaissance missions will depend on our adaptation to GPS-denied environments. Cyber-attacks such as GPS spoofing and jamming are even more immediate threats. Transmitting on the same radio frequencies at a high enough power will deny the service of the radio spectrum to the GPS receiver and it can allow an attacker confuse a UAV. If you have ever flown with any major airline, this also concerns you, because chances are your flight was brought to a safe landing by the Triplex-Autoland system, which too depends on GPS. The grave ramifications of someone with a big antenna, a soldering iron, a degree in EE and malicious intent, can range from the GPS in your automobile directing you to train tracks to armed UAVs, guided munitions and re-entry vehicles getting re-routed.
In collaboration with Space Systems and Controls Laboratory (SSCL) I created of one of the most influential aircraft in the U.S. today; the one-of-a-kind Saint- Helicopter, my brainchild, the smallest IUAV helicopter in the world which is fully autonomous, fully self-contained, and featuring on-board monocular simultaneous localization and mapping capability. In other words this machine was capable to draw floor plans of previously unknown buildings and urban areas, in flight, without GPS coverage, autonomously. SSCL is a NASA sponsored independent research laboratory under the Iowa Space Grant Consortium (ISGS), which is further funded by research grants and private donations from Boeing and Lockheed-Martin. It is the laboratory that built and operated the first generation of small spacecraft in Iowa. SSCL projects flew on-board the Space Shuttle Endeavor, and the NASA KC-135A. Saint-Vertigo with the SSCL brand on it was demonstrated to U.S. Air Force, Boeing, RCI, IEEE Robotics and Automation Society, as well as U.S. Army helicopter pilots with flight hours in Vietnam. I have dreamed and created it from scratch, including the airframe, electronics, computer-architectures, control systems, as well as software and algorithms. It required understanding of five different engineering disciplines to invent it. It proved an impacting research platform which allowed development of solutions for bridging the gap in between practical GPS coverage and image navigation. It was well received by the robotics and aerospace society, and the peer-reviewed scientific contributions of this machine are already giving the research in its field a new direction. Saint-Vertigo is a compact, rugged, 3D-agile IUAV transportable in a backpack, very difficult to shoot at, and can fly in congested, isolated, GPS-denied, or hostile areas where fixed-wing aircraft cannot take off, fly through, or land. The strategic advantage this can bring to US Troops and Special Forces in environments where conventional surveillance is not applicable (e.g., below-canopy jungles and riverine environments) aside, my technology is paving the way for GPS-independent navigation systems of the future. The civilian uses of such a spatially aware flying robot, will be in environments that preclude or discourage direct human involvement such as escape from fire and floods, disaster response for nuclear facilities, inspecting bridges, wind turbines, and dams for dangerous cracks and flaws (Minneapolis I-35 Bridge collapse was preventable with such continuous monitoring), search-and-rescue, as well as monitoring the mechanical and structural health of the electric power infrastructure where it can survey an area, process sensor data, identify risk, and help people make safe transit through a dangerous area. This could save countless lives in an urban conflagration or natural disaster. It attracted a $500,000 grant from the Air Force Research Laboratory and $600.000 from Office of Naval Research.
Hard, brittle and wear-resistant materials like ceramics pose a problem when being machined using conventional machining processes. Machining ceramics even with a diamond cutting tool is very difficult and costly. Near net-shape processes, like laser evaporation, produce micro-cracks that require extra finishing. Thus it is anticipated that ceramic machining will have to continue to be explored with new-sprung techniques before ceramic materials become commonplace. This numerical investigation results from the numerical simulations of the thermal and mechanical modeling of simultaneous material removal from hard-to-machine materials using both laser ablation and conventional tool cutting utilizing the finite element method. The model is formulated using a two dimensional, planar, computational domain. The process simulation acronymed, LAHM (Laser Ablation Hybrid Machining), uses laser energy for two purposes. The first purpose is to remove the material by ablation. The second purpose is to heat the unremoved material that lies below the ablated material in order to ``soften'' it. The softened material is then simultaneously removed by conventional machining processes. The complete solution determines the temperature distribution and stress contours within the material and tracks the moving boundary that occurs due to material ablation. The temperature distribution is used to determine the distance below the phase change surface where sufficient ``softening'' has occurred, so that a cutting tool may be used to remove additional material. The model incorporated for tracking the ablative surface does not assume an isothermal melt phase (e.g. Stefan problem) for laser ablation. Both surface absorption and volume absorption of laser energy as function of depth have been considered in the models. LAHM, from the thermal and mechanical point of view is a complex machining process involving large deformations at high strain rates, thermal effects of the laser, removal of
The aim of this study was to evaluate the damage tolerance of different zirconia-based materials. Bars of one hard machined and one soft machined dental zirconia and an experimental 95% zirconia 5% alumina ceramic were subjected to 100,000 stress cycles (n = 10), indented to provoke cracks on the tensile stress side (n = 10), and left untreated as controls (n = 10). The experimental material demonstrated a higher relative damage tolerance, with a 40% reduction compared to 68% for the hard machined zirconia and 84% for the soft machined zirconia.
The relationships between the fatigue crack growth rate ( d a / d N ) and stress intensity factor range ( Δ K ) are not always linear even in the Paris region. The stress ratio effects on fatigue crack growth rate are diverse in different materials. However, most existing fatigue crack growth models cannot handle these nonlinearities appropriately. The machine learning method provides a flexible approach to the modeling of fatigue crack growth because of its excellent nonlinear approximation and multivariable learning ability. In this paper, a fatigue crack growth calculation method is proposed based on three different machine learning algorithms (MLAs): extreme learning machine (ELM), radial basis function network (RBFN) and genetic algorithms optimized back propagation network (GABP). The MLA based method is validated using testing data of different materials. The three MLAs are compared with each other as well as the classical two-parameter model ( K * approach). The results show that the predictions of MLAs are superior to those of K * approach in accuracy and effectiveness, and the ELM based algorithms show overall the best agreement with the experimental data out of the three MLAs, for its global optimization and extrapolation ability.
A process for improving the strength of laser-machined articles formed of a silicon-based ceramic material such as silicon nitride, in which the laser-machined surface is immersed in an etching solution of hydrofluoric acid and nitric acid for a duration sufficient to remove substantially all of a silicon film residue on the surface but insufficient to allow the solution to unduly attack the grain boundaries of the underlying silicon nitride substrate. This effectively removes the silicon film as a source of cracks that otherwise could propagate downwardly into the silicon nitride substrate and significantly reduce its strength.