Aircraft Icing Detection, Identification, and Reconfigurable Control Based on Kalman Filtering and Neural Networks

Flight in all weather conditions has necessitated correctly detecting icing and taking reasonable measures against it. This work aims at the detection and identification of airframe icing based on statistical properties of aircraft dynamics and reconfigurable control protecting aircraft from hazardous icing conditions. A Kalman filter is used for the data collection for the detection of icing, which aerodynamically deteriorates flight performance. A neural network process is applied for the identification of icing model of the aircraft, which is represented by five parameters based on past experiments for iced wing airfoils. Icing is detected by a Kalman filtering innovation sequence approach. A neural network structure is embodied such that its inputs are the aircraft estimated measurements and its outputs are the parameters affected by ice, which corresponds to the aircraft inverse dynamic model. The necessary training and validation set for the neural network model of the iced aircraft are obtained from the simulations of nominal model, which are performed for various icing conditions. In order to decrease noise effects on the states and to increase training performance of the neural network, the estimated states by the Kalman filter are used. A suitable neural network model of aircraft inverse dynamics is obtained by using system identification methods and learning algorithms. This trained model is used as an application for the control of the aircraft that has lost its controllability due to icing. The method is applied to F16 military and A340 commercial aircraft models and the results seem to be good enough.     

Experimental and numerical modeling of the gas atomization nozzle for gas flow behavior

Gas atomization is a widely used process for manufacturing of fine metal- and alloy-powder. To ensure a stable process with high yields of metal powder, the negative pressure at the melt delivery tube tip base and no flow separation conditions are necessary for a good atomization process. An important feature of these jets is that flow separation may occur over the outer surface of the liquid delivery tube for some conditions. Flow separation cause solidification and accumulation of metal, leading to a shape alteration of the liquid delivery tube in gas atomization process. Using computational fluid dynamics (CFD) software, a parametric study was conducted to determine the effects of atomizing gas pressure on the melt delivery tube tip base pressure and flow separation. Atomization gas pressures of 1.0, 1.3, 1.7, 2.2, and 2.7 MPa were used in the CFD model to initialize the pressure in gas inlet. CFD simulations were performed and the modeling results were compared with experimental data. These results showed that the CFD modeling can be used for the estimation of the melt tip base pressure of the nozzle. It is found that the flow separation formation is strongly dependent on the atomizing gas pressure.     

Minimally Invasive and Regenerative Therapeutics

Advances in biomaterial synthesis and fabrication, stem cell biology, bioimaging, microsurgery procedures, and microscale technologies have made minimally invasive therapeutics a viable tool in regenerative medicine. Therapeutics, herein defined as cells, biomaterials, biomolecules, and their combinations, can be delivered in a minimally invasive way to regenerate different tissues in the body, such as bone, cartilage, pancreas, cardiac, skeletal muscle, liver, skin, and neural tissues. Sophisticated methods of tracking, sensing, and stimulation of therapeutics in vivo using nano‐biomaterials and soft bioelectronic devices provide great opportunities to further develop minimally invasive and regenerative therapeutics (MIRET). In general, minimally invasive delivery methods offer high yield with low risk of complications and reduced costs compared to conventional delivery methods. Here, minimally invasive approaches for delivering regenerative therapeutics into the body are reviewed. The use of MIRET to treat different tissues and organs is described. Although some clinical trials have been performed using MIRET, it is hoped that such therapeutics find wider applications to treat patients. Finally, some future perspective and challenges for this emerging field are highlighted.