In this study, a set of ceria-based catalysts were synthesized using microwave radiation coupled with sol-gel method for CO oxidation in Proton Exchange Membrane Fuel Cells (PEMFCs). The effect of Cu loading, and synthesis medium were investigated. The obtained catalysts exhibited particles with a random-shaped and a macroporous texture (SEM and porosity studies). The XRD characterization confirmed the solid-solution formation with the exception of Ce-Sm-20Cu material. Representative Raman spectra were collected in a complementary fashion with XRD. The Raman results supported the formation of fluorite cubic cell of ceria (F2g band) and the presence of oxygen vacant sites. The CO oxidation tests exhibited that the catalytic activity increases as the Cu loading increases in the Ce-Sm-xCu (x: 3, 5, 7, 10 and 20 at.%). The T50?the temperature at which 50% of the CO is converted?for the various catalysts showed a decrease in the temperature (i.e. higher activity) as the at.% Cu is increased.
Four-dimensional (4D) printing uses time-activated materials in the process of 3D printing which allows manufacturing of complex structures that change shape with time. Smart materials such as Shape Memory Polymers (SMP) exhibit the ability to change shape when subjected to heat, this allows programming of structures that can alter their properties with their shape (property tuning). The emergence of 4D printing in research requires the further investigation of the behavior of 3D printed SMPs to better clarify its behavior when made into usable application. This work aims to address the elastic behavior of a 4D printed dumbbell specimen under multiple constant programming displacement cycles. In addition, the tunability of elastic behavior is addressed by increasing programming displacement. Results indicates the negligible effect of programming cycles on the elastic behavior and the ability to tune elastic properties of 3D printed SMP materials.
This paper presents battery energy management system (BEM) in electric vehicles that run on an indirect field-oriented control (IFOC) drive system. This IFOC utilizes a Model Predictive Controller (MPC) as a speed regulator that takes into account the State of Charge (SOC) of the battery and optimizes the energy consumed from the battery by adjusting the induction motor stator current Iq. The MPC incorporates the SOC information into the optimization algorithm by adjusting the weights on the control signal Iq thus restricting its variation and consequently reduce the SOC usage. Simulation results have been obtained and a comparison between the conventional speed control MPC and an MPC with tuned weights demonstrate that both speed controllers managed to reached the required speed; however, when the SOC was used to determine the weights on Iq in the MPC, the total SOC usage was significantly reduced and therefore the battery life was extended.
Poly lactic acid (PLA), a biodegradable polymer that is derived from renewable raw materials such as corn starch and sugarcane, was used as a thermoplastic matrix in order to develop a biodegradable thermal insulation material. The Date-Pit powder (DPP) was used as a filler in the prepared renewable composites. The samples were prepared with different percentages weights of DPP (0-40 wt. %) using melt extruder and compression molding machine. PLA-DPP composites were then checked to different thermal and mechanical properties. Increasing the DPP content led to a decrease in the thermal conductivity of composite. Adding the date pit to PLA matrices reduced slightly the mechanical strength of composites, however, the measured mechanical strength was greater than that of many commercial heat insulators.
The usefulness of satellite imagery for mapping land cover classes is demonstrated. The study area, Abu Dhabi Emirate/United Arab Emirates, has witnessed considerable growth in population and regional economies during last decades. Greening and agricultural efforts have encouraged farmers to increase their properties hence cultivating more farms especially date palms. To assess and map the amount and extent of these plantations, remote sensing integrated with GIS proved to be a very powerful approach. The aim of the current study is to acquire accurate and reliable map of the most recent and updated land cover classes of the lands of the Emirate mainly date palms. Our focus is on date palm plantations class given that the UAE has the largest number of date palms for any single country in the world. Latest Landsat-8 OLI scenes from 2018 were used and a hybrid classification combining supervised and unsupervised classifications integrated with GIS were applied to achieve our objective. The outcomes of this study are: 1) a database of Landsat-8 OLI imagery of 2018 covering the whole emirate of Abu Dhabi, 2) a medium scale map representing main LULC classes and, 3) a GIS thematic layer of date palm extent in the emirate.
This paper deals with the design and the implementation of an underwater robot. The proposed design is based on a similar one taken from the literature. The developed CAD model is used to 3D print the different parts of the robot. The controller is based on an Arduino board and the actuator used is a servo motor. The prototype is built and tested.
This study explores the appropriateness of different turbulence models in a 2D numerical simulation of an airfoil with a rotating leading-edge cylinder. The validity of the employed turbulence models has been validated with experimental data for symmetric flow over NACA0024 airfoil. All four models are appropriate to model flow over the symmetric airfoil and are capable to match the experimental results. At 5? angle of attack, all turbulence models were able to better match the experimental results at the positive pressure surface than at the negative pressure surface.
As vehicle-to-vehicle communication and autonomous vehicles penetrate the market of smart cities, more techniques to solve the problem of traffic flow optimization become available. This paper addresses a new approach to tackle the problem of traffic flow optimization by simultaneously controlling the speeds and routes of vehicles. Both of these quantities can be controlled accurately in self-driving cars. The objective function is set to minimize the collective fuel consumption and traveling time of all drivers in the network. This solution can potentially improve the smoothness of traffic flow, because vehicles do not stop at intersections. Simulations were performed using MATLAB mixed-integer linear programming solver and were shown to give the optimal paths and speeds for 8 groups of cars in a 16-intersection network with a run time of less than 10 seconds.
Identifying amino acids and investigating protein structures help in isolating and understanding diseases associated with the malfunction in protein folding. The first step in understanding protein structure involves identifying the sequence of amino acids. Most current techniques for detecting amino acids are complex and time-consuming. However, with the advancement of functionalized smart materials, such as graphene and nanoscale semiconductors, the sensitivity could be improved, allowing handheld amino acid sensors. We briefly review the different schemes used in detecting amino acids, based on condensed matter phases along with the importance of studying the interface between amino acids/proteins and solid-state materials.
Third order LCL filter has several advantages over the L filter, but the associated problem of resonance can cause system instability, where resonance damping becomes necessary. Active damping can be provided by designing a state feedback controller. This paper includes the evaluation of our designs of integral linear quadratic regulator (LQR), feedback linearization (FBL) with disturbance observer based control (DOBC) together with full-order observer (FOO), reduced- order observer (ROO), and Kalman filter (KF) in terms of total harmonic distortion (THD) and robustness against changes in the grid impedance.
