Optimization of an axial fan for air cooled condensers

We report on the low noise optimization of an axial fan specifically designed for the cooling of CSP power plants. The duty point presents an uncommon combination of a load coefficient of 0.11, a flow coefficient of 0.23 and a static efficiency ηstat > 0.6. Calculated fan Reynolds number is equal to Re = 2.85 x 107. Here we present a process used to optimize and numerically verify the fan performance. The optimization of the blade was carried out with a Python code through a brute-force-search algorithm. Using this approach the chord and pitch distributions of the original blade are varied under geometrical constraints, generating a population of over 24000 different possible individuals. Each individual was then tested using an axisymmetric Python code. The software is based on a blade element axisymmetric principle whereby the rotor blade is divided into a number of streamlines. For each of these streamlines, relationships for velocity and pressure are derived from conservation laws for mass, tangential momentum and energy of incompressible flows. The final geometry was eventually chosen among the individuals with the maximum efficiency. The final design performance was then validated through with a CFD simulation. The simulation was carried out using a RANS approach, with the cubic k -  low Reynolds turbulence closure of Lien et al. The numerical simulation was able to verify the air performance of the fan and was used to derive blade-to-blade distributions of design parameters such as flow deviation, velocity components, specific work and diffusion factor of the optimized blade. All the computations were performed in OpenFoam, an open source C++- based CFD library. This work was carried out under MinWaterCSP project, funded by EU H2020 programme

Characterization of Fe-N nanocrystals and nitrogen–containing inclusions in (Ga,Fe)N thin films using transmission electron microscopy

Nanometric inclusions filled with nitrogen, located adjacent to FenN (n¼3 or 4) nanocrystals within (Ga,Fe)N layers, are identified and characterized using scanning transmission electron microscopy (STEM) and electron energy-loss spectroscopy (EELS). High-resolution STEM images reveal a truncation of the Fe-N nanocrystals at their boundaries with the nitrogen-containing inclusions. A controlled electron beam hole drilling experiment is used to release nitrogen gas from an inclusion in situ in the electron microscope. The density of nitrogen in an individual inclusion is measured to be 1.460.3 g/cm3. These observations provide an explanation for the location of surplus nitrogen in the (Ga,Fe)N layers, which is liberated by the nucleation of FenN (n>1) nanocrystals during growth

Paramagnetic GaN:Fe and ferromagnetic (Ga,Fe)N - relation between structural, electronic, and magnetic properties

We report on the metalorganic chemical vapor deposition (MOCVD) of GaN:Fe and (Ga,Fe)N layers on c-sapphire substrates and their thorough characterization via high-resolution x-ray diffraction (HRXRD), transmission electron microscopy (TEM), spatially-resolved energy dispersive X-ray spectroscopy (EDS), secondary-ion mass spectroscopy (SIMS), photoluminescence (PL), Hall-effect, electron-paramagnetic resonance (EPR), and magnetometry employing a superconducting quantum interference device (SQUID). A combination of TEM and EDS reveals the presence of coherent nanocrystals presumably FexN with the composition and lattice parameter imposed by the host. From both TEM and SIMS studies, it is stated that the density of nanocrystals and, thus the Fe concentration increases towards the surface. In layers with iron content x<0.4% the presence of ferromagnetic signatures, such as magnetization hysteresis and spontaneous magnetization, have been detected. We link the presence of ferromagnetic signatures to the formation of Fe-rich nanocrystals, as evidenced by TEM and EDS studies. This interpretation is supported by magnetization measurements after cooling in- and without an external magnetic field, pointing to superparamagnetic properties of the system. It is argued that the high temperature ferromagnetic response due to spinodal decomposition into regions with small and large concentration of the magnetic component is a generic property of diluted magnetic semiconductors and diluted magnetic oxides showing high apparent Curie temperature.Comment: 21 pages, 30 figures, submitted to Phys. Rev.

Study on the presence and perception of coypu (Myocastor coypus Molina, 1782) in three areas of Lazio region (Italy)

Adriani, S., Bonanni, M., Amici, A

Is the Italian strategy to face the problem of stray dogs sustainable? A case study of two small municipalities in central Italy

Adriani, S., Bonanni, M., Amici, A

Progress in the research on HPV vaccination: updates from the 25th International Papillomavirus Conference in Malmo, Sweden, 2009

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Monte Carlo Tree Search Planning for continuous action and state space

Sequential decision-making in real-world environments is an important problem of artificial intelligence and robotics. In the last decade reinforcement learning has provided effective solutions in small and simulated environments but it has also shown some limits on large and real-world domains characterized by continuous state and action spaces. In this work, we aim to evaluate some state-of-the-art algorithms based on Monte Carlo Tree Search planning in continuous state/action spaces and propose a first version of a new algorithm based on action widening. Algorithms are evaluated on a synthetic domain in which the agent aims to control a car through a narrow curve for reaching the goal in the shortest possible time and avoiding the car going off the road. We show that the proposed method outperforms the state-of-the-art techniques