Groups of diffeomorphisms and the solution of the classical Euler equations for a perfect fluid.

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On the motion of incompressible fluids

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Simple Preparation of Ni and NiO Nanoparticles Using Raffinate Solution Originated from Spent NiMH Battery Recycling

Nickel (Ni) and nickel oxide (NiO) nanoparticles were produced by a combination of precipitation and reduction/calcination methods using the raffinate solution originated from laboratory scale spent NiMH recovery process. Ni recovery from the solution reached 99.8% by a simple precipitation step using baking soda. X-ray diffraction, FTIR spectroscopy, carbon analyzer and thermal gravimetric analysis techniques were used to characterize the precipitate. Metallic and oxide nanoparticles were obtained by hydrogen reduction and calcination under air atmosphere of the precipitate at 400\ua0\ub0C, respectively for 30–90\ua0min residence times. The crystal structure, crystallite size, morphology, particle size and surface area of the samples, as well as carbon residue content in the particles were detected by particle characterization methods. The results indicate that spherical Ni nanoparticles have a crystallite size about 37\ua0nm, and particle sizes of around 100\ua0nm. The agglomeration of the nanoparticles reduces by increasing residence time. NiO nanoparticles have finer crystallite and particle sizes than the metallic samples produced at the same temperature and residence times. The results show that the combination of the simple methods presented can be an alternative process for producing advanced particles from spent NiMH batteries

Developing restoration schemes for a road transportation network in the event of a disaster

Transportation systems such as rail, road, and waterways are key component of critical infrastructure systems, providing connectivity between other components to enable the production and distribution of goods and services. During large scale disasters such as earth quakes and floods, this connectivity is disrupted, restricting or completely halting the flow of goods and services. To ensure that the connectivity between the different modes of transportation are restored in an aftermath of these disruptions, the interdependence between them and the importance of individual elements to the overall connectivity have to be studied and formulated to develop a system-level restoration plan. This paper presents a framework to develop efficient restoration schemes for a road transportation network in an aftermath of a disruption. The road transportation network is modelled using graph theory analytics. Using a system oriented parameter such as the Eigen-vector centrality measure associated with the road transportation, it is possible to understand the importance of different network components. This model captures the interdependence between the different elements in the road transportation network critical in understanding failure effects by identifying the important nodes in the network using the Eigen-vector centrality measure. The model is constructed from publically available data for Saint-Louis, Missouri. By performing a sensitivity analysis, we have found that the node with the highest Eigen-vector centrality measures are shown to provide a higher value within a ninety-five percent confidence level, indicating low sensitivity to changes in input parameters. This provides a measure to determine the most important nodes to place back into service to assist in restoring an urban center\u27s supply chain in the wake of an extreme event. --Abstract, page iii