The development of technology for the electrodeposition of aluminum alloys and beryllium Final report

Technology development for electrodeposition of aluminum alloys and berylliu

Cohomological characterization of vector bundles on multiprojective spaces

We show that Horrock's criterion for the splitting of vector bundles on \PP^n can be extended to vector bundles on multiprojective spaces and to smooth projective varieties with the weak CM property (see Definition 3.11). As a main tool we use the theory of $n$-blocks and Beilinson's type spectral sequences. Cohomological characterizations of vector bundles are also showed

Simulating the Effects of Substrate Pre-Heating on the Final Structure of Steel Parts Built by Laser Powder Deposition

Tool steel parts built by laser powder deposition often present a heterogeneous distribution of properties caused by the complex structural transformations that occur during the deposition process. A model describing these transformations has been developed. It couples finite element heat transfer calculations with transformation kinetic theory to predict the final microstructure and properties of the material and their variation across a laser powder deposited part. Pre-heating is often used to reduce the residual stresses and the risk of thermal distortion and cracking. However, this changes the heat transfer conditions and affects the final microstructure and properties. In this work the proposed model was used to evaluate the effects of substrate preheating on the final hardness distribution. The results show that the final hardness depends considerably on the initial temperature of the substrate.Mechanical Engineerin

Growth-Driven Percolations: The Dynamics of Community Formation in Neuronal Systems

The quintessential property of neuronal systems is their intensive patterns of selective synaptic connections. The current work describes a physics-based approach to neuronal shape modeling and synthesis and its consideration for the simulation of neuronal development and the formation of neuronal communities. Starting from images of real neurons, geometrical measurements are obtained and used to construct probabilistic models which can be subsequently sampled in order to produce morphologically realistic neuronal cells. Such cells are progressively grown while monitoring their connections along time, which are analysed in terms of percolation concepts. However, unlike traditional percolation, the critical point is verified along the growth stages, not the density of cells, which remains constant throughout the neuronal growth dynamics. It is shown, through simulations, that growing beta cells tend to reach percolation sooner than the alpha counterparts with the same diameter. Also, the percolation becomes more abrupt for higher densities of cells, being markedly sharper for the beta cells.Comment: 8 pages, 10 figure