Processes controlling atmospheric dispersion through city centres

We develop a process-based model for the dispersion of a passive scalar in the turbulent flow around the buildings of a city centre. The street network model is based on dividing the airspace of the streets and intersections into boxes, within which the turbulence renders the air well mixed. Mean flow advection through the network of street and intersection boxes then mediates further lateral dispersion. At the same time turbulent mixing in the vertical detrains scalar from the streets and intersections into the turbulent boundary layer above the buildings. When the geometry is regular, the street network model has an analytical solution that describes the variation in concentration in a near-field downwind of a single source, where the majority of scalar lies below roof level. The power of the analytical solution is that it demonstrates how the concentration is determined by only three parameters. The plume direction parameter describes the branching of scalar at the street intersections and hence determines the direction of the plume centreline, which may be very different from the above-roof wind direction. The transmission parameter determines the distance travelled before the majority of scalar is detrained into the atmospheric boundary layer above roof level and conventional atmospheric turbulence takes over as the dominant mixing process. Finally, a normalised source strength multiplies this pattern of concentration. This analytical solution converges to a Gaussian plume after a large number of intersections have been traversed, providing theoretical justification for previous studies that have developed empirical fits to Gaussian plume models. The analytical solution is shown to compare well with very high-resolution simulations and with wind tunnel experiments, although re-entrainment of scalar previously detrained into the boundary layer above roofs, which is not accounted for in the analytical solution, is shown to become an important process further downwind from the source.

Dust and smoke transport from Africa to South America: Lidar profiling over Cape Verde and the Amazon rainforest

Quasi-simultaneous vertically resolved multiwavelength aerosol Raman lidar observations were conducted in the near field (Praia, Cape Verde, 15 degrees N, 23.5 degrees W) and in the far field (Manaus, Amazon basin, Brazil, 2.5 degrees S, 60 degrees W) of the long-range transport regime between West Africa and South America. Based on a unique data set (case study) of spectrally resolved backscatter and extinction coefficients, and of the depolarization ratio a detailed characterization of aerosol properties, vertical stratification, mixing, and aging behavior during the long-distance travel in February 2008 (dry season in western Africa, wet season in the Amazon basin) is presented. While highly stratified aerosol layers of dust and smoke up to 5.5 km height were found close to Africa, the aerosol over Manaus was almost well-mixed, reached up to 3.5 km, and mainly consisted of aged biomass burning smoke. Citation: Ansmann, A., H. Baars, M. Tesche, D. Muller, D. Althausen, R. Engelmann, T. Pauliquevis, and P. Artaxo (2009), Dust and smoke transport from Africa to South America: Lidar profiling over Cape Verde and the Amazon rainforest, Geophys. Res. Lett., 36, L11802, doi: 10.1029/2009GL037923.

Structural integrity identification based on smart materials and neural networks

This paper presents a non-model based technique to detect, locate, and characterize structural damage by combining the impedance-based structural health monitoring technique with an artificial neural network. The impedance-based structural health monitoring technique, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations (typically>30 kHz), this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors. In order to quantitatively assess the state of structures, two sets of artificial neural networks, which utilize measured electrical impedance signals for input patterns, were developed. By employing high frequency ranges and by incorporating neural network features, this technique is able to detect the damage in its early stage and to estimate the nature of damage without prior knowledge of the model of structures. The paper concludes with an experimental example, an investigation on a massive quarter scale model of a steel bridge section, in order to verify the performance of this proposed methodology.

Structural health evaluation by optimization techinique and artificial neural network

This paper presents two different approaches to detect, locate, and characterize structural damage. Both techniques utilize electrical impedance in a first stage to locate the damaged area. In the second stage, to quantify the damage severity, one can use neural network, or optimization technique. The electrical impedance-based, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations, this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors, and therefore, it is able to detect the damage in its early stage. Optimization approaches must be used for the case where a good condensed model is known, while neural network can be also used to estimate the nature of damage without prior knowledge of the model of the structure. The paper concludes with an experimental example in a welded cubic aluminum structure, in order to verify the performance of these two proposed methodologies.

Impedance-based structural health monitoring with artificial neural networks

This paper presents a non-model based technique to detect, locate, and characterize structural damage by combining the impedance-based structural health monitoring technique with an artificial neural network. The impedance-based structural health monitoring technique, which utilizes the electromechanical coupling property of piezoelectric materials, has shown engineering feasibility in a variety of practical field applications. Relying on high frequency structural excitations (typically >30 kHz), this technique is very sensitive to minor structural changes in the near field of the piezoelectric sensors. In order to quantitatively assess the state of structures, multiple sets of artificial neural networks, which utilize measured electrical impedance signals for input patterns, were developed. By employing high frequency ranges and by incorporating neural network features, this technique is able to detect the damage in its early stage and to estimate the nature of damage without prior knowledge of the model of structures. The paper concludes with experimental examples, investigations on a massive quarter scale model of a steel bridge section and a space truss structure, in order to verify the performance of this proposed methodology.

Lidar observation campaign of sugar cane fires and industrial emissions in the State of São Paulo, Brazil

Brazil has an important role in the biomass burning, with the detection of approximately 100,000 burning spots in a single year (2007). Most of these spots occur in the southern part of the Amazon basin during the dry season (from August to november) and these emissions reach the southeast of the country, a highly populated region and with serious urban air pollution problems. With the growing demand on biofuels, sugarcane is considerably expanding in the state of São Paulo, being a strong contributor to the bad air quality in this region. In the state of São Paulo, the main land use are pasture and sugarcane crop, that covers around 50% and 10% of the total area, respectively. Despite the aerosol from sugarcane burning having reduced atmospheric residence time, from a few days to some weeks, they might get together with those aerosol which spread over long distances (hundreds to thousands of kilometers). In the period of June through February 2010 a LIDAR observation campaign was carried in the state of São Paulo, Brazil, in order to observe and characterize optically the aerosols from two distinct sources, namely, sugar cane biomass burning and industrial emissions. For this purpose 2 LIDAR systems were available, one mobile and the other placed in a laboratory, both working in the visible (532 nm) and additionally the mobile system had a Raman channel available (607 nm). Also this campaign counted with a SODAR, a meteorological RADAR specially set up to detect aerosol echoes and gas-particle analyzers. To guarantee a good regional coverage 4 distinct sites were available to deploy the instruments, 2 in the near field of biomass burning activities (Rio Claro and Bauru), one for industrial emissions (Cubatão) and others from urban sources (São Paulo). The whole campaign provide the equivalent of 30 days of measurements which allowed us to get aerosol optical properties such as backscattering/extinction coefficients, scatter and LIDAR ratios, those were used to correlate with air quality and meteorological indicators and quantities. In this paper we should focus on the preliminary results of the Raman LIDAR system and its derived aerosol optical quantities. © 2010 Copyright SPIE - The International Society for Optical Engineering.

Desenvolvimento de um algoritmo computacional MoM 3D aplicado em nanoplasmônica

Este trabalho apresenta o desenvolvimento de um algoritmo computacional para análise do espalhamento eletromagnético de nanoestruturas plasmônicas isoladas. O Método dos Momentos tridimensional (MoM-3D) foi utilizado para resolver numericamente a equação integral do campo elétrico, e o modelo de Lorentz-Drude foi usado para representar a permissividade complexa das nanoestruturas metálicas. Baseado nesta modelagem matemática, um algoritmo computacional escrito em linguagem C foi desenvolvido. Como exemplo de aplicação e validação do código, dois problemas clássicos de espalhamento eletromagnético de nanopartículas metálicas foram analisados: nanoesfera e nanobarra, onde foram calculadas a resposta espectral e a distribuição do campo próximo. Os resultados obtidos foram comparados com resultados calculados por outros modelos e observou-se uma boa concordância e convergência entre eles.

Development of computational 3D MoM algorithm for nanoplasmonics

In this paper, we present an algorithm for full-wave electromagnetic analysis of nanoplasmonic structures. We use the three-dimensional Method of Moments to solve the electric field integral equation. The computational algorithm is developed in the language C. As examples of application of the code, the problems of scattering from a nanosphere and a rectangular nanorod are analyzed. The calculated characteristics are the near field distribution and the spectral response of these nanoparticles. The convergence of the method for different discretization sizes is also discussed.

Analysis of modified bowtie nanoantennas in the excitation and emission regimes

In this work, we analyze modified bowtie nanoantennas with polynomial sides in the excitation and emission regimes. In the excitation regime, the antennas are illuminated by an incident plane wave, and in the emission regime, the excitation is fulfilled by infinitesimal electric dipole positioned in the gap of the nanoantennas. Several antennas with different sizes and polynomial order were numerically analyzed by method of moments. The results show that these novel antennas possess a controllable resonance by the polynomial order and good characteristics of near field enhancement and confinement for applications in enhancement of spontaneous emission of a single molecule.

Trajetórias tecnológicas da indústria de telefonia móvel: um exame prospectivo de tecnologias emergentes

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Production and characterization of Tm3+/Yb3+ codoped pedestal-type PbO-GeO2 waveguides

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Numerical study of Mach number and thermal effects on sound radiation by a mixing layer

Mach number and thermal effects on the mechanisms of sound generation and propagation are investigated in spatially evolving two-dimensional isothermal and non-isothermal mixing layers at Mach number ranging from 0.2 to 0.4 and Reynolds number of 400. A characteristic-based formulation is used to solve by direct numerical simulation the compressible Navier-Stokes equations using high-order schemes. The radiated sound is directly computed in a domain that includes both the near-field aerodynamic source region and the far-field sound propagation. In the isothermal mixing layer, Mach number effects may be identified in the acoustic field through an increase of the directivity associated with the non-compactness of the acoustic sources. Baroclinic instability effects may be recognized in the non-isothermal mixing layer, as the presence of counter-rotating vorticity layers, the resulting acoustic sources being found less efficient. An analysis based on the acoustic analogy shows that the directivity increase with the Mach number can be associated with the emergence of density fluctuations of weak amplitude but very efficient in terms of noise generation at shallow angle. This influence, combined with convection and refraction effects, is found to shape the acoustic wavefront pattern depending on the Mach number.