Numerical methods and tangible interfaces for pollutant dispersion simulation

Dissertação apresentada para obtenção do Grau de Doutor em Engenharia do Ambiente, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Use of a condom in sex relations by HIV carriers

The frequency with which condoms are used in sex relations by subjects with HIV was determined by interviewing 132 individuals, 82 men and 50 women, most of them from São Paulo state and some from other regions of the country, all of them seen at an outpatient clinic of the School of Medicine in Botucatu. The women were younger, were of lower educational level and had poorer professional qualification than men. Also, a greater proportion of women were widowed, separated or divorced. We observed that 43.9% of men and 72% of women had been contaminated by the sexual route, but only 41.2% of the men and 31.8% of the women reported the use of a condom after the diagnosis of infection, with most men and women preferring sexual abstinence. The results enable the conclusion that there is still a need to continue to provide information about the use of condoms and to guarantee their free-of-charge distribution due to the low levels of education and professional qualification of the individuals studied. The data also suggest that campaigns for the dissemination of preventive measures should consider the social and cultural differences of infected women.

Semantic relations extraction from unstructured information for domain ontologies enrichment

Based in internet growth, through semantic web, together with communication speed improvement and fast development of storage device sizes, data and information volume rises considerably every day. Because of this, in the last few years there has been a growing interest in structures for formal representation with suitable characteristics, such as the possibility to organize data and information, as well as the reuse of its contents aimed for the generation of new knowledge. Controlled Vocabulary, specifically Ontologies, present themselves in the lead as one of such structures of representation with high potential. Not only allow for data representation, as well as the reuse of such data for knowledge extraction, coupled with its subsequent storage through not so complex formalisms. However, for the purpose of assuring that ontology knowledge is always up to date, they need maintenance. Ontology Learning is an area which studies the details of update and maintenance of ontologies. It is worth noting that relevant literature already presents first results on automatic maintenance of ontologies, but still in a very early stage. Human-based processes are still the current way to update and maintain an ontology, which turns this into a cumbersome task. The generation of new knowledge aimed for ontology growth can be done based in Data Mining techniques, which is an area that studies techniques for data processing, pattern discovery and knowledge extraction in IT systems. This work aims at proposing a novel semi-automatic method for knowledge extraction from unstructured data sources, using Data Mining techniques, namely through pattern discovery, focused in improving the precision of concept and its semantic relations present in an ontology. In order to verify the applicability of the proposed method, a proof of concept was developed, presenting its results, which were applied in building and construction sector.

The role of dispersion into assets allocation

Dispersion of returns has gained a lot of attention as a measure to distinguish good and bad investment opportunities time. In the following dissertation, the cross-sectional returns volatility is analyzed over a fifteen year period across the S&P100 Index composition. The main inference drawn from the data sample is that the canonical measure of dispersion is highly macro-risk driven and therefore more biased towards returns volatility rather than its correlation component.

Probing dispersion and re-agglomeration phenomena upon melt-mixing of polymer-functionalized graphite nanoplates

A one-step melt-mixing method is proposed to study dispersion and re-agglomeration phenomena of the as-received and functionalized graphite nanoplates in polypropylene melts. Graphite nanoplates were chemically modified via 1,3-dipolar cycloaddition of an azomethine ylide and then grafted with polypropylene-graft-maleic anhydride. The effect of surface functionalization on the dispersion kinetics, nanoparticle re-agglomeration and interface bonding with the polymer is investigated. Nanocomposites with 2 or 10 wt% of as-received and functionalized graphite nanoplates were prepared in a small-scale prototype mixer coupled to a capillary rheometer. Samples were collected along the flow axis and characterized by optical microscopy, scanning electron microscopy and electrical conductivity measurements. The as-received graphite nanoplates tend to re-agglomerate upon stress relaxation of the polymer melt. The covalent attachment of a polymer to the nanoparticle surface enhances the stability of dispersion, delaying the re-agglomeration. Surface modification also improves interfacial interactions and the resulting composites presented improved electrical conductivity.

Dispersion and re-agglomeration of graphite nanoplates in polypropylene melts under controlled flow conditions

The kinetics of GnP dispersion in polypropylene melt was studied using a prototype small scale modular extensional mixer. Its modular nature enabled the sequential application of a mixing step, melt relaxation, and a second mixing step. The latter could reproduce the flow conditions on the first mixing step, or generate milder flow conditions. The effect of these sequences of flow constraints upon GnP dispersion along the mixer length was studied for composites with 2 and 10 wt.% GnP. The samples collected along the first mixing zone showed a gradual decrease of number and size of GnP agglomerates, at a rate that was independent of the flow conditions imposed to the melt, but dependent on composition. The relaxation zone induced GnP re-agglomeration, and the application of a second mixing step caused variable dispersion results that were largely dependent on the hydrodynamic stresses generated.

Dispersion of graphite nanoplates during melt mixing

Artigo publicado a convite da Society for Polymer Engineers

Dispersion of fillers in viscoelastic polymer matrices using Eulerian-Lagrangian approaches

Understanding the behavior of c omplex composite materials using mixing procedures is fundamental in several industrial processes. For instance, polymer composites are usually manufactured using dispersion of fillers in polymer melt matrices. The success of the filler dispersion depends both on the complex flow patterns generated and on the polymer melt rheological behavior. Consequently, the availability of a numerical tool that allow to model both fluid and particle would be very useful to increase the process insight. Nowadays there ar e computational tools that allow modeling the behavior of filled systems, taking into account both the behavior of the fluid (Computational Rheology) and the particles (Discrete Element Method). One example is the DPMFoam solver of the OpenFOAM ® framework where the averaged volume fraction momentum and mass conservation equations are used to describe the fluid (continuous phase) rheology, and the Newton’s second law of motion is used to compute the particles (discrete phase) movement. In this work the refer red solver is extended to take into account the elasticity of the polymer melts for the continuous phase. The solver capabilities will be illustrated by studying the effect of the fluid rheology on the filler dispersion, taking into account different fluid types (generalized Newtonian or viscoelastic) and particles volume fraction and size. The results obtained are used to evaluate the relevance of considering the fluid complex rheology for the prediction of the composites morphology

Understanding the dispersion of fillers in polymer matrices

Understanding the mixing process of complex composite materials is fundamental in several industrial processes. For instance, the dispersion of fillers in polymer melt matrices is commonly employed to manufacture polymer composites, using a twin-screw extruder. The effectiveness of the filler dispersion depends not only on the complex flow patterns generated, but also on the polymer melt rheological behavior. Therefore, the availability of a numerical tool able to predict mixing, taking into account both fluid and particles phases would be very useful to increase the process insight, and thus provide useful guidelines for its optimization. In this work, a new Eulerian-Lagrangian numerical solver is developed OpenFOAM® computational library, and used to better understand the mechanisms determining the dispersion of fillers in polymer matrices. Particular attention will be given to the effect of the rheological model used to represent the fluid behavior, on the level of dispersion obtained. For the Eulerian phase the averaged volume fraction governing equations (conservation of mass and linear momentum) are used to describe the fluid behavior. In the case of the Lagrangian phase, Newton’s second law of motion is used to compute the particles trajectories and velocity. To study the effect of fluid behavior on the filler dispersion, several systems are modeled considering different fluid types (generalized Newtonian or viscoelastic) and particles volume fraction and size. The results obtained are used to correlate the fluid and particle characteristics on the effectiveness of mixing and morphology obtained.

Microstructure and mechanical properties of carbon nanotube reinforced cementitious composites developed using a novel dispersion technique

The authors also acknowledge Centre for Textile Science and Technology (University of Minho) and FIBRENAMICS PLATFORMfor providing required conditions for this research. Sincere thanks are also due to Mr. Pedro Samuel Leite and Mr. Carlos Jesus for their kind help in sample preparation and testing.

Recurrence relations for Clifford algebra-valued orthogonal polynomials

The theory of orthogonal polynomials of one real or complex variable is well established as well as its generalization for the multidimensional case. Hypercomplex function theory (or Clifford analysis) provides an alternative approach to deal with higher dimensions. In this context, we study systems of orthogonal polynomials of a hypercomplex variable with values in a Clifford algebra and prove some of their properties.

Processo de intervenção no espaço urbano de Braga: Espaço coletivo como novo estrato de relações

Dissertação de mestrado - Área de especialização Arquitetura Cidade e Território