<p>The overall purpose of this thesis work has been to further our understanding of the growth and removal of inclusions in gas- and induction-stirred ladles. The primary focus has been on alumina inclusions. </p><p>Growth mechanisms were studied using data from fundamental mathematical models of gas- and induction-stirred ladles. The results showed the turbulence mechanism to be the most dominant in alumina inclusion growth. The dynamic growth and removal of inclusions in a gas-stirred ladle was studied using mathematical modelling. The model results showed concentration gradients of inclusions. The effect was most obvious in the steel flow past the removal sites: top slag, ladle refractory, and gas plume (bubble flotation). A new removal model was developed for large spherical caps bubbles. </p><p>In order to verify the predicted concentration gradients for the size population of inclusions, three experiments were carried out in production. The sampling equipment enabled sampling at five different positions and different locations at the same time. The results showed that concentration gradients of inclusions do exist both in induction-stirred and gas-stirred ladles. A theoretical analysis showed that the drag force on the inclusions to be the dominating force and that therefore inclusions follow the fluid flow. </p><p>The cluster behaviour of alumina inclusions were examined on steel samples taken in an industrial-scale deoxidation experiment in a ladle. The samples were examined by microscope and the results used to study cluster growth. It was found that there was rapid cluster growth due to collision during stirring and that at the end of the deoxidation experiment a majority of the small inclusions were bound in clusters. The cluster growth data determined using the microscopic results were compared with predicted cluster-growth data. A method was developed for converting the experimental data observed per unit area into data given per unit volume and vice versa. An expression for the collision diameter of the cluster was also developed. The results showed that the predicted cluster growth agreed well with the microscopic observations for the assumptions made in the growth model.</p>

The overall purpose of this thesis work has been to further our understanding of the growth and removal of inclusions in gas- and induction-stirred ladles. The primary focus has been on alumina inclusions. Growth mechanisms were studied using data from fundamental mathematical models of gas- and induction-stirred ladles. The results showed the turbulence mechanism to be the most dominant in alumina inclusion growth. The dynamic growth and removal of inclusions in a gas-stirred ladle was studied using mathematical modelling. The model results showed concentration gradients of inclusions. The effect was most obvious in the steel flow past the removal sites: top slag, ladle refractory, and gas plume (bubble flotation). A new removal model was developed for large spherical caps bubbles. In order to verify the predicted concentration gradients for the size population of inclusions, three experiments were carried out in production. The sampling equipment enabled sampling at five different positions and different locations at the same time. The results showed that concentration gradients of inclusions do exist both in induction-stirred and gas-stirred ladles. A theoretical analysis showed that the drag force on the inclusions to be the dominating force and that therefore inclusions follow the fluid flow. The cluster behaviour of alumina inclusions were examined on steel samples taken in an industrial-scale deoxidation experiment in a ladle. The samples were examined by microscope and the results used to study cluster growth. It was found that there was rapid cluster growth due to collision during stirring and that at the end of the deoxidation experiment a majority of the small inclusions were bound in clusters. The cluster growth data determined using the microscopic results were compared with predicted cluster-growth data. A method was developed for converting the experimental data observed per unit area into data given per unit volume and vice versa. An expression for the collision diameter of the cluster was also developed. The results showed that the predicted cluster growth agreed well with the microscopic observations for the assumptions made in the growth model.

PAULA, Demétrius Ribeiro de. Dinâmica de redes neurais e formação de agregados em redes complexas. 2006. 90 f. Dissertação (Mestrado em Física) - Programa de Pós-Graduação em Física, Departamento de Física, Centro de Ciências, Universidade Federal do Ceará, Fortaleza, 2006. / Submitted by Edvander Pires (edvanderpires@gmail.com) on 2014-11-03T18:54:59Z No. of bitstreams: 1 2006_dis_drpaula.pdf: 978829 bytes, checksum: 6f46a6d334b9c066ec1350d74f8beb77 (MD5) / Approved for entry into archive by Edvander Pires(edvanderpires@gmail.com) on 2014-11-03T19:00:07Z (GMT) No. of bitstreams: 1 2006_dis_drpaula.pdf: 978829 bytes, checksum: 6f46a6d334b9c066ec1350d74f8beb77 (MD5) / Made available in DSpace on 2014-11-03T19:00:08Z (GMT). No. of bitstreams: 1 2006_dis_drpaula.pdf: 978829 bytes, checksum: 6f46a6d334b9c066ec1350d74f8beb77 (MD5) Previous issue date: 2006 / The process by which news trends and ideas propagate in social communities can have a profound impact in the life of individuals. To understand thi process, we introduce a competitive cluster growth model in complex networks. In our model, each cluster represents the set of individuals with a certain opinion or preference. We investigate how the cluster size distribution depends on the topology of the network and how it is affected by the number of initial seeds dispersed in the structure. We study our model using different network models, namely, the Erdos-Renyi geometry, the preferential attachment model, and the so-called Apollonian network. This last complex geometry displays a cluster size distribution that follows a power-law with an exponent 1.0. Similar results have been obtained for the distributions of number of votes per candidate in the proportional elections for federal representation in Brazil. In the second part of this work, we investigate the temporal behavior of neural networks with small world topology and in networks built according to the preferential attachment model. In the first case we study the effect of the range of connections on the behavior of the time series. In both topologies, we detect the existence of cycles and investigate how their periods depend on the size of the system. / Este dissertação foi dividida em duas partes, na primeira parte nós propomos um modelo de crescimento competitivo de gregados em redes complexas para simular a propagação de idéias ou opiniões em comunidades. Investigamos como as distribuições de tamanhos de agregados variam com a topologia de construção da rede e com o número de sementes aleatoriamente dispersas na estrutura. Para tal, analisamos redes do tipo de Erdos-Rényi, redes de contato preferencial e a chamada rede Apoloniana. Esta última apresenta distribuições de tamanho de agregado em forma de uma lei de potência com um expoente aproximadamente 1. Resultados similares são observados com as distribuições obtidas para as frações de votos por candidato às eleições proporcionais para deputados no Brasil. Na segunda parte, analisamos o comportamento temporal da atividade neural em redes com características de mundo pequeno e em redes construídas segundo o modelo do contato preferencial. Nesta primeira topologia, estudamos como a série temporal se comporta com a variação do alcance das conexões. Em ambas as topologias, observamos a formação de períodos e investigamos como estes variam com o tamanho da rede.

Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgico / Este dissertaÃÃo foi dividida em duas partes, na primeira parte nÃs propomos um modelo de crescimento competitivo de gregados em redes complexas para simular a propagaÃÃo de idÃias ou opiniÃes em comunidades. Investigamos como as distribuiÃÃes de tamanhos de agregados variam com a topologia de construÃÃo da rede e com o nÃmero de sementes aleatoriamente dispersas na estrutura. Para tal, analisamos redes do tipo de Erdos-RÃnyi, redes de contato preferencial e a chamada rede Apoloniana. Esta Ãltima apresenta distribuiÃÃes de tamanho de agregado em forma de uma lei de potÃncia com um expoente aproximadamente 1. Resultados similares sÃo observados com as distribuiÃÃes obtidas para as fraÃÃes de votos por candidato Ãs eleiÃÃes proporcionais para deputados no Brasil. Na segunda parte, analisamos o comportamento temporal da atividade neural em redes com caracterÃsticas de mundo pequeno e em redes construÃdas segundo o modelo do contato preferencial. Nesta primeira topologia, estudamos como a sÃrie temporal se comporta com a variaÃÃo do alcance das conexÃes. Em ambas as topologias, observamos a formaÃÃo de perÃodos e investigamos como estes variam com o tamanho da rede. / The process by which news trends and ideas propagate in social communities can have a profound impact in the life of individuals. To understand thi process, we introduce a competitive cluster growth model in complex networks. In our model, each cluster represents the set of individuals with a certain opinion or preference. We investigate how the cluster size distribution depends on the topology of the network and how it is affected by the number of initial seeds dispersed in the structure. We study our model using different network models, namely, the Erdos-Renyi geometry, the preferential attachment model, and the so-called Apollonian network. This last complex geometry displays a cluster size distribution that follows a power-law with an exponent 1.0. Similar results have been obtained for the distributions of number of votes per candidate in the proportional elections for federal representation in Brazil. In the second part of this work, we investigate the temporal behavior of neural networks with small world topology and in networks built according to the preferential attachment model. In the first case we study the effect of the range of connections on the behavior of the time series. In both topologies, we detect the existence of cycles and investigate how their periods depend on the size of the system.

Ionic liquids (ILs) have made a great impact on materials science and are being explored for potential applications in several disciplines. In this article, we briefly highlight the current state-of-the-art techniques employing ILs as new crystallisation media, working as neutral solvent, template or charge compensating species. The use of an IL as environmental friendly solvent offers many advantages over traditional crystallisation methods. The change from molecular to ionic reaction media leads to new types of materials being accessible. Room temperature ILs have been found to be excellent solvent systems for the crystallisation of a wide range of substances and morphologies ranging from nanoscopic crystals to micro- and even to macroscopic crystals. Moreover, high temperature routes, such as crystallisation from melts or gas phase deposition, have been replaced by convenient room or low temperature syntheses, employing ILs as reaction media. / Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.

[...] Mes travaux portent sur les clusters structurant le réseau et l'innovation car 1) le cluster impacte collectivement plutôt qu’individuellement la sortie du réseau, 2) les couplages intra et inter-cluster représentent la structure même des clusters mais ils influencent différemment l'innovation ou la croissance du cluster, 3) un certain compromis reste à définir entre la structure dense et éparse des différents réseaux. Un cluster est de façon générale défini comme un groupe de choses similaires ou de personnes qui travaillent sur des sujets analogues. Selon le domaine auquel il s’applique, même si l’idée reste la même, la définition s’affine. En sciences des organisations, un cluster représente un regroupement d’entreprises et d’institutions qui interagissent entre-elles par le biais de contrats, d’opérations formelles ou informelles et de réunions occasionnelles afin de contribuer collectivement à un résultat innovant. [...] La thèse est structurée comme suit. Dans l'introduction générale, nous passons en revue la littérature des connaissances existantes qui sert de base pour le cadre conceptuel des documents. Nous définissons ensuite certains concepts utilisés dans les trois articles présentés tels que la structure de réseau complexe (utilisée dans le premier article), l'innovation et les liens de réseau (utilisés principalement dans le deuxième article), et la gestion des connaissances utilisées (dans le troisième article). Dans le premier article, nous discutons les différents mécanismes de formation de liens dictés par les réseaux dirigés permettant de distinguer la distribution des degrés. Dans le deuxième article, nous abordons l'impact de la dynamique de groupe sur l'innovation du groupe de projet OSS. Dans le troisième article, nous nous attachons à l'impact du transfert des connaissances à l'intérieur des groupes sur le transfert des connaissances entre les groupes. L'annexe A permettra de discuter la modélisation analytique de la croissance des réseaux sociaux en utilisant la projection de réseaux multicouches ; l'annexe B sera l’occasion de présenter statistiquement le lien entre les relations intragroupe et les relations intergroupe. / [...] However, there is a gap in the literature with regard to the analysis of cluster or group structure as an input and cluster or group innovation as an output, e.g. “impact of network cluster structure on cluster innovation and growth”, i.e. how intra- and inter-cluster coupling, structural holes and tie strength impact cluster innovation and growth; and how intra-cluster density affects inter-cluster coupling; that I address in my thesis.Therefore, I focus on the cluster (or group of individuals) rather than the individual to analyze both network structure and innovation, because 1) clusters represent collective impact on network output rather than individuals’ impact, 2) intra and inter cluster couplings both represent cluster structure but have different impacts on cluster innovation and growth, 3) trade-offs among dense and sparse network cluster structures are different from those associated with networks of individuals. [...] The thesis is structured as follows. In the general introduction, I review the literature of existing knowledge in the field, which serves as a basis for the conceptual framework for the papers. I then define certain concepts used in the papers, such as complex network structure used in the first paper, innovation and network ties mainly used in the second paper, and knowledge management used in the third paper. In the first paper I discuss directed networks’ different link formation mechanisms causing degree distribution distinction. In the second paper, I discuss the impact of group dynamics on OSS project group innovation. In the third paper, I discuss impact of knowledge transfer inside groups onto knowledge transfer between groups. In appendix A, I discuss analytical modeling of social network growth using multilayer network projection; and in appendix B, I discuss statistically how intragroup ties and intergroup ties are related.