Reactores a tório: o futuro da energia nuclear de fissão

Dissertação para a obtenção do grau de mestre em Engenharia Electrotécnica Ramo de Energia

Durability performance of self-compacting concrete (SCC) with binary and ternary mixes of fly ash and limestone filler

The basic objective of this work is to evaluate the durability of self-compacting concrete (SCC) produced in binary and ternary mixes using fly ash (FA) and limestone filler (LF) as partial replacement of cement. The main characteristics that set SCC apart from conventional concrete (fundamentally its fresh state behaviour) essentially depend on the greater or lesser content of various constituents, namely: greater mortar volume (more ultrafine material in the form of cement and mineral additions); proper control of the maximum size of the coarse aggregate; use of admixtures such as superplasticizers. Significant amounts of mineral additions are thus incorporated to partially replace cement, in order to improve the workability of the concrete. These mineral additions necessarily affect the concrete’s microstructure and its durability. Therefore, notwithstanding the many well-documented and acknowledged advantages of SCC, a better understanding its behaviour is still required, in particular when its composition includes significant amounts of mineral additions. An ambitious working plan was devised: first, the SCC’s microstructure was studied and characterized and afterwards the main transport and degradation mechanisms of the SCC produced were studied and characterized by means of SEM image analysis, chloride migration, electrical resistivity, and carbonation tests. It was then possible to draw conclusions about the SCC’s durability. The properties studied are strongly affected by the type and content of the additions. Also, the use of ternary mixes proved to be extremely favourable, confirming the expected beneficial effect of the synergy between LF and FA. © 2015 RILEM.

Fonte comutada de baixa tensão para utilização em supercondensadores como fonte primária de energia

Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo Energia

Exploiting the bin-class histograms for feature selection on discrete data

In machine learning and pattern recognition tasks, the use of feature discretization techniques may have several advantages. The discretized features may hold enough information for the learning task at hand, while ignoring minor fluctuations that are irrelevant or harmful for that task. The discretized features have more compact representations that may yield both better accuracy and lower training time, as compared to the use of the original features. However, in many cases, mainly with medium and high-dimensional data, the large number of features usually implies that there is some redundancy among them. Thus, we may further apply feature selection (FS) techniques on the discrete data, keeping the most relevant features, while discarding the irrelevant and redundant ones. In this paper, we propose relevance and redundancy criteria for supervised feature selection techniques on discrete data. These criteria are applied to the bin-class histograms of the discrete features. The experimental results, on public benchmark data, show that the proposed criteria can achieve better accuracy than widely used relevance and redundancy criteria, such as mutual information and the Fisher ratio.

Projeto de fundações e estrutura de um hotel em Lisboa

Trabalho de Projeto para obtenção do grau de mestre em Engenharia Civil na Área de Especialização em Estruturas

FPGA-based architecture for hyperspectral unmixing

This paper proposes an FPGA-based architecture for onboard hyperspectral unmixing. This method based on the Vertex Component Analysis (VCA) has several advantages, namely it is unsupervised, fully automatic, and it works without dimensionality reduction (DR) pre-processing step. The architecture has been designed for a low cost Xilinx Zynq board with a Zynq-7020 SoC FPGA based on the Artix-7 FPGA programmable logic and tested using real hyperspectral datasets. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low cost embedded systems.

Competitiveness of chitosan-based implants

Biomaterials have been extensively developed and applied in medical devices. Among these materials, bioabsorbable polymers have attracted special attention for orthopedic applications where a transient existence of an implant can provide better results, when compared with permanent implants. Chitosan, a natural biopolymer, has generated enormous interest due to its various advantages such as biocompatibility, biodegradability and osteoconductive properties. In this paper, an assessment of the potential of a developed innovative production process of 3D solid and dense chitosan-based products for biomedical applications is performed and presented. Therefore, it starts with a brief explanation of the technology, highlighting its main features. Then, several potential applications and their markets were identified and assessed. After choosing a primary application and market, its potential as well as its uncertainties and risks were identified. A business model suggesting how to materialize the value from the application was sketched. After that, a brief description of the market as well as the identification of the main competitors and their distinctive features was made. The supply chain analysis and the go-to-market strategy were the following steps. In the end, a final recommendation based on the assessment of the information was prepared.

Utilização de coberturas ajardinadas de vegetação intensiva, extensiva e horta urbana em edificações

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil