Upgrade of an industrial building: BIM model of the as-built situation and evaluation of modifications

Dissertação de mestrado integrado in Civil Engineering

Fundamental studies on natural deep eutectic solvents: physico-chemical, thermal and rheological properties

When combined at particular molar fractions, sugars, aminoacids or organic acids a present a high melting point depression, becoming liquids at room temperature. These are called Natural Deep Eutectic Solvents – NADES and are envisaged to play a major role on the chemical engineering processes of the future. Nonetheless, there is a significant lack of knowledge of its fundamental and basic properties, which is hindering their industrial applications. For this reason it is important to extend the knowledge on these systems, boosting their application development [1]. In this work, we have developed and characterized NADES based on choline chloride, organic acids, amino acids and sugars. Their density, thermal behavior, conductivity and polarity were assessed for different compositions. The conductivity was measured from 0 to 40 °C and the temperature effect was well described by the Vogel-Fulcher-Tammann equation. The morphological characterization of the crystallizable materials was done by polarized optical microscopy that provided also evidence of homogeneity/phase separation. Additionally, the rheological and thermodynamic properties of the NADES and the effect of water content were also studied. The results show these systems have Newtonian behavior and present significant viscosity decrease with temperature and water content, due to increase on the molecular mobility. The anhydrous systems present viscosities that range from higher than 1000Pa.s at 20°C to less than 1Pa.s at 70°C. DSC characterization confirms that for water content as high as 1:1:1 molar ratio, the mixture retains its single phase behavior. The results obtained demonstrate that the NADES properties can be finely tunned by careful selection of its constituents. NADES present the necessary properties for use as extraction solvents. They can be prepared from inexpensive raw materials and tailored for the selective extraction of target molecules. The data produced in this work is hereafter importance for the selection of the most promising candidates avoiding a time consuming and expensive trial and error phase providing also data for the development of models able to predict their properties and the mechanisms that allow the formation of the deep eutectic mixtures.

Bioactive ceramics for tissue engineering and regenerative medicine derived from marine sponges

Publicado em "Journal of tissue engineering and regenerative medicine". Vol. 8, suppl. s1 (2014)

A proteção cumulativa do design pelo Direito de Autor e pelo Direito da Propriedade Industrial: o caso especial do contrato de trabalho

Dissertação de mestrado em Direito dos Contratos e das Empresas

Feasibility of internally stiffened thin-walled beams for industrial applications

Several types of internally reinforced thin-walled beams are subjected to a feasibility evaluation of its mechanical behavior for industrial applications. The adapting of already existing efficient sandwich geometries to hollow-box beams of larger dimensions may reveal promising results. Novel types of sandwich beams under bending and torsion uncoupled loadings are studied in terms of stiffness behavior in static analysis. For the analysis of the solutions, the models are built using the Finite Element Method (FEM) software ANSYS Mechanical APDL. The feasibility of the novel beams was determined by the comparison of the stiffness behavior of the novel hollow-box beams with conventional hollow-box beams. An efficiency parameter was defined in order to determine the feasibility. It is found that the novel geometries represent an excellent improvement under bending loadings, better than under torsion loadings. Nevertheless, for bending and torsion combined loadings, if bending loads are predominant, the beams can still be interesting for some applications, in particular those with mobile parts.

A UML-based approach for modeling industrial control applications

The main purpose of the poster is to present how the Unified Modeling Language (UML) can be used for diagnosing and optimizing real industrial production systems. By using a car radios production line as a case study, the poster shows the modeling process that can be followed during the analysis phase of complex control applications. In order to guarantee the continuity mapping of the models, the authors propose some guidelines to transform the use cases diagrams into a single object diagram, which is the main diagram for the next phases of the development.

Valorization of agro-industrial wastes towards the production of rhamnolipids

In this work, oil mill wastewater (OMW), a residue generated during olive oil extraction, was evaluated as an inducer of rhamnolipid production. Using a medium containing as sole ingredients corn steep liquor (10%, v/v), sugarcane molasses (10%, w/v) and OMW (25%, v/v), Pseudomonas aeruginosa #112 produced 4.5 and 5.1 g of rhamnolipid per liter in flasks and reactor, respectively, with critical micelle concentrations as low as 13 mg/l. Furthermore, in the medium supplemented with OMW, a higher proportion of more hydrophobic rhamnolipid congeners was observed comparing with the same medium without OMW. OMW is a hazardous waste which disposal represents a serious environmental problem; therefore, its valorization as a substrate for the production of added-value compounds such as rhamnolipids is of great interest. This is the first report of rhamnolipid production using a mixture of these three agro-industrial by-products, which can be useful for the sustainable production of rhamnolipids.

Real-Time decision support using data mining to predict blood pressure critical events in intensive medicine patients

Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%.