Thermal conditions affecting heat transfer in FDM/FFE: a contribution towards the numerical modelling of the process

The performance of parts produced by Free Form Extrusion (FFE), an increasingly popular additive manufacturing technique, depends mainly on their dimensional accuracy, surface quality and mechanical performance. These attributes are strongly influenced by the evolution of the filament temperature and deformation during deposition and solidification. Consequently, the availability of adequate process modelling software would offer a powerful tool to support efficient process set-up and optimisation. This work examines the contribution to the overall heat transfer of various thermal phenomena developing during the manufacturing sequence, including convection and radiation with the environment, conduction with support and between adjacent filaments, radiation between adjacent filaments and convection with entrapped air. The magnitude of the mechanical deformation is also studied. Once this exercise is completed, it is possible to select the material properties, process variables and thermal phenomena that should be taken in for effective numerical modelling of FFE.

Pervasive business intelligence platform to improve the quality of decision process in primary and secondary education – A Portuguese case study

Business Intelligence (BI) can be seen as a method that gathers information and data from information systems in order to help companies to be more accurate in their decision-making process. Traditionally BI systems were associated with the use of Data Warehouses (DW). The prime purpose of DW is to serve as a repository that stores all the relevant information required for making the correct decision. The necessity to integrate streaming data became crucial with the need to improve the efficiency and effectiveness of the decision process. In primary and secondary education, there is a lack of BI solutions. Due to the schools reality the main purpose of this study is to provide a Pervasive BI solution able to monitoring the schools and student data anywhere and anytime in real-time as well as disseminating the information through ubiquitous devices. The first task consisted in gathering data regarding the different choices made by the student since his enrolment in a certain school year until the end of it. Thereafter a dimensional model was developed in order to be possible building a BI platform. This paper presents the dimensional model, a set of pre-defined indicators, the Pervasive Business Intelligence characteristics and the prototype designed. The main contribution of this study was to offer to the schools a tool that could help them to make accurate decisions in real-time. Data dissemination was achieved through a localized application that can be accessed anywhere and anytime.

Step towards multiplatform framework for supporting pediatric and neonatology care unit decision process

Children are an especially vulnerable population, particularly in respect to drug administration. It is estimated that neonatal and pediatric patients are at least three times more vulnerable to damage due to adverse events and medication errors than adults are. With the development of this framework, it is intended the provision of a Clinical Decision Support System based on a prototype already tested in a real environment. The framework will include features such as preparation of Total Parenteral Nutrition prescriptions, table pediatric and neonatal emergency drugs, medical scales of morbidity and mortality, anthropometry percentiles (weight, length/height, head circumference and BMI), utilities for supporting medical decision on the treatment of neonatal jaundice and anemia and support for technical procedures and other calculators and widespread use tools. The solution in development means an extension of INTCare project. The main goal is to provide an approach to get the functionality at all times of clinical practice and outside the hospital environment for dissemination, education and simulation of hypothetical situations. The aim is also to develop an area for the study and analysis of information and extraction of knowledge from the data collected by the use of the system. This paper presents the architecture, their requirements and functionalities and a SWOT analysis of the solution proposed.

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.

Improvign mixing processes with the help of numerical tools

In several industrial applications, highly complex behaviour materials are used together with intricate mixing processes, which difficult the achievement of the desired properties for the produced materials. This is the case of the well-known dispersion of nano-sized fillers in a melt polymer matrix, used to improve the nanocomposite mechanical and/or electrical properties. This mixing is usually performed in twin-screw extruders, that promote complex flow patterns, and, since an in loco analysis of the material evolution and mixing is difficult to perform, numerical tools can be very useful to predict the evolution and behaviour of the material. This work presents a numerical based study to improve the understanding of mixing processes. Initial numerical studies were performed with generalized Newtonian fluids, but, due to the null relaxation time that characterize this type of fluids, the assumption of viscoelastic behavior was required. Therefore, the polymer melt was rheologically characterized, and, a six mode Phan-Thien-Tanner and Giesekus models were used to fit the rheological data. These viscoelastic rheological models were used to model the process. The conclusions obtained in this work provide additional and useful data to correlate the type and intensity of the deformation history promoted to the polymer nanocomposite and the quality of the mixing obtained.

Mudança narrativa: emergência e evolução de protonarrativas em terapia cognitivo - comportamental

Dissertação de mestrado integrado em Psicologia

Inkjet printing technology for flexible pressure sensors

Tese de Doutoramento Ciência e Engenharia de Polímeros e Compósitos.

Spatio-temporal modelling of environmental data

Programa Doutoral em Matemática e Aplicações.

A demonstration case on the derivation of process-level logical architectures for ambient assisted living ecosystems

When representing the requirements for an intended software solution during the development process, a logical architecture is a model that provides an organized vision of how functionalities behave regardless of the technologies to be implemented. If the logical architecture represents an ambient assisted living (AAL) ecosystem, such representation is a complex task due to the existence of interrelated multidomains, which, most of the time, results in incomplete and incoherent user requirements. In this chap- ter, we present the results obtained when applying process-level modeling techniques to the derivation of the logical architecture for a real industrial AAL project. We adopt a V-Model–based approach that expresses the AAL requirements in a process-level perspec- tive, instead of the traditional product-level view. Additionally, we ensure compliance of the derived logical architecture with the National Institute of Standards and Technology (NIST) reference architecture as nonfunctional requirements to support the implementa- tion of the AAL architecture in cloud contexts.

Cooking process evaluation on mercury content in fish

This study evaluated different cooking processes (roasted, cooked and fried) on total mercury (Hg) content in fish species most consumed by Manaus residents and surrounding communities, Amazon region. The results obtained for total Hg in natura and after the three types of preparation (roasted, cooked and fried) for 12 fish species showed a significant Hg concentration variation. In the present study the cooked and frying processes resulted in higher Hg losses for Pacu, Pescada, Jaraqui, Curimatã, Surubin and Aruanã fish species, most of them presenting detritivorous and carnivorous feeding habits. The higher Hg losses in the roasting process occurred for Sardinha, Aracu, Tucunaré, Pirapitinga, Branquinha and Tambaqui fish species, most of them being omnivorous and herbivorous fish species. Some micronutrients (Ca, Fe, K, Na, Se and Zn) in fish species in natura were also determined in order to perform a nutritional evaluation regarding these micronutrients.

Description of behavioral patterns of Podocnemis erythrocephala (Spix, 1824) (Testudines: Podocnemididae) (Red-headed river turtle) in captivity, Manaus, Amazonas, Brazil

The biology and ecology of South American turtles is still poorly known, particularly, for the Brazilian species. Laboratory studies are essential to understand the life cycles of aquatic turtles species and to help in formulating management plans for their conservation. As a contribution to the knowledge of Podocnemis erythrocephala species, we give a description of its species-typical behaviors, categorized as: maintenance, locomotion, feeding, agonistic and reproduction, based on captives observations of four pairs of turtles in an aquarium in Manaus, Brazil. Similarities and differences with the repertoires of other turtle species are discussed, concluding that turtles have much more complex adaptative strategies and social life than was believed.

Sustentabilidade no Design: uma abordagem aos resíduos limpos das indústrias do calçado

Dissertação de mestrado em Design e Marketing

Structural and successional variability of periphytic algal community in a Amazonian lake during the dry and rainy season (Rio Branco, Acre)

The colonization process and successional patterns of a periphytic algal community were evaluated in a Amazonian Viveiro Lake (Rio Branco, Acre, Brazil). Sampling was performed over a period of 35 days; at four-day intervals for 20 days, and then at five-day intervals. Water sampling for physical, chemical and biological analyses was done during the dry and rainy season. Glass slides were used as artificial substrates for periphyton colonization. The structural community was evaluated through population density, algae class, diversity indices and descriptive species. Species richness, diversity and evenness increased as succession progressed. While density of Bacillariophyceae, Euglenophyceae and Zygnemaphyceae increased with succession, Cyanobacteria remained dominant. Synechocystis aquatilis, Synechocystis diplococcus and Navicula pseudolanceolata were the main descriptive species in both the dry and rainy season. Cymbela tumida, Frustulia rhomboides, Trachelomonas lacustris and Closterium acicularis was correlated with an increase in hydrologic level during the rainy season. Conversely, the density of Chlamydomonas sp., Chroomonas nordstedtii, Trachelomonas volvocinopsis, Trachelomonas volvocina and Synechococcus linearis was correlated with an increase in water transparency during the dry season. In general, the periphytic algal community showed high diversity and species richness independent of season. Season also had little influence on representation of algae class and main descriptive species. However, successional patterns varied by season, and changes in hydrologic levels acted directly on the succession path of periphytic algae. More research on periphyton dynamics is needed to improve our understanding of tropical lake ecosystems, especially in Amazonian.

Effector memory CD4+ T cells are associated with cognitive performance in a senior population

Objective: Immunosenescence and cognitive decline are common markers of the aging process. Taking into consideration the heterogeneity observed in aging processes and the recently described link between lymphocytes and cognition, we herein explored the possibility of an association between alterations in lymphocytic populations and cognitive performance. Methods: In a cohort of cognitively healthy adults (n = 114), previously characterized by diverse neurocognitive/psychological performance patterns, detailed peripheral blood immunophenotyping of both the innate and adaptive immune systems was performed by flow cytometry. Results: Better cognitive performance was associated with lower numbers of effector memory CD4(+) T cells and higher numbers of naive CD8(+) T cells and B cells. Furthermore, effector memory CD4(+) T cells were found to be predictors of general and executive function and memory, even when factors known to influence cognitive performance in older individuals (e.g., age, sex, education, and mood) were taken into account. Conclusions: This is the first study in humans associating specific phenotypes of the immune system with distinct cognitive performance in healthy aging.