Using glass-fibre reinforced polymer composites in the production of sustainable water storage vessels

The present work focuses on the use of the life cycle assessment (LCA) and life cycle costing (LCC)methodologies to evaluate environmental and economic impacts of polymers and polymer composites materials and products. Initially a literature review is performed in order to assess the scope and limitations of existing LCA and LCC studies on these topics. Then, a case study, based on the production of a water storage glass-fibre reinforced polymer (GFRP) composite storage tank, is presented. The storage tank was evaluated via a LCA/LCC integrated model, a novel way of analysing the life cycle (LC) environmental and economic performances of structural products. The overarching conclusion of the review is that the environmental and economic performances of polymers composites in non-mobile applications are seldom assessed and never in a combined integrated way.

Modeling microbes: New methods for integrated metabolic and regulatory network reconstruction

PhD Thesis in Bioengineering

Impact performance prediction of injection-molded talc-filled polypropylene through thermomechanical environment assessment

Due to the fact that different injection molding conditions tailor the mechanical response of the thermoplastic material, such effect must be considered earlier in the product development process. The existing approaches implemented in different commercial software solutions are very limited in their capabilities to estimate the influence of processing conditions on the mechanical properties. Thus, the accuracy of predictive simulations could be improved. In this study, we demonstrate how to establish straightforward processing-impact property relationships of talc-filled injection-molded polypropylene disc-shaped parts by assessing the thermomechanical environment (TME). To investigate the relationship between impact properties and the key operative variables (flow rate, melt and mold temperature, and holding pressure), the design of experiments approach was applied to systematically vary the TME of molded samples. The TME is characterized on computer flow simulation outputsanddefined bytwo thermomechanical indices (TMI): the cooling index (CI; associated to the core features) and the thermo-stress index (TSI; related to the skin features). The TMI methodology coupled to an integrated simulation program has been developed as a tool to predict the impact response. The dynamic impact properties (peak force, peak energy, and puncture energy) were evaluated using instrumented falling weight impact tests and were all found to be similarly affected by the imposed TME. The most important molding parameters affecting the impact properties were found to be the processing temperatures (melt andmold). CI revealed greater importance for the impact response than TSI. The developed integrative tool provided truthful predictions for the envisaged impact properties.

Thermal characterization of polyhydroxyalkanoates and poly(lactic acid) blends obtained by injection molding

In this work we present the thermal characterization of the full scope of polyhydroxyalcanoate and poly(lactic acid) blends obtain by injection molding. Blends of polyhydroxyalcanoate and poly(lactic acid) (PHA/PLA) were prepared in different compositions ranging from 0–100% in steps of 10%. The blends were injection molded and then characterized by differential scanning calorimetry (DSC), scanning electron microscopy (SEM) and wide angle X-ray diffraction (WAXD). The increment of PHA fraction increased the degree of crystallinity of the blend and the miscibility of the base polymers as verified by the Fox model. The WAXD analysis indicates that the presence of PHA hindered the PLA crystallization. The crystallization evolution trough PHA weight fraction (wf) shows a phase inversion around 50-60%. SEM analyses confirmed that the miscibility of PHA/PLA blends increased with the incorporation of PHA and became total for values of PHA higher that 50%.

An assessment of chronic kidney diseases

Kidney renal failure means that one’s kidney have unexpectedlystoppedfunctioning,i.e.,oncechronicdiseaseis exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapiddeteriorationoftherenalfunction,butisoftenreversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis. The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow onetoconsiderincomplete,unknown,and evencontradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively.

Search for the bb¯ decay of the Standard Model Higgs boson in associated (W/Z)H production with the ATLAS detector

A search for the bb¯ decay of the Standard Model Higgs boson is performed with the ATLAS experiment using the full dataset recorded at the LHC in Run 1. The integrated luminosities used from pp collisions at s√=7 and 8 TeV are 4.7 and 20.3 fb−1, respectively. The processes considered are associated (W/Z)H production, where W→eν/μν, Z→ee/μμ and Z→νν. The observed (expected) deviation from the background-only hypothesis corresponds to a significance of 1.4 (2.6) standard deviations and the ratio of the measured signal yield to the Standard Model expectation is found to be μ=0.52±0.32(stat.)±0.24(syst.) for a Higgs boson mass of 125.36 GeV. The analysis procedure is validated by a measurement of the yield of (W/Z)Z production with Z→bb¯ in the same final states as for the Higgs boson search, from which the ratio of the observed signal yield to the Standard Model expectation is found to be 0.74±0.09(stat.)±0.14(syst.).

Simulation of OWES with five-Level converter linked to the grid: Harmonic assessment

This paper deals with a computing simulation for an offshore wind energy system taking into account the influence of the marine waves action throughout the floating platform. The wind energy system has a variable-speed turbine equipped with a permanent magnet synchronous generator and a full-power five level converter, injecting energy into the electric grid through a high voltage alternate current link. A reduction on the unbalance of the voltage in the DC-link capacitors of the five-level converter is proposed by a strategic selection of the output voltage vectors. The model for the drive train of the wind energy system is a two mass model, including the dynamics of the floating platform. A case study is presented and the assessment of the quality of the energy injected into the electric grid is discussed.

Numerical modeling and assessment of the thermal environment in an industrial premise of automotive components

Dissertação de mestrado em Engenharia Industrial

An innovative framework for probabilistic-based structural assessment with an application to existing reinforced concrete structures

A novel framework for probabilistic-based structural assessment of existing structures, which combines model identification and reliability assessment procedures, considering in an objective way different sources of uncertainty, is presented in this paper. A short description of structural assessment applications, provided in literature, is initially given. Then, the developed model identification procedure, supported in a robust optimization algorithm, is presented. Special attention is given to both experimental and numerical errors, to be considered in this algorithm convergence criterion. An updated numerical model is obtained from this process. The reliability assessment procedure, which considers a probabilistic model for the structure in analysis, is then introduced, incorporating the results of the model identification procedure. The developed model is then updated, as new data is acquired, through a Bayesian inference algorithm, explicitly addressing statistical uncertainty. Finally, the developed framework is validated with a set of reinforced concrete beams, which were loaded up to failure in laboratory.

Development of a model for occupational risk acceptance criteria definition in industrial settings

Doctoral Dissertation for PhD degree in Industrial and Systems Engineering

O currículo da formação em engenharia no âmbito do processo de bolonha: desenvolvimento de competências e perfil profissional na perspetiva dos docentes, dos estudantes e dos profissionais

Tese de Doutoramento em Ciências da Educação (área de especilização em Desenvolvimento Curricular).

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

Dissertação de mestrado integrado in Civil Engineering

In vitro digestion and stability assessment of b-lactoglobulin/riboflavin nanostructures

B-Lactoglobulin (b-Lg) is the major protein fraction of bovine whey serum and a primary gelling agent. b-Lg has a high nutritional value, is stable at low pH being highly resistant to proteolytic degradation in the stomach, besides, it has the ability of acting as an encapsulating agent. This study aims at assessing the ability of b-Lg nanostructures to associate a nutraceutical - i.e. riboflavin - and release it in a controlled manner throughout an in vitro gastrointestinal (GI) system. For this reason b-Lg nanostructures loaded with riboflavin were critically characterized in terms of their morphology (i.e. size, polydispersity, -potential and shape) by dynamic light scattering (DLS) and transmission electron microscopy (TEM), and efficiency to associate to riboflavin through spectrofluorimetry. Furthermore, these nanocomplexes were evaluated in an in vitro GI model, simulating the physiological conditions. Stable b-Lg nanostructures were obtained at pH 6, of spherical shape, characterized by particle size of 172±1 nm, low polydispersity (i.e. PDI of 0.06±0.02), -potential of -32±3 mV and association efficiency (AE) of 26±1 %. b-Lg nanostructures showed to be stable upon their passage throughout stomach (i.e. particle size, PDI and potential of 248±10 nm, 0.18±0.03 and 18±3 mV, respectively). Concerning their passage throughout the intestine, such nanostructures were mostly degraded in the duodenum. Regarding riboflavin, a release of about 11 % was observed after their passage through stomach, while 35 %, 38 % and 5 % were the released percentages of the total riboflavin associated observed after passage through duodenum, jejunum and ileum, respectively. Hence,b-Lg nanostructures showed to be suitable carriers for riboflavin until the intestine, where their degradation occurs. b-Lg also showed to be structurally stable, under food simulant conditions (yoghurt simulant, composed of 3 % acetic acid), over 14 days, with a protective effect upon riboflavin activity, releasing it in a 7 day period.

Zebrafish embryos as in vivo model for toxicity evaluation: screening of nanoparticle formulations DODAB:MO and DODAC:MO

Dissertação de mestrado em Molecular Genetics