PLSR Models for Mechanical Strengths of Concrete Composite Materials Reinforced with Pultrusion Wastes

In this paper, we present two Partial Least Squares Regression (PLSR) models for compressive and flexural strength responses of a concrete composite material reinforced with pultrusion wastes. The main objective is to characterize this cost-effective waste management solution for glass fiber reinforced polymer (GFRP) pultrusion wastes and end-of-life products that will lead, thereby, to a more sustainable composite materials industry. The experiments took into account formulations with the incorporation of three different weight contents of GFRP waste materials into polyester based mortars, as sand aggregate and filler replacements, two waste particle size grades and the incorporation of silane adhesion promoter into the polyester resin matrix in order to improve binder aggregates interfaces. The regression models were achieved for these data and two latent variables were identified as suitable, with a 95% confidence level. This technological option, for improving the quality of GFRP filled polymer mortars, is viable thus opening a door to selective recycling of GFRP waste and its use in the production of concrete-polymer based products. However, further and complementary studies will be necessary to confirm the technical and economic viability of the process.

Effect of temperature on the shear strength of aluminium single lap bonded joints for high temperature applications

An experimental and numerical investigation into the shear strength behaviour of adhesive single lap joints (SLJs) was carried out in order to understand the effect of temperature on the joint strength. The adherend material used for the experimental tests was an aluminium alloy in the form of thin sheets, and the adhesive used was a high-strength high temperature epoxy. Tensile tests as a function of temperature were performed and numerical predictions based on the use of a bilinear cohesive damage model were obtained. It is shown that at temperatures below Tg, the lap shear strength of SLJs increased, while at temperatures above Tg, a drastic drop in the lap shear strength was observed. Comparison between the experimental and numerical maximum loads representing the strength of the joints shows a reasonably good agreement.

A cellulosic liquid crystal pool for cellulose nanocrystals: structure and molecular dynamics at high shear rates

Cellulose and its derivatives, such as hydroxypropylcellulose (HPC) have been studied for a long time but they are still not well understood particularly in liquid crystalline solutions. These systems can be at the origin of networks with properties similar to liquid crystalline (LC) elastomers. The films produced from LC solutions can be manipulated by the action of moisture allowing for instance the development of a soft motor (Geng et al., 2013) driven by humidity. Cellulose nanocrystals (CNC), which combine cellulose properties with the specific characteristics of nanoscale materials, have been mainly studied for their potential as a reinforcing agent. Suspensions of CNC can also self-order originating a liquid-crystalline chiral nematic phases. Considering the liquid crystalline features that both LC-HPC and CNC can acquire, we prepared LC-HPC/CNC solutions with different CNC contents (1,2 and 5 wt.%). The effect of the CNC into the LC-HPC matrix was determined by coupling rheology and NMR spectroscopy - Rheo-NMR a technique tailored to analyse orientational order in sheared systems. (C) 2015 Elsevier Ltd. All rights reserved.

Rheo-NMR study of water-based cellulose liquid crystal system at high shear rates

Since long ago cellulosic lyotropic liquid crystals were thought as potential materials to produce fibers competitive with spidersilk or Kevlar, yet the processing of high modulus materials from cellulose-based precursors was hampered by their complex rheological behavior. In this work, by using the Rheo-NMR technique, which combines deuterium NMR with rheology, we investigate the high shear rate regimes that may be of interest to the industrial processing of these materials. Whereas the low shear rate regimes were already investigated by this technique in different works [1-4], the high shear rates range is still lacking a detailed study. This work focuses on the orientational order in the system both under shear and subsequent relaxation process arising after shear cessation through the analysis of deuterium spectra from the deuterated solvent water. At the analyzed shear rates the cholesteric order is suppressed and a flow-aligned nematic is observed which for the higher shear rates develops after certain time periodic perturbations that transiently annihilate the order in the system. During relaxation the flow aligned nematic starts losing order due to the onset of the cholesteric helices leading to a period of very low order where cholesteric helices with different orientations are forming from the aligned nematic, followed in the final stage by an increase in order at long relaxation times corresponding to the development of aligned cholesteric domains. This study sheds light on the complex rheological behavior of chiral nematic cellulose-based systems and opens ways to improve its processing. (C) 2015 Elsevier Ltd. All rights reserved.

Rheo-optical characterization of liquid crystalline acetoxypropylcellulose melt undergoing large shear flow and relaxation after flow cessation

The rheological and structural characteristics of acetoxypropylcellulose (APC) nematic melt are studied at shear rates ranging from 10 s(-1) to 1000 s(-1) which are relevant to extrusion based processes. APC shows a monotonic shear thinning behavior over the range of shear rates tested. The negative extrudate-swell shows a minimum when a critical shear rate (gamma) over dot(c) is reached. For shear rates smaller than (gamma) over dot(c), the flow-induced texture consists of two set of bands aligned parallel and normal to the flow direction. At shear rates larger than (gamma) over dot(c), the flow induced texture is reminiscent of a 2 fluids structure. Close to the shearing walls, domains elongated along the flow direction and stacked along the vorticity are imaged with POM, whereas SALS patterns indicate that the bulk of the sheared APC is made of elliptical domains oriented along the vorticity. No full nematic alignment is achieved at the largest shear rate tested. Below (gamma) over dot(c), the stress relaxation is described by a stretched exponential. Above (gamma) over dot(c), the stress relaxation is described by a fast and a slow process. The latter coincides with the growth of normal bands thicknesses, as the APC texture after flow cessation consists of two types of bands with parallel and normal orientations relative to the flow direction. Both bands thicknesses do not depend on the applied shear rate, in contrast to their orientation. (C) 2015 Elsevier Ltd. All rights reserved.

A Fractional Perspective to the Bond Graph Modelling of World Economies

Inspired in dynamic systems theory and Brewer’s contributions to apply it to economics, this paper establishes a bond graph model. Two main variables, a set of inter-connectivities based on nodes and links (bonds) and a fractional order dynamical perspective, prove to be a good macro-economic representation of countries’ potential performance in nowadays globalization. The estimations based on time series for 50 countries throughout the last 50 decades confirm the accuracy of the model and the importance of scale for economic performance.

Estudo comparativo da resistência à tração de juntas adesivas de sobreposição simples e dupla

O método de união com ligações adesivas está cada vez mais a ser utilizado na conceção de estruturas mecânicas, por causa das vantagens significativas desta técnica em comparação com as ligações tradicionais. De facto, as juntas com ligação adesiva estão sob investigação intensa há bastante tempo. Entre as vantagens, destaca-se a redução de peso e possibilidade de unir diferentes materiais, incluindo compósitos, sem danificar as estruturas a ligar. Os adesivos comerciais variam desde resistentes e frágeis (por exemplo, Araldite® AV138) a menos resistentes e dúcteis (por exemplo, Araldite® 2015). Uma nova família de adesivos de poliuretano combina elevada resistência e ductilidade (por exemplo, Sikaforce® 7888). Este trabalho compara o desempenho à tração dos três adesivos supracitados, em juntas de alumínio (Al6082-T651) de sobreposição simples e dupla, com variação dos valores de comprimento de sobreposição (LO). A análise numérica de modelos de dano coesivo (MDC) foi realizada para analisar as tensões de arrancamento (oy) e as de corte (txy) na camada adesiva, para estudar a variável de dano do MDC durante o processo de rotura e para avaliar a capacidade MDC na previsão da resistência da junta. A análise da resistência e da variável de dano ajudou na compreensão das diferenças entre os adesivos no que se refere ao processo de rotura e resistência da junta. Observou-se que as juntas de sobreposição dupla apresentam uma distribuição de tensões bastante mais favorável relativamente às juntas de sobreposição simples, principalmente devido à eliminação da flexão do substrato interior. Como resultado, a resistência destas juntas foi tipicamente superior ao dobro da observada para as juntas de sobreposição simples, com exceção de algumas configurações de junta em que houve plastificação extensa ou mesmo rotura dos substratos por tração. O trabalho proposto permitiu também concluir que as previsões MDC são tipicamente precisas, e qual a família de adesivos é mais adequada para cada configuração de junta, com a clara vantagem para o Sikaforce® 7888. Como resultado deste trabalho, foram propostas diretrizes de conceção para juntas adesivas.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Aplicação de um método de correlação de imagem para a determinação da tenacidade à fratura em corte de adesivos estruturais

Qualquer estrutura hoje em dia deve ser resistente, robusta e leve, o que aumentou o interesse industrial e investigação nas ligações adesivas, nomeadamente pela melhoria das propriedades de resistência e fratura dos materiais. Com esta técnica de união, o projeto de estruturas pode ser orientado para estruturas mais leves, não só em relação à economia direta de peso relativamente às juntas aparafusas ou soldadas, mas também por causa da flexibilidade para ligar materiais diferentes. Em qualquer área da indústria, a aplicação em larga escala de uma determinada técnica de ligação supõe que estão disponíveis ferramentas confiáveis para o projeto e previsão da rotura. Neste âmbito, Modelos de Dano Coesivo (MDC) são uma ferramenta essencial, embora seja necessário estimar as leis MDC do adesivo à tração e corte para entrada nos modelos numéricos. Este trabalho avalia o valor da tenacidade ao corte (GIIC) de juntas coladas para três adesivos com ductilidade distinta. O trabalho experimental consiste na caracterização à fratura ao corte da ligação adesiva por métodos convencionais e pelo Integral-J. Além disso, pelo integral-J, é possível definir a forma exata da lei coesiva. Para o integral-J, é utilizado um método de correlação de imagem digital anteriormente desenvolvido para a avaliação do deslocamento ao corte do adesivo na extremidade da fenda (δs) durante o ensaio, acoplado a uma sub-rotina em Matlab® para a extração automática de δs. É também apresentado um trabalho numérico para avaliar a adequabilidade de leis coesivas triangulares aproximadas em reproduzir as curvas força-deslocamento (P-δ) experimentais dos ensaios ENF. Também se apresenta uma análise de sensibilidade para compreender a influência dos parâmetros coesivos nas previsões numéricas. Como resultado deste trabalho, foram estimadas experimentalmente as leis coesivas de cada adesivo pelo método direto, e numericamente validadas, para posterior previsão de resistência em juntas adesivas. Em conjunto com a caraterização à tração destes adesivos, é possível a previsão da rotura em modo-misto.

Treasury bond returns and U.S. political cycles

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

The sovereign CDS-Bond basis: From a crisis perspective

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Financial crisis spillovers to the corporate sector: Bank-dependent borrowers versus bond market paticipants

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Government bond yield spreads in EMU countries: The story of an ephemeral convergence

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

Bond fund runs: The financial crisis case

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics