Numerical Method to Predict Void Formation during The Liquid Composite Molding Process

Void formation during the injection phase of the liquid composite molding process can be explained as a consequence of the non-uniformity of the flow front progression. This is due to the dual porosity within the fiber perform (spacing between the fiber tows is much larger than between the fibers within in a tow) and therefore the best explanation can be provided by a mesolevel analysis, where the characteristic dimension is given by the fiber tow diameter of the order of millimeters. In mesolevel analysis, liquid impregnation along two different scales; inside fiber tows and within the open spaces between the fiber tows must be considered and the coupling between the flow regimes must be addressed. In such cases, it is extremely important to account correctly for the surface tension effects, which can be modeled as capillary pressure applied at the flow front. Numerical implementation of such boundary conditions leads to illposing of the problem, in terms of the weak classical as well as stabilized formulation. As a consequence, there is an error in mass conservation accumulated especially along the free flow front. A numerical procedure was formulated and is implemented in an existing Free Boundary Program to reduce this error significantly.

Performance of concrete made with aggregates recycled from precasting industry waste: influence of the crushing process

The aim of this paper is to evaluate the influence of the crushing process used to obtain recycled concrete aggregates on the performance of concrete made with those aggregates. Two crushing methods were considered: primary crushing, using a jaw crusher, and primary plus secondary crushing (PSC), using a jaw crusher followed by a hammer mill. Besides natural aggregates (NA), these two processes were also used to crush three types of concrete made in laboratory (L20, L45 e L65) and three more others from the precast industry (P20, P45 e P65). The coarse natural aggregates were totally replaced by coarse recycled concrete aggregates. The recycled aggregates concrete mixes were compared with reference concrete mixes made using only NA, and the following properties related to the mechanical and durability performance were tested: compressive strength; splitting tensile strength; modulus of elasticity; carbonation resistance; chloride penetration resistance; water absorption by capillarity; water absorption by immersion; and shrinkage. The results show that the PSC process leads to better performances, especially in the durability properties.

Semi-destructive in situ tests as support to the assessment of a conservation process

This paper refers to the assessment on site by semi-destructive testing (SDT) methods of the consolidation efficiency of a conservation process developed by Henriques (2011) for structural and non-structural pine wood elements in service. This study was applied on scots pine wood (Pinus sylvestris L.) degraded by fungi after treatment with a biocidal product followed by consolidation with a polymeric product. This solution avoids substitutions of wood moderately degraded by fungi, improving its physical and mechanical characteristics. The consolidation efficiency was assessed on site by methods of drill resistance and penetration resistance. The SDT methods used showed good sensitivity to the conservation process and could evaluate their effectiveness. (C) 2015 Elsevier Ltd. All rights reserved.

The impact of driving styles on fuel consumption: a data-warehouse-and-data-mining-based discovery process

This paper discusses the results of applied research on the eco-driving domain based on a huge data set produced from a fleet of Lisbon's public transportation buses for a three-year period. This data set is based on events automatically extracted from the control area network bus and enriched with GPS coordinates, weather conditions, and road information. We apply online analytical processing (OLAP) and knowledge discovery (KD) techniques to deal with the high volume of this data set and to determine the major factors that influence the average fuel consumption, and then classify the drivers involved according to their driving efficiency. Consequently, we identify the most appropriate driving practices and styles. Our findings show that introducing simple practices, such as optimal clutch, engine rotation, and engine running in idle, can reduce fuel consumption on average from 3 to 5l/100 km, meaning a saving of 30 l per bus on one day. These findings have been strongly considered in the drivers' training sessions.

Multiple linear and principal component regressions for modelling ecotoxicity bioassay response

The ecotoxicological response of the living organisms in an aquatic system depends on the physical, chemical and bacteriological variables, as well as the interactions between them. An important challenge to scientists is to understand the interaction and behaviour of factors involved in a multidimensional process such as the ecotoxicological response.With this aim, multiple linear regression (MLR) and principal component regression were applied to the ecotoxicity bioassay response of Chlorella vulgaris and Vibrio fischeri in water collected at seven sites of Leça river during five monitoring campaigns (February, May, June, August and September of 2006). The river water characterization included the analysis of 22 physicochemical and 3 microbiological parameters. The model that best fitted the data was MLR, which shows: (i) a negative correlation with dissolved organic carbon, zinc and manganese, and a positive one with turbidity and arsenic, regarding C. vulgaris toxic response; (ii) a negative correlation with conductivity and turbidity and a positive one with phosphorus, hardness, iron, mercury, arsenic and faecal coliforms, concerning V. fischeri toxic response. This integrated assessment may allow the evaluation of the effect of future pollution abatement measures over the water quality of Leça River.

Localização de ontologias - elementos para a construção de uma abordagem

O desenvolvimento de recursos multilingues robustos para fazer face às exigências crescentes na complexidade dos processos intra e inter-organizacionais é um processo complexo que obriga a um aumento da qualidade nos modos de interacção e partilha dos recursos das organizações, através, por exemplo, de um maior envolvimento dos diferentes interlocutores em formas eficazes e inovadoras de colaboração. É um processo em que se identificam vários problemas e dificuldades, como sendo, no caso da criação de bases de dados lexicais multilingues, o desenvolvimento de uma arquitectura capaz de dar resposta a um conjunto vasto de questões linguísticas, como a polissemia, os padrões lexicais ou os equivalentes de tradução. Estas questões colocam-se na construção quer dos recursos terminológicos, quer de ontologias multilingues. No caso da construção de uma ontologia em diferentes línguas, processo no qual focalizaremos a nossa atenção, as questões e a complexidade aumentam, dado o tipo e propósitos do artefacto semântico, os elementos a localizar (conceitos e relações conceptuais) e o contexto em que o processo de localização ocorre. Pretendemos, assim, com este artigo, analisar o conceito e o processo de localização no contexto dos sistemas de gestão do conhecimento baseados em ontologias, tendo em atenção o papel central da terminologia no processo de localização, as diferentes abordagens e modelos propostos, bem como as ferramentas de base linguística que apoiam a implementação do processo. Procuraremos, finalmente, estabelecer alguns paralelismos entre o processo tradicional de localização e o processo de localização de ontologias, para melhor o situar e definir.

Optimization of antioxidants extraction from coffee silverskin, aroasting by-product, having in view a sustainable process

Coffee silverskin is a major roasting by-product that could be valued as a source of antioxidant compounds. The effect of the major variables (solvent polarity, temperature and extraction time) affecting the extraction yields of bioactive compounds and antioxidant activity of silverskin extracts was evaluated. The extracts composition varied significantly with the extraction conditions used. A factorial experimental design showed that the use of a hydroalcoholic solvent (50%:50%) at 40 °C for 60 min is a sustainable option to maximize the extraction yield of bioactive compounds and the antioxidant capacity of extracts. Using this set of conditions it was possible to obtain extracts containing total phenolics (302.5 ± 7.1 mg GAE/L), tannins (0.43 ± 0.06 mg TAE/L), and flavonoids (83.0 ± 1.4 mg ECE/L), exhibiting DPPHradical dot scavenging activity (326.0 ± 5.7 mg TE/L) and ferric reducing antioxidant power (1791.9 ± 126.3 mg SFE/L). These conditions allowed, in comparison with other “more effective” for some individual parameters, a cost reduction, saving time and energy.

A interação das marcas com o público através do Facebook: o mercado dos smartphones e as marcas Samsung e Apple

Dissertação de Mestrado apresentado ao Instituto de Contabilidade e Administração do Porto para a obtenção do grau de Mestre em Marketing Digital sob orientação de Sandrina Teixeira Anabela Ribeiro

Analysis of diffusion process in fractured reservoirs using fractional derivative approach

The fractal geometry is used to model of a naturally fractured reservoir and the concept of fractional derivative is applied to the diffusion equation to incorporate the history of fluid flow in naturally fractured reservoirs. The resulting fractally fractional diffusion (FFD) equation is solved analytically in the Laplace space for three outer boundary conditions. The analytical solutions are used to analyze the response of a naturally fractured reservoir considering the anomalous behavior of oil production. Several synthetic examples are provided to illustrate the methodology proposed in this work and to explain the diffusion process in fractally fractured systems.

Portuguese strategy for occupational safety and health 2008-2012 for public administration : priorites for action, progress in the implementation of the proposed measures and their impact on occupational safety outcomes

Apresentação realizada no OH&S Forum 2011 - International Forum on Occupational Health and Safety: Policies, profiles and services, na Finlândia de, 20 a 22 Junho de 2011.

Lean applied to logistics: a case study

This project aims to study the implementation of Lean principles and tools in several levels of logistics, from internal logistics to interface with distribution center and suppliers, in an industrial plant. The main focus of all efforts is to create the conditions to approach the continuous flow scenario in the manufacturing processes. The subject of improvement actions is a company whose core activity is car seat production, more specifically the car seat cover production and assembly. This focuses the assembly process, which requires the usage of a considerable variety of components and therefore is an important obstacle to the implementation of continuous flow. The most salient issues are related with inefficient interaction between sections and late supply of components in assembly lines, forcing the operator to abandon his work station and leading to production interruption. As an operational methodology, actions from Lean philosophy and optimization were implemented according to project management principles.

Railway vehicle modelling for the vehicle-track interaction compatibility analysis

Railway vehicle homologation, with respect to running dynamics, is addressed via dedicated norms. The results required, such as, accelerations and/or wheel-rail contact forces, obtained from experimental tests or simulations, must be available. Multibody dynamics allows the modelling of railway vehicles and their representation in real operations conditions, being the realism of the multibody models greatly influenced by the modelling assumptions. In this paper, two alternative multibody models of the Light Rail Vehicle 2000 (LRV) are constructed and simulated in a realistic railway track scenarios. The vehicle-track interaction compatibility analysis consists of two stages: the use of the simplified method described in the norm "UIC 518-Testing and Approval of Railway Vehicles from the Point of View of their Dynamic Behaviour-Safety-Track Fatigue-Running Behaviour" for decision making; and, visualization inspection of the vehicle motion with respect to the track via dedicated tools for understanding the mechanisms involved.

Análise numérica e experimental de um modelo dinâmico da ponte ferroviária de Antuã

Mestrado em Engenharia Civil – Ramo Estruturas

Influence of the crushing process of recycled aggregates on concrete properties

This work intends to evaluate the (mechanical and durability) performance of concrete made with coarse recycled concrete aggregates (CRCA) obtained using two crushing processes: primary crushing (PC) and primary plus secondary crushing (PSC). This analysis intends to select the most efficient production process of recycled aggregates (RA). The RA used here resulted from precast products (P), with strength classes of 20 MPa, 45 MPa and 65 MPa, and from laboratory-made concrete (L) with the same compressive strengths. The evaluation of concrete was made with the following tests: compressive strength; splitting tensile strength; modulus of elasticity; carbona-tion resistance; chloride penetration resistance; capillary water absorption; and water absorption by immersion. These findings contribute to a solid and innovative basis that allows the precasting industry to use without restrictions the waste it generates. © (2015) Trans Tech Publications, Switzerland.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.