192 resultados para Mantas de sisal
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This paper evaluates the advantages of using hardwood short fibre pulp (eucalyptus) as alternative to softwood long fibre pulp (pinus) and polymer fibres, traditionally used in reinforcement of cement-based materials. The effects of cellulose fibre length on microstructure and on mechanical performance of fibre-cement composites were evaluated before and after accelerated ageing cycles. Hardwood pulp fibres were better dispersed in the cement matrix and provided higher number of fibres per unitary weight or volume, in relation to softwood long fibre pulp. The short reinforcing elements lead to an effective crack bridging of the fragile matrix, which contributes to the improvement of the mechanical performance of the composite after ageing. These promising results show the potential of eucalyptus short fibres for reducing costs by both the partial replacement of expensive synthetic fibres in air curing process and the energy savings during pulp refining. (C) 2009 Elsevier B.V. All rights reserved.
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Proceedings of International Conference Conference Volume 7830 Image and Signal Processing for Remote Sensing XVI Lorenzo Bruzzone Toulouse, France | September 20, 2010
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n the last decades the biocomposites have been widely used in the construction, automobile and aerospace industries. Not only the interface transition zone (ITZ) but also the heterogeneity of natural fibres affects the mechanical behaviour of these composites. This work focuses on the numerical and experimental analyses of a polymeric composite fabricated with epoxy resin and unidirectional sisal and banana fibres. A three-dimensional model was set to analyze the composites using the elastic properties of the individual phases. In addition, a two-dimensional model was set taking into account the effective composite properties obtained by micromechanical models. A tensile testing was performed to validate the numerical analyses and evaluating the interface condition of the constitutive phases.
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Mestrado em Engenharia Química - Ramo Optimização Energética na Indústria Química
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Cada vez mais é necessário inovar e optimizar, sendo todos os processos susceptíveis a melhorias contínuas. A inovação e empenho no desenvolvimento destas novas soluções resultam do “know-how” já existente e da necessidade permanente de incrementar a produtividade com vista a uma maior competitividade, a flexibilidade e assegurar simultaneamente a qualidade dos produtos manufacturados. Com vista a incrementar a flexibilidade, torna-se necessário reduzir significativamente os tempos de “set-up” e o ”lead-time”, com vista a assegurar a entrega dos produtos de forma cada vez mais rápida. Este objectivo pode ser conseguido através de uma normalização dos elementos que constituem a linha de pultrusão. Implicitamente, observa-se um aumento de produtividade com esta medida. Neste trabalho pretende-se optimizar e flexibilizar todo o processo de pultrusão de perfis estruturais. Foram considerados todos os elementos do sistema, desde o armazém das fibras (“rack”) até à fieira de pultrusão. Foi dedicada particular atenção ao sistema de guiamento das fibras e mantas, à tina onde as fibras são impregnadas em resina, normalizadas as placas de posicionamento das fibras em direcção à entrada da fieira e revisto todo o processo de montagem e fixação da fieira, assim como o sistema de aquecimento da mesma. Com a implementação destes novos sistemas foi conseguida uma poupança significativa de tempo de “set-up” e foram claramente reduzidos os custos unitários de produção. A garantia de qualidade foi também incrementada.
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Hyperspectral imaging can be used for object detection and for discriminating between different objects based on their spectral characteristics. One of the main problems of hyperspectral data analysis is the presence of mixed pixels, due to the low spatial resolution of such images. This means that several spectrally pure signatures (endmembers) are combined into the same mixed pixel. Linear spectral unmixing follows an unsupervised approach which aims at inferring pure spectral signatures and their material fractions at each pixel of the scene. The huge data volumes acquired by such sensors put stringent requirements on processing and unmixing methods. This paper proposes an efficient implementation of a unsupervised linear unmixing method on GPUs using CUDA. The method finds the smallest simplex by solving a sequence of nonsmooth convex subproblems using variable splitting to obtain a constraint formulation, and then applying an augmented Lagrangian technique. The parallel implementation of SISAL presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory. The results herein presented indicate that the GPU implementation can significantly accelerate the method's execution over big datasets while maintaining the methods accuracy.
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Hyperspectral imaging has become one of the main topics in remote sensing applications, which comprise hundreds of spectral bands at different (almost contiguous) wavelength channels over the same area generating large data volumes comprising several GBs per flight. This high spectral resolution can be used for object detection and for discriminate between different objects based on their spectral characteristics. One of the main problems involved in hyperspectral analysis is the presence of mixed pixels, which arise when the spacial resolution of the sensor is not able to separate spectrally distinct materials. Spectral unmixing is one of the most important task for hyperspectral data exploitation. However, the unmixing algorithms can be computationally very expensive, and even high power consuming, which compromises the use in applications under on-board constraints. In recent years, graphics processing units (GPUs) have evolved into highly parallel and programmable systems. Specifically, several hyperspectral imaging algorithms have shown to be able to benefit from this hardware taking advantage of the extremely high floating-point processing performance, compact size, huge memory bandwidth, and relatively low cost of these units, which make them appealing for onboard data processing. In this paper, we propose a parallel implementation of an augmented Lagragian based method for unsupervised hyperspectral linear unmixing on GPUs using CUDA. The method called simplex identification via split augmented Lagrangian (SISAL) aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The efficient implementation of SISAL method presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory.
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One of the main problems of hyperspectral data analysis is the presence of mixed pixels due to the low spatial resolution of such images. Linear spectral unmixing aims at inferring pure spectral signatures and their fractions at each pixel of the scene. The huge data volumes acquired by hyperspectral sensors put stringent requirements on processing and unmixing methods. This letter proposes an efficient implementation of the method called simplex identification via split augmented Lagrangian (SISAL) which exploits the graphics processing unit (GPU) architecture at low level using Compute Unified Device Architecture. SISAL aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The proposed implementation is performed in a pixel-by-pixel fashion using coalesced accesses to memory and exploiting shared memory to store temporary data. Furthermore, the kernels have been optimized to minimize the threads divergence, therefore achieving high GPU occupancy. The experimental results obtained for the simulated and real hyperspectral data sets reveal speedups up to 49 times, which demonstrates that the GPU implementation can significantly accelerate the method's execution over big data sets while maintaining the methods accuracy.
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In hyperspectral imagery a pixel typically consists mixture of spectral signatures of reference substances, also called endmembers. Linear spectral mixture analysis, or linear unmixing, aims at estimating the number of endmembers, their spectral signatures, and their abundance fractions. This paper proposes a framework for hyperpsectral unmixing. A blind method (SISAL) is used for the estimation of the unknown endmember signature and their abundance fractions. This method solve a non-convex problem by a sequence of augmented Lagrangian optimizations, where the positivity constraints, forcing the spectral vectors to belong to the convex hull of the endmember signatures, are replaced by soft constraints. The proposed framework simultaneously estimates the number of endmembers present in the hyperspectral image by an algorithm based on the minimum description length (MDL) principle. Experimental results on both synthetic and real hyperspectral data demonstrate the effectiveness of the proposed algorithm.
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Dissertação para obtenção do Grau de Mestre em Engenharia química e bioquímica
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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
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UNL - NSBE
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This paper reports the first attempt of characterizing various physical, mechanical and chemical properties of Quiscal fibres, used by the native communities in Chile and investigating the influence of atmospheric dielectric barrier discharge plasma treatment on various properties such as diameter and linear density, fat, wax and impurity%, moisture regain, chemical elements and groups, thermal degradation, surface morphology, etc. According to the experimental observations, Quiscal fibre has lower tenacity than most of the technical grade natural fibres such as sisal, hemp, flax, etc., and plasma treatment at optimum dose improved its tenacity to the level of sisal fibres. Plasma treatment also reduced the amount of fat, wax and other foreign impurities present in Quiscal fibres as well as removed lignin and hemicellulose partially from the fibre structure. Plasma treatment led to functionalization of Quiscal fibre surface with chemical groups, as revealed from attenuated total reflection spectroscopy and also confirmed from the elemental analysis using energy dispersive Xray technique and pH and conductivity measurements of fibre aqueous extract. The wetting behavior of Quiscal fibre also improved considerably through plasma treatment. However, untreated and plasma treated Quiscal fibres showed similar thermal degradation behavior, except the final degradation stage, in which plasma treated fibres showed higher stability and incomplete degradation unlike the untreated fibres. The experimental results suggested that the plasma treated Quiscal fibres, like other technical grade natural fibres, can find potential application as reinforcement of composite materials for various industrial applications.
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The growing concerns regarding the environmental impact generated by the use of inorganic materials in different fields of application increased the interest towards products based on materials with low environmental impact. In recent years, researchers have turned their attention towards the development of materials obtained from renewable sources, easily recoverable or biodegradable at the end of use. In the field of civil structures, a few attempts have been done to replace the most common composites (e.g. carbon and glass fibers) by materials less harmful to the environment, as natural fibers. This work presents a comprehensive experimental research on the mechanical performance of natural fibers for the strengthening of masonry constructions. Flax, hemp, jute, sisal and coir fibers have been investigated both from physical and mechanical points of view. The fibers with better performance were tested together with three different matrices (two of organic nature) in order to produce composites. These experimental results represent a useful database for understanding the potentialities of natural fibers as strengthening systems.
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Current societal challenges increasingly demand the need to seek for efficient and sustainable solutions to daily problems. Construction, as a result of its activity, is one of the main responsible industry for the exploitation of resources and greenhouse gas emissions. In this way, several research works are being undertaken to change some of the current practices. This paper presents the work being done at University of Minho to study de degradation of natural fibers when used as a sustainable solution for soil reinforcement. Jute and sisal fibrous structures (0º/90º) were studied in terms of their degradation over time, when incorporated into soil and when subject to accelerated aging tests in a QUV weathering test equipment. Results show that the process of biodegradation of natural fibers is clearly accelerated by the action of temperature, moisture and solar radiation, explaining further degradation of jute and sisal fibers when exposed to these factors, although more pronounced in jute fabric structures.