8 resultados para influence in mechanical properties
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Tissue engineering arises from the need to regenerate organs and tissues, requiring the development of scaffolds, which can provide an optimum environment for tissue growth. In this work, chitosan with different molecular weights was used to develop biodegradable 3D inverted colloidal crystals (ICC) structures for bone regeneration, exhibiting uniform pore size and interconnected network. Moreover, in vitro tests were conducted by studying the influence of the molecular weight in the degradation kinetics and mechanical properties. The production of ICC included four major stages: fabrication of microspheres; assembly into a cohesive structure, polymeric solution infiltration and microsphere removal. Chitosan’s degree of deacetylation was determined by infrared spectroscopy and molecular weight was obtained via capillary viscometry. In order to understand the effect of the molecular weight in ICC structures, the mass loss and mechanical properties were analyzed after degradation with lysozyme. Structure morphology observation before and after degradation was performed by scanning electron microscopy. Cellular adhesion and proliferation tests were carried out to evaluate ICC in vitro response. Overall, medium molecular weight ICC revealed the best balance in terms of mechanical properties, degradation rate, morphology and biological behaviour.
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Annals of Microbiology, 59 (4) 705-713 (2009)
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This study focus on the probabilistic modelling of mechanical properties of prestressing strands based on data collected from tensile tests carried out in Laboratório Nacional de Engenharia Civil (LNEC), Portugal, for certification purposes, and covers a period of about 9 years of production. The strands studied were produced by six manufacturers from four countries, namely Portugal, Spain, Italy and Thailand. Variability of the most important mechanicalproperties is examined and the results are compared with the recommendations of the ProbabilisticModel Code, as well as the Eurocodes and earlier studies. The obtained results show a very low variability which, of course, benefits structural safety. Based on those results, probabilistic modelsfor the most important mechanical properties of prestressing strands are proposed.
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Dissertação para obtenção do Grau de Mestre em Engenharia de Materiais
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Dissertação para obtenção do Grau de Mestre em Biotecnologia
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Durability of Building Materials and Components (Vasco Peixoto de de Freitas, J.M.P.Q. Delgado, eds.), Building Pathology and Rehabilitation, vol. 3, VIII, 105-126. ISBN: 978-3-642-37474-6 (Print) 978-3-642-37475-3 (Online). Springer-Verlag Berlin Heidelberg. DOI: 10.1007/978-3-642-37475-3_5
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Cement & Concrete Composites 45 (2014) 264–271
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Composite materials have a complex behavior, which is difficult to predict under different types of loads. In the course of this dissertation a methodology was developed to predict failure and damage propagation of composite material specimens. This methodology uses finite element numerical models created with Ansys and Matlab softwares. The methodology is able to perform an incremental-iterative analysis, which increases, gradually, the load applied to the specimen. Several structural failure phenomena are considered, such as fiber and/or matrix failure, delamination or shear plasticity. Failure criteria based on element stresses were implemented and a procedure to reduce the stiffness of the failed elements was prepared. The material used in this dissertation consist of a spread tow carbon fabric with a 0°/90° arrangement and the main numerical model analyzed is a 26-plies specimen under compression loads. Numerical results were compared with the results of specimens tested experimentally, whose mechanical properties are unknown, knowing only the geometry of the specimen. The material properties of the numerical model were adjusted in the course of this dissertation, in order to find the lowest difference between the numerical and experimental results with an error lower than 5% (it was performed the numerical model identification based on the experimental results).