48 resultados para Analytical hierarchical process
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Dissertação de mestrado em Técnicas de Caracterização e Análise Química
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This work focused on how different types of oil phase, MCT (medium chain triglycerides) and LCT (long chain triglycerides), exert influence on the gelation process of beeswax and thus properties of the organogel produced thereof. Organogels were produced at different temperatures and qualitative phase diagrams were constructed to identify and classify the type of structure formed at various compositions. The microstructure of gelator crystals was studied by polarized light microscopy. Melting and crystallization were characterized by differential scanning calorimetry and rheology (flow and small amplitude oscillatory measurements) to understand organogels' behaviour under different mechanical and thermal conditions. FTIR analysis was employed for a further understanding of oil-gelator chemical interactions. Results showed that the increase of beeswax concentration led to higher values of storage and loss moduli (G, G) and complex modulus (G*) of organogels, which is associated to the strong network formed between the crystalline gelator structure and the oil phase. Crystallization occurred in two steps (well evidenced for higher concentrations of gelator) during temperature decreasing. Thermal analysis showed the occurrence of hysteresis between melting and crystallization. Small angle X-ray scattering (SAXS) analysis allowed a better understanding in terms of how crystal conformations were disposed for each type of organogel. The structuring process supported by medium or long-chain triglycerides oils was an important exploit to apprehend the impact of different carbon chain-size on the gelation process and on gels' properties.
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In recent decades, an increased interest has been evidenced in the research on multi-scale hierarchical modelling in the field of mechanics, and also in the field of wood products and timber engineering. One of the main motivations for hierar-chical modelling is to understand how properties, composition and structure at lower scale levels may influence and be used to predict the material properties on a macroscopic and structural engineering scale. This chapter presents the applicability of statistic and probabilistic methods, such as the Maximum Likelihood method and Bayesian methods, in the representation of timber’s mechanical properties and its inference accounting to prior information obtained in different importance scales. These methods allow to analyse distinct timber’s reference properties, such as density, bending stiffness and strength, and hierarchically consider information obtained through different non, semi or destructive tests. The basis and fundaments of the methods are described and also recommendations and limitations are discussed. The methods may be used in several contexts, however require an expert’s knowledge to assess the correct statistic fitting and define the correlation arrangement between properties.