No / Rheological characterisation of hydroxyapatite -high density polyethylene (HA-HDPE) composites has been performed in terms of isothermal compressibility and wall slip. Addition of HA to the polymer melt decreases the compressibility of the melt. The unfilled HDPE was found to exhibit wall slip at shear stresses as low as 0.10 MPa. The flow curves of the composites showed three distinct regions: a gradient at low shear rates; a plateau region; and a gradient at higher shear rate. An increase in rheometer pressure seems to suppress the slip in composites. The 40 vol.-% HA-HDPE composite exhibited two critical shear stresses, one corresponding to wall slip, which occurs in the lower shear rate region of the flow curve, and the other corresponding to a plateau, which is identified with the stick-slip behaviour of unfilled HDPE reported in the literature. The plateau shear stress increased with filler volume fraction and this effect is attributed to the decreased compressibility of the melt. A good correlation with a negative correlation coefficient was found to exist between compressibility and shear stress in the plateau region. The slip observed in unfilled HDPE and at low shear rates in the 40 vol.-% HA- HDPE systems has been explained in terms of a low molecular weight polymer layer formed at the melt/wall interface. The large interfacial slip observed in the plateau region is attributed to complete disentanglement of adsorbed chains from free chains at the melt/wall interface at and beyond the plateau region.

Made available in DSpace on 2014-12-17T14:08:53Z (GMT). No. of bitstreams: 1 FranciscaFNS_DISSERT.pdf: 1424383 bytes, checksum: 6d399b5a60f42e3c2b87657eb17e44e0 (MD5) Previous issue date: 2013-02-05 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / Atualmente, ? de grande interesse o estudo de m?todos de previs?o de S?ries Temporais, ou seja, conseguir identificar e predizer algumas caracter?sticas do processo num ponto futuro. Na engenharia de petr?leo uma das atividades essenciais ? a estimativa de produ??o de ?leo existente nas reservas petrol?feras de reservat?rios maduros. O c?lculo dessas reservas ? crucial para a determina??o da viabilidade econ?mica de sua explota??o. Para tanto, a ind?stria do petr?leo faz uso de t?cnicas convencionais de modelagem de reservat?rios como simula??o num?rica matem?tica para previs?o da produ??o de petr?leo. Diante deste fato, o objetivo fundamental deste trabalho ? propor uma metodologia de An?lise de S?ries Temporais baseada nos tradicionais modelos estat?sticos de Box & Jenkins, que em conjunto com a t?cnica inteligente de Redes Neurais Artificiais (RNA s), possibilite a constru??o de um modelo h?brido de predi??o de dados de produ??o de petr?leo, tomando por base a capacidade que a rede tem em aprender com a experi?ncia e partir para generaliza??o baseada no seu conhecimento pr?vio. Para tanto, a Rede Neural ser? treinada com a finalidade de estimar e corrigir os erros associados ao modelo estat?stico de S?rie Temporal, de forma a aproximar a s?rie estimada ? s?rie de dados original. Os dados da S?rie Temporal em estudo referem-se ? curva de vaz?o de petr?leo de um reservat?rio localizado em um campo da regi?o nordeste do Brasil. A s?rie em estudo foi obtida no per?odo 31de julho do ano 1998 ate 31 de dezembro de 2007, com os dados (vaz?o) sendo obtidos com intervalos mensais, totalizando 127 meses de informa??es. O algoritmo de predi??o proposto pela Rede Neural receber? como entrada os erros gerados pelo modelo estat?stico de s?rie e fornecer? como sa?da uma estimativa do erro no tempo n+h onde h representa o horizonte de predi??o. Os erros estimados pela Rede Neural ser?o adicionados ao Modelo de S?rie Temporal com a finalidade de corrigi-lo. Por fim, ser? feito um estudo comparativo da performance preditiva do modelo de Box & Jenkins cl?ssico e o modelo de Box & Jenkins corrigido pela Rede Neural. A arquitetura recorrente em estudo neste trabalho dever? ser capaz de prover estimativas confi?veis, tanto para um horizonte de predi??o de passos simples quanto para um horizonte de m?ltiplos passos. O software utilizado para realiza??o do ajuste do modelo estat?stico de S?rie Temporal foi o R Project for Statistical Computing - vers?o 2.14.1. Para fazer as implementa??es necess?rias da Rede Neural, a ferramenta computacional utilizada foi o software Matlab Vers?o 7.0.2 (R2011a)

This master's thesis deals with the identification of the material flow curve from record of tensile test of smooth cylindrical specimen. First, necessary theory background is presented. Basic terms of incremental theory of plasticity, tensile test procedure and processing its outputs are described. Furthermore, possibilities of mathematical expression of the elastic-plastic material constitutive law, thus mathematical expression of the material flow curve itself. Mechanism of ductile damage of material is explained briefly as well. Overview of recent methods of the flow curve identification is given, focused on cases, when the stress distribution in a specimen is not uniaxial. That is either kind of analytic correction of basic formulas derived for uniaxial stress state, or application of mathematical optimization techniques combined with numerical simulation of the tensile test. Also unusual method of neural network is mentioned. For 8 given materials, the flow curve identification was performed using different methods. Namely by analytic correction, optimization, sequential identification and neural network. Algorithms of the last two methods were modified. Based on assessment of obtained results, application field and adjusting the parameters of single algorithms was recommended. It showed up, that an effective way to the accurate and credible results is the combination of different methods during flow curve identification procedure.

No / The effect of matrix polymer and filler content on the rheological behavior of hydroxyapatite-filled injection molding grade high-density polyethylene (HDPE) has been studied. Studies of the flow curves revealed that the matrix and the composite exhibit three distinct regions in the flow curve, namely, a pseudoplastic region at low to moderate shear rates, a plateau and a second pseudoplastic region at high shear rates. The shear stress corresponding to the plateau (Tc) is dependent on both the filler concentration and the melt temperature. Addition of HA in the HDPE matrix increases the value of Tc and decreases compressibility of the melt. An increase in temperature also raises the value of Tc. From the nature of flow curves it is concluded that the matrix polymer largely decides the rheology of the composite.