Equilibrium self-assembly of colloids with distinct interaction sites: Thermodynamics, percolation, and cluster distribution functions

We calculate the equilibrium thermodynamic properties, percolation threshold, and cluster distribution functions for a model of associating colloids, which consists of hard spherical particles having on their surfaces three short-ranged attractive sites (sticky spots) of two different types, A and B. The thermodynamic properties are calculated using Wertheim's perturbation theory of associating fluids. This also allows us to find the onset of self-assembly, which can be quantified by the maxima of the specific heat at constant volume. The percolation threshold is derived, under the no-loop assumption, for the correlated bond model: In all cases it is two percolated phases that become identical at a critical point, when one exists. Finally, the cluster size distributions are calculated by mapping the model onto an effective model, characterized by a-state-dependent-functionality (f) over bar and unique bonding probability (p) over bar. The mapping is based on the asymptotic limit of the cluster distributions functions of the generic model and the effective parameters are defined through the requirement that the equilibrium cluster distributions of the true and effective models have the same number-averaged and weight-averaged sizes at all densities and temperatures. We also study the model numerically in the case where BB interactions are missing. In this limit, AB bonds either provide branching between A-chains (Y-junctions) if epsilon(AB)/epsilon(AA) is small, or drive the formation of a hyperbranched polymer if epsilon(AB)/epsilon(AA) is large. We find that the theoretical predictions describe quite accurately the numerical data, especially in the region where Y-junctions are present. There is fairly good agreement between theoretical and numerical results both for the thermodynamic (number of bonds and phase coexistence) and the connectivity properties of the model (cluster size distributions and percolation locus).

Optimal design of piezolaminated structures using B-spline strip finite element models

A package of B-spline finite strip models is developed for the linear analysis of piezolaminated plates and shells. This package is associated to a global optimization technique in order to enhance the performance of these types of structures, subjected to various types of objective functions and/or constraints, with discrete and continuous design variables. The models considered are based on a higher-order displacement field and one can apply them to the static, free vibration and buckling analyses of laminated adaptive structures with arbitrary lay-ups, loading and boundary conditions. Genetic algorithms, with either binary or floating point encoding of design variables, were considered to find optimal locations of piezoelectric actuators as well as to determine the best voltages applied to them in order to obtain a desired structure shape. These models provide an overall economy of computing effort for static and vibration problems.

Avaliação da influência dos parâmetros de ensaio no índice de fluidez de termoplásticos

O presente trabalho teve como objectivos avaliar a influência de diversas grandezas e parâmetros de ensaio no índice de fluidez de termoplásticos e calcular a incerteza associada às determinações. Numa primeira fase, procedeu-se à identificação dos principais parâmetros que influenciam a determinação do índice de fluidez, tendo sido seleccionados a temperatura do plastómetro, o peso de carga, o diâmetro da fieira, o comprimento da medição, o tipo de corte e o número de provetes. Para avaliar a influência destes parâmetros na medição do índice de fluidez, optou-se pela realização de um planeamento de experiências, o qual foi dividido em três etapas. Para o tratamento dos resultados obtidos utilizou-se como ferramenta a análise de variância. Após a completa análise dos desenhos factoriais, verificou-se que os efeitos dos factores temperatura do plastómetro, peso de carga e diâmetro da fieira apresentam um importante significado estatístico na medição do índice de fluidez. Na segunda fase, procedeu-se ao cálculo da incerteza associada às medições. Para tal seleccionou-se um dos métodos mais usuais, referido no Guia para a Expressão da Incerteza da Medição, conhecido como método GUM, e pela utilização da abordagem “passo a passo”. Inicialmente, foi necessária a construção de um modelo matemático para a medição do índice de fluidez que relacionasse os diferentes parâmetros utilizados. Foi estudado o comportamento de cada um dos parâmetros através da utilização de duas funções, recorrendo-se novamente à análise de variância. Através da lei de propagação das incertezas foi possível determinar a incerteza padrão combinada,e após estimativa do número de graus de liberdade, foi possível determinar o valor do coeficiente de expansão. Finalmente determinou-se a incerteza expandida da medição, relativa à determinação do índice de fluidez em volume.

Evaluation of the influence of testing parameters on the melt flow index of thermoplastics

The main goals of the present work are the evaluation of the influence of several variables and test parameters on the melt flow index (MFI) of thermoplastics, and the determination of the uncertainty associated with the measurements. To evaluate the influence of test parameters on the measurement of MFI the design of experiments (DOE) approach has been used. The uncertainty has been calculated using a "bottom-up" approach given in the "Guide to the Expression of the Uncertainty of Measurement" (GUM). Since an analytical expression relating the output response (MFI) with input parameters does not exist, it has been necessary to build mathematical models by adjusting the experimental observations of the response variable in accordance with each input parameter. Subsequently, the determination of the uncertainty associated with the measurement of MFI has been performed by applying the law of propagation of uncertainty to the values of uncertainty of the input parameters. Finally, the activation energy (Ea) of the melt flow at around 200 degrees C and the respective uncertainty have also been determined.