Indiana University-Purdue University Indianapolis (IUPUI) / Our ability to engineer materials is limited by our capacity to tailor the material’s microstructure morphology and predict resulting properties. The insufficient knowledge on microstructure-property relationship is due to complexity and randomness in all materials at different scales. The objective of this research is to establish a design optimization methodology for microstructured materials. The material design problem is stated as finding the optimum microstructure to maximize the desired performance satisfying material processing constrains. This problem has been solved in this thesis by means of numerical techniques through four main steps: microstructure characterization, model reconstruction, property evaluation, and optimization. Two methods of microstructure characterizations have been investigated along with the advantages and disadvantages of each method. The first microstructure characterization method is a statistical method which utilizes correlation functions to extract the microstructural information. Algorithms for calculating these correlations functions have been developed and optimized based on their computational cost using MATLAB software. The second microstructure characterization method is physical characterization which works based on evaluation of physical features in microstructured domain. These features have been measured by means of MATLAB codes. Three model reconstruction techniques are proposed based on these characterization methods and employed to generate material models for further evaluation. The first reconstructing algorithm uses statistical functions to reconstruct the statistical equivalent model through simulating annealing optimization method. The second algorithm uses cellular automaton concepts to simulate the grain growth utilizing physical descriptors, and the third one generates elliptical inclusions in a material matrix using physical characteristic of microstructure. The finite element method is used to analysis the mechanical behavior of material models. Several material samples with different microstructural characteristics have been generated to model the micro-scale design domain of AZ31 magnesium alloy and magnesium matrix composite with silicon carbide fibers. Then, surrogate models have been created based on these samples to approximate the entire design domain and demonstrate the sensitivity of the desired mechanical property to two independent microstructural features. Finally, the optimum microstructure characteristics of material samples for fracture strength maximization have been obtained.

[pt] Estruturas treliçadas espaciais são arranjos geométricos de barras amplamente utilizados em coberturas de edificações. Diversos fatores favorecem o seu uso, tais como a capacidade de vencer grandes vãos e a facilidade em assumir diversas formas. A busca pela geometria ótima é um objetivo importante no projeto de estruturas, onde o interesse principal é minimizar o custo da estrutura. O objetivo deste trabalho é apresentar um sistema computacional capaz de minimizar o peso de estruturas treliçadas cuja geometria é definida por curvas de Bézier. Portanto, os pontos de controle das curvas de Bézier são utilizados como variáveis de projeto. As áreas das seções transversais das barras e a altura da treliça também são consideradas como variáveis de projeto e restrições sobre a tensão de escoamento e a tensão crítica de Euler são impostas no problema de otimização. A estrutura é analisada por meio do método dos elementos finitos considerando a hipótese do comportamento linear físico e geométrico. Os algoritmos de otimização usados neste trabalho utilizam o gradiente da função objetivo e das restrições em relação às variáveis de projeto. O sistema computacional desenvolvido neste trabalho foi escrito em linguagem MATLAB e conta com uma integração com o SAP2000 por meio da OAPI (Open Application Programming Interface). Os resultados numéricos obtidos demonstram a eficiência e a aplicabilidade deste sistema. / [en] Spatial truss structures are geometrical arrangements of bars widely used in building roofs. Several factors favor their use, such as the ability to overcome large spans and the capability of assuming a variety of configurations. The search for optimal geometry is an important goal in the design of structures, where the main interest is to minimize the cost of the structure. The objective of this work is to present a computational system capable of minimizing the weight of truss structures whose geometry is defined by Bézier curves. Therefore, the control points of the Bézier curves are used as design variables. The cross-sectional areas of the bars and the truss height are also considered as design variables and constraints on the yield stress and Euler critical stress are imposed on the optimization problem. The structure is analyzed using truss elements considering the physical and geometric linear behavior. The optimization algorithms used in this work require the gradient of the objective function and constraints with respect to the design variables. The computational system developed in this work was written in MATLAB and has an integration with SAP2000 through the OAPI (Open Application Programming Interface). The obtained numerical results demonstrate the efficiency and applicability of the developed system.