Polymeric composites reinforced with bio-materials have advantages over composites with synthetic reinforcements. Bio-based composites use low-cost and renewable reinforcements, have nonabrasive properties for machining, have improved damping characteristics, and have potential for energy recycling. However, the limited use of bio-based composites is because their mechanical properties are typically much lower than those of synthetic composites. The objective of this study was to combine state-of-the-art imaging tools with emerging numerical modeling methods for an integrated, multi-level characterization of bio-based reinforcements and their composites. Digital photography (2D) will allow collection of full-field digital images of the surface of sample composites, which will be used for characterization of the morphological structure of fillers (copper wire or wood particle) and of model composites. Mechanical experiments (tension load) on isolated fillers and on model composites will allow imaging of the deformed material. By correlating relative positions of thousands of surface features between consecutive images, digital image correlation (DIC) algorithms can be used to map surface deformation fields and calculate surface strain fields. Digital imaging methods can only record deformations and strains. The interpretation of those strains in terms of material properties, such as position-dependent modulus of a heterogeneous composite material, requires simultaneous modeling. The modeling must use morphology-based methods that can handle anisotropy, heterogeneity, and the complex structure of bio-based composites such as wood plastic composites. This research used the material point method (MPM) as a modeling tool. MPM is a particle-based, meshless method for solving problems in computational mechanics. The crucial advantage of MPM over other methods is the relative ease of translating pixels from digital images into material points in the analysis. Thus digital images (2D) used in our experiments were used as direct input to the MPM software, so that the actual morphologies, rather than idealized geometries, were modeled. This procedure removes typical uncertainties connected with idealization of the internal features of modeled materials. It also removes variability of specimen to specimen due to morphology variations. Full-field imaging techniques and computer modeling methods for analysis of complex materials have developed independently. This research Coupled imaging and modeling and used inverse problem methodology for studying bio-particulate composites. The potential of coupling experiments with morphology-based modeling is a relatively new area. This work studied the morphology and mechanical properties of copper wire (for validation experiments) and wood particles used for reinforcement in polymer composites. The goal was to determine the in situ mechanical and interfacial properties of copper wire and then wood particles. By comparison of DIC results to MPM, the conclusion is MPM simulation works well by simulating 3D composite structure and using Matlab software to do qualitative and quantitative comparisons. Copper validation tests showed that copper wire is too stiff compared to polymer such that the inclusion modulus had low effect on the surface strains (DIC experimental results). Wood particle worked better because modulus of wood is much lower than copper. By qualitative comparison of the wood particle specimens, we could deduce that the in situ properties of wood particles are lower than bulk wood. Quantitative analysis concentrated on small area and got more exact results. In a 90 degree particle quantitative study, MPM simulations were shown to be capable of tracking the structure of wood particle plastic, which involved failure. The entire approach, however, is not very robust. We can get some results for mechanical properties, but it does not seem possible to extract all anisotropic properties from a few DIC tests, as some researcher have suggested. / Graduation date: 2012

[pt] Os problemas geotécnicos e geológicos envolvem a descrição do comportamento de materiais tais como solo e rocha e sua eventual interação com fluidos e estruturas. Em geral, a evolução desses problemas é caracterizada por grandes deformações e deslocamentos, descontinuidades, heterogeneidades e um comportamento constitutivo complexo. A abordagem deste tipo de problemas requer técnicas numéricas que levem em conta essas características, sem apresentar inconvenientes numéricos associados à distorção dos elementos como acontece no método dos elementos finitos (FEM). A presente tese desenvolve um algoritmo computacional baseado no método do ponto material (MPM) para aproximar a solução das equações governantes dos fenômenos mencionados. O algoritmo é baseado numa formulação dinâmica tridimensional do contínuo, considerando grandes deformações. Os amortecimentos de Rayleigh o local não viscoso são incorporados para modelar problemas dinâmicos e quase-estáticos. A geração dinâmica das poro-pressões é formulada assumindo o meio poroso saturado e um ponto material para discretizar a mistura. Diversas técnicas de suavização das pressões são avaliadas em problemas de impacto sobre meios saturados. Diferentes modelos constitutivos são implementados para modelar tanto a formação da superfície de ruptura e o processo de escoamento da massa de solo durante as instabilidades, quanto a gênese, evolução e quantificação de zona de falhas nos processos geológicos. Para a abordagem da discretização de problemas de escala geológica de grande número de partículas usando o MPM, uma metodologia é proposta e verificada com a discretização do deslizamento do Daguangbao, na China. Visando à diminuição do tempo computacional, o algoritmo é implementado segundo o paradigma de programação paralela. / [en] Geotechnical and geological problems involve the description of the behavior of materials such as soil and rock, and their eventual interaction with fluids and structures. In general, the evolution of these problems is characterized by large deformations and displacements, discontinuities, heterogeneities and complex constitutive behavior. Addressing these problems requires numerical techniques that take these characteristics into account, without numerical drawbacks associated with element distortion as occurs in the finite element method (FEM). In this thesis is developed a computational algorithm based on the material point method (MPM) to approximate the solution of the governing equations to the mentioned phenomena. The algorithm is based on a three-dimensional dynamic formulation of the continuum considering large deformations. Rayleigh damping and non-viscous local damping are incorporated to model dynamic and quasi-static problems. The dynamic generation of pore pressures is formulated assuming the saturated porous medium and a single material point to discretize the mixture. Different techniques are evaluated to mitigate spurious pressure in impact problems on saturated media. Different constitutive models are implemented to model the failure surface and the soil mass flow process during slope instabilities, as well as the genesis, evolution and failure zone quantification in geological processes. To address the discretization of large-scale geological problems using MPM, a methodology is proposed and validated with the discretization of the Daguangbao landslide, in China. In order to decrease the computational time, the algorithm is implemented according to the parallel programming paradigm.