In this thesis, the contact behavior of the conduct particles in the anisotropic conductive film (ACF) packaging process is investigated. The thermal elastic-plastic finite element (FE) model is employed to simulate the contact process. The commercial MARC finite element method package is used in this work. Two contact models of the ACF packaging are studied : the single particle and the multiple-particles models. In the single particle model a simple axial symmetric FE model is used to simulate the variation of elastic-plastic deformations during packaging process. The effect of coating thickness on the contact deformation is discussed. To explore the effect of particle distribution on the contact deformation and the conduct behavior in the ACF packaging, the multiple-particles 3D model has also been studied. However, to overcome the computing difficulties introduced from huge degrees of freedom, the equivalent nonlinear springs are employed to stand for some conductive particles. The effect of particle distribution and particle parameters on the conductive behavior are studied. Results indicate that the conductive particle parameters may affect the conductive characteristics significantly in the ACF packaging process.

Confined particulate systems, particularly powder compacts, are widely used in various applications in industries such as pharmaceutical, automotive, agriculture, and energy production. Due to their extensive applications, characterization of these materials is of great importance for optimizing their performance and manufacturing processes. Modeling approaches capable of capturing the heterogeneity and complex behavior are effective at predicting the macroscopic behavior of granular systems. These modeling approaches utilize information about the microstructure evolution of these materials during compaction processes at the mesoscale (particle-scale). Using these types of modeling depend on accurate contact formulation between inter-particle contacts. The challenge comes in formulating these contact models that accurately predict force-area-deformation relationships. In this work, contact laws are presented for elastic-ideally plastic particles and plastic particles with power-law hardening under unconfined (simple compression) and confined (die and hydrostatic compaction) compression. First, material properties for a set of finite element simulations are obtained using space-filling design. The finite element simulations are used for verification and building an analytical framework of the contact radius and contact pressure which allows for efficient determination of the contact force. Semi-mechanistic contact laws are built for elastic-ideally plastic spherical particles that depend on material properties and loading configuration. Then, rigid-plastic assumption is used to modify the contact laws to consider power-law hardening effects while keeping loading configuration dependency. Finally, after building and verifying the contact laws, they are used to estimate hardening properties, contact radius evolution, and stress response of micro-crystalline cellulose particles under different loading configurations using experimental data from simple compression.

Articular cartilage covers the articulating ends of diarthrodial joints. It plays a vital role in the function of the musculoskeletal system by allowing almost frictionless motion to occur between the articular surfaces of a diarthrodial joint. Study of cartilage contact behavior will help to understand the intrinsic biomechanical properties related to cartilage degeneration and related pathology. In order to study the mechanical behavior of the cartilage a FEM based computational model of the knee-joint was developed from MRI data. A heuristic algorithm was developed based on Image processing techniques using Evolve2D toolbox and edge detection. An indigenous path following algorithm to capture minute details of bone and soft tissue curvature was developed using Image Processing Toolbox of Matlab. Parts including femur, tibia, femoral and tibial cartilages, lateral & medial menisci were extracted as a point cloud from each of the slices and rendered into a 3D model using GUI driven CAD package RHINOCEROS 4.0. Commercial FE software HYPERMESH 9.0 was used to develop FE model from geometric model. Cartilage and Menisci were modeled using eight node hexahedral elements and bones were modeled using four node quadrilateral elements. Bones were assumed to be rigid. Cartilage and menisci were assumed to be linearly elastic, isotropic and homogenous. The knee joint was subjected to a uniaxial compressive load with tibia remaining fixed and femur subjected to two primary boundary conditions: 1.Flexion - extension and Varus - Valgus rotation constrained; 2.Only Varus - Valgus rotation constrained. Parameters such as contact area, contact pressure, contact force, centre of contact pressure, mises stress distribution; maximum and minimum principal stresses were studied at maximum compressive load condition and also in intermittent steps. This model considered both geometric and contact non-linearity. From the FE analysis, it was observed that peak contact deformation and contact area on both femoral and tibial medial cartilage was found to be greater than the lateral side under full extension condition. More than 50% of the load transmission was through the medial side - which could be an indication of cartilage degeneration. Deformation of lateral meniscus was more than the medial meniscus under angular constrained conditions. Loading history during intermittent steps suggested that contact area on lateral tibial cartilage increased with load, indicating joint asymmetry. These results indicate the importance of the rotational constraints (boundary conditions) and represent more accurate physiological behavior of knee joint. Role of menisci in this study was analyzed, which indicated that consideration of menisci is essential in biomechanical estimation of load transmission. In conclusion, detailed segmentation to develop geometric model, precise boundary conditions & time dependent behavior of cartilage and menisci helped in understanding knee joint load bearing capacity to a better accuracy and can potentially give rise to designing better cartilage implants.