Modeling of Hygro-Mechanical Behaviour through Raffia vinifera Fiber during the Water Diffusion Phenomenon

In an industrial context where the use of friendly materials is encouraged, natural fibers of vegetable origin become more solicited for the reinforcement of composite materials. This work deals with the modeling of the hygro-mechanical behavior through raffia vinifera fiber during the diffusion phenomenon. The modeling of water diffusion through the raffia vinifera fiber is described by Fick’s second law and taking into account the swelling phenomenon of the fiber. The equation obtained is solved numerically by the finite difference method, and the evolution of the fiber radius as a function of time is obtained. By applying the Leibniz integration rule, a mathematical expression to predict the evolution of this radius as a function of time is proposed. It is observed numerically and analytically an increase of the dimensionless fiber radius with time up to a critical value after what one observes the saturation. This model allowed us to propose a mathematical model describing the absorption kinetics of the raffia vinifera fiber through its absorption ratio. By comparing the results of this model with the experimental results from the literature, one observes a good agreement. Moreover, the induced stresses in the fiber during the water diffusion can also be estimated with the proposed mathematical model expression of fiber. These stresses increase with time and can reach between 5 and 7 GPa. The results of this work can be used to predict the behavior of the raffia vinifera fiber inside a composite material during its development.

Investigation of Meniscus Effect on Microbond Test of Typha Fiber/Epoxy Matrix

The microbond test was one of the methods to examine the interfacial shear strength (IFSS) value of fiber and polymer matrix. The meniscus angle that formed at both ends of the matrix is difficult to control while manufacturing the specimen for the microbond test. Therefore, the effect of meniscus angle must be evaluated. In this paper, we evaluated the impact of variations of the meniscus angle against the maximum von-mises stress and the IFSS value of the Typha fiber epoxy matrix by finite element method. The geometry of the microbond test specimen was modeled with 0.25 mm fiber radius, 2 mm fiber length, 1.75 mm embedded length of the matrix, and varied the meniscus angles with 22°, 30°, 45°, 60°, 75°, and 90°. The mesh type quad-dominated CAX4R is used on fiber and matrix, while quad COHAX4 is applied to the cohesive element between fiber and matrix. The constantly applied displacement was adjusted to the upper end of the fiber at 0.6 mm. The simulation results showed that the difference in maximum stress obtained in each model. Furthermore, that is not given much difference in IFSS value. It can be concluded that the meniscus angle affects the maximum von-mises stress but not too much-affected IFSS value of the fiber and epoxy matrix.

Mechanical modeling of textile composites using fiber-reinforced voxel models

The fiber-reinforced voxel modeling technique is proposed to analyze the stress field and predict stiffness properties of textile composites. The textile reinforcements and matrix materials are modeled by virtual fibers and 3D voxel elements separately. Then the virtual fibers are “inserted” into the background voxel elements to construct the fiber-reinforced voxel elements. Stiffness properties of each fiber-reinforced voxel element are determined using volume average method based on the volume fraction and orientation of the virtual fibers it occupies. Geometry modeling and meshing of the complex reinforcements and matrix regions are avoided. As the reinforcements are generated in quasi-fiber scale, contact interactions and compaction deformations of the yarns can be modeled with high fidelity. A composite model containing one crimped yarn is used to verify the proposed method by comparing the calculating results of the fiber-reinforced voxel and traditional meso-scale models. The effect of voxel meshing density and virtual fiber radius on the simulation accuracy is also analyzed. Mechanical modeling of a multiply plain weave composite is performed by this model. Influence of nesting and compaction of the plies on the stress field can be fully characterized.

A Theoretical Model for the Triple Phase Boundary of Solid Oxide Fuel Cell Electrospun Electrodes

Electrospinning is a new state-of-the-art technology for the preparation of electrodes for solid oxide fuel cells (SOFC). Electrodes fabricated by this method have been proven to have an experimentally superior performance compared with traditional electrodes. However, the lack of a theoretic model for electrospun electrodes limits the understanding of their benefits and the optimization of their design. Based on the microstructure of electrospun electrodes and the percolation threshold, a theoretical model of electrospun electrodes is proposed in this study. Electrospun electrodes are compared to fibers with surfaces that were coated with impregnated particles. This model captures the key geometric parameters and their interrelationship, which are required to derive explicit expressions of the key electrode parameters. Furthermore, the length of the triple phase boundary (TPB) of the electrospun electrode is calculated based on this model. Finally, the effects of particle radius, fiber radius, and impregnation loading are studied. The theory model of the electrospun electrode TPB proposed in this study contributes to the optimization design of SOFC electrospun electrode.

Long-Term Dissolution of Glass Fibers in Water Described by Dissolving Cylinder Zero-Order Kinetic Model: Mass Loss and Radius Reduction

Glass fibers are degraded when they are exposed to water. In this work, a model is developed that uses zero-order kinetics for predicting a decreasing glass fiber radius. The model is used to describe experimental test results of almost half a year long-term dissolution of R-glass fibers. The model is able to predict both mass loss and radius reduction kinetics using the same four parameters: initial fiber radius (r0), rate constants for both short-term degradation $\left( K_{0}^{I} \right)$and steady-state degradation $\left( K_{0}^{II} \right)$and the time when steady-state kinetics are reached (tst). All parameters can be easily determined from initial radius measurements and mass loss evolution in time. Elements released and detected during degradation were Na, K, Ca, Mg, Fe, Al, Si and Cl. Rate constants were obtained for individual ion release and for the total mass loss. The contribution of Si to the total mass loss was the largest (56.1% by mass). It governed the dissolution process. The kinetics of radius reduction are also reported. The radius reduction was found to be linear with time during the steady-state dissolution. The zero-order kinetic constant and the density of the glass describe the rate (proportionality) of the dissolution.

Diffusion-weighted magnetic resonance spectroscopy enables cell-specific monitoring of astrocyte reactivity in vivo

The diffusion of brain intracellular metabolites, as measured using diffusion-weighted magnetic resonance spectroscopy in vivo, is thought to specifically depend on the cellular structure constraining them. However, it has never been established that variations of metabolite diffusion, e.g. as observed in some diseases, could indeed be linked to alterations of cellular morphology. Here we demonstrate, in a mouse model of reactive astrocytes, that advanced diffusion-weighted magnetic resonance spectroscopy acquisition and modeling techniques enable non-invasive detection of reactive astrocyte hypertrophy (increased soma radius, increased fiber radius and length), as inferred from variations of myo-inositol diffusion, and as confirmed by confocal microscopy ex vivo. This establishes that specific alterations of intracellular metabolite diffusion can be measured and related to cell-specific morphological alterations. Furthermore, as reactive astrocytes are a hallmark of many brain pathologies, this work opens exciting perspectives for neuroscience and clinical research.