This article aims to study the non-Fickian water absorption process in vegetable fiber-reinforced polymer composite using the Langmuir-type model, evaluating the influence of mass diffusivity on the process. The numerical solutions of the governing equations were obtained using the finite-volume method. Transient results of the local and average moisture content, free and entrapped water molecules concentration considering the constant diffusivity and as a function of the average and local moisture content were presented and analyzed. It was observed that the mass diffusivity effectively influences the water absorption behavior, especially in the initial time of the process, where higher differences in the water migration rates into the material are found. The largest free and entrapped water molecule concentration gradients were found close to the composite surface, especially when considering constant mass diffusivity.
The purpose of this article was to theoretically study the non-Fickian moisture absorption process in vegetable-fiber-reinforced polymer composites using a Langmuir-type model. Here, the focus was on evaluating the effect of the water layer thickness that surrounds the composite during the water migration process. The solutions of the governing equations were obtained using the finite volume method, considering constant thermophysical properties and non-deformable material. The results for the local and average moisture content and concentration, gradient values, and the transient rates of the free and bound (water) molecules in the process were presented and analyzed. It was observed that the water layer thickness strongly influenced the water absorption kinetics, the moisture content gradient values, and the equilibrium moisture content inside the material. It is envisaged that this new approach will contribute to better interpretation of experimental data and a better understanding of the physical phenomenon of water absorption, which directly affects the properties of composite materials.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations鈥揷itations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.