Mechanical Response of Random Fibrous Structures subjected to Local Contractile Forces

Random fibrous networks are integral structural components found in a wide range of materials, encompassing both biological and non-biological domains. These networks contribute to the structural support and unique functionalities exhibited by materials such as paper, fabric, rubber, cell cytoskeleton, and extracellular matrix (ECM). The mechanical behaviors displayed by fibrous networks are distinctive, with nonlinear strain stiffening being a notable characteristic. As a result, there has been a growing interest in studying these network-based materials for two primary reasons. Firstly, there is a strong desire to understand the behavior and functionality of fibrous networks in their natural environments and gain insights into the underlying mechanisms that contribute to their unique mechanical behavior. Secondly, exploring fibrous materials opens up possibilities for developing advanced materials that mimic or even exceed the unique properties exhibited by natural networks. This thesis focuses on investigating the nonlinear strain stiffening behavior of random fibrous networks through simulations and analyses under various loading conditions. The aim is to gain a deeper understanding of their mechanical response and functionalities. Additionally, the influence of prestress on network behavior and the significance of random networks in the long-range transmission of physical cues are examined. By studying the effect of prestress on fibrous networks, the goal is to enhance our understanding of their response in real-world conditions. Furthermore, investigating the role of random networks in the transmission of physical cues provides valuable insight into how these networks facilitate communication within materials. The study of fibrous random networks offers significant potential in understanding their unique mechanical response, paving the way for the development of materials with tailored structural properties.