LAUSR

Random fiber networks constitute the solid skeleton of many biological materials such as the cytoskeleton of cells and extracellular matrix of soft tissues. These random networks show unique mechanical properties such as nonlinear shear strain stiffening and strain softening when subjected to preextension and precompression, respectively. In the present study, we perform numerical simulations in order to characterize the influence of axial prestress on the nonlinear mechanical response of random network structures as a function of their micromechanical and geometrical properties. We build our numerical network models using the microstructure of disordered hexagonal lattices and quantify their nonlinear shear response as a function of uniaxial prestress strain. We consider three different material models for individual fibers and fully characterize their influence on the mechanical response of prestressed networks. Moreover, we investigate the influence of geometric disorder, keeping the network connectivity constant, and the randomness in the stiffness of individual fibers, keeping their mean stiffness constant. The effects of network connectivity and bending rigidity of fibers are also determined. Several important conclusions are made, including that the tensile and compressive prestress strains, respectively, increase and decrease the initial network shear stiffness, but have no effect on the maximum shear modulus. We discuss our findings in terms of microstructural properties such as the local strain energy distribution.