Micromechanics of Fiber Networks

Abstract: The current trends in papermaking involve, but are not limited to, maintaining the dry strength of paper material at a reduced cost. Since any small changes in the process affect several factors at once, it is difficult to relate the exact impact of these changes promptly. Hence, the detailed models of the network level of a dry sheet have to be studied extensively in order to attain the infinitesimal changes in the final product.In Paper A, we have investigated a relation between micromechanical processes and the stress–strain curve of a dry fiber network during tensile loading. The impact of “non-traditional” bonding parameters, such as compliance of bonding regions, work of separation and the actual number of effective bonds, is discussed. In Paper B, we studied the impact of the chemical composition of the fiber cell wall, as well as its geometrical properties, on the fiber mechanical properties using the three-dimensional model of a fiber with helical orientation of microfibrils at a range of different microfibril angles (MFA). In order to accurately characterize the fiber and bond properties inside the network, via statistical distributions, microtomography studies on the handsheets have been carried out. This work is divided into two parts: Paper C, which describes the methods of data acquisition and Paper D, where we discuss the extracted data. Here, all measurements were performed at a fiber level, providing data on the fiber width distribution, width-to-height ratio of isotropically oriented fibers and contact density. In the last paper, we utilize data thus obtained in conjunction with fiber morphology data from Papers C and D to update the network generation algorithm in order to produce more realistic fiber networks. We also successfully verified the models with the help of experimental results from dry sheets tested under uniaxial tensile tests. We carry out numerical simulations on these networks to ascertain the influence of fiber and bond parameters on the network strength properties.