Monitoring the physical state of wood during multiple tensile load-unload cycles by the eigenvalue distribution of near infrared spectra

Wood is a typical viscoelastic material that shows a clear mechanical hysteresis loop during cyclic loading, which implies the irreversibility of the process and is important for the processing and long-term utility of wood. Changes in the physical state of wood were examined during multiple tensile load-unload cycles based on the eigenvalue distribution of the near-infrared spectra. The set of eigenvalues H = {λ1, λ2, …, λ n }, calculated from the spectral matrix successively acquired during the cycling test, was treated as the Hamiltonian, which represents the energy eigenstate of the wood. Using statistical physics and random matrix theory, the variation in the physical state of wood was discussed from both macroscopic and microscopic perspectives. Unlike traditional methods, the energy state of wood can be followed in real time during cyclic loading; in other words, the Helmholtz free energy and Shannon entropy varied with load changes. The commutator, defined by the density and diagonal matrix of H, could be used to quantitatively evaluate the irreversible changes in wood during the cyclic processes. The proposed method is independent of a specific coordinate system, and can therefore be applied using a wide variety of chemical information other than that obtained from the near-infrared spectra.