This study used a mechanochemical method to analyze the recycling mechanism of polyurethane foam and optimize the recycling process. The use of mechanochemical methods to regenerate the polyurethane foam powder breaks the C–O bond of the polyurethane foam and greatly enhances the activity of the powder. Based on orthogonal test design, the mesh, proportion, temperature, and time were selected to produce nine recycled boards by heat pressing. Then, the influence of four factors on the thermal conductivity and tensile strength of the recycled board was analyzed. The results show that 120 mesh polyurethane foam powder has strong activity, and the tensile strength can reach 9.913 Mpa when it is formed at 205 °C and 40 min with 50% PP powder. With the help of the low thermal conductivity of the polyurethane foam, the thermal conductivity of the recycled board can reach 0.037 W/m·K at the parameter of 40 mesh, 80%, 185 °C, 30 min. This research provides an effective method for the recycling of polyurethane foam.

A recycling process of waste thermosetting polyurethane plastics was proposed based on the mechanochemical method, aiming at the three-dimensional network cross-linking structure of thermosetting polyurethane. Orthogonal experimental design was adopted to select three factors of crushing speed, crushing time, and feed amount to determine the best crushing parameters. Then, the waste polyurethane insulation boards were crushed and degraded by the mechanism of regenerative forming with the adjustable speed test machine. Accordingly, the recycled powder was obtained. Finally, nine kinds of polyurethane recycled composite plates were prepared by hot pressing process. The degradation effect of thermosetting polyurethane was analyzed by Fourier transform infrared spectroscopy, scanning electron microscope, and X-ray diffraction. Moreover, the mechanical properties and thermal insulation properties of recycled composite plates were tested and analyzed. The results show that the network cross-linking molecular structure of waste thermosetting polyurethane plastics is destroyed by the effect of mechanochemical action, and methyl and aldehyde groups are decomposed. Therefore, a recycled powder with strong reactivity and plasticity is generated, which improves the activity regeneration ability. After adding thermoplastic resin, the mechanical properties and formability of recycled composite plates are enhanced, with maximum tensile strength up to 9.913 MPa. Correspondingly, the thermal insulation performance of plates is reduced. However, the minimum thermal conductivity can also reach 0.056 W/m·K. This study provides an effective method for the recycling of thermosetting polyurethane plastics.

The discrete element method (DEM) is commonly used to study various powders in motion during transportation, screening, mixing, etc.; this requires several microscopic parameters to characterize the complex mechanical behavior of the particles. Herein, a new discrete element parameter calibration method is proposed to calibrate the ultrafine agglomerated powder (recycled polyurethane powder). Optimal Latin hypercube sampling and virtual simulation experiments were conducted using the commercial DEM software; the microscopic variables included the static friction coefficient between the particles, collision recovery coefficient, Johnson–Kendall–Roberts surface energy, static friction coefficient between the particles and wall, and collision recovery coefficient. A predictive model based on genetic-algorithm-optimized feedforward neural network (back propagation) was developed to calibrate the microscopic DEM simulation parameters. The cycle search algorithm and mean-shift cluster analysis were used to confirm the input parameters’ range by comparing the mean value of the dynamic angle of repose measured via the batch accumulation test. These parameters were verified by the baffle lifting method and the rotating drum method. This calibration method, once successfully developed, will be suitable for use in a variety of fine viscous powder dynamic flow conditions.