The incorporation of rare earth oxides and nano-silica has been found to significantly enhance the mechanical and tribological characteristics of phenolic-based hybrid nanocomposites. In this work, the impact of these additives was investigated through single-factor experiments. The study revealed that cerium oxide and yttrium oxide were the primary factors influencing changes in the impact strength, shear strength, coefficient of friction, and wear rate. Additionally, the content of nano-silica exerted the most substantial influence on the hardness and compressive strength of the specimens. Furthermore, the material ratios of the phenolic-based hybrid nanocomposites were optimized using an orthogonal experimental design and a fuzzy comprehensive evaluation method. The optimal material ratio for these nanocomposites was determined to be 2% cerium oxide, 2.5% yttrium oxide, and 3% nano-silica, based on their mechanical, frictional, and wear properties. This research provides valuable insights for the development of new brake friction materials with low friction and high wear resistance and contributes to meeting the demand for polymer composites with superior mechanical performance in diverse applications.

Numerical simulation is a vital tool in the development of FeCrAl alloy cladding tubes, with its reliability closely tied to the predictive accuracy of the thermal deformation constitutive model used. In this study, hot compression tests on 0Cr23Al5 alloy were conducted using a Gleeble-3800 thermal compression testing machine (Dynamic Systems Inc., located in Albany, NY, USA), across a temperature range of 850–1050 °C and a strain rate range of 0.1–10 s⁻¹. Based on the data obtained, both the Arrhenius constitutive model and the artificial neural network (ANN) model were developed. The ANN model demonstrated significantly superior predictive accuracy, with an average absolute relative error (AARE) of only 0.70% and a root mean square error (RMSE) of 1.99 MPa, compared to the Arrhenius model (AARE of 4.30% and RMSE of 14.47 MPa). Further validation via the VUHARD user subroutine in ABAQUS revealed that the ANN model has good applicability and reliability in numerical simulations, with its predicted flow stress showing high consistency with the experimental data. The ANN model developed in this study can effectively predict the rheological stress of FeCrAl alloys during hot deformation. It provides methodological support for high-fidelity constitutive modeling of the flow stress of FeCrAl alloys and offers a reliable constitutive model for simulating the thermomechanical load response behavior of FeCrAl alloys.