Trial Production of Heavy-Duty Metal Rubber Based on Predictive Model of Relative Density Mechanics

Abstract:

The predictive model and design of heavy-duty metal rubber shock absorber for the powertrains of heavy-load mining vehicles were investigated. The microstructural characteristics of the wire mesh were elucidated using fractal graphs. A numerical model based on virtual fabrication technique was established to propose a design scheme for the wire mesh component. Four sets of wire mesh shock absorbers with various relative densities were prepared and a predictive model based on these relative densities was established through mechanical testing. To further enhance the predictive accuracy, a variable transposition fitting method was proposed to refine the model. Residual analysis was employed to quantitatively validate the results against those obtained from an experimental control group. The results show that the improved model exhibits higher predictive accuracy than the original model, with the determination coefficient (R²) of 0.9624. This study provides theoretical support for designing wire mesh shock absorbers with reduced testing requirements and enhanced design efficiency.