Parameter optimization of particle-reinforced adhesive bonded joints based on the response surface method

Abstract

We investigated the effects of process parameters on the quality of alumina-reinforced adhesive bonded joints. Single-lap joints of 1.5-mm-thick aluminum alloy 5182 sheets were prepared by adhesive bonding with particulate composite adhesive. The multivariate regression models between process parameters (particle size, adhesive layer thickness, and mass fraction) and response values (failure load, energy absorption value) were established, and the models were verified by experiments. The adhesive layer was modeled using the ABAQUS CPS4R mesh element. The representative volume element (RVE) model was then established to simulate the failure of adhesively bonded joints during tensile tests. The findings indicate that particle size has the biggest impact on the failure load of the joints, and particle mass fraction has the highest influence on the energy absorption value of the joints. The optimum process parameters ranges are: particle size of 0.046 mm, adhesive layer thickness of 0.6 mm, and mass fraction of 5%. As per finite element analysis, the failure load and tensile modulus of the adhesive layer decrease as particle size and particle volume fraction increase.