The Property Parameters Research And Geometry Optimization Of The Bimetal Bonding Structure

Adhesive structures are widely used in the machinery manufacturing,aerospace and the other fields.Optimizing their bonding performance can improve the mechanical strength and bearing capacity of the aerospace and mechanical equipment.This article takes the double cantilever beam bonding structures and the lap joints as the research objects.We mainly study its performance factors and size optimization.First of all,keeping the maximum value of interface stress and the fracture energy of the bonding member at the complete failure unchanged.Based on the energy point of view,the relationship between the shape parameters of the bonding interface different cohesion models are studied,which provides a theoretical basis for the setting of the interface parameters in the subsequent finite element simulation of the bonding structures.Secondly,The influence of changes in parameters such as geometric dimensions on the bearing capacity of bonded components is analyzed.We have obtained the effect of different influencing factors on its bonding performance.Finally,based on the above research,we take the simulation results of the bonded structures as the sample points to optimize their geometrical dimensions.It gives a design solution with the optimal bearing capacity and tensile and shear strength of the bonded structures and improves the service life of the bonding equipments.The main research contents of this article are as follows:1.The different shape cohesion models such as exponential,polynomial,trilinear and bilinear are used to characterize the mechanical properties of the bonding interface.By keeping the interface fracture energy and the maximum stress constant,we derived the relationship between the shape parameters of each model based on the tension-displacement relationship.Among them,the interface shape parameters of any two cohesive models can be expressed with each other.2.Based on the particle swarm optimization and genetic algorithm,the tangential and normal interface performance parameters of aluminum alloy bonding structures are identified.Taking the shape parameters of exponential model as the reference,the relative errors of the polynomial,three-line and bilinear model normal shape parameter inversion recognition and prediction values are 1.76%,1.54% and 3.13%.The relative errors between the inversion recognition and prediction of the tangential shape parameters are 2.84%,4.83% and 3.55%.The error is small,which verifies the accuracy of the derived relationship.3.In order to optimize the performance of the bonding structures in the future,the influence of the change of the geometry of the bonding structur on its bonding performance was analyzed.For the double cantilever beam bonding structure,when the bonding layer is thin,increasing the thickness of the steel plate and the thickness of the bonding layer can improve the bonding strength of the bonding structures.After the thickness of the adhesive layer reaches a certain value,the adhesive performance does not change significantly.In the processing of design,we should focus on eliminating the possible cracks.The dangerous point of the lap joint is the end of the joint.Within a certain range,appropriately increasing the thickness of the aluminum alloy plate,the overlap length and the thickness of the adhesive layer can improve the bonding performance of the overlap joint.Too thick adhesive will reduce the connection efficiency of the lap joint.4.Taking the thickness of the adhesive layer of the bonding structures,the overlap length,the thickness of the aluminum alloy plates,the maximum stress,the thickness of the steel plates and the critical opening displacement as the design variables,the finite element simulation results from the previous chapter were used as orthogonal sample points.Based on the multi-objective genetic algorithm of the isight platform,this paper optimizes the geometric size of the bonding structures.It gives the optimal design solution of the bonding structures with the best connection efficiency and carrying capacity.