Finite Element Simulation of Flexible Roll Forming with Supplemented Material Data and the Experimental Verification

Flexible roll forming is a promising manufacturing method for the production of variable cross section products. Considering the large plastic strain in this forming process which is much larger than that of uniform deformation phase of uniaxial tensile test, the widely adopted method of simulating the forming processes with non-supplemented material data from uniaxial tensile test will certainly lead to large error. To reduce this error, the material data is supplemented based on three constitutive models. Then a finite element model of a six passes flexible roll forming process is established based on the supplemented material data and the original material data from the uniaxial tensile test. The flexible roll forming experiment of a B pillar reinforcing plate is carried out to verify the proposed method. Final cross section shapes of the experimental and the simulated results are compared. It is shown that the simulation calculated with supplemented material data based on Swift model agrees well with the experimental results, while the simulation based on original material data could not predict the actual deformation accurately. The results indicate that this material supplement method is reliable and indispensible, and the simulation model can well reflect the real metal forming process. Detailed analysis of the distribution and history of plastic strain at different positions are performed. A new material data supplement method is proposed to tackle the problem which is ignored in other roll forming simulations, and thus the forming process simulation accuracy can be greatly improved.

Mathematical model for abrasive suspension jet cutting based on orthogonal test design

This paper describes the application of orthogonal test design coupled with non-linear regression analysis to optimize abrasive suspension jet （AS J） cutting process and construct its cutting model. Orthogonal test design is applied to cutting stainless steel. Through range analysis on experiment results, the optimal process conditions for the cutting depth and the kerr ratio of the bottom width to the top width can be determined. In addition, the analysis of ranges and variances are all employed to identify various factors： traverse rate, working pressure, nozzle diameter, standoff distance which denote the importance order of the cutting parameters affecting cutting depth and the kerf ratio of the bottom width to the top width. ~rthermore, non-linear regression analysis is used to establish the mathematical models of the cutting parameters based on the cutting depth and the kerr ratio. Finally, the verification experiments of cutting parameters＇ effect on cutting performance, which show that optimized cutting parameters and cutting model can significantly improve the prediction of the cutting ability and quality of ASJ.