Isothermal forging stands as an effective technology for the production of large-scale titanium alloy multi-rib components.However,challenges have persisted,including die underfilling and strain concentration due to t...Isothermal forging stands as an effective technology for the production of large-scale titanium alloy multi-rib components.However,challenges have persisted,including die underfilling and strain concentration due to the complex material flow and heterogeneous deformation within the forging die cavity.While approaches centered on optimized billet designs have mitigated these challenges,uncertainties in process parameters continue to introduce unacceptable variations in forming accuracy and stability.To tackle this issue,this study introduced a multi-objective robust optimization approach for billet design,accounting for the multi-rib eigenstructure and potential uncertainties.The approach includes finite element(FE)modeling for analyzing the die-filling and strain inhomogeneity within the multi-rib eigenstructure.Furthermore,it integrated image acquisition perception and feed back technologies(IAPF)for real-time monitoring of material flow and filling sequences within die rib-grooves,validating the accuracy of the FE modeling.By incorporating dimensional parameters of the billet and uncertainty factors,including friction,draft angle,forming temperature,speed,and deviations in billet and die,quantitative analyses on the rib-groove filling and strain inhomogeneity with fluctuation were conducted.Subsequently,a dual-response surface model was developed for statistical analysis of the cavity filling and strain homogeneity.Finally,the robust optimization was processed using a non-dominated sorting genetic algorithm II(NSGA-II)and validated using the IAPF technologies.The proposed approach enables robust design enhancements for rib-groove filling and strain homogeneity in titanium alloy multi-rib components.展开更多
基金Supported by National Natural Science Foundation of China(Grant No.52005241)Jiangxi Provincial Natural Science Foundation(Grant Nos.20232BAB204050,20224BAB204045)China Scholarship Council(Grant No.202208360107).
文摘Isothermal forging stands as an effective technology for the production of large-scale titanium alloy multi-rib components.However,challenges have persisted,including die underfilling and strain concentration due to the complex material flow and heterogeneous deformation within the forging die cavity.While approaches centered on optimized billet designs have mitigated these challenges,uncertainties in process parameters continue to introduce unacceptable variations in forming accuracy and stability.To tackle this issue,this study introduced a multi-objective robust optimization approach for billet design,accounting for the multi-rib eigenstructure and potential uncertainties.The approach includes finite element(FE)modeling for analyzing the die-filling and strain inhomogeneity within the multi-rib eigenstructure.Furthermore,it integrated image acquisition perception and feed back technologies(IAPF)for real-time monitoring of material flow and filling sequences within die rib-grooves,validating the accuracy of the FE modeling.By incorporating dimensional parameters of the billet and uncertainty factors,including friction,draft angle,forming temperature,speed,and deviations in billet and die,quantitative analyses on the rib-groove filling and strain inhomogeneity with fluctuation were conducted.Subsequently,a dual-response surface model was developed for statistical analysis of the cavity filling and strain homogeneity.Finally,the robust optimization was processed using a non-dominated sorting genetic algorithm II(NSGA-II)and validated using the IAPF technologies.The proposed approach enables robust design enhancements for rib-groove filling and strain homogeneity in titanium alloy multi-rib components.
