Data driven multi-fidelity approximate modeling optimization of stiffened conical shell for large launch vehicle
CHEN Chaolei
WANG Zhixiang
LEI Yongjun
WANG Jie
Abstract：In order to improve the load-bearing efficiency of the stiffened conical shell in large launch vehicle,the lightweight design of the stiffened conical shell was carried out via a data-driven multi-fidelity approximate modeling optimization method.Aiming at the problems such as low efficiency and insufficient accuracy of the single fidelity approximate modeling optimization method,a data-driven multi-fidelity approximate modeling optimization framework was built based on variable-fidelity expected improvement(VF-EI)point criterion,and accordingly the optimization design of stiffened conical shell structure was carried out.Based on the finite element models of stiffened conical shells with different mesh sizes,a Co-Kriging multi-fidelity approximate model for the collapse load of stiffened conical shells was established.In the optimization iteration,multi-fidelity sampling points were generated by using VF-EI point criterion,and the global and local approximation accuracy of Co-Kriging multi-fidelity approximation model was improved sequently.Moreover,the optimization efficiency and accuracy of the proposed method were demonstrated by comparing with radial basis function approximation model and Kriging model.Besides,11.5%weight reduction of the optimized stiffened conical shell structure is obtained compared with the initial design,which has certain engineering application value.
Keywords：Stiffened conical shellMulti-fidelity approximate modelingSequence approximate optimization methodLightweight designVF-EI point criterion
Publication Date：2025-04-15
Online Publishing Date：2026-09-12(First online date of this platform, not the publication date of the document)
Pages：10( 148-157 )