Open AccessA New Conjugate Gradient Method and Application to Dynamic Load Identification Problems
Author(s) -
Lin J. Wang,
Xiang Gao,
You Xie,
Jun J. Fu,
Yongle Du
Publication year - 2021
Language(s) - English
DOI - 10.20855/ijav.2021.26.21746
Subject(s) - conjugate gradient method , convergence (economics) , gradient descent , regularization (linguistics) , airfoil , mathematical optimization , algorithm , gradient method , computer science , mathematics , artificial neural network , structural engineering , engineering , artificial intelligence , economics , economic growth
In this paper, a modified conjugate gradient (MCG) algorithm is proposed for solving the force reconstruction problems in practical engineering. This new method is derived from a stable regularization operator and is also strictly proved using the mathematical theory. Moreover, we also prove the sufficient descent and global convergence characteristic of the newly developed algorithm. Finally, the proposed algorithm is applied to force reconstruction for the airfoil structure and composite laminated cylindrical shell. Numerical simulations show that the proposed method is highly efficient and has robust convergence performances. Additionally, the accuracy of the proposed algorithm in identifying the expected loads is satisfactory and acceptable in practical engineering.