TY - GEN
T1 - A NOVEL OBJECTIVE FUNCTION FOR THE INVERSE PROBLEM OF SIMULTANEOUS IDENTIFICATION OF UNKNOWN YOUNGS MODULUS AND BOUNDARY CONDITIONS WITH NOISY AND PARTIAL OBSERVATION
AU - Xu, Tian
AU - Du, Shilun
AU - Li, Murong
AU - Hu, Yingda
AU - Wang, Zhen
AU - Lei, Yong
N1 - Publisher Copyright:
Copyright © 2022 by ASME.
PY - 2022
Y1 - 2022
N2 - The biomechanical models of the surgical navigation systems need patient-specific elastic properties and boundary conditions to calculate the deformation of soft tissues. However, these information cannot be directly obtained in a real endoscopic surgical scenarios. Many studies have been carried out focusing on identification of unknown elastic parameters and boundary conditions. But they rarely estimate these unknown parameters together. For the convergence of unknown parameters with observation error, some methods add regularization terms to the objective functions which are complex and sometimes rely on experience. In this paper, a novel objective function based on the gradient of displacement field is proposed, which can ensure the convergence of unknown Young's modulus and boundary conditions without additional regularization terms. A"two field"construction method, which can convert this ill-posed inverse problem to two well-posed problems, is introduced to construct this objective function. The sensitivity analysis is conducted based on approximate differential method and the Gauss-Newton (GN) method is applied to minimize the objective function and update unknown parameters. The proposed objective function is compared with a few classical objective functions in a series of numerical experiments based on the linear elastic finite element model. The results of numerical experiments show the advantages and feasibility of the proposed objective function.
AB - The biomechanical models of the surgical navigation systems need patient-specific elastic properties and boundary conditions to calculate the deformation of soft tissues. However, these information cannot be directly obtained in a real endoscopic surgical scenarios. Many studies have been carried out focusing on identification of unknown elastic parameters and boundary conditions. But they rarely estimate these unknown parameters together. For the convergence of unknown parameters with observation error, some methods add regularization terms to the objective functions which are complex and sometimes rely on experience. In this paper, a novel objective function based on the gradient of displacement field is proposed, which can ensure the convergence of unknown Young's modulus and boundary conditions without additional regularization terms. A"two field"construction method, which can convert this ill-posed inverse problem to two well-posed problems, is introduced to construct this objective function. The sensitivity analysis is conducted based on approximate differential method and the Gauss-Newton (GN) method is applied to minimize the objective function and update unknown parameters. The proposed objective function is compared with a few classical objective functions in a series of numerical experiments based on the linear elastic finite element model. The results of numerical experiments show the advantages and feasibility of the proposed objective function.
KW - finite element method
KW - inverse problem
KW - material parameters
KW - unknown boundary conditions
UR - https://www.scopus.com/pages/publications/85140893012
U2 - 10.1115/MSEC2022-85516
DO - 10.1115/MSEC2022-85516
M3 - 会议稿件
AN - SCOPUS:85140893012
T3 - Proceedings of ASME 2022 17th International Manufacturing Science and Engineering Conference, MSEC 2022
BT - Additive Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation; Nano/Micro/Meso Manufacturing
PB - American Society of Mechanical Engineers
T2 - ASME 2022 17th International Manufacturing Science and Engineering Conference, MSEC 2022
Y2 - 27 June 2022 through 1 July 2022
ER -