TY - GEN
T1 - Damage identification using static and dynamic responses based on topology optimization and lasso regularization
AU - Sugai, Ryo
AU - Saito, Akira
AU - Saomoto, Hidetaka
N1 - Funding Information:
This project was supported in part by Japan Society for the Promotion of Science (JSPS), Grant-in-Aid for Scientific Research(C), grant number 20K11855. The support of JSPS is gratefully acknowledged.
PY - 2020
Y1 - 2020
N2 - This paper presents a damage identification method based on topology optimization and Lasso regularization. The method uses static displacements or dynamic responses to identify damages of structures. The method has the potential to identify damages with high fidelity, in comparison with ordinary damage identification method based on optimization with parameterized geometry of the damages. However, it is difficult to precisely detect damage using topology optimization due mostly to the large number of design variables. Therefore, supposing that the damage is sufficiently small, we propose a method adding Lasso regularization to the objective functions to suppress active design variables during topology optimization process. To verify the effectiveness of the proposed method, we conducted a set of numerical experiments for static and dynamic problems. We have succeeded in suppressing active design variables and delete artificially generated damages and the location and shape of damage have been precisely identified.
AB - This paper presents a damage identification method based on topology optimization and Lasso regularization. The method uses static displacements or dynamic responses to identify damages of structures. The method has the potential to identify damages with high fidelity, in comparison with ordinary damage identification method based on optimization with parameterized geometry of the damages. However, it is difficult to precisely detect damage using topology optimization due mostly to the large number of design variables. Therefore, supposing that the damage is sufficiently small, we propose a method adding Lasso regularization to the objective functions to suppress active design variables during topology optimization process. To verify the effectiveness of the proposed method, we conducted a set of numerical experiments for static and dynamic problems. We have succeeded in suppressing active design variables and delete artificially generated damages and the location and shape of damage have been precisely identified.
UR - http://www.scopus.com/inward/record.url?scp=85096193001&partnerID=8YFLogxK
U2 - 10.1115/DETC2020-22279
DO - 10.1115/DETC2020-22279
M3 - Conference contribution
AN - SCOPUS:85096193001
T3 - Proceedings of the ASME Design Engineering Technical Conference
BT - 32nd Conference on Mechanical Vibration and Noise (VIB)
PB - American Society of Mechanical Engineers (ASME)
T2 - ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2020
Y2 - 17 August 2020 through 19 August 2020
ER -