LIU, Wenchang ;WU, Chaohua ;CHEN, Xingan . An Eigenfrequency-Constrained Topology Optimization Method with Design Variable Reduction. Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 70, n.3-4, p. 159-169, december 2023. ISSN 0039-2480. Available at: <https://www.sv-jme.eu/article/an-eigenfrequency-constrained-topology-optimization-method-with-design-variable-reduction/>. Date accessed: 20 dec. 2024. doi:http://dx.doi.org/10.5545/sv-jme.2023.739.
Liu, W., Wu, C., & Chen, X. (2024). An Eigenfrequency-Constrained Topology Optimization Method with Design Variable Reduction. Strojniški vestnik - Journal of Mechanical Engineering, 70(3-4), 159-169. doi:http://dx.doi.org/10.5545/sv-jme.2023.739
@article{sv-jmesv-jme.2023.739,
author = {Wenchang Liu and Chaohua Wu and Xingan Chen},
title = {An Eigenfrequency-Constrained Topology Optimization Method with Design Variable Reduction},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {70},
number = {3-4},
year = {2024},
keywords = {Eigenfrequency constraint; topology optimization; bi-directional evolutionary structural optimization; design variable reduction; Lagrange multiplier method; },
abstract = {The dynamic response of structures heavily relies on eigenfrequency, so the optimization of eigenfrequency is valuable in various working conditions. The bi-directional evolutionary structural optimization (BESO) method has been widely applied due to its ability to eliminate grayscale elements. Based upon BESO, this paper introduces a topology optimization method that incorporates eigenfrequency constraints and reduces the number of design variables. In this method, the optimization objective was to minimize compliance. The Lagrange multiplier was used to introduce eigenfrequency constraints, allowing for coordinated control of compliance and eigenfrequency. To prevent oscillation during the optimization process, the sensitivity was normalized. Additionally, to achieve faster convergence, the variables were reduced after meeting volume constraints. The numerical examples demonstrate the effectiveness of this method in increasing the eigenfrequency of the structure and avoiding resonance.},
issn = {0039-2480}, pages = {159-169}, doi = {10.5545/sv-jme.2023.739},
url = {https://www.sv-jme.eu/article/an-eigenfrequency-constrained-topology-optimization-method-with-design-variable-reduction/}
}
Liu, W.,Wu, C.,Chen, X. 2024 December 70. An Eigenfrequency-Constrained Topology Optimization Method with Design Variable Reduction. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 70:3-4
%A Liu, Wenchang %A Wu, Chaohua %A Chen, Xingan %D 2024 %T An Eigenfrequency-Constrained Topology Optimization Method with Design Variable Reduction %B 2024 %9 Eigenfrequency constraint; topology optimization; bi-directional evolutionary structural optimization; design variable reduction; Lagrange multiplier method; %! An Eigenfrequency-Constrained Topology Optimization Method with Design Variable Reduction %K Eigenfrequency constraint; topology optimization; bi-directional evolutionary structural optimization; design variable reduction; Lagrange multiplier method; %X The dynamic response of structures heavily relies on eigenfrequency, so the optimization of eigenfrequency is valuable in various working conditions. The bi-directional evolutionary structural optimization (BESO) method has been widely applied due to its ability to eliminate grayscale elements. Based upon BESO, this paper introduces a topology optimization method that incorporates eigenfrequency constraints and reduces the number of design variables. In this method, the optimization objective was to minimize compliance. The Lagrange multiplier was used to introduce eigenfrequency constraints, allowing for coordinated control of compliance and eigenfrequency. To prevent oscillation during the optimization process, the sensitivity was normalized. Additionally, to achieve faster convergence, the variables were reduced after meeting volume constraints. The numerical examples demonstrate the effectiveness of this method in increasing the eigenfrequency of the structure and avoiding resonance. %U https://www.sv-jme.eu/article/an-eigenfrequency-constrained-topology-optimization-method-with-design-variable-reduction/ %0 Journal Article %R 10.5545/sv-jme.2023.739 %& 159 %P 11 %J Strojniški vestnik - Journal of Mechanical Engineering %V 70 %N 3-4 %@ 0039-2480 %8 2023-12-13 %7 2023-12-13
Liu, Wenchang, Chaohua Wu, & Xingan Chen. "An Eigenfrequency-Constrained Topology Optimization Method with Design Variable Reduction." Strojniški vestnik - Journal of Mechanical Engineering [Online], 70.3-4 (2024): 159-169. Web. 20 Dec. 2024
TY - JOUR AU - Liu, Wenchang AU - Wu, Chaohua AU - Chen, Xingan PY - 2024 TI - An Eigenfrequency-Constrained Topology Optimization Method with Design Variable Reduction JF - Strojniški vestnik - Journal of Mechanical Engineering DO - 10.5545/sv-jme.2023.739 KW - Eigenfrequency constraint; topology optimization; bi-directional evolutionary structural optimization; design variable reduction; Lagrange multiplier method; N2 - The dynamic response of structures heavily relies on eigenfrequency, so the optimization of eigenfrequency is valuable in various working conditions. The bi-directional evolutionary structural optimization (BESO) method has been widely applied due to its ability to eliminate grayscale elements. Based upon BESO, this paper introduces a topology optimization method that incorporates eigenfrequency constraints and reduces the number of design variables. In this method, the optimization objective was to minimize compliance. The Lagrange multiplier was used to introduce eigenfrequency constraints, allowing for coordinated control of compliance and eigenfrequency. To prevent oscillation during the optimization process, the sensitivity was normalized. Additionally, to achieve faster convergence, the variables were reduced after meeting volume constraints. The numerical examples demonstrate the effectiveness of this method in increasing the eigenfrequency of the structure and avoiding resonance. UR - https://www.sv-jme.eu/article/an-eigenfrequency-constrained-topology-optimization-method-with-design-variable-reduction/
@article{{sv-jme}{sv-jme.2023.739},
author = {Liu, W., Wu, C., Chen, X.},
title = {An Eigenfrequency-Constrained Topology Optimization Method with Design Variable Reduction},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {70},
number = {3-4},
year = {2024},
doi = {10.5545/sv-jme.2023.739},
url = {https://www.sv-jme.eu/article/an-eigenfrequency-constrained-topology-optimization-method-with-design-variable-reduction/}
}
TY - JOUR AU - Liu, Wenchang AU - Wu, Chaohua AU - Chen, Xingan PY - 2023/12/13 TI - An Eigenfrequency-Constrained Topology Optimization Method with Design Variable Reduction JF - Strojniški vestnik - Journal of Mechanical Engineering; Vol 70, No 3-4 (2024): Strojniški vestnik - Journal of Mechanical Engineering DO - 10.5545/sv-jme.2023.739 KW - Eigenfrequency constraint, topology optimization, bi-directional evolutionary structural optimization, design variable reduction, Lagrange multiplier method, N2 - The dynamic response of structures heavily relies on eigenfrequency, so the optimization of eigenfrequency is valuable in various working conditions. The bi-directional evolutionary structural optimization (BESO) method has been widely applied due to its ability to eliminate grayscale elements. Based upon BESO, this paper introduces a topology optimization method that incorporates eigenfrequency constraints and reduces the number of design variables. In this method, the optimization objective was to minimize compliance. The Lagrange multiplier was used to introduce eigenfrequency constraints, allowing for coordinated control of compliance and eigenfrequency. To prevent oscillation during the optimization process, the sensitivity was normalized. Additionally, to achieve faster convergence, the variables were reduced after meeting volume constraints. The numerical examples demonstrate the effectiveness of this method in increasing the eigenfrequency of the structure and avoiding resonance. UR - https://www.sv-jme.eu/article/an-eigenfrequency-constrained-topology-optimization-method-with-design-variable-reduction/
Liu, Wenchang, Wu, Chaohua, AND Chen, Xingan. "An Eigenfrequency-Constrained Topology Optimization Method with Design Variable Reduction" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 70 Number 3-4 (13 December 2023)
Strojniški vestnik - Journal of Mechanical Engineering 70(2024)3-4, 159-169
© The Authors 2024. CC BY 4.0 Int.
The dynamic response of structures heavily relies on eigenfrequency, so the optimization of eigenfrequency is valuable in various working conditions. The bi-directional evolutionary structural optimization (BESO) method has been widely applied due to its ability to eliminate grayscale elements. Based upon BESO, this paper introduces a topology optimization method that incorporates eigenfrequency constraints and reduces the number of design variables. In this method, the optimization objective was to minimize compliance. The Lagrange multiplier was used to introduce eigenfrequency constraints, allowing for coordinated control of compliance and eigenfrequency. To prevent oscillation during the optimization process, the sensitivity was normalized. Additionally, to achieve faster convergence, the variables were reduced after meeting volume constraints. The numerical examples demonstrate the effectiveness of this method in increasing the eigenfrequency of the structure and avoiding resonance.