Dynamic Topology Optimization of Rubber Rollers Based on the CNN-SIMP Hybrid Algorithm

MENG Luyao; RAO Jianping; TU Juncheng; ZHANG Yuhao; GAO Zhenqing

doi:10.19554/j.cnki.1001-3563.2026.09.027

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Packaging Engineering ›› 2026, Vol. 47 ›› Issue (9) : 255-266. DOI: 10.19554/j.cnki.1001-3563.2026.09.027

Automatic and Intelligent Technology

Dynamic Topology Optimization of Rubber Rollers Based on the CNN-SIMP Hybrid Algorithm

MENG Luyao¹, RAO Jianping², TU Juncheng^1,*, ZHANG Yuhao¹, GAO Zhenqing¹

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Abstract

To address the vibration suppression and lightweight design requirements of rubber rollers in printing equipment under high-speed dynamic operating conditions, the work aims to propose a CNN-SIMP hybrid topology optimization method, in which a convolutional neural network surrogate model is employed to replace repeated finite element iterations and thus enable rapid dynamic-response-driven design. A dynamic topology optimization model was established by maximizing the weighted enhancement of the 4^th-6^th natural frequencies while constraining the maximum equivalent stress under harmonic loading and the prescribed volume fraction. During the optimization process, the three-dimensional density field was circumferentially projected into a 64×64 two-dimensional equivalent density map, based on which a CNN surrogate model was constructed to rapidly predict modal frequencies and stress responses. Then, periodic three-dimensional finite element recalculations were further introduced to suppress error accumulation. The optimized roller achieved a mass reduction of 7.398%, a decrease of 28.59% in maximum equivalent stress, and a reduction of 67.15% in maximum total deformation. Compared with the conventional SIMP method, the proposed method improved computational efficiency by a factor of 6.2, while the optimized structure maintained good consistency in major load-transfer paths and dynamic response characteristics. The proposed CNN-SIMP hybrid algorithm can significantly improve the efficiency of dynamic topology optimization while ensuring the rationality of the optimization results, and it provides an effective approach for the lightweight and low-vibration design of key rotating components in printing equipment.

Key words

topology optimization / solid isotropic material with penalization (SIMP) / convolutional neural network (CNN) / dynamic response / lightweight design

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MENG Luyao, RAO Jianping, TU Juncheng, ZHANG Yuhao, GAO Zhenqing. Dynamic Topology Optimization of Rubber Rollers Based on the CNN-SIMP Hybrid Algorithm[J]. Packaging Engineering. 2026, 47(9): 255-266 https://doi.org/10.19554/j.cnki.1001-3563.2026.09.027

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