Mr. Maxim Gokova Profile

Maxim Gokova

at DTU

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Proceedings Article | 9 May 2024 Presentation + Paper

Unveiling design criteria of hollow fibers dielectric elastomer actuators: a computational and experimental study

Sina Jafarzadeh, Maxim Gökova, Zhaoqing Kang, Liyun Yu, Anne Ladegaard Skov

Proceedings Volume 12945, 129450O (2024) https://doi.org/10.1117/12.3010130

KEYWORDS: Dielectric elastomer actuators, Silicon, Dielectrics, Electrodes, Design, Deformation, Robots, Simulations, Robotics

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Dielectric elastomer actuators (DEAs) have been proclaimed as a transformative technology with applications spanning from robotics to biomedical devices. They are especially appealing because of their key characteristics, including low weight and lifetime. However, there are still challenges in tuning these actuators for desirable mechanical performance. Here, we examine the effects of geometry and material characteristics like inner diameter and Young's modulus on the performance of hollow fiber dielectric elastomer actuators (HFDEAs). These parameters were chosen because they are amenable to experimental validation and play a straightforward, yet significant, role in DEA performance. The model's parameters are based on experimental data, giving our computational simulations a solid foundation. The study takes into consideration the electro-mechanical coupling using finite element method (FEM) simulations in COMSOL Multiphysics. While the electrodes' attraction to one another results in length expansion, the results suggest that the larger surface charge density on the internal electrode compared to the inner one in hollow fiber DEAs results in radial expansion as well. This model also provides an estimation on the actuator holding force which is challenging to evaluate experimentally. According to preliminary results, careful parameter selection can indeed increase the holding force, thereby enhancing the actuator's overall effectiveness. In conclusion, this study provides an understanding of design parameters of HFDEA offering a comprehensive framework for HFDEA design by integrating both experimental and computational approaches.

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