Modelling of soft fiber-reinforced bending actuators through transfer learning from a machine learning algorithm trained from FEM data

Ye, Yongkai; Scharff, Rob B.N.; Long, Sifang; Han, Chaoyue; Du, Dongdong

doi:10.1016/j.sna.2024.115095

Sensors and Actuators A: Physical

2024

DOI: 10.1016/j.sna.2024.115095

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Modelling of soft fiber-reinforced bending actuators through transfer learning from a machine learning algorithm trained from FEM data

Yongkai Ye,

Rob B.N. Scharff,

Sifang Long

et al.

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2024

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Cited by 3 publications

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Investigation and optimization of energy absorption performance of axially joined metal and composite foam-filled hybrid tubes

Meriç,

Gedikli

2024

J Braz. Soc. Mech. Sci. Eng.

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Hybrid structures attract attention because they eliminate the disadvantages of composite and metal materials and have many potential applications. In this study, the energy absorption performances of single, double and triple hybrid tubes formed from different materials as metal/metal and metal/composite were examined experimentally and numerically. The hybrid tubes were lled with ve different functional aluminum foams of different densities to improve their energy-absorbing performance. Multi-objective optimization (MOO) studies were carried out to obtain the highest speci c energy absorption (SEA) and the lowest peak force con guration for each of the single, double and triple hybrid tubes. In MOO studies, functional foam densities (500-1500 kg/m 3 ) and wall thicknesses (1-4 mm) were optimized by genetic algorithm. As a result, absorbed energy (AE) and SEA values of hybrid tubes with optimum foam densities and wall thicknesses increased.

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Investigation and optimization of energy absorption performance of axially joined metal and composite foam-filled hybrid tubes

Meriç,

Gedikli

2024

J Braz. Soc. Mech. Sci. Eng.

View full text Add to dashboard Cite

show abstract

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Ye,

Han,

Kang

et al. 2024

Computers and Electronics in Agriculture

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Wang,

Zhang,

Liu

et al. 2024

Soft Robotics

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Modelling of soft fiber-reinforced bending actuators through transfer learning from a machine learning algorithm trained from FEM data

Cited by 3 publications

References 30 publications

Investigation and optimization of energy absorption performance of axially joined metal and composite foam-filled hybrid tubes

Investigation and optimization of energy absorption performance of axially joined metal and composite foam-filled hybrid tubes

Development of a novel variable-curvature soft gripper used for orientating broccoli in the trimming line

Toward Damage-Less Robotic Fragile Fruit Grasping: A Closed-Loop Force Control Method for Pneumatic-Driven Soft Gripper

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