Fengpeng Yang
6 Papers
2 Citations
Fengpeng Yang is an academic researcher. The author has contributed to research in topics: Computer science & Engineering. The author has an hindex of 2, co-authored 6 publications.
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Papers
Origami dynamics based soft piezoelectric energy harvester for machine learning assisted self-powered gait biometric identification
TL;DR: In this paper , a pedal self-powered gait sensor is developed with energy harvesting technology, which can transform the motion of human walking to biometric information, and the features of the voltage signals output by the generator are extracted and input into the neural network for training and testing.
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Bio-inspired programmable multi-stable origami
TL;DR: In this paper , a programmable path to multi-stability of the Kresling origami by introducing bio-inspired nonlinear creases is presented, where position of stable equilibria can be programmable by varying free-stress dihedral angle of the crease.
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Bistable programmable origami based soft electricity generator with inter-well modulation
Cenling Huang,Ting Tan,Zhemin Wang,Xiaochun Nie,Shimin Zhang,Fengpeng Yang,Zhiliang Lin,Benlong Wang,Zhimiao Yan +8 more
TL;DR: In this paper , a soft bistable electricity generator is developed based on Kresling origami, which is capable of initiating inter-well motion for broadband energy harvesting at low frequency and low amplitude excitation based on delicately designed structural parameters.
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A new approach to solve the anti-plane crack problems by the method of fundamental solutions
TL;DR: In this article , a conformal mapping technique was proposed to solve the anti-plane crack problems without using the domain decomposition technique and/or the crack Green's function, which can be applied for many antiplane elastic problems with the simple concept and easy numerical implementation.
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The method of fundamental solutions for analytic functions in complex analysis
TL;DR: In this article , a conformal mapping technique is applied to introduce the singularities of the approximate analytic functions and reconstruct the fundamental solutions, which can be used to solve the boundary value problems of analytic functions without considering single-valuedness, which simplify the numerical analysis.
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