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Afshin Taghvaeipour

Researcher at Amirkabir University of Technology

Publications -  26
Citations -  199

Afshin Taghvaeipour is an academic researcher from Amirkabir University of Technology. The author has contributed to research in topics: Finite element method & Parallel manipulator. The author has an hindex of 6, co-authored 18 publications receiving 121 citations. Previous affiliations of Afshin Taghvaeipour include Sharif University of Technology & McGill University.

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Optimum structural design of a two-limb Schönflies motion generator

TL;DR: In this article, the optimal dimensions of a two-limb Schonflies motion generator to maximize the overall stiffness of the robot structure is investigated. But the authors focus on the stiffness matrix of the two-legged robot and do not consider the sensitivity analysis of robot stiffness with respect to some design parameters.
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High-frequency robust position control of a nonlinear piezoelectric bending actuator:

TL;DR: Azoelectric bending actuators have been widely used in a variety of micro and nano-applications, including atomic force microscopy, micro assembly, cell manipulation, and in general, micro elect... as mentioned in this paper.
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Post-Yield characteristics of electrorheological fluids in nonlinear vibration analysis of smart sandwich panels

TL;DR: In this article, the nonlinear free vibration analysis of sandwich plates containing electrorheological fluid as the core layer has been studied, since yield stress of the ER fluid is relatively low.
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Elastodynamics of a two-limb Schönflies motion generator

TL;DR: In this article, the authors presented an elastodynamic analysis of a two-limb Schonflies motion generator for a pick-and-place operation with the first six natural frequencies.

Kinematic Reliability Analysis of 3-PSS manipulator based on the explicit solution and design of experiment method

TL;DR: This paper aims at the kinematic reliability analysis of the 3-PSS parallel robot and finds that the difference between the reliability values obtained by the design of experiments and the Monte Carlo Simulation methods is %4.7.