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Technical Brief

An Evolutionary Soft-Add Topology Optimization Method for Synthesis of Compliant Mechanisms With Maximum Output Displacement

[+] Author and Article Information
Chih-Hsing Liu

Department of Mechanical Engineering,
National Cheng Kung University,
Tainan 701, Taiwan
e-mail: chliu@mail.ncku.edu.tw

Guo-Feng Huang, Ta-Lun Chen

Department of Mechanical Engineering,
National Cheng Kung University,
Tainan 701, Taiwan

Manuscript received November 5, 2016; final manuscript received April 29, 2017; published online June 22, 2017. Assoc. Editor: Larry L. Howell.

J. Mechanisms Robotics 9(5), 054502 (Jun 22, 2017) (12 pages) Paper No: JMR-16-1343; doi: 10.1115/1.4037000 History: Received November 05, 2016; Revised April 29, 2017

This paper presents an evolutionary soft-add topology optimization method for synthesis of compliant mechanisms. Unlike the traditional hard-kill or soft-kill approaches, a soft-add scheme is proposed in this study where the elements are equivalent to be numerically added into the analysis domain through the proposed approach. The objective function in this study is to maximize the output displacement of the analyzed compliant mechanism. Three numerical examples are provided to demonstrate the effectiveness of the proposed method. The results show that the optimal topologies of the analyzed compliant mechanisms are in good agreement with previous studies. In addition, the computational time can be greatly reduced by using the proposed soft-add method in the analysis cases. As the target volume fraction in topology optimization for the analyzed compliant mechanism is usually below 30% of the design domain, the traditional methods which remove unnecessary elements from 100% turn into inefficient. The effect of spring stiffness on the optimized topology has also been investigated. It shows that higher stiffness values of the springs can obtain a clearer layout and minimize the one-node hinge problem for two-dimensional cases. The effect of spring stiffness is not significant for the three-dimensional case.

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Figures

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Fig. 1

Load scheme and its equivalent load cases

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Fig. 2

Analysis domain of the 2D force–displacement inverter mechanism

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Fig. 3

Objective function ratio and volume fraction versus iteration number for the 2D inverter mechanism

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Fig. 4

Optimized topologies at specific iterations for the 2D inverter mechanism

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Fig. 5

The effect of spring stiffness on optimized topology for the 2D inverter mechanism

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Fig. 6

Analysis domain of the 2D crunching mechanism

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Fig. 7

Objective function ratio and volume fraction versus iterations for the 2D crunching mechanism

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Fig. 8

Optimized topologies at specific iterations for the 2D crunching mechanism

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Fig. 9

The effect of spring stiffness on optimized topology for the 2D crunching mechanism

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Fig. 10

Analysis domain of the 3D inverter mechanism

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Fig. 11

Objective function ratio and volume fraction versus iterations for the 3D inverter mechanism

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Fig. 12

Optimized topologies at specific iterations for the 3D inverter mechanism

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Fig. 13

The effect of spring stiffness on optimized topology for the 3D inverter mechanism: (a) input = output = 105 N/m, (b) input = output = 107 N/m, and (c) input = output = 1012 N/m

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