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

    Source: Journal of Mechanisms and Robotics:;2017:;volume( 009 ):;issue: 005::page 54502
    Author:
    Liu, Chih-Hsing
    ,
    Huang, Guo-Feng
    ,
    Chen, Ta-Lun
    DOI: 10.1115/1.4037000
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: 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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      An Evolutionary Soft-Add Topology Optimization Method for Synthesis of Compliant Mechanisms With Maximum Output Displacement

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4235150
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    contributor authorLiu, Chih-Hsing
    contributor authorHuang, Guo-Feng
    contributor authorChen, Ta-Lun
    date accessioned2017-11-25T07:18:22Z
    date available2017-11-25T07:18:22Z
    date copyright2017/22/6
    date issued2017
    identifier issn1942-4302
    identifier otherjmr_009_05_054502.pdf
    identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4235150
    description abstractThis 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.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleAn Evolutionary Soft-Add Topology Optimization Method for Synthesis of Compliant Mechanisms With Maximum Output Displacement
    typeJournal Paper
    journal volume9
    journal issue5
    journal titleJournal of Mechanisms and Robotics
    identifier doi10.1115/1.4037000
    journal fristpage54502
    journal lastpage054502-12
    treeJournal of Mechanisms and Robotics:;2017:;volume( 009 ):;issue: 005
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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