2015
DOI: 10.1016/j.engstruct.2014.10.052
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Volume preserving projection filters and continuation methods in topology optimization

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Cited by 70 publications
(29 citation statements)
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“…(29). Furthermore, the minimum compliance problem is self-adjoint and this problem can be solved using various optimization algorithms which are presented in detail in our previous work [1,14,15]. Another topology optimization problem considered in this study is the compliant mechanism problem.…”
Section: Problem Formulationmentioning
confidence: 98%
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“…(29). Furthermore, the minimum compliance problem is self-adjoint and this problem can be solved using various optimization algorithms which are presented in detail in our previous work [1,14,15]. Another topology optimization problem considered in this study is the compliant mechanism problem.…”
Section: Problem Formulationmentioning
confidence: 98%
“…The Method of Moving Asymptotes (MMA) with default setting (s ini ¼ 0:5, s incr ¼ 1:2 and s decr ¼ 0:7) is employed as the optimizer in this study [18]. In order to avoid or mitigate the premature convergence to a local minimum as well as obtain the discrete black-white solutions, a continuation scheme for penalization parameter p is adopted [15]. In the continuation scheme, p value for the k th continuation step is set as p k ¼ 1 þ 0:1 Â k until p ¼ 3 is reached, and for every continuation step 25 iterations are carried out.…”
Section: Numerical Experimentsmentioning
confidence: 99%
“…13 [42]. The domain is discretized with 120 Â 60 mesh, and first an unpenalized problem with penalty parameter p ¼ 1 is considered and the filter radius is R ¼ 4:0.…”
Section: Problem-5: Topology Optimization Of Compliant Mechanismsmentioning
confidence: 99%
“…Many articles use the technique of solving a sequence of problems with increasing value of p, such as Li and Khandelwal (2015), Watada et al (2011), Sigmund and Petersson (1998), Petersson and Sigmund (1998), Watada and Ohsaki (2009), Buhl et al (2000), and Edwards et al (2007) among others. These articles claim this method helps to avoid ending in a local minimum.…”
Section: Introductionmentioning
confidence: 99%