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How to vary the evaluation number during continuation approach for solving Topology Optimization problem?

Posted 2019年1月17日 GMT-5 10:27 Optimization Version 5.4 2 Replies

H. LI
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Dear Mr./Mrs.,

The latest released example "Bracket — Topology Optimization" demonstrate how to implement the continuation approach in topology optimization problem, please refer to the following website: https://cn.comsol.com/model/bracket-topology-optimization-69891

My question is: In this "Bracket" demo example, the evaluation number for each continuation step remain the same which was set to 50 in this example. Is it possible to vary the eval numb for different steps? For example, the maximum evaluation number is set to 30, 40, 50 and 60 for continuation step 1, 2, 3 and 4, respectively.

Kindly regards, Hao

2 Replies Last Post 2019年1月17日 GMT-5 23:22
Kristian Ejlebjærg Jensen COMSOL Employee

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Posted: 6 years ago 2019年1月17日 GMT-5 15:07
Updated: 6 years ago 2019年1月17日 GMT-5 15:07

The maximum number of model evaluation cannot depend on the value of parameters, but it is possible to

  1. Create four different studies (the 2nd initialized with the 1st etc) and set the parameters for each study using the auxilliary sweep functionality. A fifth study could then be used to run all four studies using study references.

  2. Alternatively, a single study can be initialized with itself and one can then use a model method to change the maximum number of model evaluations as well as the value of parameters.

The maximum number of model evaluation cannot depend on the value of parameters, but it is possible to 1. Create four different studies (the 2nd initialized with the 1st etc) and set the parameters for each study using the auxilliary sweep functionality. A fifth study could then be used to run all four studies using study references. 2. Alternatively, a single study can be initialized with itself and one can then use a model method to change the maximum number of model evaluations as well as the value of parameters.
H. LI
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Posted: 6 years ago 2019年1月17日 GMT-5 23:22

The maximum number of model evaluation cannot depend on the value of parameters, but it is possible to

  1. Create four different studies (the 2nd initialized with the 1st etc) and set the parameters for each study using the auxilliary sweep functionality. A fifth study could then be used to run all four studies using study references.

  2. Alternatively, a single study can be initialized with itself and one can then use a model method to change the maximum number of model evaluations as well as the value of parameters.

Thanks Kristian for your kind help!

>The maximum number of model evaluation cannot depend on the value of parameters, but it is possible to > >1. Create four different studies (the 2nd initialized with the 1st etc) and set the parameters for each study using the auxilliary sweep functionality. A fifth study could then be used to run all four studies using study references. > >2. Alternatively, a single study can be initialized with itself and one can then use a model method to change the maximum number of model evaluations as well as the value of parameters. Thanks Kristian for your kind help!

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