An optimization method for dynamics of structures with repetitive component patterns

Didem Akcay-Perdahcioglu, Marcellinus Hermannus Maria Ellenbroek, Peter van der Hoogt, Andries de Boer

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)
46 Downloads (Pure)

Abstract

The occurrence of dynamic problems during the operation of machinery may have devastating effects on a product. Therefore, design optimization of these products becomes essential in order to meet safety criteria. In this research, a hybrid design optimization method is proposed where attention is focused on structures having repeating patterns in their geometries. In the proposed method, the analysis is decomposed but the optimization problem itself is treated as a whole. The model of an entire structure is obtained without modeling all the repetitive components using the merits of the Component Mode Synthesis method. Backpropagation Neural Networks are used for surrogate modeling. The optimization is performed using two techniques: Genetic Algorithms (GAs) and Sequential Quadratic Programming (SQP). GAs are utilized to increase the chance of finding the location of the global optimum and since this optimum may not be exact, SQP is employed afterwards to improve the solution. A theoretical test problem is used to demonstrate the method.
Original languageUndefined
Pages (from-to)557-567
Number of pages11
JournalStructural and multidisciplinary optimization
Volume39
Issue number6
DOIs
Publication statusPublished - 2009

Keywords

  • IR-69762
  • METIS-262739

Cite this

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title = "An optimization method for dynamics of structures with repetitive component patterns",
abstract = "The occurrence of dynamic problems during the operation of machinery may have devastating effects on a product. Therefore, design optimization of these products becomes essential in order to meet safety criteria. In this research, a hybrid design optimization method is proposed where attention is focused on structures having repeating patterns in their geometries. In the proposed method, the analysis is decomposed but the optimization problem itself is treated as a whole. The model of an entire structure is obtained without modeling all the repetitive components using the merits of the Component Mode Synthesis method. Backpropagation Neural Networks are used for surrogate modeling. The optimization is performed using two techniques: Genetic Algorithms (GAs) and Sequential Quadratic Programming (SQP). GAs are utilized to increase the chance of finding the location of the global optimum and since this optimum may not be exact, SQP is employed afterwards to improve the solution. A theoretical test problem is used to demonstrate the method.",
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An optimization method for dynamics of structures with repetitive component patterns. / Akcay-Perdahcioglu, Didem; Ellenbroek, Marcellinus Hermannus Maria; van der Hoogt, Peter; de Boer, Andries.

In: Structural and multidisciplinary optimization, Vol. 39, No. 6, 2009, p. 557-567.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - An optimization method for dynamics of structures with repetitive component patterns

AU - Akcay-Perdahcioglu, Didem

AU - Ellenbroek, Marcellinus Hermannus Maria

AU - van der Hoogt, Peter

AU - de Boer, Andries

PY - 2009

Y1 - 2009

N2 - The occurrence of dynamic problems during the operation of machinery may have devastating effects on a product. Therefore, design optimization of these products becomes essential in order to meet safety criteria. In this research, a hybrid design optimization method is proposed where attention is focused on structures having repeating patterns in their geometries. In the proposed method, the analysis is decomposed but the optimization problem itself is treated as a whole. The model of an entire structure is obtained without modeling all the repetitive components using the merits of the Component Mode Synthesis method. Backpropagation Neural Networks are used for surrogate modeling. The optimization is performed using two techniques: Genetic Algorithms (GAs) and Sequential Quadratic Programming (SQP). GAs are utilized to increase the chance of finding the location of the global optimum and since this optimum may not be exact, SQP is employed afterwards to improve the solution. A theoretical test problem is used to demonstrate the method.

AB - The occurrence of dynamic problems during the operation of machinery may have devastating effects on a product. Therefore, design optimization of these products becomes essential in order to meet safety criteria. In this research, a hybrid design optimization method is proposed where attention is focused on structures having repeating patterns in their geometries. In the proposed method, the analysis is decomposed but the optimization problem itself is treated as a whole. The model of an entire structure is obtained without modeling all the repetitive components using the merits of the Component Mode Synthesis method. Backpropagation Neural Networks are used for surrogate modeling. The optimization is performed using two techniques: Genetic Algorithms (GAs) and Sequential Quadratic Programming (SQP). GAs are utilized to increase the chance of finding the location of the global optimum and since this optimum may not be exact, SQP is employed afterwards to improve the solution. A theoretical test problem is used to demonstrate the method.

KW - IR-69762

KW - METIS-262739

U2 - 10.1007/s00158-009-0399-8

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VL - 39

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EP - 567

JO - Structural and multidisciplinary optimization

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