Abstract

This article presents numerically efficient computational models for solving exemplary problems of parametric optimization with the use of the finite element method. Building computational models involved applying a non-standard usage of superelements. In the problems of static analysis, static condensation method was used for model reduction. In the case dynamic problem, component mode synthesis method was applied. The advantages of the adopted modelling methodology were shown with reference to the time required to find the optimal solution. The issue, so far overlooked in this type of analyses, of the relationship between the modelling methodology and the size of the files generated during the analysis was also mentioned.

Highlights

  • Numerical efficiency of a finite element (FE) model is of key importance when solving a parametric optimization problem

  • The object of discussion will be the issue so far overlooked in this type of analyses, concerning the relation between the applied modelling methodology and the size of the files generated during the analysis

  • Using a method for computational model reduction when solving a parametric optimization problem has led to tangible results as follows:

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Summary

Introduction

Numerical efficiency of a finite element (FE) model is of key importance when solving a parametric optimization problem. Advances in Mechanical Engineering interpolated with the use of shape function and treated as boundary conditions for the submodel Such modelling methods are applied which enable to reduce the size of the problem (the number of degrees of freedom of the model) by reducing the number of nodes in the model. It is worth noting that the cited works do not undertake the problem of using model reduction methods in parametric optimization tasks It is, important to answer the question whether building the reduced model is a reasonable action from the point of view of benefits that can be obtained by solving an optimization problem. It may be beneficial to apply superelements for modelling objects with repetitive fragments for which it is possible to define the so-called secondary superelements

Methodology of solving optimization problems
Findings
Conclusion
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