Influence of the evolutionary optimization parameters on the optimal topology

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2 Citazioni (Scopus)

Abstract

Topological optimization can be considered as one of the most general types of structural optimization. Between all known topological optimization techniques, the Evolutionary Structural Optimization represents one of the most efficient and easy to implement approaches. Evolutionary topological optimization is based on a heuristic general principle which states that, by gradually removing portions of inefficient material from an assigned domain, the resulting structure will evolve towards an optimal configuration. Usually, the initial continuum domain is divided into finite elements that may or may not be removed according to the chosen efficiency criteria and other parameters like the speed of the evolutionary process, the constraints on displacements and/or stresses, the desired volume reduction, etc. All these variables may influence significantly the final topology. The main goal of this work is to study the influence of both the different optimization parameters and the used efficiency criteria on the optimized topology. In particular, two different evolutionary approaches, based on the von Mises stress and the Strain Energy criteria, have been implemented and analyzed. Both approaches have been deeply investigated by means of a systematic simulation campaign aimed to better understand how the final topology can be influenced by different optimization parameters (e.g. rejection ratio, evolutionary rate, convergence criterion, etc..). A simple case study (a clamped beam) has been developed and simulated and the related results have been compared. Despite the object simplicity, it can be observed that the evolved topology is strictly related to the selected parameters and criteria.
Lingua originaleEnglish
Titolo della pubblicazione ospiteAdvances on Mechanics, Design Engineering and Manufacturing
Pagine15-24
Numero di pagine10
Stato di pubblicazionePublished - 2017

Serie di pubblicazioni

NomeLECTURE NOTES IN MECHANICAL ENGINEERING

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Fluid Flow and Transfer Processes

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    Ingrassia, T., & Mancuso, A. (2017). Influence of the evolutionary optimization parameters on the optimal topology. In Advances on Mechanics, Design Engineering and Manufacturing (pagg. 15-24). (LECTURE NOTES IN MECHANICAL ENGINEERING).