Fine tuning straightening process using genetic algorithms and finite element methods

  1. Pernía, A. 1
  2. Martínez-De-Pisón, F.J. 1
  3. Ordieres, J. 2
  4. Alba, F. 1
  5. Blanco, J. 1
  1. 1 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

  2. 2 Universidad Politécnica de Madrid
    info

    Universidad Politécnica de Madrid

    Madrid, España

    ROR https://ror.org/03n6nwv02

Revista:
Ironmaking and Steelmaking

ISSN: 0301-9233

Año de publicación: 2010

Volumen: 37

Número: 2

Páginas: 119-125

Tipo: Artículo

DOI: 10.1179/030192309X12549935902301 SCOPUS: 2-s2.0-77949459789 WoS: WOS:000274484000006 GOOGLE SCHOLAR

Otras publicaciones en: Ironmaking and Steelmaking

Repositorio institucional: lock_openAcceso abierto Editor

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Resumen

The process of straightening steel sections is used not only to actually straighten the product but also to reduce its internal residual stresses. Fine tuning this process within an industrial plant is complicated because of the time needed for conducting the tests and the difficulties in measuring the final residual stresses. This paper presents a methodology based on genetic algorithms and finite element analysis that seeks the best position of the rollers to produce a straightened product with the minimum amount of residual stresses. The process consists of simulating multiple roller positions using a previously validated finite element model and analysing the resulting residual stresses. Genetic programming is used to choose the best solutions that will give rise to the next generation of individuals. For several generations, the system combines a series of optimum solutions in which residual solutions are minimised. The best solutions obtained enable the rollers to be positioned in a way that guarantees a good end quality for the product. © 2010 Institute of Materials, Minerals and Mining.