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Investigation of as-cast light alloys by selected homogenization techniques with microstructure effects

  • Ludmila Parashkevova*
  • , Pedro Egizabal
  • *Autor correspondiente de este trabajo
  • Bulgarian Academy of Sciences

Producción científica: Capítulo del libro/informe/acta de congresoCapítulorevisión exhaustiva

1 Cita (Scopus)

Resumen

In the present contribution, upgrading the findings of previous works, [1, 2], new models are proposed for evaluation of effective mechanical properties of light alloys regarded as multiphase composites. These models are aimed to improve the mechanical properties predictions of two groups light alloys: die cast Mg alloys AZ and metal foams with closed cells. The presented models are variants of Mean Field Homogenization (MFH) approach and Differential Homogenization Method, (DHM), both accounting for microstructure size effects. They are appropriate for composite structures where the content of non- matrix phases is predominant. The microstructure - properties relationships for AZ Mg alloy with Continuous (C) and Discontinuous (D) intermetallic phase precipitations are investigated applying MFH and DHM approaches. The basic distinction between cases (C) and (D) consists of different arrangement and volume fraction of harder intermetallic phase Mg17Al12. The type of the microstructure observed depends mainly on the applied cooling regime and chemical composition of the alloy. The elastic-plastic properties predictions for both types of microstructure topology are compared and discussed. The elastic behavior of foams with closed pores is simulated applying DHM, where the size sensitive variant of Mori-Tanaka scheme is used as a basic ‘dilute case’ procedure. The method is developed to closed form solutions of corresponding system of differential equations. The results obtained by means of the size-sensitive DHM are compared with experimental data for aluminium and glass foams taken from the literature.

Idioma originalInglés
Título de la publicación alojadaStudies in Computational Intelligence
EditorialSpringer Verlag
Páginas355-368
Número de páginas14
DOI
EstadoPublicada - 2019

Serie de la publicación

NombreStudies in Computational Intelligence
Volumen793
ISSN (versión impresa)1860-949X

Huella

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