Metamodels’ Development for High Pressure Die Casting of Aluminum Alloy

Simulation is a very useful tool in the design of the part and process conditions of high-pressure die casting (HPDC), due to the intrinsic complexity of this manufacturing process. Usually, physics-based models solved by finite element or finite volume methods are used, but their main drawback is t...

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Autores principales:	Eva Anglada, Fernando Boto, Maider García de Cortazar, Iñaki Garmendia
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	simulation modeling FEM metamodel gradient boosting die casting Mining engineering. Metallurgy TN1-997
Acceso en línea:	https://doaj.org/article/b1f0a73361b54a639de29845d625fac9
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spelling	oai:doaj.org-article:b1f0a73361b54a639de29845d625fac92021-11-25T18:21:40ZMetamodels’ Development for High Pressure Die Casting of Aluminum Alloy10.3390/met111117472075-4701https://doaj.org/article/b1f0a73361b54a639de29845d625fac92021-10-01T00:00:00Zhttps://www.mdpi.com/2075-4701/11/11/1747https://doaj.org/toc/2075-4701Simulation is a very useful tool in the design of the part and process conditions of high-pressure die casting (HPDC), due to the intrinsic complexity of this manufacturing process. Usually, physics-based models solved by finite element or finite volume methods are used, but their main drawback is the long calculation time. In order to apply optimization strategies in the design process or to implement online predictive systems, faster models are required. One solution is the use of surrogate models, also called metamodels or grey-box models. The novelty of the work presented here lies in the development of several metamodels for the HPDC process. These metamodels are based on a gradient boosting regressor technique and derived from a physics-based finite element model. The results show that the developed metamodels are able to predict with high accuracy the secondary dendrite arm spacing (SDAS) of the cast parts and, with good accuracy, the misrun risk and the shrinkage level. Results obtained in the predictions of microporosity and macroporosity, eutectic percentage, and grain density were less accurate. The metamodels were very fast (less than 1 s); therefore, they can be used for optimization activities or be integrated into online prediction systems for the HPDC industry. The case study corresponds to several parts of aluminum cast alloys, used in the automotive industry, manufactured by high-pressure die casting in a multicavity mold.Eva AngladaFernando BotoMaider García de CortazarIñaki GarmendiaMDPI AGarticlesimulationmodelingFEMmetamodelgradient boostingdie castingMining engineering. MetallurgyTN1-997ENMetals, Vol 11, Iss 1747, p 1747 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	simulation modeling FEM metamodel gradient boosting die casting Mining engineering. Metallurgy TN1-997
spellingShingle	simulation modeling FEM metamodel gradient boosting die casting Mining engineering. Metallurgy TN1-997 Eva Anglada Fernando Boto Maider García de Cortazar Iñaki Garmendia Metamodels’ Development for High Pressure Die Casting of Aluminum Alloy
description	Simulation is a very useful tool in the design of the part and process conditions of high-pressure die casting (HPDC), due to the intrinsic complexity of this manufacturing process. Usually, physics-based models solved by finite element or finite volume methods are used, but their main drawback is the long calculation time. In order to apply optimization strategies in the design process or to implement online predictive systems, faster models are required. One solution is the use of surrogate models, also called metamodels or grey-box models. The novelty of the work presented here lies in the development of several metamodels for the HPDC process. These metamodels are based on a gradient boosting regressor technique and derived from a physics-based finite element model. The results show that the developed metamodels are able to predict with high accuracy the secondary dendrite arm spacing (SDAS) of the cast parts and, with good accuracy, the misrun risk and the shrinkage level. Results obtained in the predictions of microporosity and macroporosity, eutectic percentage, and grain density were less accurate. The metamodels were very fast (less than 1 s); therefore, they can be used for optimization activities or be integrated into online prediction systems for the HPDC industry. The case study corresponds to several parts of aluminum cast alloys, used in the automotive industry, manufactured by high-pressure die casting in a multicavity mold.
format	article
author	Eva Anglada Fernando Boto Maider García de Cortazar Iñaki Garmendia
author_facet	Eva Anglada Fernando Boto Maider García de Cortazar Iñaki Garmendia
author_sort	Eva Anglada
title	Metamodels’ Development for High Pressure Die Casting of Aluminum Alloy
title_short	Metamodels’ Development for High Pressure Die Casting of Aluminum Alloy
title_full	Metamodels’ Development for High Pressure Die Casting of Aluminum Alloy
title_fullStr	Metamodels’ Development for High Pressure Die Casting of Aluminum Alloy
title_full_unstemmed	Metamodels’ Development for High Pressure Die Casting of Aluminum Alloy
title_sort	metamodels’ development for high pressure die casting of aluminum alloy
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/b1f0a73361b54a639de29845d625fac9
work_keys_str_mv	AT evaanglada metamodelsdevelopmentforhighpressurediecastingofaluminumalloy AT fernandoboto metamodelsdevelopmentforhighpressurediecastingofaluminumalloy AT maidergarciadecortazar metamodelsdevelopmentforhighpressurediecastingofaluminumalloy AT inakigarmendia metamodelsdevelopmentforhighpressurediecastingofaluminumalloy
_version_	1718411280436428800

Metamodels’ Development for High Pressure Die Casting of Aluminum Alloy

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