skip to main content
Language:
Search Limited to: Search Limited to: Resource type Show Results with: Show Results with: Search type Index

A scalable parallel finite element framework for growing geometries: application to metal additive manufacturing

info:eu-repo/semantics/openAccess ;ISSN: 0029-5981 ;EISSN: 1097-0207 ;DOI: 10.1002/nme.6085

Digital Resources/Online E-Resources

Citations Cited by
  • Title:
    A scalable parallel finite element framework for growing geometries: application to metal additive manufacturing
  • Author: Miranda Neiva, Eric ; Badia, Santiago ; Martín Huertas, Alberto Francisco ; Chiumenti, Michèle
  • Subjects: Adaptive mesh refinement ; Additive manufacturing ; Anàlisi numèrica ; Domain decomposition ; Enginyeria dels materials ; Fabricació ; Finite elements ; Manufacturing processes ; Matemàtiques i estadística ; Mathematical models ; Metal·lúrgia ; Models matemàtics ; Mètodes en elements finits ; Parallel computing ; Powder-bed fusion ; Àrees temàtiques de la UPC
  • Description: This is the accepted version of the following article: [ Neiva, E, Badia, S, Martín, A F, Chiumenti, M. A scalable parallel finite element framework for growing geometries. Application to metal additive manufacturing. Int J Numer Methods Eng. 2019. https://doi.org/10.1002/nme.6085], which has been published in final form at https://onlinelibrary.wiley.com/doi/abs/10.1002/nme.6085 This work introduces an innovative parallel, fully-distributed finite element framework for growing geometries and its application to metal additive manufacturing. It is well-known that virtual part design and qualification in additive manufacturing requires highly-accurate multiscale and multiphysics analyses. Only high performance computing tools are able to handle such complexity in time frames compatible with time-to-market. However, efficiency, without loss of accuracy, has rarely held the centre stage in the numerical community. Here, in contrast, the framework is designed to adequately exploit the resources of high-end distributed-memory machines. It is grounded on three building blocks: (1) Hierarchical adaptive mesh refinement with octree-based meshes; (2) a parallel strategy to model the growth of the geometry; (3) state-of-the-art parallel iterative linear solvers. Computational experiments consider the heat transfer analysis at the part scale of the printing process by powder-bed technologies. After verification against a 3D benchmark, a strong-scaling analysis assesses performance and identifies major sources of parallel overhead. A third numerical example examines the efficiency and robustness of (2) in a curved 3D shape. Unprecedented parallelism and scalability were achieved in this work. Hence, this framework contributes to take on higher complexity and/or accuracy, not only of part-scale simulations of metal or polymer additive manufacturing, but also in welding, sedimentation, atherosclerosis, or any other physical problem where the physical domain of interest grows in time. Peer Reviewed
  • Publisher: John Wiley & sons
  • Creation Date: 2019-09
  • Language: English
  • Identifier: ISSN: 0029-5981
    EISSN: 1097-0207
    DOI: 10.1002/nme.6085
  • Source: Recercat
Back to results list
INSPIRE LIBRARY - TON DUC THANG UNIVERSITY (84-028) 37 755 057 Feedback
19 Nguyen Huu Tho St. Dist.7, HCM thuvien@tdtu.edu.vn

Copyright © 2017 INSPIRE LIBRARY - TON DUC THANG UNIVERSITY

Searching Remote Databases, Please Wait