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A Geometry-Based Welding Distortion Prediction Tool.
Granell, Ignacio; Ramos, Abel; Carnicero, Alberto.
Afiliação
  • Granell I; Institute for Research in Technology, Pontifical Comillas University, Santa Cruz de Marcenado 26, 28015 Madrid, Spain.
  • Ramos A; Ansys Inc., Paseo de la Castellana, 81, Planta 9, 28046 Madrid, Spain.
  • Carnicero A; Institute for Research in Technology, Pontifical Comillas University, Santa Cruz de Marcenado 26, 28015 Madrid, Spain.
Materials (Basel) ; 14(17)2021 Aug 24.
Article em En | MEDLINE | ID: mdl-34500881
ABSTRACT
The prediction of welding distortion requires expertise in computer simulation programs, a clear definition of the nonlinear material properties, and mesh settings together with the nonlinear solution settings of a coupled thermal-structural analysis. The purpose of this paper is to present the validation of an automatic simulation tool implemented in Ansys using Python scripting. This tool allows users to automate the preparation of the simulation model with a reduced number of inputs. The goal was, based on some assumptions, to provide an automated simulation setup that enables users to predict accurate distortion during the welding manufacturing process. Any geometry prepared in a CAD software can be used as the input, which gave us much geometrical flexibility in the shapes and sizes to be modeled. A thermomechanical loosely coupled analysis approach together with element birth and death technology was used to predict the distortions. The automation of the setup enables both simulation and manufacturing engineers to perform welding-induced distortion prediction. The results showed that the method proposed predicts distortion with 80-98% accuracy.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Materials (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Espanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Materials (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Espanha